GEOCHEMICAL SIGNATURES OF STABLE PLANETARY SURFACES: OXIDATIVE WEATHERING PROCESSES ON EARTH AND MARS by MARK ROBERT SALVATORE B.Sc., The Pennsylvania State University, 2008 Sc.M., Brown University, 2010 A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN THE DEPARTMENT OF GEOLOGICAL SCIENCES AT BROWN UNIVERSITY PROVIDENCE, RHODE ISLAND MAY 2013 © Copyright 2013, Mark R. Salvatore This dissertation by Mark Robert Salvatore is accepted in its present form by the Department of Geological Sciences as satisfying the dissertation requirements of the degree of Doctor of Philosophy. _________________ ____________________________________ Date John F. Mustard, Brown University Advisor _________________ ____________________________________ Date James W. Head III, Brown University Advisor Recommended to the Graduate Council _________________ ____________________________________ Date Reid F. Cooper, Brown University Reader _________________ ____________________________________ Date Alberto E. Saal, Brown University Reader _________________ ____________________________________ Date A. Deanne Rogers, Stony Brook University Reader Approved by the Graduate Council _________________ ____________________________________ Date Peter M. Weber, Brown University Dean of the Graduate School iii MARK ROBERT SALVATORE Curriculum Vitae Planetary Geosciences Group Office: 310 Lincoln Field Bldg. Dept. of Geological Sciences Email: Mark_Salvatore@brown.edu Brown University Telephone: (401) 863-3379 324 Brook Street, Box 1846 Fax: (401) 863-3978 Providence, RI 02912 http://planetary.brown.edu/grad_pages/Salvatore EDUCATION 2013 Ph.D. (exp.), Geological Sciences, Brown University Dissertation: Geochemical signatures of stable planetary surfaces: Oxidative weathering processes on Earth and Mars Advisors: Dr. John F. Mustard and Dr. James W. Head III 2010 Sc.M., Geological Sciences, Brown University Thesis: Definitive evidence of Hesperian basalt in Acidalia and Chryse planitiae Advisors: Dr. John F. Mustard and Dr. Michael B. Wyatt 2008 B.Sc., Geography, Student Marshal, The Pennsylvania State University Thesis: Relationship between transverse aeolian ridges and climate on Mars Advisor: Dr. Derrick J. Lampkin RESEARCH SUMMARY - Oxidative weathering in hyper-arid and hypo-thermal environments - Characterization of recent chemical alteration on Mars - Field, laboratory, and orbital studies in the McMurdo Dry Valleys of Antarctica - Reflectance and emission spectroscopy (orbital- and laboratory-based) PROFESSIONAL EXPERIENCE 2013- Postdoctoral Research Associate (accepted position), Arizona State University Advisor: Dr. Philip Christensen 2008-present Graduate Student, Brown University Advisors: Dr. John F. Mustard, Dr. James W. Head III, and Dr. Michael B. Wyatt 2011 Imagery Lead, Desert Research and Technology Studies, NASA Lyndon B. Johnson Space Center Science Operations Lead: Dr. Dean B. Eppler 2009-2010 Field Work, McMurdo Dry Valleys, Antarctica Principal Investigators: Dr. Michael B. Wyatt and Dr. James W. Head III 2008 Research Assistant, NASA Lyndon B. Johnson Space Center Advisor: Dr. M. Justin Wilkinson 2007 Research Intern, Lunar and Planetary Institute Advisors: Dr. Carlton C. Allen and Dr. Dorothy Z. Oehler 2006 Research Intern, Center for Earth and Planetary Studies, Smithsonian Institution Advisors: Dr. James R. Zimbelman and Dr. Thomas R. Watters TEACHING EXPERIENCE 2011 Teaching Assistant, GE1350 (Weather and Climate), Brown University Instructor: Dr. Meredith G. Hastings 2010 Teaching Assistant, GE1350 (Weather and Climate), Brown University Instructor: Dr. Meredith G. Hastings 2009 Teaching Assistant, GE0050 (Mars, Moon and the Earth), Brown University Instructors: Dr. Michael B. Wyatt and Dr. Caleb I. Fassett 2009 Instructor, Brown University SPARK Program Course: Hello from Mars (Introduction to Martian Geoscience) Salvatore, Page 1 of 3 iv PEER-REVIEWED PUBLICATIONS Accepted & Published 2. Salvatore M. R., Mustard J. F., Head J. W., Marchant D. R. and Wyatt M. B. (2013), Characterization of spectral and geochemical variability within the Ferrar Dolerite of the McMurdo Dry Valleys, Antarctica: Weathering, alteration, and magmatic processes. Antarctic Science, accepted. 1. Salvatore M. R., Mustard J. F., Wyatt M. B. and Murchie S. L. (2010), Definitive evidence of Hesperian basalt in Acidalia and Chryse planitiae. J. Geophys. Res. 115, E07005, doi:10.1029/2009JE003519. Submitted & In Review 2. Salvatore M. R., Mustard J. F., Head J. W. and Cooper R. F. (2013), Oxidative weathering in Antarctica and evidence for a cold and dry Amazonian Mars. Nature Geoscience, submitted. 1. Salvatore M. R., Mustard J. F., Head J. W., Cooper R. F., Marchant D. R. and Wyatt M. B. (2013), Development of alteration rinds by oxidative weathering processes in Beacon Valley, Antarctica, and implications for Mars. Geochimica et Cosmochimica Acta, in review. In Preparation 2. Jackson C. R. M., Cheek L. C., Williams K. B., Dyar M. D., Breves E. A., Salvatore M. R., Prissel T. C., Dhingra D., Pieters C. M., Parman S. W. and Cooper R. F. (2013), Spectral properties of aluminate spinels and application to lunar remote sensing. 1. Salvatore M. R., Mustard J. F., Head J. W., Cooper R. F. and Wyatt M. B. (2013), The spectral influence of oxidative weathering on martian low albedo terrain. SELECTED PRESENTATIONS & PUBLISHED ABSTRACTS Invited Talks - Stony Brook University, Department of Geosciences, February 2013 Title: Oxidative weathering on Earth and Mars: Laboratory and orbital analyses First-Authored Abstracts (Since 2011) - Salvatore M. R., Mustard J. F., Head J. W., Cooper R. F., Marchant D. R. and Wyatt M. B. (2013), Oxidative weathering on Mars and implications for chemical alteration during the Amazonian epoch. LPSC XLIV, abstract 1339. - Salvatore M. R., Mustard J. F., Head J. W., Marchant D. R., Cooper R. F. and Wyatt M. B. (2013), Spectral and chemical characterization of hyper-arid and hypo-thermal oxidation processes as an analog for Amazonian alteration on Mars (Invited). AGU Fall Mtg., abstract P11F-06. - Salvatore M. R., Mustard J. F., Head J. W., Marchant D. R. and Wyatt M. B. (2012), Compositional remote sensing of the McMurdo Dry Valleys: Integrated analyses of primary and secondary processes within the Ferrar Dolerite. SCAR Open Sci. Conf. XXXII, abstract 654. - Salvatore M. R., Mustard J. F., Head J. W., Cooper R. F., Marchant D. R. and Wyatt M. B. (2012), Characterizing widespread oxidation processes on Mars: Alteration rind development and effects on spectroscopic investigations. LPSC XLIII, abstract 1597. - Salvatore M. R., Mustard J. F., Head J. W., Marchant D. R., Wyatt M. B. and Seeley J. (2012), Linking orbital, field, and laboratory analyses of dolerites in the McMurdo Dry Valleys of Antarctica: Terrestrial studies and planetary applications. LPSC XLIII, abstract 1590. - Salvatore M. R., Mustard J. F., Head J. W., Cooper R. F., Marchant D. R. (2011), Widespread, juvenile alteration of the Ferrar Dolerite in Beacon Valley, Antarctica. AGU Fall Mtg., abstract P31C-1717. - Salvatore M. R., Mustard J. F., Head J. W. and Seeley J. (2011), Verification of spectral mapping of the McMurdo Dry Valleys using in situ and laboratory techniques. GSA Joint Ann. Mtg., abstract 284-7. - Salvatore M. R., Wyatt M. B., Mustard J. F., Head J. W., Cooper R. F. and Marchant D. R. (2011), Constraining the chemical alteration of rock surfaces of the Ferrar Dolerite in Beacon Valley, Antarctica. 11th Intl. Symp. on Ant. Earth Sci., Br. Geol. Surv., Edinburgh, U.K. - Salvatore M. R., Wyatt M. B., Mustard J. F. and Head J. W. (2011), Development of alteration rinds on the Ferrar Dolerite of the Antarctic Dry Valleys: Initial characterization. LPSC XLII, abstract 1479. Salvatore, Page 2 of 3 v - Salvatore M. R., Wyatt M. B., Mustard J. F., Head J. W., Marchant D. R. (2010), Near-infrared spectral diversity of the Ferrar Dolerite in Beacon Valley, Antarctica: Implications for martian climate and surface compositions. LPSC XLI, abstract 2290. - Salvatore M. R., Mustard J. F., Wyatt M. B., Murchie S. L. and Barnouin-Jha O. S. (2009), Assessing the mineralogy of Acidalia Planitia, Mars, using near-infrared orbital spectroscopy. LPSC XL, abstract 2050. - Salvatore M. R., Wilkinson M. J., Allen C. C. and Oehler D. Z. (2008), Terrestrial megafans as an analog for ridged unit of SW Arabia Terra, Mars: Current observations and future analysis. LPSC XXXIX, abstract 1455. - Salvatore M. R., Allen C. C., Oehler D. Z. and Wilkinson M. J. (2007), Geomorphologic interpretation of southwest Arabia Terra, Mars: Evidence for regional, long-duration fluvial activity. AGU Fall Mtg., abstract P13B-1293. - Salvatore M. R. and Zimbelman J. R. (2006), Investigation of martian transverse aeolian ridges. AGU Fall Mtg., abstract P31B-0129. OUTREACH & SERVICE - Co-Convener, American Geophysical Union Annual Fall Meeting, 2011. Session: Nanocrystalline Materials on Earth and Mars (P20) - Undergraduate Advising Andrea Weber (2012): Inorganic approaches to climate reconstruction in Lake Towuti, Indonesia. - Graduate student leadership positions, Brown University Board of Governors, Brown University Faculty/Graduate Student Club, 2010-present. Representative, Professional Development Seminars, 2010-2012. Graduate student liaison, faculty search committees, 2010-2011. President, Geosciences Graduate Student Association, 2009-2010. - Guest speaker, 2006-2012. Recent Locations: Cresskill High School (Cresskill, NJ), Lincoln Elementary School (Ridgefield Park, NJ), Civil Air Patrol Pennsylvania Wing (Fort Indiantown Gap, PA). Recent Lectures: Past, Present, and Future of Manned Spaceflight; Global Warming and Future Impacts; Exploring Mars: Rovers and Landers; The Antarctic Environment. - Volunteer, Greene County Habitat for Humanity, Waynesburg, PA, 2001-2012. - President, Geography International Honor Society Gamma Theta Upsilon, 2007-2008. The Pennsylvania State University Chapter. - Volunteer, Mars Day! 2006, Smithsonian Institution, 2006. HONORS & AWARDS - Best Poster, Scientific Committee on Antarctic Research (SCAR) Open Science Conference, 2012. - U.S. Congressional Antarctic Service Medal, United States Antarctic Program, 2012. - Outstanding Student Paper Award, American Geophysical Union Annual Fall Meeting, 2011. - Honorary Mention, Stephen E. Dwornik Award – Best Paper, Lunar and Planetary Science Conference, 2009. - Student Marshal, College of Earth and Mineral Sciences, The Pennsylvania State University, 2008. - Schreyer Honors Scholar – Highest Distinction, The Pennsylvania State University, 2008. PROFESSIONAL ASSOCIATIONS - American Geophysical Union (AGU), 2006 – present. - Geological Society of America (GSA), 2011 – present. - Association of American Geographers (AAG), 2007 – 2009. Salvatore, Page 3 of 3 vi Acknowledgements To my advisors, Jack Mustard and Jim Head, for teaching me how to think critically and to harness my enthusiasm into disciplined and productive energy. You have both provided me with many wonderful opportunities during my tenure as a graduate student. In particular, you taught me to be an independent researcher and to pursue my own research interests. You never hesitated to nudge me in the right direction, which is certainly a major reason why I have been able to make it to this point in my academic career. Your combined generosity in providing guidance and stability throughout my time at Brown also ensured that my research and career goals remained intact, and for that I will be forever grateful. To my defense committee, for all of the wonderful scientific discussions over the past five years, in addition to the helpful comments and suggestions still to come. To Reid Cooper, for your countless hours and tireless efforts to teach a macroscale-thinking planetary geologist the wonders of nanoscale material properties and analytical techniques. To Alberto Saal, for your endless encouragement and support, both academic and non-academic. To Deanne Rogers, for laying the foundation upon which much of this dissertation is rooted, and for the motivation and guidance that you have selflessly provided. I’m excited to see what more there is to learn regarding martian surface compositions! To all of my professors and mentors at Brown University and other institutions, thank you for the advice, suggestions, and support over the past five years. To Mike Wyatt, for helping me to mature from an undergraduate student, and for the opportunity to take an active role in the designing and execution of two successful field seasons in Antarctica. To Meredith Hastings, for sharpening my teaching skills and for allowing me to grow and develop as an instructor. To Jim Russell, for your generosity and guidance both in the classroom and in the field. Thank you for all of the technical assistance and mentoring that I have received throughout my tenure at Brown University, particularly from Dave Murray, Joe Orchardo, Takahiro Hiroi, and Bill Collins. Thank you all for spending that extra time to teach me not only how things work, but also why things work. A special thank you is reserved for all of my professors, advisors, and mentors prior to my time at Brown University, particularly those at Penn State University (especially Derrick Lampkin and Jim Kasting), the Center for Earth and Planetary Studies (especially Jim Zimbelman and Tom Watters), NASA Johnson Space Center (especially Carl Allen, Dorothy Oehler, and M. Justin Wilkinson), and the Lunar and Planetary Institute. Hall of Fame pitcher Bob Lemon once said, “I’ve come to the conclusion that the two most important things in life are good friends and a good bullpen.” I couldn’t agree more. To my teammates on the Fall River Blue Jays and the East Greenwich Coyotes, especially Jose, Jeremy, Chris, Tom, Adam, and Shawn. It’s hard to describe the relationship that I have developed with my teammates, but it’s underscored by a mutual dedication, commitment, and loyalty that I have yet to experience anywhere else. Let’s just say that I wouldn’t step into a 2-seam fastball for anybody. To my friends from Penn State University, particularly Allison O’Black, for nine years of continuous encouragement. vii To Theresa Stone, for helping me stay sane through these difficult times, for your patience and understanding, and for assuring me that my heart is not about to suddenly stop or explode on more than a handful of occasions. To my friends and colleagues from Brown University, particularly my friends, roommates, and fellow students that I’ve known for 5+ years. This includes (but is certainly not limited to) Danny and McCall Burau, Rocio Caballero Gill, Leah Cheek, Jay Dickson, Kerri Donaldson Hanna, Bethany Ehlmann, Caleb Fassett, Heather Ford, Chris Havlin, David Hollibaugh Baker, Alex Kasprak, Laura Kerber, Bronwen Konecky, Shannon Loomis, Linda Meyers, Gareth Morgan, Edgard Rivera-Valentin, Jess Rodysill, Jeff Salacup, Victor Schmidt, Angela Stickle, and Chen Sun. Thank you for accompanying me on this academic, professional, and personal marathon and helping me to grow and mature along the way. And to the continuing graduate students in the Department of Geological Sciences, thank you for your friendship and support, and I look forward to watching your continued success in the future. To Colin Jackson, while not the best PlayStation2 NASCAR teammate, I can’t think of anyone more selfless or willing to offer guidance, suggestions, or advice. I look forward to a long future of collaborative science that is rivaled only by our even longer friendship. To my friends from Cresskill, many of whom I’ve known for more than a quarter of a century. I wish there were some way that I could repay you for your encouragement and support throughout the years. Here’s to closing out the rest of that century as close friends. Thank you, Liz Beck, TJ Berardo, Erin Goldrick, Neil Hartmann, Jackie Knight, Lauren Luciani, Shaun Mitchell, Jayme Moran, Melissa Rosario, Gwenn Santoro, Carolyn Thomasma, and Katie Zanone. Finally, to my loving and caring family, whose support has been my backbone throughout my graduate studies. To Chris, for our continuance as the “babies” of the family and for preceding me to Rhode Island and showing me where all of the best inexpensive restaurants reside. I’m extremely proud of your hard work and look forward to your continued success. To Brian and Erin, for being quick to provide comfort and encouragement, and for listening to my countless tirades without hesitation or criticism. I hope that our long discussions about the New York Mets and tacky television continue, either on your couch or via Skype. To Amelia, my wonderful Goddaughter, for disproving my hypothesis that there exists nothing more beautiful in the universe than a well developed alteration rind. And finally, to my parents, Lois and Vinnie, for absolutely everything. Words cannot begin to describe my appreciation, gratitude, or love for you both. This dissertation is dedicated to a very special person whose presence remains with me today and every day. Her commitment to her family, both immediate and extended, was truly inspirational. Unfortunately, she passed away before the completion of my graduate studies, but not before making a lasting impact on my life and the life of so many other people. She will be remembered forever in the hearts and minds of her friends and family, and in the compassion that she instilled upon everyone who knew her. To Adrienne Murphy, for your courage, your love, and your omnipresence in our family. We miss you dearly. viii TABLE OF CONTENTS Title Page ............................................................................................................................. i Copyright Page.................................................................................................................... ii Signature Page ................................................................................................................... iii Curriculum Vitae ............................................................................................................... iv Acknowledgements ........................................................................................................... vii Table of Contents ............................................................................................................... ix Chapter One: Geochemical investigations of cold and dry chemical weathering in desert landscapes: An introduction............................................................................. 1 1.0 Motivation ................................................................................................................. 2 1.1 Characterizing hyper-arid and hypo-thermal chemical alteration on Earth ........ 5 1.2 Understanding recent weathering on Mars ........................................................... 8 2.0 Approach ................................................................................................................. 10 2.1 Field studies ....................................................................................................... 11 2.2 Remote sensing ................................................................................................... 12 2.3 Laboratory analyses ............................................................................................ 12 3.0 Dissertation Summary ............................................................................................. 13 References ...................................................................................................................... 16 Figure Descriptions ........................................................................................................ 24 Figures............................................................................................................................ 26 Chapter Two: Development of alteration rinds by oxidative weathering processes in Beacon Valley, Antarctica, and implications for Mars. ......................... 29 Abstract .......................................................................................................................... 30 1.0 Introduction ............................................................................................................. 31 2.0 Background ............................................................................................................. 34 3.0 Geographic Setting.................................................................................................. 36 4.0 Methods................................................................................................................... 39 5.0 Results ..................................................................................................................... 44 5.1 Chemistry ............................................................................................................. 45 5.2 Mineralogy ........................................................................................................... 47 5.3 Morphology .......................................................................................................... 52 6.0 Discussion ............................................................................................................... 54 7.0 Implications for Surface Alteration on Mars .......................................................... 65 8.0 Conclusions ............................................................................................................. 71 Acknowledgements ........................................................................................................ 72 References ...................................................................................................................... 73 Figure and Table Descriptions ....................................................................................... 89 Figures............................................................................................................................ 96 Tables ........................................................................................................................... 111 ix Chapter Three: Characterization of spectral and geochemical variability within the Ferrar Dolerite of the McMurdo Dry Valleys, Antarctica: Weathering, alteration, and magmatic processes ...................................................... 115 Abstract ........................................................................................................................ 116 Key Words ................................................................................................................... 116 1.0 Introduction and Geologic Setting ........................................................................ 117 2.0 Methods................................................................................................................. 123 2.1 Laboratory spectral investigations .................................................................... 123 2.2 Orbital data acquisition, calibration, and atmospheric removal ...................... 124 2.3 Identification of spectrally pure dolerite using ASTER TIR data ...................... 132 2.4 Identification of spectral variability within the Ferrar Dolerite using ASTER TIR data ........................................................................................................ 134 2.5 Resultant spectral products................................................................................ 135 3.0 Results ................................................................................................................... 135 3.1 Laboratory spectroscopy ................................................................................... 136 3.2 Lithological mapping from orbit........................................................................ 139 3.3 Spectral variability of pure dolerite ................................................................... 140 3.4 Chemical variability within the Ferrar Dolerite ............................................... 143 4.0 Discussion ............................................................................................................. 144 4.1 Identification and distribution of doleritic signatures ....................................... 144 4.2 Geochemical evolution of the Ferrar Dolerite .................................................. 148 5.0 Conclusions ........................................................................................................... 149 Acknowledgements ...................................................................................................... 151 References .................................................................................................................... 152 Figure and Table Descriptions ..................................................................................... 158 Figures.......................................................................................................................... 164 Tables ........................................................................................................................... 182 Chapter Four: Oxidative weathering in Antarctica and evidence for a cold and dry Amazonian Mars. ........................................................................................... 185 Main Text ..................................................................................................................... 186 Methods........................................................................................................................ 193 Spectral analyses of dolerite samples ....................................................................... 193 Orbital data retrieval and calibration ...................................................................... 193 Assembly of endmember library and linear unmixing .............................................. 195 References .................................................................................................................... 195 Figure and Table Descriptions ..................................................................................... 200 Figures.......................................................................................................................... 202 Tables ........................................................................................................................... 205 Chapter Five: The spectral influence of oxidative weathering on martian low albedo terrain. ........................................................................................................ 207 Abstract ........................................................................................................................ 208 1.0 Introduction ........................................................................................................... 209 x 2.0 Methods................................................................................................................. 212 2.1 Laboratory spectroscopy ................................................................................... 212 2.2 Visible/Near-infrared orbital spectroscopy ....................................................... 215 2.3 Thermal infrared orbital spectroscopy .............................................................. 217 3.0 Results ................................................................................................................... 219 3.1 Laboratory analyses (Table 2) ........................................................................... 219 3.2 Orbital analyses (Regional) ............................................................................... 221 3.3 Orbital analyses (Local) .................................................................................... 225 3.3.1 Acidalia Planitia .......................................................................................... 226 3.3.2 Syrtis Major ................................................................................................. 228 3.4 Summary ............................................................................................................ 231 4.0 Discussion ............................................................................................................. 232 4.1 Assumptions regarding oxidative weathering products and processes ............. 232 4.2 Effects of oxidative weathering on apparent surface composition .................... 234 4.3 Distribution of oxidative weathering products on Mars .................................... 237 4.4 Implications for Amazonian climate .................................................................. 240 5.0 Conclusions ........................................................................................................... 243 References .................................................................................................................... 246 Figure and Table Descriptions ..................................................................................... 257 Figures.......................................................................................................................... 264 Tables ........................................................................................................................... 281 Chapter Six: On the current and future investigation of pervasive oxidative alteration processes on Earth and Mars. .................................................................... 286 1.0 Summary and Significance of Work ..................................................................... 287 2.0 Outstanding Questions .......................................................................................... 290 2.1 What is the primary mechanism for the migration of cations to rock surfaces during oxidative weathering in Beacon Valley, Antarctica? ...................... 291 2.2 What is the cause of the large amount of variability observed in X- ray diffraction data and what is the relationship to spectroscopic measurements?.......................................................................................................... 291 2.3 What is the origin of the spectral variations observed in oxidative weathering products?................................................................................................ 293 2.4 How does oxidative weathering influence the spectral signatures of different primary compositions? ........................................................................... 294 2.5 How does oxidative weathering progress under different climatic conditions? ................................................................................................................ 296 2.6 What is the rate of oxidative weathering in terrestrial and martian environments? ........................................................................................................... 297 3.0 Future Work and Concluding Remarks ................................................................ 298 3.1 Future work ........................................................................................................ 298 3.1.1 Field studies ................................................................................................. 300 3.1.2 Laboratory analyses..................................................................................... 301 3.1.3 Remote analyses ........................................................................................... 302 3.2 Concluding remarks ........................................................................................... 304 xi References .................................................................................................................... 304 Figure Descriptions ...................................................................................................... 308 Figures.......................................................................................................................... 310 Appendix A: Multispectral map of the McMurdo Dry Valleys: Description, methodology, and parameterization. ..................................................... 314 Main Text ..................................................................................................................... 315 References .................................................................................................................... 319 Figure and Table Descriptions ..................................................................................... 321 Figures.......................................................................................................................... 323 Tables ........................................................................................................................... 340 Appendix B: Database of samples collected during the 2009-2010 and 2010-2011 field seasons supporting National Science Foundation grant ANT-0739702. ................................................................................................................ 361 Main Text ..................................................................................................................... 362 Figure and Table Descriptions ..................................................................................... 365 Figure ........................................................................................................................... 367 Table ............................................................................................................................ 368 xii 1 Chapter One: Geochemical investigations of cold and dry chemical weathering in desert landscapes: An introduction. M. R. Salvatore1 1 Department of Geological Sciences, Brown University, Providence, RI 02912, USA 2 1.0 Motivation The martian surface represents an ancient and preserved landscape that provides information about the evolution of climatic and geologic environments during the early history of our solar system (Fig. 1). Compared to the Earth, Mars has undergone a relatively rapid geologic and climatic evolution that has resulted in the barren and geologically dormant surface that we observe today. The cause, timing, and duration of this rapid evolution are largely unknown, but are likely related to a combination of events including the declining strength of the martian magnetic field, the end of heavy impactor bombardment, the formation of the Tharsis volcanic province, and the hydrodynamic loss of volatiles to space (Jakosky and Phillips, 2001). Even less constrained are the geochemical and environmental precursors and results associated with these transitions. It is predicted that the Earth will undergo a similar evolutionary fate as a result of cooling of the planet’s interior and solidification of our multifaceted liquid outer core. Therefore, understanding the timing, duration, magnitude, and geochemistry associated with these transitions will help to elucidate how and when these significant transitions may occur on Earth. Using crater counting and stratigraphic relationships, it is estimated that more than 70% of the exposed martian surface is older than 3 Ga (Scott and Tanaka 1986, Greeley and Guest 1987, Tanaka and Scott 1987). The oldest of these terrains also exhibit geomorphic and spectral evidence for widespread aqueous activity, indicating that liquid water was present and active within our solar system during the earliest history of the terrestrial planets. However, the information stored within these ancient geologic units is only as valuable as our abilities to identify, measure, and interpret it. For more 3 than a century, the capabilities available to investigate the martian surface have continuously improved in terms of spatial, radiometric, temporal, and spectral resolution. Visible imagery is now able to easily resolve a golf cart-sized object on the martian surface, while hyperspectral VNIR spectrometers are capable of acquiring fifteen three- dimensional (two spatial and one spectral) pixels within the area of a single American football field. These higher quality datasets provide the information necessary to ask and answer complex questions related to the evolution of the martian geologic and climatic system, which can provide crucial details regarding the evolution of the other terrestrial planets within our solar system. The effects of exposing these landscapes to the martian environment for billions of years have gone largely unstudied. Our current understanding of the martian climate system suggests that the latter half of martian history has been dominated by extremely cold and arid environmental conditions (Fig. 1). Most studies of these ancient terrains have overlooked the influence of recent environmental conditions on the chemical and spectral evolution of the martian surface since the exposure of these geologic units. However, a critical questions remain unanswered: What are the effects of cold, dry, and oxidizing environments on the observed surface spectra, and what (if any) are the underlying chemical and/or mineralogical consequences of these conditions? This dissertation details our investigation of the effects of cold, dry, and oxidizing environments on the modification of surface compositions and spectral signatures, with particular emphasis on remote detection and the accompanying spectral modifications. We utilize the McMurdo Dry Valleys (MDV) of Antarctica as a natural laboratory to investigate these alteration processes given their pervasive hyper-arid and hypo-thermal 4 environmental conditions. Our laboratory investigations focus on samples collected from Beacon Valley, the coldest and driest of the primary MDV (Doran et al., 2002) where the products of cold and dry alteration processes are well preserved throughout the extremely stable landscape (Salvatore et al., 2013b) (Fig. 2). The floor of Beacon Valley is also dominated by clasts of the Ferrar Dolerite, a quartz-normative shallow intrusive tholeiitic basalt that has been regarded as a good analog to martian basalts (Harvey, 2001; Chevrier et al., 2006). This fortuitous pairing of analog environmental and geochemical conditions provides the framework necessary to associate recent chemical alteration in both environments. Comparisons between the MDV and Mars is not a novel idea; the MDV have been long regarded as an analog for martian surface processes due to the extremely cold and dry environmental conditions. Investigations of this analog locale have included studies on geomorphology (e.g., Marchant and Head, 2007), soil formation (e.g., Gibson et al., 1983), microbial ecosystems (e.g., McKay et al., 1992), lacustrine environments (e.g., Andersen et al., 1993), and primary mineralogy (e.g., Harvey, 2001). While localized chemical alteration products in the MDV have been compared to potential martian weathering processes (e.g., Allen and Conca, 1991; Bishop et al., 1996), few studies have sought to characterize the relationship between cold, dry, stable, and oxidizing conditions and pervasive rock weathering on broad spatial scales. Furthermore, the use of orbital spectroscopy to identify hyper-arid and hypo-thermal chemical alteration products on both Earth and Mars is a significant and novel contribution to both terrestrial and martian geochemical studies (Salvatore et al., 2013a). 5 The outline of the contributions reported in this dissertation are prefaced with a brief overview of our current understanding of cold and dry chemical alteration processes on Earth and the evolution of chemical alteration processes on Mars: 1.1 Characterizing hyper-arid and hypo-thermal chemical alteration on Earth Chemical weathering is a fundamental aspect of surface modification on any planetary surface, with the nature, extent, and resultant alteration products varying widely depending on a plethora of environmental conditions. The lunar surface, for example, undergoes chemical weathering as a result of micrometeorite impact processes and interactions with the solar wind, producing nanometer-sized particles of metallic iron that significantly modifies our spectral investigations of surface compositions (Pieters et al., 2000, and references therein). Due to the presence of an atmosphere and the surplus of near-neutral water, subaerial chemical weathering on Earth is dominated by water-rock interactions (Lasaga, 1984). Under the traditional chemical alteration paradigm, primary crystalline materials are broken down into poorly crystalline secondary alteration products, consisting largely of amorphous aluminosilicate gels with high chemical reactivities (Wada, 1989; Schwertmann and Taylor, 1989; Shoji et al., 1993). These poorly crystalline components are then transformed into less reactive but more crystalline alteration products (Vitousek et al., 1997). While specific alteration pathways vary widely due to the composition of the parent material, the amount and chemistry (e.g., pH) of liquid water, the age of the surface, the presence and activity of biological materials, and other factors, this alteration pathway is a well characterized framework with which to base studies of subaerial chemical alteration on Earth. 6 Desert environments, though, are substantially different in terms of their routes of chemical alteration. In most desert environments, rates of physical erosion tend to dominate relative to rates of chemical weathering (Stoffer, 2004). Despite these slow rates, the influence of chemical weathering in these environments is clearly evident on a variety of scales. For example, rock coatings and alteration rinds are prevalent in desert environments where highly stable surfaces are exposed for longer durations than in regions with greater amounts of precipitation and physical erosion (Dorn, 2009). Elemental chemistries of soils in desert environments have also shown unique geochemical trends as a result of the paucity of liquid water and the limited extent of chemical alteration (Gibson et al., 1983). The MDV of Antarctica are unique in their extreme environmental conditions as well as their antiquity (≥ 8.1 Ma in some locations; Marchant et al., 2002). The sub- freezing mean annual temperatures, desiccating and frequent hurricane-force winds, and extremely low water-equivalent mean annual precipitation are unlike any other geomorphic or environmental location on Earth (Doran et al., 2002; Marchant and Head, 2007; Fountain et al., 2009). Considerable attention has been given to the interaction between surface and subsurface waters with the valley soils, with particular emphasis on biogeochemical consequences (e.g., Lyons et al., 2003; Gooseff et al., 2003; Gooseff et al., 2006). Less attention has been dedicated to the effects of chemical weathering on rock surfaces, although pivotal research has laid the foundation required to investigate these unique processes and resultant products. This work was spearheaded by Glazovskaya (1958), who was the first to identify the presence of staining in iron-bearing minerals on rock surfaces in Antarctica. Additional studies that characterize rock 7 weathering processes in the Antarctic are nicely summarized by Campbell and Claridge (1987). Of particular note are the studies by Glasby et al. (1981) and Allen and Conca (1991). Glasby et al. (1981) were the first to document the diffusive nature of alteration rinds (referred to in their study as “desert varnish”) on the surfaces of the Ferrar Dolerite, a shallow intrusive igneous lithology of basaltic composition that is the focus of our Antarctic studies throughout this dissertation. Though the means of dolerite alteration was declared “ambiguous” from their study, their thorough laboratory investigations and documentation of the relationship between the rock surfaces and the local environments was an inspiration for the work presented in this dissertation. Allen and Conca (1991) focus primarily on chemical alteration that occurs within etch pits that form on dolerite surfaces. While the maturity of alteration documented in their study exceeds the pervasive and ubiquitous surface oxidation described in this work, and while this study was not the first to relate the Antarctic environment to that of Mars, their work was the first to link infrared spectroscopic measurements to other laboratory analyses in the MDV. This association provides the foundation for the work presented in this dissertation and for linking spectroscopy with the complex relationship between geology and climatology in the MDV. Since the work of Glasby et al. (1981), few studies have investigated the nature of dolerite surface alteration in the MDV, and those that have did not focus on the nature of the alteration process itself (e.g. Chevrier et al., 2006). Several critical questions have remained unanswered: Can we better understand the alteration process at work on the Ferrar Dolerites in the MDV? How well developed or mature are these alteration products? What are the resultant chemical, mineralogical, and spectral signatures 8 associated with alteration in cold and dry terrestrial environments? Lastly, what is the relationship between cold and dry alteration on Earth and Mars, where the entire surface can be considered a cold and dry desert? 1.2 Understanding recent weathering on Mars Extensive evidence suggests that Mars was once a warmer, wetter, and more geologically active planet than the present. Integrated valley networks (Fassett and Head, 2008) and striking outflow channels (Baker et al., 1992) indicate regional- (if not global-) scale systems of fluvial activity, possibly resulting in the presence of one or more extensive bodies of standing water (Parker et al., 1993). More recent spectral evidence also confirms the geochemical effects of aqueous activity. The identification of Fe-/Mg- bearing smectite clays (Poulet et al., 2005), mono- and poly-hydrated sulfates (Gendrin et al., 2005; Langevin et al., 2005), opaline silica (Milliken et al., 2008), carbonates (Ehlmann et al., 2008), crystalline hematite (Christensen et al., 2000), and a range of other hydrated phases (e.g. Ehlmann et al., 2009) through the use of VNIR and TIR orbital spectroscopy has confirmed that not only has liquid water interacted with the martian crust, but it was capable of chemical alteration through its interaction with in situ geologic materials. While the exact timing and geologic provenance of these alteration products has been extensively debated, it is clear that the majority of chemical alteration took place during the first half of martian history, followed by a near-complete desiccation and cessation of aqueous alteration. The cold and dry surface conditions that we presently observe on Mars are the result of the tenuous martian atmosphere (Lammer et al., 2009). The bulk of martian aqueous activity likely terminated contemporaneously with the evolution of the martian 9 atmosphere, with the last episodes of widespread fluvial activity dated at roughly 3.5 Ga (Hartmann, 2005; Fassett and Head, 2007). The evolution from an ancient warmer and wetter climate to one that has remained cold and dry for the most recent ~3.0 Ga of martian history is also supported by orbital spectral datasets (Bibring et al., 2006). These observed morphological and geochemical signatures likely signify the effective termination of widespread aqueous alteration and the preservation of the martian surface. However, TIR orbital data from the Thermal Emission Spectrometer (TES) instrument on the Mars Global Surveyor (Christensen et al., 2001) have been interpreted to indicate that large extents of the martian surface have experienced chemical alteration since the termination of extensive aqueous activity. The high-latitude Surface Type 2 (ST2) spectral unit, as initially reported by Bandfield et al. (2000), has since been interpreted to represent the spectral contribution from a range of proposed alteration mineralogies, most of which require substantial quantities of liquid water. Smectite clays (Wyatt and McSween, 2002), micron-thick amorphous silica coatings (Kraft et al., 2003), palagonite (Morris et al., 2003), zeolites (Minitti and Hamilton, 2010), Al- or Fe-rich opaline silica (Michalski et al., 2005), Si-rich mineraloids (Michalski et al., 2005), and allophane (Rampe et al., 2012) have all been proposed as potential sources of the TIR spectral signatures observed across the martian high latitudes. These proposed compositional components are seemingly at odds with VNIR spectral data because (1) their associated VNIR spectral features have not been identified, and (2) their distribution within terrain that has been dated as Amazonian (~3.1 Ga to present; Hartmann and Neukum, 2001) in age suggests that considerable aqueous alteration has occurred since Mars has transitioned into the hyper-arid and hypo-thermal desert observed today. 10 The nature and abundance of this surface component has direct implications for the evolution of the martian surface over its geologic history. If significant amounts of chemical alteration have occurred, what environmental conditions must have been present? Why are these alteration products confined to the high latitudes, particularly in the northern hemisphere? If the altered component is hydrated, why is there no evidence for hydration in the VNIR wavelength region? Can hyper-arid and hypo-thermal chemical alteration account for the observed spectral signatures? 2.0 Approach This work investigates the geochemical evolution of planetary surfaces as they interact with their hypo-thermal, hyper-arid, and hyper-stable climatic environments. These environmental conditions are pertinent to the polar regions of the Earth, with particular emphasis on the MDV of Antarctica, as well as the majority of the martian surface, which has not experienced substantial aqueous activity throughout most of its geologic history (Bibring et al., 2006). In order to investigate the geochemical nature and evolution of these surfaces, we use a variety of analytical tools to obtain, extract, and process data followed by subsequent verification and interpretation. This dissertation details the use of a multitude of different datasets and techniques to investigate alteration products and processes, and demonstrates how the use of multiple datasets at a variety of analytical scales and resolutions can provide key insights into the geochemical evolution of weathering products in cold and dry environments. To investigate the processes and products of chemical alteration in cold and dry conditions on Earth, we have developed a multifaceted research strategy that operates on 11 a variety of spatial, temporal, and spectral scales (Fig. 3). We have used this strategy to effectively identify and interpret alteration products of the Ferrar Dolerite as products of oxidative chemical alteration. In addition, we engaged in extensive analyses of martian orbital datasets to further characterize both the VNIR and TIR spectral signatures and relate them to our understanding of martian climate evolution. Below, we detail the analytical approach utilized in both our terrestrial and martian investigations: 2.1 Field studies Aside from the samples themselves, in situ data and sample collection provide invaluable contextual information. Experiencing the hyper-arid and hypo-thermal environmental conditions prevalent in Beacon Valley provides a uniquely personal connection to the evolution of the Ferrar Dolerite and its oxidative weathering processes. The dearth of aqueous activity and hydrous alteration is also realized during field studies. Other climate variables, including wind speed and direction, the amount of solar radiation incident upon rock surfaces, and variations in the temperature of rock surfaces can all change significantly over short temporal durations. As a result, in situ data collection and analysis is crucial for determining the magnitude and frequency of this variability and its relationship to the otherwise fossilized landscape. Aerial and orbital remote sensing, while providing an unprecedented amount of spatial coverage, suffers from limitations in spatial resolution. Variables such as surface roughness, rock cover, and subsurface properties are typically only estimated using remote datasets. The ability to ground truth these datasets establishes the link between properties beyond the resolution of the remote sensors and the large spatial scales beyond the capabilities of traditional field work. In tandem, this pairing provides the confidence 12 in extracting a range of valuable information over vast spatial expanses with remote datasets. 2.2 Remote sensing On the other end of ground truthing, remote sensing exploits the properties inherent to liquid, gaseous, and solid materials and records them with their associated spatial information. In this dissertation, we primarily utilize multi- and hyper-spectral spectroscopic datasets, which record energy either reflected or emitted from the surface following interactions with the surface materials. While characterizing the surface composition is the desired outcome of these analyses, many other factors contribute to these remote datasets. For example, planetary atmospheres contribute significantly to the recorded spectral signatures measured by remote instruments. As a result, steps must be taken to remove both the additive and multiplicative contributions from these remote datasets due to atmospheric contamination. 2.3 Laboratory analyses One such way to assess the performance of remotely acquired data is to calibrate these datasets using laboratory investigations. Laboratory analyses of a suite of diverse surface samples provide well calibrated data that should reflect that obtained using remote datasets over regions of similar properties. For example, the spectral signatures of basalts measured in a laboratory setting should be comparable to those signatures obtained from orbit over basaltic terrains, following calibration and correction of the remote dataset. Laboratory analyses exploit the compositional, structural, and textural properties of materials and their relationship to each other. For instance, in Chapter Three, we show 13 that MgO content of dolerites is directly related to the abundance of orthopyroxene (opx) within the samples. Opx has unique spectral signatures that can be measured from orbit. As a result, laboratory measurements can be used to relate the spectral properties of opx in collected samples to the MgO content of the same samples, and this relationship can then be used to estimate MgO content throughout the pure dolerite surfaces in the MDV (Salvatore et al., 2013a). In such instances, and through laboratory analyses, it is possible to map and analyze different properties of surfaces that cannot be directly measured using remote datasets. Laboratory analyses, along with sample collection and contextual information collected during field work, can also help to reconstruct the temporal evolution of a surface. In the case of surface alteration and chemical weathering, the progression of these processes with time is of critical importance. Stratigraphic relationships and other methods can be used in the field to reconstruct the relative ages of materials. With this information, laboratory analyses can be used to identify a range of differences between these samples and provide information as to the temporal evolution of alteration products. Establishing an understanding for the alteration trends can help to constrain the conditions necessary for that material to evolve in such a fashion. However, it is only through this detailed laboratory characterization that such information regarding temporal evolution can be ascertained. 3.0 Dissertation Summary The first half of this dissertation focuses on investigating the processes and products of chemical alteration of a particular lithology in the MDV of Antarctica 14 (Chapter Two). The resultant spectral signatures associated with these alteration products enable us to investigate the distribution of these alteration products throughout the MDV using multispectral VNIR and TIR orbital datasets (Chapter Three). The second half of this dissertation expands upon this work in the MDV by investigating the spectral and chemical signatures of the martian surface using both VNIR and TIR orbital spectroscopic datasets (Chapters Four and Five). The cold and dry environmental conditions of both the MDV and Mars, in addition to the presence of a “Mars-relevant” lithology in the MDV (the Ferrar Dolerite; Harvey, 2001), make this association possible. The wealth of both VNIR and TIR spectral data also provide the near-global coverage of the martian surface necessary to investigate trends in the spatial distribution of geochemical signatures. These spatial trends provide additional information regarding the climatic and volcanic evolution of Mars. Identifying an analytical technique that is capable of identifying the products of oxidative chemical weathering is necessary to associate the cold and dry chemical alteration processes in the MDV with those occurring on the martian surface. In Chapter Two, we demonstrate how VNIR and TIR spectroscopic datasets provide the clearest evidence for oxidative alteration processes. While neither the VNIR reflectance signatures nor the TIR emission signatures of oxidative alteration are individually unique, their concordance and mutual occurrence is unique from any other known alteration process. In Chapter Three, these spectroscopic signatures are investigated from orbit throughout the MDV using both VNIR and TIR multispectral orbital datasets, which reveal their heterogeneous distribution throughout the study region. 15 The last fifteen years have seen a momentous increase in the volume of VNIR and TIR orbital observations of the martian surface. These high-resolution global datasets provide the data necessary to investigate the distribution of these unique spectral signatures associated with oxidative alteration processes. In Chapter Four, we present the initial dual VNIR and TIR (termed “pan-spectral”) investigation of the martian surface, focusing on two characteristic yet disparate spectral terrains. The identification of significant abundances of oxidative alteration products, in addition to the non-detection of hydrated mineral phases, emphasizes the cold and dry nature of the martian surface during the Amazonian geologic epoch (~ 3.1 Ga to present, Hartmann and Neukum, 2001). This investigation is further expanded in Chapter Five, where all nine unique spectral shapes associated with martian low albedo (dust-free) terrains (as identified by Rogers et al. (2007) and Rogers and Christensen (2007)) are characterized using both VNIR and TIR orbital spectroscopy. The modeled mineral abundances associated with this new investigation provide new information regarding both the primary and secondary geochemical evolution of the martian surface. More localized investigations of the two regions initially studied in Chapter Four (Acidalia Planitia and Syrtis Major) reveal spatial variations and trends that further our understanding of the ancillary spectral variations associated with oxidative alteration. These additional spectral variations provide further insight into the interpretation of planetary surface compositions from orbit given the altered spectral signatures as a result of oxidative weathering processes. This dissertation concludes with a summary of regional- and global-scale VNIR and TIR spectral investigations, with implications for the evolution of the martian surface as a function of time, chemical alteration, and climate change. Outstanding questions and 16 future research directions are also highlighted, as the characterization of the martian surface is a continuous process that is dependent upon the available datasets and the imagination of planetary scientists to pose new and exciting hypotheses. 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References include [1] Hartmann and Neukum (2001); [2] McKay et al. (1996); [3] Treiman (2005); [4] Nyquist et al. (2001); [5] Carr and Head (2010); [6] Fassett and Head (2008); [7] Ehlmann et al. (2011); [8] Bibring et al. (2006). Figure 2. A multispectral map of the McMurdo Dry Valleys, highlighting the location of Beacon Valley, from Salvatore et al. (2013a). The map colors represent the following spectral parameterizations: Red maps the strength of the broad 1 μm absorption feature, which is unique to the Ferrar Dolerite. Green maps the spectral slope in the near-infrared, which is strongest in the quartz- and feldspar-bearing lithologies of the Beacon Supergroup and the basement granites, granodiorites, and gneisses. Blue 25 maps the thermal infrared spectral feature associated with the presence of quartz, and is uniquely high in the Beacon Supergroup where quartzites dominate. Ice and snow has been masked from the multispectral map and is overlain for effect. The floor of Beacon Valley is dominated by quartz-normative doleritic clasts, which are characteristically purple in this color scheme. Figure 3. A conceptual model of the analytical techniques used in this dissertation. 26 Chapter 1, Figure 1. 27 Chapter 1, Figure 2. 28 Chapter 1, Figure 3. 29 Chapter Two: Development of alteration rinds by oxidative weathering processes in Beacon Valley, Antarctica, and implications for Mars. M. R. Salvatore1, J. F. Mustard1, J. W. Head1, R. F. Cooper1, D. R. Marchant2, and M. B. Wyatt1 1 Department of Geological Sciences, Brown University, Providence, RI 02912, USA 2 Department of Earth Sciences, Boston University, Boston, MA 02215, USA In press in its current form in: Geochimica et Cosmochimica Acta DOI: 10.1016/j.gca.2013.04.002 30 Abstract Alteration of fresh rock surfaces proceeds very rapidly in most terrestrial environments so that initial stages of modification of newly exposed surfaces are quickly masked by subsequent aqueous weathering processes. The hyper-arid and hypo-thermal environment of Beacon Valley, Antarctica, is limited in terms of available liquid water and energy available for alteration, which severely slows weathering processes so that the initial stages of alteration can be studied in detail. We report on the nature of initial chemical alteration of the Ferrar Dolerite in Beacon Valley, Antarctica, using a multiplicity of approaches to characterize the process. We suggest that initial chemical alteration is primarily driven by cation migration in response to the oxidizing environment. Morphological studies of altered rock surfaces reveal evidence of small- scale leaching and dissolution patterns as well as physical erosion due to surface weakening. Within the alteration front, mineral structures are largely preserved and alteration is only indicated by discrete zones of discoloration. Mineralogical investigations expose the complexity of the alteration process; visible/near-infrared reflectance and mid-infrared emission spectroscopy reveal significant variations in mineralogical contributions that are consistent with the introduction of oxide and amorphous phases at the surfaces of the rocks, while X-ray diffraction analyses reveal no definitive changes in mineralogy or material properties. Chemical analyses reveal large- scale trends that are consistent with cation migration and leaching, while small-scale electron microprobe analyses indicate that chemical variations associated with magmatic processes are still largely preserved within the alteration rind. This work confirms the incomplete and immature chemical alteration processes at work in the McMurdo Dry 31 Valleys. Liquid water is not a significant contributor to the alteration process at this early stage of rind development, but assists in the removal of alteration products and their local accumulation in the surrounding sediments. These results also suggest that the McMurdo Dry Valleys (and Beacon Valley, in particular) are relevant terrestrial analogs to hyper- arid and hypo-thermal alteration processes that may be dominant on the martian surface. 1.0 Introduction Igneous rocks are immediately susceptible to chemical alteration upon exposure to the terrestrial atmosphere (Wilson, 2004). The rate of alteration is directly related to the temperature and chemistry of both the water and the atmosphere to which these precursor materials are exposed (Lasaga, 1984). These variables also control the relative solubility of the constituent minerals and the transport coefficients for the mineral ionic components and, consequently, the types of products that will form during chemical alteration. Identifying locales where the resultant alteration products are in relative equilibrium with the environment in which they formed can yield valuable information regarding the climatic variables and starting compositions from which the weathering products were derived. In warm and wet climates, mineral dissolution and elemental leaching occur rapidly and on relatively short geologic timescales. For example, in the Hawaiian Islands, > 90% of Ca, Mg, and Si are leached from their basaltic precursor soils after approximately 20,000 years during subaerial weathering in warm and wet tropical climates, resulting in heavily leached oxisols (Chadwick et al., 1999). Cold and/or arid climates, however, experience much slower rates of chemical alteration. For example, mature coatings and varnishes form on rock surfaces in arid environments on the order of 32 10-6 – 10-5 m ka-1 and often contain immature alteration products (i.e., silica glaze, Fe/Mn oxides) (Dorn, 2009; Liu and Broecker, 2000). Modest amounts of chemical alteration have also been observed in the coldest and driest locations on Earth. Previous studies have shown that the tholeiitic Ferrar Dolerite of the McMurdo Dry Valleys (MDV) of Antarctica has undergone relatively minor chemical alteration despite prolonged (up to 106 yr) exposure to the environment (Campbell and Claridge, 1987). The most substantial alteration products observed on dolerites in the MDV are pervasive, red/brown alteration rinds on rock surfaces (Glasby et al., 1981) with more soluble salt species present where the evaporation of liquid water is focused (Bockheim, 2002). However, debates continue as to whether these rinds are depositional in nature (e.g., Staiger et al., 2006) or the result of leaching and alteration of the primary lithology to secondary products (e.g., Chevrier et al., 2006). Throughout this manuscript, the term “rind” will be used to describe internally derived alteration horizons, while the term “coating” will be reserved to describe externally derived depositional features (Fig. 1). Desert varnishes and other depositional coatings are commonly found in terrestrial desert environments and their chemistry and formation mechanism are highly variable (Dorn, 2009). The presence of lithobionts can result in the formation of biofilms and other biological coatings where conditions allow (Viles, 1995). Abiotic mechanisms include the cementation of dust, clays, metals, or other mobile element species to rock surfaces (Dorn, 2009). Most coatings lie uncomfortably on the surfaces of rocks, which can be easily identified in thin section. Rinds, however, do not exhibit a discontinuity between the underlying unweathered rock and the altered surface above. Instead, rinds are characterized by a gradational transition 33 from unaltered rock interiors to their altered surfaces (e.g., Sak et al., 2004; Hausrath et al., 2008), as was first described in Antarctic dolerites by Glasby et al. (1981). Glasby et al. (1981) therefore conclude that alteration rinds must be derived from leaching of material from the inner regions of rocks and subsequent oxidation and alteration, rather than an accretionary or externally derived mechanism. This definition of an alteration rind is adopted throughout this study and the mechanism of alteration rind formation is investigated further. Building on the significant contributions of these previous works, we have integrated morphological, chemical, and mineralogical analyses of a suite of representative dolerites in a well-characterized environmental setting in order to bring a range of new techniques to this problem. This integrated approach is designed to address the following questions: What are the alteration processes and products associated with the chemical alteration of tholeiites under hyper-arid and hypo-thermal conditions? Additionally, what is the nature of the pervasive alteration rinds on doleritic clasts and how are these rinds related to the environment under which they formed? How do rinds differ from coatings and what are the fundamental differences in processes and timescales? In this study, we investigate the chemical weathering of the Ferrar Dolerite in Beacon Valley, the coldest, driest, and most stable of the MDV (Marchant and Head, 2007) (Fig. 2). We both qualitatively and quantitatively compare the altered surfaces of 14 doleritic clasts to their unaltered interiors by integrating morphological, chemical, and mineralogical analyses. This further understanding of the unaltered and altered lithologies, in conjunction with an established understanding of the geologically recent 34 environmental conditions, allows us to unravel the process of initial chemical alteration that is dominating dolerite surfaces in Beacon Valley. 2.0 Background Chemical alteration throughout the MDV and the resultant alteration products have been extensively studied for more than 50 years. Early studies of dolerite alteration and the development and preservation of alteration rinds is synthesized in Campbell and Claridge (1987) and references therein, where they are primarily described as desert varnishes or “staining”. None of the early studies identified a biological contribution to the alteration process, which differs from mid-latitude desert varnishes that commonly contain a significant biological component (Dorn, 2009). These early investigations describe how Fe is weathered out of ferromagnesian minerals and redeposited as coatings on quartz and feldspar grains on the rock surface (Campbell and Claridge, 1987). Initial chemical studies revealed that the rinds and coatings on dolerites are enriched in Fe and Si, but not Mn, which also suggests that they are not genetically related to traditional desert varnishes in hot desert regions (Glasby et al., 1981; Talkington et al., 1982). Allen and Conca (1991) focused on the formation and development of etch pits on dolerite surfaces. They document that solar heating of dark rock surfaces results in the melting of snow trapped in surface cracks and pits. As liquid water is focused and concentrated in surface etch pits, evaporation results in the precipitation of a variety of soluble salt species, followed by the crystallization of illite and quartz (Allen and Conca, 1991). This material is then easily scoured and removed by aeolian processes. A subsequent analysis of etch pits and their relationship to martian surface observations 35 (Head et al., 2011) corroborates these earlier studies and discusses how more extensive physical and chemical alteration and the resultant formation of etch pits is dominated by transient episodes of surface wetting controlled by snowmelt and solar heating. These transient processes can potentially dominate the physical and chemical properties of rock surfaces in locations where chemical and physical erosion are limited (Head et al., 2011). Other recent alteration studies have focused on the Ferrar Dolerite largely due to its compositional similarities to martian basalts (Harvey, 2001; Chevrier et al., 2006). In contrast to the results of Glasby et al. (1981), Chevrier et al. (2006) identify a decrease in Si in the altered surface of a weathered dolerite relative to its unweathered interior, in addition to the formation of (oxy)hydroxides and “porous” textures at the surface of their analyzed sample. Staiger et al. (2006) analyzed several dolerites from Vernier Valley and concluded that “varnish” thickness increases with increasing exposure age. In addition, VNIR reflectance and MIR emission spectroscopic studies have been performed by Wyatt et al. (2008) and Salvatore et al. (2010a; 2011a; 2011b; 2011c) in conjunction with various other analytical techniques. Their results indicate substantial spectral variations between dolerite interiors and their altered surfaces with only minor mineralogical or chemical variations. Many outstanding questions remain following these foundational studies: (1) What is the true morphologic nature of these alteration rinds (coatings, staining, varnishing)? Such information would help to determine the formation mechanism and extent of chemical alteration and leaching experienced by the dolerites in Beacon Valley. (2) What are the chemical and mineralogical signatures of the alteration products and how do they differ from the unaltered rock interiors? The alteration and leaching of 36 distinct mineral and elemental species can help to constrain the necessary environmental conditions. Lastly, (3) what is the process that forms the observed alteration signatures and what can it tell us about the environment under which these signatures formed? Our detailed analyses of samples from the McMurdo Dry Valleys aim to address these questions. 3.0 Geographic Setting Beacon Valley, Antarctica (77º 49’ S, 160º 39’ E), is the southernmost of the McMurdo Dry Valleys (Fig. 2). In addition, its latitude, distance from the Ross Sea (~ 70 km), mean elevation of approximately 1200 m HAE (height above the World Geodetic System 1984 (WGS84) ellipsoid), and proximity to the East Antarctic Ice Sheet make Beacon Valley one of the coldest, driest, and, as a result, most stable valleys of the MDV (Marchant and Denton, 1996; Marchant and Head, 2007). It has a mean annual temperature of -22º C (Doran et al., 2005) and mean annual water equivalent precipitation of less than 10 mm yr-1 (Schwerdtfeger, 1984; Fountain et al., 2009). Beacon Valley is largely dominated by atmospheric conditions generated over the East Antarctic Ice Sheet; deposition of snow derived from the ice sheet and frequent gravity-driven katabatic wind events are two such examples. This is confirmed by the widespread distribution and abundance of nitrate salts, which are derived from snow blown off of the East Antarctic Ice Sheet and are different from the sulfates and chlorides found in valleys closer to the Ross Sea (Bao and Marchant, 2006). Stratified and undisturbed ash deposits found on the floor of Beacon Valley have been dated to 8.1 Ma by Sugden et al. (1995), verifying the antiquity and stability of the valley surface. The stability of the surface and the absence 37 of fluvial activity make Beacon Valley an ideal natural laboratory for weathering experiments in cold and hyper-arid terrestrial environments. The walls of Beacon Valley are composed of Devonian-Triassic Beacon Supergroup sandstones, siltstones, and orthoquartzites and intrusive sills of the Jurassic Ferrar Dolerite (McElroy and Rose, 1987). These dolerites are shallow intrusive igneous rocks composed primarily of plagioclase and pyroxene that underwent minor deuteric alteration during their emplacement (McAdam, 2008). The chemistry and mineralogy of the Ferrar Dolerite has been extensively studied (e.g., Gunn, 1962; 1963; 1965; 1966; Kyle et al., 1981; Heimann et al., 1994; Marsh, 2004; Bédard et al., 2007). The exposure of these sills was initiated by substantial uplift and tilting of the Transantarctic Mountains that began ~50 Ma (Gleadow and Fitzgerald, 1987) and continued through the late Oligocene and early Miocene (~25 Ma) (Denton et al., 1993). Beacon Valley is partially filled by a cold-based (dry) debris-covered glacier with a till dominated by doleritic clasts, fragments, and sediments, the age and structure of which has also been extensively studied in previous investigations (e.g., Sugden et al., 1995; Marchant et al., 2002). In upper Beacon Valley, the till material originates from rockfall near the head of several tributary glaciers (e.g., Mullins Valley and Friedman Valley) and is transported downhill into Beacon Valley as a sublimation till (Levy et al., 2006; Marchant and Head, 2007; Kowalewski et al., 2010; Kowalewski et al., 2012). As a result, this “geologic conveyor belt” provides the opportunity to study alteration and erosion with constraints on surface exposure age. Marchant and Head (2007) designated Beacon Valley as the archetype of the Stable Upland Zone (SUZ) in their microclimate architecture of the MDV (Fig. 2). In 38 this zone, liquid water is limited to minor amounts of snowmelt, typically only on rock surfaces that have been heated by solar radiation, with no fluvial activity present. Pitted rocks are common in the SUZ and are the result of snowmelt accumulation on rock surfaces, localized aqueous alteration, and scouring by aeolian processes (Allen and Conca, 1991; Head et al., 2011). Sublimation polygons, formed by thermal contraction of subsurface glacial ice or permafrost with excess ice, dominate surfaces in the SUZ as a result of the lack of significant surface melting and saturated active layer cryoturbation. At lower elevations and closer to the coast, the valleys transition from the SUZ to the Inland Mixed Zone (IMZ), characterized by localized transient fluvial activity and associated intermittent subsurface fluvial activity, discontinuous ice cement, and sand- wedge polygons. The warmest and wettest of the microclimate zones is the Coastal Thaw Zone (CTZ), which is located at the lowest elevations and closest to the Ross Sea. Seasonal fluvial activity results in channelized flow, evaporative salt accumulations, and ice-wedge polygons. All of the rock samples analyzed in this study are from central Beacon Valley, well within the SUZ, and have experienced only transient liquid water from snowmelt and no fluvial activity. However, the presence of some minor amounts of liquid water is required to explain the observed surface pitting on many samples (Allen and Conca, 1991; Head et al., 2011) as well as the salt accumulations and horizons present under many rocks and within the underlying regolith, respectively, as is discussed in Bao and Marchant (2006), Marchant and Head (2007), Bao et al. (2008), and Head et al. (2011). 39 4.0 Methods Fourteen dolerite float samples (largely flat-lying and approximately 103-104 cm3 in size) were collected along a 2.5 km transect through upper Beacon Valley. Landscape age in the study area is determined from a combination of cosmogenic-nuclide analyses of surface clasts (Marchant et al., 2007; Schaefer et al., 2000) and 40Ar/39Ar dating of undisturbed ash fall deposits (Marchant et al., 1996; 2002). Using these methods, Marchant et al. (2007) determined that the minimum duration for rock exposure in the study area is ~0.64 Ma, and may be considerably greater (Fig. 2). This finding is consistent with measured horizontal ice flow velocities (as derived from repeat satellite interferometry (Rignot et al., 2000)), which suggest that transport of supraglacial debris from the headwall source in Mullins Valley to the study site in upper Beacon Valley could take hundreds of thousands of years. Each of the fourteen dolerite samples were selected based on their apparent antiquity, estimated based on the visual extent of rind development (continuous oxidized surface, no evidence of flaking, glossy and specular sheen), the presence of a horizontal surface with ventifaction along the edges of the sample, and surface pitting, which is expected to increase in abundance and depth as a function of age (e.g., Staiger et al., 2006; Marchant and Head, 2007). Rocks were subsampled into chips, powders, and thick/thin sections at Brown University for subsequent morphological, mineralogical, and chemical analyses. Rock chips were created by fragmenting larger samples using a rock hammer to avoid the influence of saw abrasion on the different spectroscopic techniques, and also to avoid the use of water or solvents to help prevent the dissolution of soluble species. Thin and thick sections were created using standard practices, which include preparation using water as 40 a cleaning and lubricating agent. Although the epoxies used during this process were not impregnated with hardening agents, the coherent crystalline nature of the samples, both within and away from the alteration rind, prevented any flaking, cracking, or other types of damage to the samples. In an attempt to isolate the uppermost altered surfaces of these rocks, powders were created using a diamond-tipped rotary drill to abrade the outer surface and to remove the alteration rind from the underlying unaltered rock. This procedure was done without the use of water or solvents, preventing the possibility of mineral or chemical dissolution during the sample preparation process. Based on visual observations and test samples, it was determined that the average sampling depth of this method is roughly 500 μm. The test samples, which consisted of dolerites not analyzed in this study, were optically inspected to determine rind thickness prior to abrasion. Following abrasion and surface removal, thick sections were created to determine the extent of surface material that was removed. The average sampling depth was found to be approximately 500 μm. It should be noted that, in some instances, unaltered rock interiors may contribute to the rock powders derived from the altered surfaces. This inevitable consequence of sample preparation should not influence the analyses, as we are investigating the nature of chemical alteration and not the terminal products of alteration. Powders derived from the unaltered centers of the rocks were produced using the same method to ensure consistency and homogeneous sampling. Several laboratory techniques were implemented to investigate the formation processes and nature of alteration rinds on the Ferrar Dolerite (Table 1). Rind morphology was investigated using a combination of thin and thick section optical 41 microscopy and scanning electron microscopy (SEM), which was used to investigate the character and variability of natural rock surfaces. Chemical analyses were performed using a combination of electron microprobe analyses (EPMA), inductively coupled plasma atomic emission spectroscopy via flux fusion (FF/ICP-AES), and Mössbauer spectroscopy to determine iron oxidation state. These techniques characterize the chemical composition of the samples at a variety of scales to define both the primary chemical properties of the dolerites under investigation as well as the extent and nature of chemical modification in the alteration rinds. Sample mineralogy was assessed using visible/near-infrared (VNIR) reflectance and mid-infrared (MIR) emission spectroscopy, X-ray diffraction (XRD) analyses, and Mössbauer spectroscopy. The combination of both intrusive (e.g., XRD and Mössbauer spectroscopy) and non-intrusive (e.g., VNIR and MIR spectroscopy) mineralogical analyses helps to link remote observations with laboratory measurements. SEM analyses were performed at the University of Minnesota’s LacCore Facility using a Hitachi TM-1000 Table-top SEM with a Tungsten filament and an accelerating voltage of 15 kV. Backscattered electron (BSE) images ranging from 20x – 10,000x magnification were collected to investigate the morphology of the altered surfaces as well as broad compositional variations between mineral grains and surface features. EPMA analyses were performed at the Massachusetts Institute of Technology’s Electron Microprobe Facility using wavelength dispersive spectrometry (WDS) on a JEOL JXA-8200 Superprobe with a LaB6 electron gun, an accelerating voltage of 15 kV, and a 10 nA beam current. Quantitative chemical analyses were collected in addition to 42 qualitative elemental mapping products to identify spatial variations in major element chemistry. ICP-AES analyses were performed at the Brown University Environmental Chemistry Facility. These analyses were utilized to measure the geochemistry of powdered samples in the fashion described by Murray et al. (2000). Powdered rock surfaces and interiors were divided into 40 mg aliquots, mixed with 160 mg LiBO2, and fused for 10 minutes at 1050° C. The melts were quenched in 20 mL of 10% HNO3 and agitated for one hour. The samples were then filtered through 0.45 µm filters and diluted in additional 10% HNO3. The resultant liquids were analyzed using a JY2000 Ultrace ICP Atomic Emission Spectrometer. Samples were analyzed for Si, Al, Fe, Mg, Ca, Na, K, P, Mn, and Ti using a Gaussian peak search technique and the results were calibrated and converted to weight percentages using a series of blanks and geochemical standards that were processed in the same fashion as the samples. All samples, standards, and blanks were run in duplicate to increase the robustness of the measurements. Twenty two standard measurements were run concurrently with the sample analyses to both assess the analytical uncertainty and to convert the sample measurements to oxide weight percentages. Mössbauer spectroscopy was performed at the Mount Holyoke College Department of Astronomy on three pairs of sample powders. Seventy-five mg powdered aliquots were analyzed at a temperature of 295 K on a WEB Research Co. model WT302 spectrometer using a 57Co source. The ability for Mössbauer spectroscopy to identify iron-bearing phases, to quantitatively assess the distribution of iron among these phases, 43 and to determine the distribution of iron among its oxidation states makes it a powerful tool to assess both the chemistry and mineralogy of samples. VNIR reflectance spectroscopy was performed at the Brown University Keck/NASA Reflectance Experiment Laboratory (RELAB) using a bidirectional reflectance (BDR) spectrometer, which acquires spectra between 0.32 and 2.55 µm at a 5 nm spectral sampling interval using a photomultiplier and InSb detectors (Pieters, 1983; Mustard and Pieters, 1989). Illumination and emergence angles were fixed at 30° and 0°, respectively. Both rock chips and powders were measured in the BDR spectrometer under identical experimental setups, although rock chips were slowly rotated to reduce artifacts associated with viewing or illumination geometries. MIR emission spectroscopy was performed at the Stony Brook University Vibrational Spectroscopy Laboratory using a Nicolet 6700 FTIR Spectrometer, which utilizes a deuterated L-alanine doped triglycine sulfate (DLaTGS) detector and CsI window. Measurements were made between 2000 cm-1 and 200 cm-1 at a resolution of 4 cm-1 using a CsI beamsplitter. As is standard in MIR emission spectroscopy, samples were held at 80º C to improve signal. Additional information regarding MIR measurements and calibrations can be found in Ruff et al. (1997). Only macroscopically flat rock fragments were analyzed using VNIR and MIR spectral techniques, minimizing the effects of microscale sample topography on these analyses. XRD measurements were performed at Brown University’s XRD Facility (Siemens D5000 Diffraktometer, Cu radiation source, all samples) and the University of Minnesota’s LacCore Facility (Rigaku MiniFlex CRD, Cu radiation source, all samples). XRD patterns were collected at Brown University in an attempt to perform quantitative 44 analyses, and patterns were collected at the LacCore Facility to understand and better quantify the potential contributions from smectite clays. The D5000 instrument at Brown University has been enhanced by the addition of a Gobel mirror assembly to increase the system intensity and resolution. The system utilizes a standard powder XRD setup, with the powder loaded into a sample holder that is positioned between an X-ray tube and detector. The sample stage and detector are rotated during the analysis to sweep through the full 2θ range. This setup has a 2θ range and resolution of 3° - 85° and 0.1°, respectively, and the scanning interval for each analysis was 0.2° per minute. Sample sizes were approximately 100 mg and sieved to < 63 µm. Sample preparation for the MiniFlex instrument at the University of Minnesota included agitation and suspension of a powdered sample (~250 mg, sieved to < 63 µm) in ethanol and evaporated onto an aluminum sample holder. Each sample was prepared with a calcite spike to improve quantitative statistics. Samples were run both before and after spiking to ensure that no data were lost during the sample preparation process. The MiniFlex instrument geometry is nearly identical to that of the D5000, has a 2θ range and resolution of 4° - 65° and 0.05°, respectively, and a scanning interval of 1° per minute. 5.0 Results The petrography of the samples analyzed in this study is consistent with prior studies of the Ferrar Dolerite (e.g., Elliot and Fleming, 2004). Mean grain size throughout our sample suite is highly variable, from equigranular subophitic textures with grain sizes less than 100 μm, to 800 μm subhedral and unoriented ophitic textures. This variability is due to the initial location of the dolerite clast within the sill; finer grained 45 textures are derived from the rapidly cooling sill margins, while coarser grained textures are derived from the interior of the sills. Mineral proportions are also variable at the scale of the thin sections, with ratios varying between 3:1 plagioclase feldspar and pyroxene, and vice versa. Interstitial glass is common throughout the sample suite, and quartz is present as a minor interstitial phase in some of the samples, and the abundance of these phases (up to ~25% in the least crystalline samples) is highly variable. Largely euhedral chlorite pseudomorphs have also been observed in some samples and confirmed through EPMA analyses. However, the observed chlorite abundances are minor (less than 1 vol.%, based on optical and EPMA analyses) and, as a result, their spectral, chemical, and mineralogical contributions are likely to be minor as well. 5.1 Chemistry The bulk chemistry of interior and surface powders was determined by FF/ICP- AES. These analyses show only subtle variations in major element chemistry between the rock interiors and their corresponding alteration rinds (Fig. 3; Table 2). Of particular interest are the trends of Ca and Mg, which are systematically depleted in the alteration rinds relative to their unaltered interiors, and Na and K, which are systematically enriched in the alteration rinds relative to their unaltered interiors (Fig. 4). While the Ca and Na interior and alteration rind measurements are within one standard deviation, the Mg and K measurements are outside of one standard deviation. The calculated Mössbauer isomer shift relative to metallic iron (δ), quadrupole splitting (ΔEQ) parameters, and spectral peak information are provided in Table 3. Mössbauer spectroscopy of three sample pairs (Sample 04, Sample 10, Sample 12) confirms a systematic increase in Fe3+/FeTotal from an average of 0.21 to 0.35 from rock 46 interiors to the alteration rinds, respectively (Fig. 5; Table 3). This technique identifies the ferrous iron component as principally pyroxene or chlorite (indistinguishable in Mössbauer spectroscopy due to their similar crystal structures), with no indication of ferrous iron in feldspar due to its low total Fe content. Based on other spectroscopic, chemical, and optical analyses, we conclude that pyroxene and not chlorite is the dominant ferrous component present in the dolerite samples. This technique is also able to determine that the ferric iron is present in either its original primary mineral phases or in nanophase ferric iron oxides; crystalline iron oxides and oxy-hydroxides including hematite and goethite have not been identified, indicating that mature phases are not being produced during the alteration process. The nearly pristine crystalline morphologies observed within the alteration rinds by optical microscopy and SEM confirm that no mature alteration phases (e.g, hematite, goethite) are present as large crystals within the altered zones. The subtlety of chemical alteration is also confirmed in EPMA analyses, which verifies that, on the basis of these measurements and analyses, the relative abundances of major cations are indistinguishable between the interiors and alteration rinds (Fig. 6). In addition, compositional zoning associated with an evolving magmatic chemistry during crystallization are visible both within the unaltered rock interiors and the alteration rinds (white arrows, Fig. 6). More intense alteration processes likely would have masked the minor chemical variations that we observe, and their preservation within the alteration rinds of several samples supports the interpretation that the rinds are only minimally altered. 47 5.2 Mineralogy XRD analyses on sample powders were utilized to determine the mineralogical constituents of the sample interiors and alteration rinds. XRD patterns (Fig. 7) show diagnostic peaks that correspond to the presence of quartz, plagioclase, and pyroxene. No additional peaks were definitively identified in alteration rinds that were not present in the unaltered interiors. Additionally, no peaks disappeared in the patterns of the alteration rinds when compared to those of the unaltered interior. These observations are consistent with the EPMA analyses, which indicate that the major mineralogy and mineral chemistries both within and outside of the alteration rind are identical. Weak, broad, and diffuse peaks associated with either poorly crystalline materials (e.g., glassy intergranular matrix) or amorphous materials (e.g., amorphous Fe-O-H phases, amorphous or pre-crystalline clay minerals) are present in the XRD patterns of both interiors and alteration rinds centered at approximately 23º 2θ (Fig. 7). The relative strengths of these broad peaks are similar, indicating that the volumetric component of amorphous or poorly crystalline components does not significantly vary within alteration rinds relative to rock interiors. These results suggest that no detectable changes are apparent between rock surfaces and their corresponding interiors. Attempts at performing quantitative mineralogical analyses on these XRD data proved problematic for several reasons. First, the signal associated with most individual measurements was low compared to instrumental noise. Second, quantitative modeling utilizing Rietveld refinement (Bish and Post, 1993; Hillier, 2000) suggested that nontronite should be present at abundances greater than 30% in both dolerite interior and surface powders despite no additional evidence for the presence of nontronite in any 48 other analytical dataset. Chlorite, which can sometimes be mistaken for nontronite in XRD analyses (e.g. Granger and Raup, 1969), was also modeled at ~5% abundance in both interiors and surfaces, suggesting that the identification of nontronite was not solely a false identification of chlorite at similar abundances. The presence of nontronite and/or chlorite at these abundances can be identified with great confidence using VNIR spectroscopy by their diagnostic absorptions at 2.29 μm and 2.35 μm, respectively, and using MIR spectroscopy by their diagnostic absorptions at 530 cm-1 and 1026 cm-1, respectively. The absence of these diagnostic features suggests that neither nontronite nor chlorite are abundant at spectrally significant quantities (> 20%; Ehlmann et al., 2012; Ruff and Christensen, 2007). No evidence of microscopic fracture networks was observed in any of the samples, suggesting that the modeled nontronite abundances are not the result of complex microfracture network formation and alteration. Third, significant inter-laboratory variability in measured sample patterns precludes the definitive quantification of mineral abundances. This inter-laboratory variability results in considerable variations in modeled mineral abundances. For these reasons, quantitative analyses of these XRD data proved indeterminate. We therefore rely on several other proven techniques to constrain the geochemical and mineralogical variations between sample surfaces and their unaltered interiors. VNIR reflectance spectroscopy reveals substantial variations between rock interiors and their corresponding surfaces (Fig. 8). Rock interiors are characterized by a broad and complex absorption feature centered near 1.0 μm that is attributed to pyroxene with possible contributions from plagioclase and/or chlorite (Clark, 1999). A weaker and broader absorption feature centered near 2.0 μm is also attributable to pyroxene. Narrow 49 absorptions near 1.4 μm, 1.9 μm, and 2.3 μm indicate minor amounts of OH-- and H2O- bearing phases (e.g., Bishop et al., 2002). While preserving the broad 1.0 μm absorption feature, VNIR spectra of rock surfaces exhibit a substantial strengthening of the Fe2+-Fe3+ charge-transfer absorption feature present at wavelengths < 0.6 μm (Morris et al., 1985), resulting in a strongly positive spectral slope between 0.5 μm and 0.7 μm. The relative lack of structure associated with this broad absorption feature is indicative of a weakly crystalline or non-crystalline ferric iron phase(s) or the presence of Fe3+ within a primary crystal structure, consistent with our Mössbauer results. The presence of crystalline ferric iron phases, including hematite and/or goethite, would produce diagnostic absorption features between 0.5 μm and 0.8 μm that are not observed in the spectra of dolerite surfaces. The 2.0 μm pyroxene absorption feature is largely masked by a negative spectral slope, which is strongly suggestive of the presence of strong OH and H2O fundamental absorption near 3.0 μm (Clark et al., 1990). The 1.4 μm and 1.9 μm hydration features in the spectra of rock surfaces are stronger than those observed in the rock interiors. However, the 2.3 μm absorption, which is a combination tone of metal- OH bends and stretches (Clark et al., 1990; Bishop et al., 2002), remains extremely weak (measured band depths of 0.33% and 0.68% for average interiors and surfaces, respectively), suggesting that the increased hydration is not associated with a significant increase in smectite clays. MIR emission spectroscopy is sensitive to the vibrational motions that occur at fundamental frequencies within crystal lattices that are indicative of crystal structure and chemical composition (e.g., Farmer, 1974; Christensen et al., 2001). MIR emission spectra of sample interiors and surfaces are shown in Figure 9. Emission spectra of rock 50 interiors show broad and complex reststrahlen bands (regions of maximum absorption due to high absorption coefficients) indicative of the presence of several primary igneous phases. Conversely, rock surface spectra have much narrower reststrahlen bands centered near 1090 cm-1 and 475 cm-1 that lack the structure and complexity found in the interior spectra, indicating that the primary igneous mineral signatures are being masked by another spectral component. MIR emission spectra of mineral components in a mixture, such as in a rock, are shown to combine linearly (Gillespie, 1992; Adams et al., 1993) and has been demonstrated for laboratory spectra of minerals (Ramsey and Christensen, 1998) and rocks (Feely and Christensen, 1999). As shown in these studies, MIR emission spectra of mineral mixtures reflect the areal abundance of the mineral components. As a result, MIR emission spectra can be modeled using linear retrieval algorithms and a suite of spectral endmembers. We have used the linear spectral deconvolution algorithm developed by Ramsey and Christensen (1998) and a customized spectral library (Table 4) to estimate the relative spectral contributions from different endmember minerals. Our endmember library is derived from the Rogers and Christensen (2007) skeleton library used to unmix martian basaltic terrains from orbit, although our library also contains several additional phyllosilicate and glass endmembers. The reduction of spectral endmember libraries is a widely used strategy to (1) reduce the number of endmembers that exhibit similar spectral shapes and to (2) only incorporate those components that are potentially present as to avoid spurious mineral identifications (e.g., Feely and Christensen, 1999; Hamilton and Christensen, 2000; Wyatt et al., 2001; Rogers and Christensen, 2007). The exclusion of a significant spectral endmember will result in 51 high RMS errors and the overprinting of those spectral signatures on the residual spectrum. The absence of either of these indicators suggests that our modeling is accounting for the majority of spectral variations. The results of this linear unmixing model are presented in Figure 10, along with the modeled endmember abundances for both averaged dolerite interiors and averaged dolerite surfaces. Dolerite interiors are best modeled by a combination of plagioclase (52 vol.%), pyroxene (21 vol.%), and synthetic Si- and K-rich glass (“SiK-Rich Glass”, 16 vol.%). While mineral proportions at the scale of the MIR measurements (~ 1 cm) are highly variable, this mineral assemblage is consistent with thin section observations and with qualitative analyses of XRD patterns. Dolerite surfaces are best modeled as pyroxene (32 vol.%), SiK-Rich Glass (21 vol.%), smectite clays (20 vol.%), and feldspar (13 vol.%). Similar to the modeled mineralogy of dolerite interiors, the combination of pyroxene and feldspar is consistent with other mineralogical and optical analyses. The modeled abundance of smectites, which is almost entirely modeled as Ca-rich montmorillonite (19 vol.%), is inconsistent with other analyses, particularly VNIR spectroscopy. In the VNIR, montmorillonite exhibits a strong absorption feature present at 2.2 μm, which is absent in VNIR spectra of dolerite surfaces. In the MIR, montmorillonite is being preferentially selected by the unmixing model to account for the strong absorption feature present at 465 cm-1. However, this spectral feature is not unique to smectites, but is common in both amorphous materials (such as glasses) and smectites. The lack of a strong dioctahedral smectite absorption feature at 530 cm-1, as well as the lack of a strong 2.2 μm absorption feature in the VNIR, strongly suggests that montmorillonite (and, more generally, smectites) is not a significant spectral phase and can instead be accounted for by the presence of additional 52 amorphous materials. To test this hypothesis, smectites were excluded from the endmember library and dolerite surfaces were remodeled. SiK-Rich Glass was indeed used to replace the previously modeled smectite component, increasing in modeled abundance from 21 vol% to 39 vol.%, and only slightly decreasing the model’s overall goodness of fit (indicated by the root-mean-squared error (RMSE)) from 0.507% to 0.581%. SEM analyses were also able to observe unique mineralogical features on dolerite surfaces. The white arrows in Figure 11a and 11b highlight etching morphologies that appear to be targeting lamellae within primary mineral grains. Lamellae have been observed in both pyroxene and plagioclase grains within our sample suite; however, we are unable to ascertain the host mineralogy of these etch patterns based on these SEM analyses. Additionally, the small scale of these lamellae (on the order of 1 μm wide, Figure 11b) precludes analyses using traditional EPMA analytical techniques, which have a resolution on the order of 5 μm. The small scale of these lamellae prevents us from determining the exact chemistry of the etched material. 5.3 Morphology Thin and thick section optical analyses of all fourteen samples clearly exhibit alteration rinds that are characterized by at least one discolored zone that, while locally variable, gradationally terminates at a near-uniform depth in each sample. The rinds transition to the unaltered interior several hundred micrometers to several millimeters within each sample (Fig. 12). These rinds can vary in thickness across very short spatial scales (< 1 mm), although their thickness typically parallels the morphology of the rock surfaces. The thickness of the discolored zones appears to be partially controlled by 53 underlying grain size, with coarser grained samples exhibiting thicker alteration rinds than finer grained samples. In all of the analyzed samples, primary crystal structures are preserved within the alteration rinds and there are no apparent discontinuities between the rock interior and the rinds (Fig. 12), consistent with the absence of depositional coatings. The gradational transition between the altered surfaces and unaltered interiors also suggests an alteration process that modifies the underlying rock in response to its surrounding environment. Figure 12 shows zones of moderately oxidized dolerite just beneath the rock surfaces (A”). These zones grade into zones of lesser oxidation (A’), which extend several millimeters into the rock interiors. A’ is identified by its less discolored nature, which is intermediate between the highly discolored A” zone and the underlying and unaltered (U) zone that exhibits no discoloration. Primary crystal structure is observed throughout both the oxidized and unoxidized zones, consistent with inward alteration of the primary rock texture, and not the depositional morphology expected from a secondary rock coating. The dolerite in Figure 12b has a slightly larger grain size than the other examples (~700 μm average length, as compared with ~225 μm average length in Figure 12d). As a result, the area of maximum discoloration is substantially thicker (~2.60 mm) in Figure 12b than that observed in the other examples (~0.85 mm for Figure 12d). SEM measurements of dolerite surfaces show pit development on a variety of spatial scales (~20 – 300 μm), flaking, and etching and dissolution morphologies (Fig. 11). Figure 11c shows evidence for extensive surface cracking (white arrow) and flake development (black arrow). Surface cracks appear to develop through individual mineral grains, as is apparent near the white arrow. The variations in contrast apparent 54 throughout the BSE image are indicative of different types of mineral grains present at the surface. Near the white arrow, a bright grain is shown to be dissected by a surface crack. Within the surface flake (indicated by the black arrow), mineral faces are clearly visible. The coalescence of surface cracks and the raised nature of the surface suggest that this surface is in the process of dislocation and removal. These observations confirm that surface cracking is occurring in the absence of a depositional coating, despite the glossy and specular sheen present on the rock surfaces. Figure 11d illustrates pitting on the sub-millimeter scale. Similar to Figure 11c, contrast variations in the BSE image represent the chemical and mineralogical variations observed throughout the sample. The appearance of primary plagioclase and pyroxene crystals (as confirmed through energy- dispersive X-ray spectroscopy (EDS)) at the sample surface confirms the absence of a chemically homogeneous surface layer and further refutes the presence of a depositional coating. The occurrence and morphology of these micro-pits suggest that they could be the precursors to the larger pits observed on dolerites (white arrow, Fig. 11d) and described by Allen and Conca (1991), Staiger et al. (2006), and Head et al. (2011). 6.0 Discussion The data obtained for rock interiors and surfaces are consistent with diffusive oxidation (Fig. 13) being the dominant chemical alteration process in Beacon Valley, in which an oxidizing environment drives the migration of cations to the free surface of the sample, resulting in distinct structural, chemical, and mineralogical signatures. The driving force behind this alteration process is the strong oxidation gradient established between the unaltered dolerites (which, like most terrestrial igneous lithologies, were 55 emplaced near the quartz-fayalite-magnetite (QFM) redox buffer) and the oxidizing Antarctic environment (fO2 = 0.21). Although the resultant products of anhydrous oxidation-driven alteration are not entirely unique, the presence of two reaction interfaces (A” and A’) in our samples, in addition to the multitude of chemical, mineralogical, and morphological observations, strongly suggest that oxidation is the dominant process that has altered these samples. Previous work has discussed the morphological and chemical signatures of such oxidation processes in basaltic glasses in both laboratory (Cooper et al., 1996a, 1996b; Smith and Cooper, 2000) and natural settings (Burkhard and Müller- Sigmund, 2007). The complex nature of poly-mineralic samples has, however, not been widely investigated in laboratory environments, and so direct comparison of Beacon Valley samples to previous reference studies is difficult. Cooper et al. (1996a, 1996b) discuss the structures and products associated with cation migration and subsequent oxidation in basaltic glass. The relatively weak morphological and compositional signatures associated with these products are easily overprinted by more mature alteration products. Only under unique circumstances are the products of this oxidation process preserved. Burkhard & Müller-Sigmund (2007) identified these metastable oxidation signatures in lobes of basaltic pahoehoe lava in Hawaii, where the altered margins between lobes were uniquely preserved as a result of rapid burial by subsequent flow lobes following the initiation of surface oxidation. This process effectively sequestered the metastable products of oxidation and protected them from physical erosion or subsequent chemical alteration. In Beacon Valley, the hyper- arid and hypo-thermal conditions prevent the formation of widespread mature alteration products (i.e., smectite clays) on rock surfaces. Transient episodes of liquid water 56 produced by snowmelt (e.g. Marchant and Head, 2007) are able to exploit defects on rock surfaces, resulting in localized concentrations of clay minerals (Allen and Conca, 1991; Head et al., 2011) and the accumulation of mobile salt species (Marchant and Head, 2007). However, the short-lived nature of this liquid water is unable to produce and preserve mature alteration phases across the majority of rock surfaces, resulting in the widespread preservation of metastable products of oxidation. Although physical erosion plays a significant role in the redistribution of material throughout Beacon Valley, the climate and valley surface in Beacon Valley are some of the most stable in the world (Marchant and Head, 2007), making Beacon Valley an ideal natural laboratory to identify the metastable products of oxidation-driven alteration. The products of oxidation-driven alteration have been carefully studied in laboratory environments (Cooper et al., 1996a, 1996b; Smith and Cooper, 2000) and, with the identification of Beacon Valley as an appropriate natural laboratory, this process (Fig. 13) can be investigated with respect to the observed chemical, mineralogical, and morphological signatures identified in the Ferrar Dolerite. When exposed to an oxidizing atmosphere, divalent cations are able to effectively migrate to the free surface of dolerites in response to the oxidation potential between the dolerite interior and the surrounding environment (Cooper et al., 1996a). The primary migrating species will be highly dependent on the chemistry and mineralogy of the dolerites, especially in dealing with complex poly-mineralic samples, although divalent cations are most susceptible to migration. The migration of cations to the free surface is charge-compensated by the inward flux of electron holes (h•, electron “vacancies” in the valence band of the mineral, specifically associated with Fe3+ occupying a site on the lattice “normally” occupied by a 57 Fe2+ cation, e.g., the M1 site in clinopyroxenes) which, in this instance, are manifested as the conversion of Fe2+ to Fe3+. The ensuing outward flux of electrons caused by the oxidation of Fe results in the transfer of electrons to environmental oxygen, which allows the oxygen ions to combine with the migratory cations to form soluble oxide species on the free surfaces of the samples. Oxidation thus occurs as the removal of cations increases the oxygen/cation ratio within the sample, not by the addition of oxygen into the sample itself. This process most efficiently dissipates the Gibbs energy despite causing significant micrometer- to millimeter-scale textural changes in the process. Here, the noted textures refer to the morphologies of the interfaces between grains as well as the spatial differences in composition (Cooper 2010). These metastable products have disrupted crystal structures that are depleted in divalent cations and are relatively enriched in Fe3+. We believe that this process and the resultant chemical and textural variations are responsible for the chemical and spectral signatures associated with these dolerite samples. The dolerite samples are characterized by the presence of two oxidation fronts (Fig. 12). These oxidation fronts are defined by distinct variations in color (i.e., apparent oxidation) in the absence of visible morphological or structural changes in crystal structure. Similar zones of discoloration are observed by Smith and Cooper (2000) and are indicative of regions of variable extents of cation migration. As the oxygen/cation ratio increases, the concentration of Fe3+ locally exceeds different redox buffers, resulting in visible heterogeneities within these mobilized zones. In addition to the total FeO content of the protolith dolerites, the thickness and sharpness of the discolored zones appear to be at least partially controlled by grain size, with coarser grained samples 58 exhibiting thicker zones of discoloration and more diffuse boundaries than finer grained samples (Fig. 12). The oxidation process detailed for glass was originally identified in crystalline oxide materials (Fehlner and Mott, 1970; Schmalzried, 1983) and further elucidated by Cooper et al. (1996a) and subsequent studies. The two fundamental properties associated with oxidation in crystalline materials (i.e., minerals) are (1) the presence of a semi- conductor condition, and (2) the presence of sufficient amounts of Fe. To establish a semi-conductor condition, the migration of divalent cations to the free surface of the minerals and rocks must be counter-balanced by a combination of the inward migration of electron holes (h•), the replacement by monovalent cations, and the presence of vacancies and point defects. Because the transport coefficient (the product of species concentration and species mobility) of h• is exceedingly large compared to that of the divalent cations (a function of the extremely high mobility of h•), the electrochemical potential gradient of h• must be equally as small in order to achieve electro-neutrality. By definition, this state satisfies the semi-conductor condition and is independent of the matrix in which the divalent cations and h• exist. This model of oxidation driven alteration is also well supported by the observed micrometer- to millimeter-scale textures and morphologies of the rocks themselves. As argued by Schmalzried (1983) and Cooper (2010) and reemphasized in this manuscript, rock textures are invaluable clues to their kinetic and alteration histories. The presence of Fe at high enough abundances to effectively charge-balance the oxidation process is necessary to create the observed signatures. Basaltic glasses and most igneous minerals contain sufficient amounts of Fe to result in substantial and visible 59 modifications, plagioclase included. Cook and Cooper (2000) show that high abundances of Fe are not required for cation-diffusion oxidation to dominate geologic materials. This process is still dominant at Fe abundances as low as 0.3 wt.%, which is lower than the amount of Fe contained within the average plagioclase crystals measured by EPMA in our study (~0.5 wt.%) (Cook and Cooper, 2000). This suggests that the redox kinetics are rate-limited by the migration of the cations and not by the abundance of Fe in all mineral types present in the dolerite. Additionally, as temperature is lowered, even less Fe is required to achieve this semi-conductor condition. While 0.3 wt.% Fe was required for the high temperature experiments described in Cook and Cooper (2000), even less is likely required at near-ambient conditions. The growth rate of alteration rinds, as presented here, should follow parabolic kinetics (Cooper et al., 1996a), where the square of thickness is proportional to the diffusivity of the rate-limiting cation and the thermodynamic driving force (normalized to RT) for oxidation. However, cation diffusion rates at the ambient conditions of Beacon Valley have not been measured, but are estimated to be extremely slow due to the extremely low temperatures despite the strong oxidation driving potential. Simple extrapolation of high-temperature volume diffusion data confirms this hypothesis (Manning, 1973). Despite these thermal difficulties, the growth kinetics are likely enhanced by other diffusive mechanisms with lower temperature sensitivities (e.g., grain boundary diffusion), by the extreme driving force for oxidation at ambient conditions, and by the surface stability and duration of exposure to the Antarctic environment. In their oxidation experiments, Cooper et al. (1996a) found that Ca2+ and Mg2+ were the dominant mobile cations, forming measurable layers of surface precipitates. 60 This migration leaves a zone of oxidized basaltic glass that is depleted in CaO and MgO, as measured using Rutherford backscattering spectroscopy. The magnitude of these depletions for CaO and MgO were found to be 8.01 mol.% and 7.75 mol.%, respectively. However, this zone is enriched in Na+ (by 16.96 mol.%) and, to a lesser extent, K+ (by 0.11 mol.%), which migrate into the divalent-cation-depleted zone from the sample interior in response to the charge imbalances. Assuming a similar process occurs in a poly-mineralic sample of similar composition, the dolerites of Beacon Valley should exhibit similar zones of depletion and precipitated layers of enrichment (Fig. 13). While no oxide coatings are visible on dolerite surfaces, the dolerites do exhibit systematic depletions of Ca and Mg in the alteration rind relative to their interiors (Table 2 and Fig. 4). In addition, Na and K are enriched in the alteration rinds relative to their respective interiors (Table 2 and Fig. 4). We interpret the lack of surface coatings enriched in oxide species on the dolerites as a result of physical erosion (i.e., aeolian abrasion) and dissolution, mobilization, and reprecipitation during transient wetting from melting snow. This interpretation is substantiated by the abundance of salt species found underneath rocks and within the regolith throughout Beacon Valley; the cations that form these salt species are derived from the overlying doleritic clasts. Claridge and Campbell (1977) identified that soils derived from dolerites are uniquely enriched in Ca and Mg relative to soils derived from other lithologies, an observation that is consistent with oxidation-driven alteration processes and subsequent oxide dissolution during transient wetting events. Following the removal of these oxide coatings, the dolerites in Beacon Valley simply exhibit alteration rinds defined by oxidation fronts that are depleted in divalent cations and enriched in monovalent cations. Optical microscopy and SEM 61 analyses show that depositional coatings are not present on rock surfaces and that primary crystal morphologies are instead present at the surfaces of these samples. The lack of coatings, which are predicted if migration, leaching, and subsequent precipitation are occurring, confirms that physical erosion and/or aqueous dissolution and mobilization away from the rock surfaces are significant processes in Beacon Valley. The specular appearance of the rock surfaces is also consistent with extensive aeolian modification and smoothing. The diversity of surface textures observed in SEM analyses is likely due to a combination of the different exposure and alteration histories of each sample, heterogeneous alteration on each individual sample surface, and modest chemical differences in the protolith. For example, more intense chemical alteration and physical erosion is able to occur in micro-topographic hollows on rock surfaces (Marchant and Head, 2007; Head et al., 2011). Conversely, in areas where water is unable to accumulate, smooth textures are able to develop as the surface matures and is not subjected to extensive physical erosion. Mineralogical observations of dolerites are largely consistent with this oxidation- driven alteration process. XRD analyses show no evidence for significant changes in mineralogy between sample interiors and the alteration rinds. Mössbauer spectroscopy confirms the significant oxidation of Fe, present solely as Fe3+ substituting for Fe2+ in the crystal structure of pyroxene or chlorite, and/or the formation of nanophase Fe oxides (npOx). Morris et al. (2006) define npOx as “a generally poorly crystalline product of oxidative weathering that contains nanometer-sized particles of Fe3+-bearing material that is embedded in a matrix and is associated with unknown proportions of H2O, O2-, OH-…, 62 and other species through the formation of chemical bonds or specific chemical adsorption.” The presence of npOx species is likely, particularly due to the reddening of dolerite surfaces in response to oxidative weathering processes. However, the abundances of these phases are small, as npOx has not been definitively identified in EPMA or VNIR analyses. Additionally, Singer (1982) showed that even at abundances of 1 wt%, these phases exhibit clear and strong absorptions in the VNIR spectral region. These significant optical contributions from Fe3+ in dolerite surfaces are accompanied by minor increases in the strength of H2O and OH- hydration features near 1.4 μm and 1.9 μm, which may suggest minor and volumetrically insignificant abundances of nanophase Fe3+-bearing hydroxide and oxyhydroxide phases or the presence of adsorbed water on the rock surface. Efforts to identify these phases using transmission electron microscopy (TEM) are ongoing, although initial results confirm the minor volumetric contribution of these optically dominant phases. Bulk chemistries are also consistent with the absence of aqueous alteration products. All dolerite interior and surface data plot below the feldspar-(pyroxene, olivine) join on a ternary FeOT + MgO, Al2O3, CaO + Na2O + K2O (FM/A/CNK) diagram (Fig. 3), which is widely considered to be a region indicative of unaltered basaltic compositions and primary igneous variability (e.g., Hurowitz and McLennan, 2007). While these authors recognize that chemical alteration under extremely acidic environments can mimic primary igneous chemical variations, such environmental conditions are not present in Antarctica, and therefore we do not consider strongly acidic aqueous alteration a likely possibility. 63 VNIR and Mössbauer spectroscopy, in tandem, indicate that Fe hydroxides/oxyhydroxides cannot be present at significant abundances near the surfaces of these samples. Mössbauer results indicate that hematite, goethite, or other crystalline Fe3+ oxides and oxyhydroxides are not present at significant abundances. The VNIR absorption features unique to these hydroxide and oxyhydroxide phases are not substantial spectral components in any of the dolerite surface spectra, indicating that they are not present in significant abundances. These phases have also not been identified in EPMA analyses, which would be capable of observing significant concentrations of sub- pixel nanophase ferric iron phases should they be present. The increased spectral contribution of amorphous aluminosilicate material, as modeled in MIR emission spectra of rock surfaces (Fig. 10), is not directly identified in any other mineralogical or chemical analysis despite being predicted products of the alteration process. Evidence for the chemical etching of plagioclase, which is identified in SEM analyses, may influence the MIR spectroscopy of these altered surfaces. The limited occurrences of these etched morphologies, however, in addition to the ubiquity of the MIR emission signatures of altered surfaces, strongly suggest that the source of these MIR spectral signatures is not associated with the observed etched morphologies. Instead, the ubiquity of the discolored alteration rind indicates that they are the likely source of the observed spectral signatures. The preferentially etched lamellae are indicative of localized aqueous modification. Additional evidence of aqueous alteration can be seen on many rock surfaces throughout Beacon Valley that exhibit surface pits and depressions. These depressions (Fig. 11d, black arrows), originally created by physical (e.g., cracks) or chemical/mineralogical (e.g., dissolution pits) defects, preferentially 64 accumulate liquid water following the melting of snow. This water is able to cause significant structural weakening as minor amounts of chemical alteration occur. Subsequent aeolian activity then acts to scour and remove this altered material, which expands the topographic depressions and creates a positive feedback that can result in large pits (white arrow) that can frequently reach diameters greater than one centimeter (e.g., Allen and Conca, 1991, Head et al., 2011). We speculate that, with time, these pits will widen and deepen as liquid water is preferentially concentrated in these hollows, allowing for more intense chemical alteration to occur, as described in Marchant and Head (2007) and Head et al. (2011). While the extent of oxidation and grain size of the sample are clearly related to the presence of multiple oxidation fronts and their depth and transition characteristics within the samples, respectively, other variables may also contribute to the morphologies observed in thin section. Considering that these samples were all selected based on the same selection criteria, we assume that they have undergone similar physical and chemical histories since their deposition. Based on cosmogenic data for nearby rocks (not analyzed in this study), we believe that all of the rocks examined here were exposed in the hyper-arid, hypo-thermal climate of Beacon Valley for at least 0.64 Ma. The rocks in the distal end of the transect may have been exposed for considerably longer time spans (Marchant et al., 2007). These data, therefore, suggest that alteration rind development is complete by 0.64 Ma. Subsequent alteration rind evolution would simply contribute to the thicknesses of the A’ and A” alteration zones, although grain size and protolith FeO content also play significant roles. 65 7.0 Implications for Surface Alteration on Mars The alteration processes and products described here are not limited to the Earth’s surface. The present day martian surface can be considered a hyper-arid and hypo- thermal desert similar to the MDV based on the work of previous climatic, lithological, and morphological analog studies (Marchant and Head, 2007, and references therein; Harvey, 2001; Glasby et al., 1981; Allen and Conca, 1991; Chevrier et al., 2006). While the oxygen fugacity of the martian atmosphere is much less than that of the Earth (fO2 = 1.3x10-3 on Mars (Owen, 1992), compared to fO2 = 0.21 on Earth), the atmosphere is still extremely oxidizing compared to the magmatic conditions experienced during the genesis of martian basalts (approximately QFM-3 to QFM-1 (Herd et al., 2002) which, for 1200º C magma, represent fO2 values of approximately 2 x 10-12 to 2 x 10-10, respectively). Oxidation-driven alteration processes, therefore, are important components of chemical weathering on the martian surface. Whether the martian surface exhibits signatures of such anhydrous alteration processes or whether these signatures have been overprinted by subsequent aqueous alteration is paramount towards understanding the extent of chemical alteration on the martian surface and the evolution of the martian climate. Aside from localized exposures of heavily weathered Noachian-aged terrain (e.g., Bibring et al., 2005; Mustard et al., 2008), VNIR and MIR spectroscopy of dust-free martian terrains has primarily identified unaltered to weakly altered basaltic landscapes (Christensen et al., 2000b; Mustard et al., 2005). These observed spectral signatures are similar to spectral measurements of the dolerites from Beacon Valley (Fig. 14). VNIR reflectance spectroscopy identifies a significant Fe3+ charge-transfer absorption feature in the visible portion of the electromagnetic spectrum, even in archetypical “unaltered” and 66 relatively dust-free basaltic regions (e.g., Singer et al., 1979), in addition to mafic signatures of varying strength (Mustard et al., 2005). Even in the representative unaltered basaltic locations (i.e., Syrtis Major), significant VNIR spectral variability has been observed and has been linked to minor amounts of surface alteration during distinct paleoclimatic episodes that ended 2.1 Ga ago (Skok et al., 2010). The spectral signatures of these altered regions are exemplified by weakened mafic signatures and the addition of a spectral slope that decreases from shorter to longer wavelengths (Skok et al., 2010). Based on this work and those performed by Minitti et al. (2007) and Fischer and Pieters (1993), Skok et al. (2010) conclude that weakly altered basalt, comparable to that observed in the basaltic plains of Gusev crater by the Mars Exploration Rover (MER) Spirit, is the likely candidate for the observed spectral features throughout Syrtis Major. MIR emission spectra of Surface Type 2 locales (as identified by the Thermal Emission Spectrometer (TES) onboard the Mars Global Surveyor spacecraft and defined in Bandfield et al. (2000)) exhibit the same narrowing of the restrahlen bands and masking of igneous spectral components as is seen in MIR emission spectra of the surfaces of Beacon dolerites (Fig. 14). Although the Surface Type 2 signature was originally interpreted as andesitic in nature (Bandfield et al., 2000), subsequent studies presented an alternate model that fit the data: partially altered basaltic signatures enriched in a sheet silicate or an amorphous component (Wyatt and McSween, 2002). Because one of the diagnostic smectite absorption features at 530 cm-1 was excluded from modeling due to an atmospheric CO2 absorption, Wyatt and McSween (2002) were unable to determine whether the spectral signatures were due to smectites or amorphous phases. However, the lack of significant concentrations of smectites seen in VNIR 67 reflectance spectra of areas dominated by Surface Type 2 (Mustard et al., 2005) and in subsequent MIR emission studies (Michalski et al., 2005; Ruff and Christensen, 2007) support the interpretation that amorphous phases are a reasonable explanation for the observed spectral signatures. The detection of olivine-bearing basalts in the immediate subsurface of Acidalia Planitia by VNIR spectroscopy (Salvatore et al., 2010b) in addition to basaltic elemental signatures in the uppermost tens of centimeters by the Gamma Ray Spectrometer onboard the Mars Odyssey spacecraft (Karunatillake et al., 2006) confirms the basaltic nature of the unaltered substrate of this archetypical Surface Type 2 locale. Both VNIR and MIR orbital spectroscopy of the martian surface confirm that volumetrically minor contributions of spectrally distinct components can have significant effects on spectroscopic studies of the martian surface. This observation is supported by the spectral studies of the Beacon dolerites, which exhibit large spectral variations despite only minimal mineralogical and chemical variations. The sensitivity of VNIR and MIR spectroscopy to the uppermost tens of microns of the surface allows for processes that alter a volumetrically minor component (including surface etching and thin rinds and/or coatings) to potentially dominate the observed spectral signatures. The implications of non-volumetrically representative spectral signatures must be taken into account when interpreting orbital spectral signatures and putting them into geologic context. Observations and analyses of the basaltic plains of Gusev crater by the MER Spirit are also suggestive of alteration that is potentially dominated largely by anhydrous processes. While multiple styles and products of alteration have been inferred or identified by Spirit within Gusev crater, we focused our study solely on the first two 68 Adirondack-class basalts investigated on the plains of Gusev crater. The basaltic rocks Adirondack and Humphrey (McSween et al., 2006) exhibit chemical trends between their alteration rinds (represented by surfaces that were brushed by the Rock Abrasion Tool (RAT)) and their interiors (represented by areas that were ground away by the RAT) that indicate the removal of divalent cations and the enrichment of monovalent cations (Gellert et al., 2006). The major element variations between the surfaces and interiors of these two rocks are nearly identical to the chemical trends observed in Beacon Valley as a result of oxidation-driven alteration processes (Fig. 15). Furthermore, VNIR multispectral data obtained from the Pancam instrument show a significantly stronger Fe3+ charge transfer absorption feature in the spectra of rock surfaces relative to their interiors (McSween et al., 2004). Lastly, Morris et al. (2004) state that the ubiquity of olivine in both the rocks and soils suggest that physical erosion (rather than aqueous alteration) dominate the materials analyzed by Spirit in the plains of Gusev crater. These rocks do not show any evidence for significant enrichments of Br, Cl, or S on their surfaces that cannot be accounted for by minor amounts of dust contamination (Gellert et al., 2006), confirming the absence of surface coatings containing these elemental species. The absence of oxide coatings on the surfaces of Adirondack and Humphrey also support the conclusion of Morris et al. (2004) and suggest that aeolian abrasion and/or minor aqueous activity (that is largely incapable of significant aqueous alteration) are able to remove these soluble oxide species from the rock surfaces. Although no spectral evidence for amorphous aluminosilicates were observed by the Mini-TES instrument on the surfaces of either Adirondack or Humphrey, there has been substantial difficulties in identifying amorphous phases and surface coatings even where other lines of evidence 69 exist (e.g., Hamilton and Ruff, 2012). This non-detection of amorphous phases by Mini- TES may be caused by several factors, including the incomplete removal of pervasive surface dust from rock surfaces, or the lack of spectral endmembers in unmixing libraries that match the observed alteration products (Hamilton and Ruff, 2012). Another possibility is that the different parental composition of the Gusev plains basalts and the Ferrar Dolerite result in varying spectral signatures associated with oxidation-driven alteration. Mössbauer spectroscopy of Adirondack and Humphrey show slight increases in Fe3+/FeTotal between rock interiors and surfaces of 0.01 and 0.04, respectively (Morris et al., 2006). This increased oxidation is more subtle than that observed for the dolerites, which show an average increase in Fe3+/FeTotal between rock interiors and surfaces of 0.14. This subtle increase in Fe3+/FeTotal may be due to either geologically recent physical erosion of the oxidized surface, slower oxidation rates on Mars relative to Beacon Valley, more recent exposure of the rock surfaces to the oxidizing environment, or some unique combination or alternative process. While the interior of the Gusev plains rock named Mazatzal is chemically and mineralogically similar to Adirondack and Humphrey, its surface exhibits multiple coatings that are enriched in Ni, Zn, and K (Gellert et al., 2006). Due to their similar charges and ionic radii (Shannon and Prewitt, 1969), Ni and Zn could easily substitute for Mg and Fe in olivine and clinopyroxene in basaltic rocks. As a result, the presence of coatings on Mazatzal may represent the soluble oxide coatings predicted to form during oxidation-driven alteration processes. However, Fe, Mg, and Ca are all depleted in these coatings relative to the interior of Mazatzal (Gellert et al., 2006) despite their predicted 70 enrichment in the coatings if they are the products of oxidation-driven alteration. As a result, the coatings on Mazatzal may not be indicative of such anhydrous alteration processes. Haskin et al. (2005) suggested that these coatings may have formed when Mazatzal was buried beneath soil or dirty snow, which would explain the concentration of soil-derived S and S-correlated elements in the coatings. Aqueous alteration processes have also been proposed to explain the observed chemical trends in the plains of Gusev crater. Hurowitz et al. (2006) proposed an acidic aqueous alteration model to explain the relationship between rock surfaces. They identify that at low pH and low water:rock ratios, Fe, Mg, and Si are more mobile than Ca, Na, and K during aqueous alteration (Hurowitz et al., 2006), resulting in alteration trends that are distinct from those found in most temperate terrestrial environments (e.g., Nesbitt and Wilson, 1992; Nesbitt and Markovics, 1997). However, the surfaces of neither Adirondack nor Humphrey are enriched in Si relative to their interiors (Gellert et al., 2006), as would be predicted in the model of acidic aqueous alteration proposed by Hurowitz et al. (2006) (Fig. 15). The relative depletion of Ca in the surface of Humphrey as well as the relative enrichment of K and Na in both Humphrey and Adirondack, together with the uniform Si concentrations, strongly suggest that acidic aqueous alteration was not the dominant alteration mechanism acting upon the currently exposed surfaces of these two rocks. Additionally, Hurowitz et al. (2006) propose that olivine dissolution is the dominant control on the alteration of the Gusev basalts. However, the ubiquity of olivine in the fine-grained sediments throughout the Gusev Plains suggests that preferential dissolution of olivine is not a significant alteration process subsequent to the formation of the local soils (Morris et al., 2004). As a result, the data suggest that 71 oxidation-driven alteration processes where preferential mineral dissolution does not occur can better explain the available chemical and spectral data derived from basaltic rocks in Gusev crater. Aqueous activity, while necessary to explain the presence of accumulated salts in Gusev soils (Haskin et al., 2005) and to assist in the removal of oxide coatings on rock surfaces, does not appear to be a significant contributor towards the alteration of rock surfaces, similar to the role of liquid water in Beacon Valley. Mini- TES observations of the surface of Mazatzal do not exhibit evidence for amorphous aluminosilicates or surface coatings, which is inconsistent with Microscopic Imager observations (McSween et al., 2006). This indicates either that the alteration products are disparate from those expected from oxidation-driven alteration, or that the spectral signatures associated with oxidation-driven alteration on rocks of compositions that are significantly different from the Ferrar Dolerite exhibit comparably different MIR spectral signatures. The inability for Mini-TES to detect these surface coatings also bolsters the hypothesis that oxidative chemical alteration is occurring on the surfaces of Adirondack and Humphrey but is not detected by the Mini-TES instrument. 8.0 Conclusions Chemical alteration in Beacon Valley, Antarctica, is driven by an oxidation potential that causes mobile divalent cations to migrate to the sample surface. The migration of these cations is charge-balanced by the inward migration of electron holes (manifested as an increase in Fe3+ that decreases from the rock surface into the unaltered rock interior), the migration of monovalent cations into the alteration rind from the sample interior, and the presence of point defects. At the near-surface, the presence of 72 ferric iron, metastable mineral structures, and surface etching results in significant spectral differences between the rock surfaces and the unaltered interiors. Deeper within the rock, mobile cation migration continues to result in oxidation, creating distinct oxidation fronts caused by the concentration of Fe3+ locally exceeding different redox buffers. No significant mineralogical variations exist between rock surfaces and interiors and chemical variations are consistent with the predicted depletion of divalent cations and enrichment of monovalent cations in the alteration rinds. The metastable products observed in Beacon Valley are the result of chemical alteration in extreme hyper-arid and hypo-thermal conditions where the products of these early stages of chemical alteration are uniquely preserved. This alteration process may also explain many of the global and local spectral and chemical observations of the martian surface. VNIR and MIR spectroscopy of the martian surface suggests the ubiquity of lightly altered basalts across the majority of relatively dust-free terrains. In addition, observations from the plains of Gusev crater suggest that similar spectral and elemental trends to those observed in Beacon Valley dominate the Adirondack and Humphrey basaltic rocks. Aqueous activity recorded in the plains of Gusev crater, like in Beacon Valley, appears to be limited to the remobilization of different elemental species rather than the significant aqueous alteration of rocks and soils. Acknowledgements This work was supported by the National Science Foundation (ANT-0739702). The authors would like to thank several people and institutions for their support and assistance with data collection, analyses, and interpretations: The National Science 73 Foundation, the United States Antarctic Program, Raytheon Polar Services Company, the staff of McMurdo Station, PHI Inc., Cherie Achilles, Nilanjan Chatterjee and the Electron Microprobe Facility at the Massachusetts Institute of Technology, M. Darby Dyar, Timothy Glotch and the Vibrational Spectroscopy Laboratory at Stony Brook University, Takahiro Hiroi and the Brown University RELAB Facility, Colin Jackson, the LacCore Facility at the University of Minnesota, Anthony McCormick, Douglas Ming, Richard Morris, David Murray, Joseph Orchardo, Stephen Parman, A. Deanne Rogers, Alberto Saal, and Paul Waltz and the School of Engineering at Brown University. 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Wyatt M. B., Horodyskyj U. N., Kelley K. A. and Neal K. M. (2008), Comparisons of TIR and LA-ICP-MS derived bulk chemistries for natural surfaces of igneous rocks. LPSC 39, abstract 2105. Figure and Table Descriptions Figure 1. The alteration rind of sample MS10_BV_06 (a), as compared to a traditional desert rock coating (b) (from Dorn, 2009). White arrows demarcate the sharp boundary between the underlying rock surface and the rock coating, while black arrows highlight layering parallel to the shape of the depositional surface. Figure 2. Geographic setting of Beacon Valley, Antarctica. (a) The location of the McMurdo Dry Valleys. (b) The McMurdo Dry Valleys and their associated microclimate zones (modified from Marchant and Head (2007)). Beacon Valley, located well within the Stable Upland Zone, is highlighted and shown in detail in (c). (c) LIDAR hillshade and digital elevation model of Beacon Valley. Surface elevation is reported in 90 meters above the World Geodetic System 1984 (WGS84) ellipsoid. The locations of samples measured in this study are shown as yellow dots, with MS10_BV_01 being the furthest north and the sample number increasing to MS10_BV_13 to the south. Cosmogenic age dates (from Marchant et al., 2007) are shown as blue text and the approximate surface motion from Mullins Valley is indicated by the blue line. Figure 3. Ternary FeOT + MgO, Al2O3, CaO + Na2O + K2O (FM/A/CNK) diagram showing the chemistry of unaltered sample interiors (dark gray dots) and alteration rinds (red dots), in addition to the chemistry of Gusev plains basalt interiors (light gray dots) and surfaces (blue dots). (a) The Beacon Valley data cluster tightly in the center of the diagram. Largely unaltered basalts fall just below the olivine-feldspar join, which is where all of the Beacon Valley samples plot. The martian basalts fall towards slightly more mafic compositions along the feldspar–(FeOT + MgO) join. A traditional terrestrial alteration path via leaching is highlighted with the orange dotted line (Nesbitt and Wilson, 1992; Nesbitt and Markovics, 1997). The gray trapezoid is expanded in (b). (b) The data are tightly clustered and do not follow traditional terrestrial leaching trends through aqueous alteration, suggesting that aqueous processes do not significantly alter rock surfaces in Beacon Valley. Similarly, Gusev plains basalts also do not follow the traditional terrestrial leaching trend. Gusev plains basaltic rocks are labeled “H” for Humphrey, “A” for Adirondack, and “M” for Mazatzal. Figure 4. Chemical ratios of oxide abundances (in wt.%) in rock surfaces relative to their interiors. Values greater than 1 indicate enrichments in rock surfaces, while values less than 1 indicate depletions in rock surfaces. Each of the 14 dolerite samples is plotted as a filled gray circle, while the average value is plotted as a filled maroon circle. 91 Of particular interest are the systematic depletions in divalent cations (Ca2+, Mg2+) and the systematic enrichments in monovalent cations (Na+, K+) in rock surfaces relative to their interiors. Figure 5. Mössbauer spectra and modeled fits for a representative dolerite interior (a) and alteration rind (b). For this sample, the modeled ferric contribution in the alteration rind increases by 21.25%, as illustrated by the increased contribution of the ferric doublet (blue modeled line). Based on the current model, the ferric phase is consistent with nanophase Fe oxides or as Fe3+ retained within a pyroxene or chlorite structure. The ferrous phases present are best modeled as Fe2+ in pyroxenes or chlorites, with pyroxenes likely being the dominant carriers based on optical analyses of thin and thick sections. Calculated Mössbauer parameters are provided in Table 3. Figure 6. (a) An optical micrograph of sample MS10_BV_05A. The location of the EPMA analysis is outlined in the yellow box, which encompasses both the alteration rind and the unaltered interior. (b) EPMA elemental map with Fe mapped as red, Al mapped as green, and Si mapped as blue. The approximate transition from the unaltered interior into the alteration rind is shown as the light yellow dashed line. There are no obvious chemical or morphological variations associated with this transition in this analysis. The white arrows highlight primary zoning in pyroxene grains, with Mg enriched in the grain interior and Fe enriched in the grain exterior. The preservation of this chemical zoning is further indication of the incomplete chemical alteration within the alteration rinds. Figure 7. Averaged XRD patterns (from Brown University’s XRD Facility) for sample interiors (black) and alteration rinds (red). Buffers of one standard deviation are 92 shown for both the interior (grey) and alteration rind (pink) patterns to highlight the magnitude of variability observed amongst the samples, which hinders quantitative XRD analyses. No filtering or background removal has been performed in order to preserve the spectral shape and to highlight the weak amorphous “hump” present in both patterns. Peak locations are identical in both the interior and alteration rind spectra, with only minor variations in peak heights, which may be due to sampling, preparation, or analyses biases or artifacts. Ab = albite, An = anorthite, Aug = augite, En = enstatite, Pl = plagioclase, Px = pyroxene, Qtz = quartz. Figure 8. Visible/Near-infrared reflectance spectra of all 14 sample interiors (a) and surfaces (b), with average interior and surface spectra shown in (c). Sample labels are abbreviated to their identifying digits. Figure 9. Mid-infrared emission spectra of all 14 sample interiors (a) and surfaces (b), with average interior and surface spectra shown in (c). Sample labels are abbreviated to their identifying digits. Figure 10. Linear unmixing model results for (a) average dolerite interiors and (b) average dolerite surfaces. Modeled spectra are shown in green. Reported results with values in % abundance are shown and are normalized to exclude the blackbody component (which is also reported). The goodness of fit of the model is reported as the root-mean-squared error (RMSE). Figure 11. Scanning electron microscope images of sample surfaces showing a variety of surface morphologies. (a) Etching and/or dissolution visible, apparently targeting lamellae or zones within individual grains (white arrows). (b) Additional etching and/or dissolution apparent along lamellae or zones (white arrows). (c) Surface 93 cracking (white arrow) and flaking (black arrow). The indicated flake (black arrow) is raised relative to the rock surface, suggesting that this portion of the surface has been at least partially dislodged. (d) Micro-pit development at the sample surface (black arrows) near a well-formed larger pit (white arrow). Figure 12. Optical micrographs of four representative samples, highlighting their alteration rinds. Grain size and morphology greatly influence the preservation and appearance of the alteration rinds. Regions labeled at U, A’, and A’’ indicate unaltered, moderately oxidized/altered, and heavily oxidized/altered portions of the rock, respectively. Samples shown are (a) MS10_BV_06, (b) MS10_BV_03, (c) MS10_BV_04, and (d) MS10_BV_05A. Figure 13. Schematic of alteration processes and products. The outward migration of cations is charge-balanced by the inward flux of electron holes (i.e., the conversion of Fe2+ to Fe3+) and the flux of monovalent cations towards the surface. Soluble cation oxide species are not observed on the sample surfaces because of their removal by physical erosion and aqueous dissolution. Oxidation fronts are visible within the samples where the local concentration of Fe3+ exceeds different redox buffers. Regions labeled at U, A’, and A’’ indicate unaltered, moderately oxidized/altered, and heavily oxidized/altered portions of the sample, respectively. Figure 14. (a) Visible/Near-infrared (VNIR) reflectance spectra of a representative dolerite interior (black) and surface (red) compared to two representative low albedo spectra (spectra from the Observatoire pour la Minéralogie, l’Eau, les Glaces et l’Activité (OMEGA) instrument). The effects of oxidation are clearly observed in both the terrestrial and martian spectra. (b) Mid-infrared (MIR) emission spectra of the 94 average dolerite interior (black spectrum) and surface (red spectrum) compared to TES Surface Type 1 (gray spectrum, from Bandfield et al. (2000)) and TES Surface Type 2 (pink spectrum, from Bandfield et al. (2000)) regions of Mars. The narrowing of the reststrahlen bands is visible in both TES Surface Type 2 and dolerite surfaces. The martian spectral signatures are consistent with those observed in Beacon dolerites as the result of oxidation-driven alteration processes. These spectra also show the sensitivity of both VNIR and MIR spectroscopy to small amounts of chemical alteration. Figure 15. Chemical ratios for the Gusev basalts Adirondack (blue circle) and Humphrey (green circle), as measured by the APXS instrument on MER Spirit via Rock Abrasion Tool (RAT) brushing (surface measurements) and grinding (interior measurements). Dolerite data are also plotted (see Figure 6 for description). Adirondack and Humphrey trends are very similar to those observed in the dolerites of the MDV, suggesting that similar anhydrous alteration processes may be dominating the chemical alteration of the Gusev basalts in the hyper-arid and hypo-thermal martian environment. Table 1. Analytical techniques used to investigate the primary composition and chemical alteration of the fourteen dolerite samples. Table 2. Major element chemistry of dolerite interior and surface powders as determined by flux fusion and ICP-AES analyses, reported in oxide weight percentages. Standard deviations were calculated using 22 standards measured concurrently with the samples. Sample names are abbreviated and should be preceded by “MS10_BV_”. Table 3. Calculated Mössbauer parameters for the three analyzed dolerite sample pairs. Parameters include isomer shift relative to metallic iron (δ), quadrupole splitting (ΔEQ), and the peak widths of the modeled fits, all reported in mm/sec. Errors associated 95 with these parameters are ±0.02-0.04 mm/sec (Dyar, 1984; Vandenberghe et al., 1994). Also provided are the peak areas of the modeled fits, presented as percent of total area. Errors are on the order of 1-3% (absolute) for relative areas of distributions. * denotes fixed parameters. Table 4. Endmember library used in the linear spectral deconvolution of mid- infrared emission data. The spectral library was created using the ASU Spectral Library v. 1.1, available at speclib.asu.edu, and with the assistance of A. D. Rogers. [1] Christensen et al. (2001a); [2] Minitti and Hamilton (2010); [3] Lane (2007); [4] Hamilton (2000); [5] Hamilton (2010); [6] Koeppen and Hamilton (2008); [7] Glotch et al. (2004); [8] Ruff (2004); [9] Wyatt et al. (2001). 96 Chapter 2, Figure 1. 97 Chapter 2, Figure 2. 98 Chapter 2, Figure 3. 99 Chapter 2, Figure 4. 100 Chapter 2, Figure 5. 101 Chapter 2, Figure 6. 102 Chapter 2, Figure 7. 103 Chapter 2, Figure 8. 104 Chapter 2, Figure 9. 105 Chapter 2, Figure 10. 106 Chapter 2, Figure 11. 107 Chapter 2, Figure 12. 108 Chapter 2, Figure 13. 109 Chapter 2, Figure 14. 110 Chapter 2, Figure 15. 111 Chapter 2, Table 1. Technique Target Sampling Depth Description Investigate the morphology and structure of Optical Microscopy Thin Sections 30 μm unaltered rock interiors and the alteration rinds. Determine whether coatings are present. Visible/Near-Infrared Identify primary and secondary minerals using (VNIR) Reflectance Rock Chips ~ 100 μm diagnostic absorption features resulting from Spectroscopy electronic and vibrational processes. (0.32 μm – 2.55 μm) Identify primary and secondary minerals using Mid-Infrared (MIR) diagnostic absorption features resulting from Emission Spectroscopy Rock Chips ~ 100 μm the fundamental vibrational frequencies within (2000 cm-1 – 200 cm-1) crystal lattices. Scanning Electron Characterize unaltered interior and alteration Rock Chips < 5 μm Microscopy (SEM) surface morphology. Identify minerals based on the diagnostic X-Ray Diffraction Rock ~ 500 μm* diffraction of X-ray beams based on the (XRD) Powders principles of Bragg’s Law. Mössbauer Rock Quantitatively assess the distribution and ~ 500 μm* Spectroscopy Powders oxidation state of iron within samples. Electron Microprobe Determine the concentration of elements using Thin Sections < 5 μm Analyses (EMPA) X-ray spectrometry. Inductively Coupled Quantitatively assess the concentration of Plasma-Atomic Rock ~ 500 μm* elements using emission spectrophotometric Emission Spectroscopy Powders techniques. (ICP-AES) 112 Chapter 2, Table 2. Sample Al2O3 CaO FeOT K2O MgO MnO Na2O P2O5 SiO2 TiO2 Total 01_int 14.19 9.78 10.44 1.03 7.00 0.17 1.85 0.08 53.93 0.66 99.13 01_sur 14.19 9.33 10.46 1.17 6.37 0.16 1.87 0.07 53.28 0.64 97.54 02_int 14.03 8.16 10.11 1.51 4.57 0.17 2.14 0.12 59.33 0.90 101.04 02_sur 13.84 7.98 9.64 1.46 4.06 0.16 2.18 0.13 57.59 0.91 97.95 03_int 13.28 8.99 11.71 1.40 4.79 0.18 2.00 0.12 58.19 0.91 101.57 03_sur 13.15 8.64 11.85 1.59 4.09 0.19 2.11 0.12 57.18 0.95 99.87 04_int 14.22 9.22 10.41 1.29 6.99 0.17 1.98 0.08 53.64 0.63 98.63 04_sur 12.38 7.73 11.28 1.59 6.83 0.18 1.68 0.09 53.63 0.67 96.06 05A_int 14.48 9.23 9.08 1.16 6.72 0.17 1.89 0.07 56.36 0.61 99.77 05A_sur 14.67 9.17 8.93 1.23 6.30 0.16 1.91 0.06 55.53 0.61 98.57 05B_int 14.53 8.98 10.33 1.31 3.96 0.17 2.08 0.08 59.28 0.84 101.56 05B_sur 12.98 7.25 10.07 1.74 3.41 0.17 2.09 0.17 61.90 0.91 100.69 06_int 13.83 10.36 10.41 0.52 5.94 0.18 2.06 0.07 55.41 0.66 99.44 06_sur 13.05 9.57 10.19 0.73 4.69 0.17 3.77 0.08 54.14 0.67 97.06 07_int 13.44 10.43 10.88 0.86 6.29 0.18 1.58 0.07 54.94 0.67 99.34 07_sur 13.10 10.04 10.73 0.95 5.65 0.18 1.58 0.07 54.94 0.69 97.93 08_int 14.07 9.36 10.66 0.21 5.46 0.18 2.02 0.07 54.40 0.73 97.16 08_sur 14.07 7.90 11.55 0.39 5.07 0.19 2.09 0.09 54.22 0.75 96.32 09_int 13.14 9.05 12.22 1.30 5.12 0.18 2.01 0.11 56.20 0.94 100.27 09_sur 13.43 9.05 11.76 1.43 4.55 0.19 2.14 0.12 59.84 0.91 103.42 10_int 12.88 8.96 11.72 1.02 5.03 0.18 1.85 0.12 54.74 0.88 97.38 10_sur 12.51 8.98 12.06 1.28 4.12 0.19 2.00 0.15 58.09 0.95 100.33 11_int 12.93 8.73 11.55 1.38 4.92 0.18 2.16 0.11 55.60 0.89 98.45 11_sur 12.93 7.72 10.86 2.12 4.38 0.18 2.86 0.13 58.29 0.95 100.42 12_int 13.88 10.41 11.31 0.81 6.15 0.20 1.73 0.08 55.53 0.78 100.88 12_sur 13.56 9.52 11.35 1.07 4.87 0.21 1.87 0.09 58.59 0.79 101.92 13_int 13.97 9.62 10.42 1.19 6.00 0.18 1.83 0.06 53.21 0.66 97.14 13_sur 13.77 8.91 9.75 1.23 5.31 0.18 1.93 0.07 56.79 0.66 98.60 Avg. Interior 13.78 9.38 10.80 1.07 5.64 0.18 1.94 0.09 55.77 0.77 99.42 Avg. Surface 13.40 8.70 10.75 1.28 4.98 0.18 2.15 0.10 56.72 0.79 99.05 St. Dev. ±0.225 ±0.465 ±0.156 ±0.047 ±0.076 ±0.004 ±0.144 ±0.013 ±0.817 ±0.052 113 Chapter 2, Table 3. Sample Phase δ (mm/s) ΔEQ (mm/s) Width Area Fe3+/FeTotal MS10_BV_04_int Ferric Phase 0.475 0.691 0.579 16 0.16 Ferrous Phase #1 1.136 2.067 0.303 68 Ferrous Phase #2 1.145 2.718 0.230* 16 MS10_BV_04_sur Ferric Phase 0.447 0.582 0.509 37 0.37 Ferrous Phase #1 1.115 2.037 0.300* 57 Ferrous Phase #2 1.147 2.693 0.230* 5 MS10_BV_10_int Ferric Phase 0.460 0.717 0.694 26 0.26 Ferrous Phase #1 1.150 2.047 0.324 40 Ferrous Phase #2 1.136 2.660 0.230* 34 MS10_BV_10_sur Ferric Phase 0.426 0.704 0.631 39 0.39 Ferrous Phase #1 1.148 2.072 0.329 46 Ferrous Phase #2 1.130 2.698 0.230* 16 MS10_BV_12_int Ferric Phase 0.454 0.632 0.500* 21 0.21 Ferrous Phase #1 1.144 2.030 0.376 53 Ferrous Phase #2 1.135 2.624 0.230* 26 MS10_BV_12_sur Ferric Phase 0.435 0.603 0.412 30 0.30 Ferrous Phase #1 1.141 2.052 0.349 63 Ferrous Phase #2 1.130 2.714 0.300* 8 114 Chapter 2, Table 4. Mineral Name Sample ID Citation Albite WAR-0244 [1] Andesine BUR-240 [1] Andesite interstitial glass MEM-5 [2] Anhydrite ML-S9 [3] Anorthite BUR-340 [1] Augite NMNH-9780 [4] Augite NMNH-122302 [4] Biotite BUR-840 [1] Bronzite NMNH-93527 [1] Calcite C40 [1] Ca-Montmorillonite STx-1 [1] Chlorite WAR-1924 [1] Dacite interstitial glass MEM-4 [2] Diopside WAR-6474 [1] Dolomite C20 [1] Fayalite WAR-RGFAY01 [1] Forsterite BUR-3720A [1] Fo60 (Olivine) KI 3362 [5] [6] Gypsum ML-S6 [3] Hedenbergite (Manganoan) DSM-HED01 [1] Avg. Martian Hematite TES-Derived [7] Heulandite --- [8] Illite IMt-2 [1] SiK-Rich Glass --- [9] Magnesiohastingsite HS-115.4B [1] Nontronite WAR-5108 [1] Pigeonite --- [4] Quartz BUR-4120 [1] Quenched Basalt --- [9] Saponite ASU-SAP01 [1] Serpentine HS-8.4B [1] Stilbite --- [8] 115 Chapter Three: Characterization of spectral and geochemical variability within the Ferrar Dolerite of the McMurdo Dry Valleys, Antarctica: Weathering, alteration, and magmatic processes. M. R. Salvatore1, J. F. Mustard1, J. W. Head III1, D. R. Marchant2, and M. B. Wyatt1 1 Department of Geological Sciences, Brown University, Providence, RI 02912, USA 2 Department of Earth Sciences, Boston University, Boston, MA 02215, USA Accepted in its current form in: Antarctic Science doi:10.1017/S0954102013000254 116 Abstract Orbital spectroscopy and laboratory analyses are utilized to identify major geochemical variations throughout the Ferrar Dolerites exposed in the McMurdo Dry Valleys (MDV) of Antarctica. Our laboratory results highlight the range of primary and secondary chemical and spectral variations observed throughout the dolerite, and provide the necessary calibration for detailed orbital investigations. Pure dolerite units are identified and analyzed throughout the MDV using Advanced Land Imager (ALI) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) orbital datasets. In conjunction with our laboratory analyses, orbital analyses indicate that the dolerite sills are dominated by MgO concentrations of approximately 6 – 7 wt.% except where influenced by orthopyroxene-laden magmatic injections, where MgO concentrations can reach as high as 32.5 wt.%. ASTER analyses also indicate that spectrally significant alteration is limited primarily to surfaces dominated by fine-grained dolerites, which form and preserve well-developed alteration rinds due to their resistance to physical erosion. The archetype of these secondary signatures is Beacon Valley, where a combination of cold, dry, and stable environmental conditions and the presence of fine grained dolerites results in strong alteration signatures. This work provides unprecedented spatial coverage of meso- and macro-scale geochemical features that, until now, have only been identified in field and laboratory investigations. Key Words ASTER, ALI, spectroscopy, geochemistry, remote sensing, alteration rinds. 117 1.0 Introduction and Geologic Setting The McMurdo Dry Valleys (MDV) of Antarctica are a series of predominantly east-west trending valleys located approximately 100 km to the northwest of McMurdo Station along the eastern flank of the Transantarctic Mountains (Fig. 1). The valleys are bordered to the west by the East Antarctic Ice Sheet and to the east by the Ross Sea and seasonal sea ice. The cold polar conditions and the glacioclimatic influences of the Transantarctic Mountains limit the mean annual water equivalent precipitation to < 50 mm yr-1, the majority of which is lost to sublimation prior to its incorporation in the local and regional hydrologic system (Fountain et al., 2009). As a result of these hypo-thermal and hyper-arid conditions, the MDV are characterized by the absence of vascular vegetation and the abundance of coarse sediments, bedrock outcrops, and ephemeral meltwater channels originating from local alpine and outlet glaciers (Doran et al., 2002). Although subtle, the resulting differences in temperature and relative humidity produce local microclimatic variations that create diverse micro-, meso-, and macro-scale landforms. (Marchant and Head, 2007). The valleys incise the Devonian-Triassic Beacon Supergroup, which are composed largely of sandstones, siltstones, and orthoquartzites, and the underlying Precambrian-Ordovician Granite Harbour Intrusives, composed of granites, granodiorites, gneisses, and orthogneisses (Isaac et al., 1995). Basaltic magmatism associated with the breakup of Gondwana at approximately 180 Ma (Fleming et al., 1997) intruded both the Beacon Supergroup and the Granite Harbour Intrusives and was emplaced in four prominent sills (the Ferrar Dolerite) and as surficial basaltic flows (the Kirkpatrick Basalt) throughout the region (Elliot and Fleming, 2004; Marsh, 2004) (Fig. 2). During 118 emplacement, the magmatic system experienced crustal assimilation (Fleming et al., 1995), complex differentiation processes (Bédard et al., 2007), and multiple injections that delivered slurries of phenocryst-laden magmatic “mush” into the lowermost portions of the intrusions (Marsh, 2004). Of the four major sills, the lower sills (Basement Sill and Peneplain Sill) exhibit the largest range of magmatic products and textures, whereas the upper sills (Asgard Sill and Mt. Fleming Sill) are characterized by near-liquid compositions and largely sub-ophitic textures (Fleming et al., 1995; Elliot and Fleming, 2004; Marsh, 2004). The dolerites within the MDV are most closely related to the Mount Fazio chemical type (MFCT) lavas of north Victoria Land, which are characterized by intermediate Mg# (~ 40-50) and MgO contents (4.5-7.5 wt.%), with higher values present where pyroxenes have accumulated (Fleming et al., 1995). The emplacement, modification, and subsequent cooling of the Ferrar Dolerite has resulted in significant chemical and mineralogical variations, which can be identified in the well-exposed outcrops throughout the MDV (Marsh, 2004; Bédard et al., 2007). Prior to cooling, additional pulses of magmatic intrusion occurred and injected orthopyroxene- (opx-) laden magmatic slurries into the two lowermost sills. These slurries, however, were unable to infiltrate the uppermost sills or reach the surface, resulting in mineralogical, chemical, and textural variations throughout the different outcrops of the Ferrar Dolerite (Marsh and Wheelock, 1994; Heyn et al., 1995; Marsh, 2004; Bédard et al., 2007). Outside the zone of opx-enrichment, dolerites exhibit an average MgO concentration of 7.0 wt.%, whereas the MgO concentration can exceed 20 wt.% within opx-rich zones (Marsh, 2004). Additionally, exposures of the Basement Sill exhibit silicic segregations (Zavala et al., 2011) as well as massive cryptic layering that 119 alternates between anorthosite (~14 wt.% CaO, 10 wt.% MgO) and pyroxenite (~8 wt.% CaO, 16 wt.% MgO) (Marsh, 2004). After emplacement of the dolerite sills, the Transantarctic Mountains underwent complex geological history that included deep burial and exhumation during the late Mesozoic and Cenozoic eras (e.g. Fitzgerald et al., 2006). Following exhumation and upon exposure to the hyper-arid and hypo-thermal Antarctic environment, the dolerites have undergone chemical alteration and micro-structural modification (e.g. Glasby et al., 1981; Head et al., 2011). In particular, dolerites undergo rapid surface modifications in response to the oxidizing Antarctic environment. In Beacon Valley, the southernmost and highest of the MDV, chemical alteration results largely from these anhydrous oxidation processes (Salvatore et al., unpublished data). In response to a strong oxidation gradient, divalent cations are preferentially removed from the rock surface, which results in the oxidation of Fe2+ to network-modifying Fe3+ and creates metastable structural changes in the rock surface (e.g. Cooper et al., 1996). These alteration products, while difficult to identify using most laboratory techniques due to the minute chemical and mineralogical variations, are easily observed in visible/near-infrared (VNIR) and thermal- infrared (TIR) spectroscopic analyses due to the near-surface modifications and the sensitivity of these techniques to the minor variations. Oxidation of iron in pyroxenes and the formation of metastable structures in response to cation migration are responsible for unique VNIR and TIR spectral signatures, respectively (Fig. 3). In the VNIR, a strong Fe2+-Fe3+ intervalence charge transfer absorption forms in the spectra of dolerite surfaces, with only subtle variations observed throughout the rest of the spectrum. No evidence for the formation of additional hydration features (e.g. sharp OH- vibrational 120 absorptions between 2.0 μm and 2.5 μm) were detected in the VNIR. In the TIR, a substantial narrowing of the primary reststrahlen features centered near 1100 cm-1 (9.1 μm) and 465 cm-1 (21.3 μm) is observed in dolerite surfaces relative to their interiors, which is thought to reflect the production of minor amounts of metastable and immature alteration products. Under the current hyper-arid and hypo-thermal environmental conditions in Beacon Valley, more mature and crystalline alteration phases (including smectite clays) are unable to form. As a result, these metastable, incomplete, and immature alteration products, which are typically overprinted in most terrestrial environments, are uniquely preserved in Beacon Valley. Understanding the spatial distribution of both primary and secondary mineralogies throughout the dolerite units will shed light on the geochemical evolution and alteration history of the MDV. In this study, we characterize the mesoscale (101 – 104 m) compositional and spectroscopic variability within the Ferrar Dolerite due to both primary and secondary processes using the Advanced Land Imager (ALI) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) orbital datasets (Table 1). Orbital spectral datasets have not been widely utilized in compositional investigations of the MDV because of the difficulties associated with photometric calibration and atmospheric correction at such high latitudes. Additionally, spectral verification and ground truthing is a challenging in remote and mountainous environments where not all lithologies or geographic regions may be easily accessible. As a result, a large component of this work has focused on the calibration and correction of these orbital datasets to obtain georeferenced and mosaicked surface reflectance and emission signatures that are acceptable for geologic and geochemical investigations. 121 Laboratory spectroscopy and chemical analyses were performed to further validate these data, to provide additional hyperspectral information on representative dolerite samples, and to determine the range of chemical variability observed due to primary magmatic evolution and secondary alteration processes. At spatial resolutions of 30 m pix-1 and 90 m pix-1, respectively, ALI and ASTER provide regional perspectives on the compositional nature of the Ferrar Dolerite across the majority of the ice-free portions of the MDV. We focus on four main geographic regions within the MDV (Fig. 1). Samples from these locations have either been extensively analyzed in previous studies or were collected by the authors and subsequently analyzed for this study. These locations include Beacon Valley, the Labyrinth of Upper Wright Valley, Central Wright Valley (including the southwestern portion of Bull Pass), and Victoria Valley. These locations highlight both the spectral and igneous diversity observed in the Ferrar Dolerite and help to limit our subsequent analyses to regions that have been well characterized. Beacon Valley is the coldest (mean annual temperature of -22º C (Doran et al., 2002)), driest (mean annual water equivalent precipitation of less than 10 mm yr-1 (Schwerdtfeger, 1984; Fountain et al., 2009)), and highest (mean elevation of approximately 1200 m above the World Geodetic System 1984 ellipsoid (Schenk et al., 2004)) of the MDV. Exposed along the valley walls are outcrops of the Asgard and Mt. Fleming sills in addition to a significant sedimentary component of the Beacon Supergroup. The valley floor, however, is composed almost entirely of doleritic clasts with only minor quartzitic and granitic components present in the northern half of the valley. The Labyrinth of Upper Wright Valley is thought to have formed as a result of 122 episodic and immense drainage of subglacial bodies of water (Lewis et al., 2006). The resultant canyon and plateau system exposes large outcrops of the Peneplain Sill of the Ferrar Dolerite. Upper Wright Glacier bounds this system to the west, the Dais of Wright Valley is present to the east, and large cliffs composed of the Beacon Supergroup flank both the northern and southern margins. Victoria Valley, in the region south of Lake Vida, hosts one of the most complete exposures of the Basement Sill and its contact with the underlying granitic basement. The shallow slope and large spatial extent reveal significant compositional diversity within the Basement Sill that is readily observable from orbit. The Basement Sill is also exposed in Central Wright Valley and Bull Pass, which exhibit some of the strongest mafic signatures identified from orbit throughout the MDV. There is a significant amount of laboratory data from samples collected in this region as a result of studies by Marsh and Wheelock (1994), Heyn et al. (1995), Fleming et al. (1995), Elliot and Fleming (2004), Marsh (2004), Bédard et al. (2007), and others, making this region particularly appealing for orbital investigations. Following radiometric and atmospheric calibration and correction of the orbital datasets, we use TIR orbital data to identify regions that are spectrally dominated by doleritic signatures. This task was performed by utilizing laboratory-derived spectral endmembers and a linear unmixing algorithm to differentiate between doleritic, quartzitic, and granitic compositions. We then assess the range of observed spectral signatures in the dominantly doleritic regions using an additional least-squares linear unmixing algorithm to identify the distribution of unique doleritic endmembers and spectral components. The distribution of these doleritic signatures throughout the MDV 123 shed light on the characteristics of magmatic intrusion as well as the production, distribution, and preservation of secondary alteration phases. 2.0 Methods 2.1 Laboratory spectral investigations Spectra of 64 altered and unaltered dolerites, granites, granodiorites, and quartzites from throughout the MDV were collected in both the VNIR (Brown University Reflectance Experiment Laboratory (RELAB) Facility and FieldSpec-3 portable VNIR spectrometer developed by Analytical Spectral Devices, Inc.) and TIR (Stony Brook University Vibrational Spectroscopy Laboratory) spectral regions. VNIR spectral measurements are sensitive to electronic transitions and vibrational processes within materials (Farmer, 1974), while TIR spectral measurements measure the fundamental vibrational motions associated with a range of geologically pertinent anion groups (SiO4, CO3, etc.) (Christensen et al., 2000). RELAB measurements were made using a bidirectional reflectance (BDR) spectrometer, which acquires spectra between 0.32 and 2.55 μm at a 5 nm spectral sampling interval using a photomultiplier and InSb detectors (Pieters, 1983; Mustard and Pieters, 1989). FieldSpec-3 measurements were made using an external light source and Spectralon white reference calibration targets. Both BDR and FieldSpec-3 illumination and emergence angles were fixed at 30º and 0º, respectively. TIR emission spectra were acquired using a Nicolet 6700 FTIR Spectrometer, which utilizes a deuterated L-alanine doped triglycine sulfate (DLaTGS) detector and CsI window. Measurements were made between 2000 cm-1 and 200 cm-1 (5 μm and 50 μm) at a sampling resolution of 4 cm-1 (variable depending on wavelength, 124 0.01 μm at 5 μm, 1.00 μm at 50 μm) using a CsI beamsplitter. All laboratory measurements were also resampled to orbital ALI and ASTER spectral bandpasses for direct comparison to these orbital datasets. Bulk chemistry of 18 unaltered dolerite samples were obtained using inductively coupled plasma atomic emission spectroscopy (ICP-AES) via the flux fusion dissolution technique (Murray et al., 2000). To dissolve the materials into solution, powdered samples were divided into 40 mg aliquots, mixed with 160 mg LiBO2, and fused for 10 minutes at 1050º C. The melts were quenched in 20 mL of 10% HNO3 and agitated for one hour. The samples were then filtered through 0.45 μm filters and diluted in additional 10% HNO3. The resultant liquids were analyzed using a JY2000 Ultrace ICP Atomic Emission Spectrometer. Elemental abundances were calculated using a Gaussian peak search technique and the results were calibrated and converted to weight percentages using a series of blanks and geochemical standards that were processed in the same fashion as the samples (Murray et al., 2000). All samples, standards, and blanks were run in duplicate to increase the measurement statistics. Each sample was measured for Si, Al, Ca, Fe, Mg, Mn, Na, K, Ti, and P. 2.2 Orbital data acquisition, calibration, and atmospheric removal ALI is a pushbroom imaging system onboard the Earth Observing-1 spacecraft. The data consist of ten spectral bands (Mendenhall et al., 2000); nine multispectral bands ranging from 0.443 μm to 2.215 μm with an optimal spatial resolution of 30 m pix-1, and one panchromatic band centered at 0.585 μm with an optimal spatial resolution of 10 m pix-1 that is not used in this study. Five ALI scenes were obtained from the U. S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center 125 website at glovis.usgs.gov (date accessed: 14 June 2011) (Table 1). These data were then converted from their original raw digital number format (Q) to calibrated digital numbers (Qcal), followed by conversion to at-sensor spectral radiance (Lλ) using the methods discussed in Chander et al. (2009): 𝐿𝜆 = 𝐺𝑟𝑒𝑠𝑐𝑎𝑙𝑒 × 𝑄𝑐𝑎𝑙 + 𝐵𝑟𝑒𝑠𝑐𝑎𝑙𝑒 where: 𝐿𝑀𝐴𝑋𝜆 − 𝐿𝑀𝐼𝑁𝜆 𝐺𝑟𝑒𝑠𝑐𝑎𝑙𝑒 = 𝑄𝑐𝑎𝑙𝑚𝑎𝑥 − 𝑄𝑐𝑎𝑙𝑚𝑖𝑛 and 𝐿𝑀𝐴𝑋𝜆 − 𝐿𝑀𝐼𝑁𝜆 𝐵𝑟𝑒𝑠𝑐𝑎𝑙𝑒 = 𝐿𝑀𝐼𝑁𝜆 − 𝑄𝑐𝑎𝑙𝑚𝑖𝑛 𝑄𝑐𝑎𝑙𝑚𝑎𝑥 − 𝑄𝑐𝑎𝑙𝑚𝑖𝑛 where Lλ is the spectral radiance at the sensor’s aperture [W/(m2 sr μm)], Qcal is the quantized calibrated pixel value [DN], Qcalmin (Qcalmax) is the minimum (maximum) quantized calibrated pixel value corresponding to LMINλ (LMAXλ) [DN], LMINλ (LMAXλ) is the spectral at-sensor radiance that is scaled to Qcalmin (Qcalmax) [W/(m2 sr μm)], Grescale is the band-specific rescaling gain factor [(W/(m2 sr μm))/DN], and Brescale is the band-specific rescaling bias factor [W/(m2 sr μm)]. 126 Atmospheric contributions were then removed from the at-sensor spectral radiance through a hybrid dark object subtraction and regression (DOS-R) method (Chavez, 1996; Lu et al., 2002). This method estimates the atmospheric contributions to a surface spectrum by measuring homogeneous surfaces over a range of illumination conditions. Assuming the last spectral band (band 10, 2.215 μm) is devoid of scattered downwelling radiance, the other spectral bands are plotted against this last spectral band and regressions are found to identify the atmospheric contributions where those bands project to zero solar input. Multiple iterations of this technique are performed over multiple spectral sampling locations in each image to derive the average atmospheric contribution for each ALI scene. Each DOS-R sampling location was selected based on the identification of a range of illumination conditions (from bright to dark, typically on slopes where a range of shadow conditions are present) as well as the verification of a geologically homogeneous surface (e.g., glacial tills on valley floors, slopes with single lithologies present). The average contributions from these spectral sampling locations are then subtracted from the previously derived at-sensor spectral radiance for each individual band in each individual image. The locations used for this DOS technique are shown in Figure 1 (orange stars) and are provided, along with the derived average atmospheric contributions, in Table 2. The assumption that ALI band 10 is devoid of scattered downwelling radiance is based on the Rayleigh equation, which predicts that the amount of scattered radiance at 2.215 μm is 0.03%. The paucity of scattered radiance and the relationship between band 10 and the other spectral bands is also shown in Figure 4. The frequency distribution of spectral radiance in 3,372 shadowed pixels measured in each band of ALI scene 127 EO1A0581152008022110KG is shown in Figure 4a and is scaled for each band. The high radiances measured in the lowest ALI bands represent the strong effects of scattering at the shortest wavelengths. However, at longer wavelengths, the contributions from scattered downwelling radiance become very small. Figure 4b is a magnified portion of Figure 4a (marked by a dashed line) and shows the scaled radiance values for the three ALI bands at wavelengths beyond 1 μm. The majority of spectral radiance values measured in band 10 are less than 0.1 W/(m2 sr μm) and represent 0.057% of the scattered downwelling radiance. This example validates our assumption that band 10 is essentially devoid of scattered downwelling radiance. An example of a DOS-R regression scatterplot is shown in Figure 4c, where 42 spectra (located near -77.75º N, 160.64º E) from a homogeneous surface under varying illumination conditions were extracted and plotted against their measured radiance values for band 10. Regressions modeled to these data exhibit good fits, and their y-intercept represents their theoretical radiance values when band 10 equals zero. In this example, the y-intercept value for band 8 is 0.7379 W/(m2 sr μm), which is equal to the scattered downwelling radiance estimated at 1.25 μm. Three in situ VNIR calibration sites were identified and measured in November of 2010. A 100 m x 100 m grid was demarcated by GPS coordinates at three different locations of varying surface albedo. Spectral measurements between 0.35 μm and 2.50 μm were made using a FieldSpec-3 portable field spectrometer every 10 meters throughout the gridded area, with calibration targets measured after every tenth measurement. These data were then averaged to produce a representative VNIR spectrum for each of the three calibration locations. However, two of the three 128 calibration locations overlap with pixels that were excluded from our spectral map due to the presence of snow and ice in the only ALI image covering these locales. To make it possible to utilize this valuable dataset, a Landsat image (Table 1) was calibrated (using the methods of Chander et al. (2009)) and atmospherically corrected using these three spectral grid locations. Spectra of four regions of overlap between the Landsat image and our multispectral map were acquired and compared to determine the agreement between the two datasets. The spectra of three doleritic regions and one quartzitic region are compared in Figure 5, which confirms that the DOS atmospheric correction technique appropriately removes the majority of atmospheric contributions from our spectral map despite the exclusion of these three calibration grids. This exercise also demonstrates the advantage of ALI data over Landsat in the ability to better resolve the diagnostic absorption features associated with the dolerites. The DOS-R atmospheric correction technique was chosen over more complex physically-based modeling (e.g., FLAASH, MODTRAN, ATCOR3) because of (1) the amplification of scattering and aerosol contributions at high latitudes, (2) the difficulty in constraining atmospheric parameters for the remote and highly variable MDV, and (3) the good agreement between ground-truthed orbital datasets and the DOS-R-corrected ALI datasets. The longer atmospheric path lengths, due to the low solar elevations at high latitudes, significantly enhance the contributions of scattering and aerosols within an image. Small errors in aerosol estimates can also result in significant errors in retrieved surface reflection values as a result of these low solar elevations. Additionally, more sophisticated physically-based atmospheric modeling requires either the collection of considerable amounts of in situ atmospheric data (e.g., weather ballon observations) 129 and/or complex atmospheric simulations. Unfortunately for studies of the MDV, the nearest site of frequent atmospheric data collection (McMurdo Station) is located 80 – 160 km to the east. Weather conditions within the MDV are also highly variable over both spatial and temporal scales (Doran et al., 2002), making modeling of atmospheric parameters extremely difficult. Lastly, our DOS-R-corrected ALI data are in good agreement with our already ground-truth corrected Landsat scenes. The results showed very good agreement, particularly at wavelengths greater than 0.6 μm where the effects of atmospheric scattering are less pronounced (Fig. 5). Further use of the DOS-R method on additional ALI scenes also resulted in good inter-scene spectral agreement, indicating that, for the purposes of our spectral and geochemical investigations, the DOS-R technique performs well. Atmospherically corrected at-sensor spectral radiance is then converted to surface reflectance using the following equation (Chander et al., 2009): 𝜋 × 𝐿𝜆 × 𝑑 2 𝜌𝜆 = 𝐸𝑆𝑈𝑁𝜆 × cos 𝜃𝑠 where ρλ is the planetary reflectance [unitless], Lλ is the spectral radiance at the sensor’s aperture [W/(m2 sr μm)], d is the Earth-Sun distance on the date of acquisition [astronomical units], ESUNλ is the mean exoatmospheric solar irradiance [W/(m2 μm)], and θs is the solar zenith angle [degrees]. Atmospherically corrected reflectance measurements of compositionally pure locations in the MDV are in good agreement with laboratory measurements (Fig. 6a), which confirms the efficacy of the DOS-R technique. 130 Following the calculation of surface reflectance for each spectral band (after atmospheric correction, ρλ is equivalent to surface reflectance), the individual spectral bands were stitched and mosaicked using the Environment for Visualizing Images (ENVI) software developed by Exelis Visual Information Solutions. ASTER thermal infrared images consist of five spectral bands ranging from 8.3 μm to 11.4 μm, have an optimal spatial resolution of 90 m pix-1, and are acquired using a whiskbroom mechanism (ERSDAC, 2005). Five ASTER scenes were utilized in the production of the spectral mapping product (Table 1) and were acquired from the NASA Land Processes Distributed Active Archive Center (LP DAAC) at https://lpdaac.usgs.gov/lpdaac/get_data/wist (date accessed: 13 August 2010). Data were acquired as Level 2B AST_05 products, which have already been calibrated and converted to surface emissivity using the Temperature/Emissivity Separation (TES) algorithm described in Gillespie et al. (1998). These data were compared to laboratory derived emissivity measurements to ensure that the pre-calibration was effective. In all cases, the Level 2B AST_05 data of compositionally pure locales throughout the MDV were spectrally consistent with laboratory-derived spectra, confirming that further corrections or calibrations were not required (Fig. 6b). The five images were mosaicked with each other and to the five ALI images to create a single multispectral dataset. The entire dataset was merged to accommodate the full spatial resolution of the ALI dataset. As a result, the ASTER dataset is highly pixilated in comparison to the ALI dataset, although no interpolation or data modification was applied during this process. The ten images were then geographically mosaicked in ENVI to produce a single image with fourteen spectral bands. All imagery was georeferenced prior to delivery, and 131 coregistration was manually verified before mosaicking. Pixels containing water, ice, snow, clouds, and shadows were removed from the spectral mosaic through isolation of their unique spectral properties, as discussed below. The resultant product consists of 1.57 x 106 multispectral data points over the ice-free MDV. A parameterization of this final spectral product is shown in Figure 1. High latitude mountainous terrains are influenced by considerable variations in illumination angle in addition to the presence of pronounced shadows. Topography and illumination angle have been shown to not influence remote spectral identifications (Domingue and Vilas, 2007), although they have been shown to have minor effects on mineral abundance estimations using nonlinear modeling techniques (Cord et al., 2005). Water, ice, snow, and clouds are easily separated from rocky surfaces using atmospherically corrected surface reflectance data. In the VNIR, water and ice have reflectance maxima in the visible wavelengths and their reflectance decreases significantly at longer wavelengths (Fig. 7a). In contrast, rocky surfaces generally exhibit relatively low reflectance values in the visible wavelengths as compared to longer wavelengths. To exploit these spectral disparities, a spectral parameter was established to identify water- and ice-rich pixels. If the corrected surface reflectance value at 0.565 μm is more than twice that at 1.65 μm, the pixel was removed from the scene. In the TIR, water and ice exhibit relatively high emissivity values across the entire ASTER spectral range relative to rocky surfaces, which exhibit large variations due to the presence of diagnostic structural vibrations (Fig. 7b). To exploit this spectral characteristic, pixels were determined to be contaminated by water or ice if the average emissivity value over 132 all five spectral bands was greater than 0.95. These pixels were identified and removed from the spectral mosaic. Spectral parameters were also developed to identify shadowed regions following the removal of pixels contaminated by water and ice. In the VNIR, pixels dominated by rocky materials typically exhibit high reflectance values in the ALI band positioned at 1.65 μm. For example, the final spectral dataset has an average reflectance value at 1.65 μm of 0.183 with a standard deviation of 0.097. Shadowed regions, however, exhibit extremely low reflectance values following atmospheric correction. As a result, pixels exhibiting a reflectance at 1.65 μm less than 0.03 were identified and removed, as they are dominated by shadows. ASTER data were already corrected for the effects of shadows during TES processing and surface emissivity derivation (Gillespie et al., 1998), and the algorithm is capable of calculating emissivity values regardless of time of day or extent of shadowing. 2.3 Identification of spectrally pure dolerite using ASTER TIR data Assessing the spectral variability within purely doleritic terrains requires that the data be limited exclusively to regions composed of dolerites and lack significant abundances of other lithologies. Deriving the areal abundance of surface compositions is theoretically straightforward using TIR emission spectroscopy due to the extremely high absorption coefficients exhibited by most geologic materials in this wavelength region. As a result, the observed spectral signal is derived from the uppermost surface and is a linear combination of the compositional constituents present on the surface (Ramsey and Christensen, 1998). Deconvolving complex mixtures in the VNIR spectral region is more complex due to the significant contribution of volume scattering of rays that have been 133 refracted into and out of individual mineral grains (Hapke, 1981). However, mineral identification and parameterization in the VNIR spectral region is a widely used technique that has been verified through both field and laboratory validation. We ran a least squares linear retrieval algorithm (Ramsey and Christensen, 1998) using spectral endmembers derived from laboratory measurements to identify regions that are spectrally dominated by dolerite using in the TIR. Because this algorithm limits the number of endmembers to one fewer than the number of spectral bands, our library is limited to a maximum of four endmembers. The four selected endmembers highlight the extremes of lithological variation throughout the MDV (Fig. 8). Unaltered dolerites from Beacon Valley and Bull Pass were selected to represent the Mg-poor and Mg-rich endmembers of the Ferrar Dolerite, respectively, while a granite from Victoria Valley and quartzite from Wright Valley were chosen to represent the Si-rich lithologic endmembers (e.g., the Granite Harbour Intrusives and the Beacon Supergroup, respectively). The results of this unmixing algorithm are reported in Fig. 9. The unmixing yields an average root-mean-squared (RMS) error of 0.0048 ± 0.0033, indicating that the majority of the spectral diversity within the scene can be accounted for by these four spectral endmembers. The highest RMS error values (0.041) appear to be associated with atmospheric contamination and clouds that were not properly removed during calibration, as the spectra do not appear consistent with any known geologic materials that are present within the MDV and are often tightly aggregated. The lack of areas with high RMS error associated with geographically coherent units indicates that no major lithologies are being excluded from our endmember library. 134 Areas identified as non-pure dolerite pixels (< 90% Mg-poor + Mg-rich dolerites, as modeled during linear unmixing) were removed from the rest of the spectral mapping product, leaving only those pixels mapped as having > 90% modeled dolerite. The sensitivity of thermal wavelengths to the presence of quartz makes the detection of even small amounts of granite and quartzite contamination possible. The 90% threshold for dolerite abundance was selected to minimize the spectral contribution of quartzites and granites; the number holds no geologic or geochemical significance. As a result, we utilized this constraint to qualitatively select our regions of spectrally pure dolerite. 2.4 Identification of spectral variability within the Ferrar Dolerite using ASTER TIR data Subsequent to subsetting pure dolerite pixels from the rest of the image, an endmember library containing unaltered Mg-rich dolerite, unaltered Mg-poor dolerite, and altered Mg-poor dolerite was used to unmix the pure dolerite pixels to assess the primary mineralogy and the extent of surface alteration contributing to these pixels (Fig. 8). An altered Mg-rich dolerite was not included in this endmember library because of its absence from our sample suite, which will be discussed below. Altered dolerite surfaces exhibit strong Fe3+ absorption features at visible wavelengths, but lack any diagnostic near-infrared spectral signatures. In contrast, altered dolerite surface exhibit a dramatic sharpening of the major TIR absorption feature centered near 9.1 μm as a result of the breakdown of microscale mineral structures (Salvatore et al., unpublished data). While considerably different from the unaltered dolerite spectra, the overall spectral shape of the altered Mg-poor dolerite is also different from that of granites or quartzites. Accordingly, in the previous unmixing algorithm, units containing substantial quantities 135 of altered dolerites were mapped as unaltered dolerites with slightly higher RMS errors; this can be seen in Figure 9f in southern Beacon Valley. To ensure that granitic or quartzitic components were successfully eliminated from the pure dolerite pixels assessed here, both granite and quartzite endmembers were alternated into this second unmixing model. Only 74 pixels were modeled as including more than 10% granite or quartzite, with the highest abundance being 15.14%. These pixels were removed to ensure that the pixels under investigation consist of spectrally pure dolerite surfaces. 2.5 Resultant spectral products Two spectral products result from the assembly of these datasets. The first product is a 14-band multispectral image of pure dolerite pixels throughout the MDV, which provides the spectral data necessary to create summary parameters (e.g., Table 3). The spatial resolution of the VNIR and TIR datasets are 30 m pix-1 and 90 m pix-1, respectively. The second product is a 5-band linear unmixing product, mapping the relative percentage of Mg-poor unaltered dolerite, Mg-poor altered dolerite, and Mg-rich unaltered dolerite throughout the scene, normalized to 100%. The other two bands consist of a modeled blackbody component, which is used to scale the endmember spectra to fit the measured ASTER data, in addition to a band containing the modeled RMS error for each pixel. These three-dimensional products (two spatial dimensions, one spectral dimension) provide the ability to assess the spatial distribution of these spectral components throughout the MDV. Additionally, spectral profiles can be generated to highlight the observed and modeled spectral variability along transects. 3.0 Results 136 Granites, quartzites, and dolerites each have unique spectral properties that can be identified and measured in the VNIR (Fig. 10) and TIR (Fig. 8). Laboratory spectral measurements provide hyperspectral data with which to interpret our multispectral orbital datasets. 3.1 Laboratory spectroscopy Laboratory VNIR spectra of samples from the Granite Harbour Intrusives (green spectrum, Fig. 10) show a relatively flat spectrum after a rapid increase in reflectance to approximately 0.6 μm with several sharp vibrational absorption features associated with OH- and H2O. These absorption features can be explained by a combination of an Al-OH phyllosilicate (likely muscovite; 1.4 μm, 1.9 μm, 2.2 μm) in addition to varying amounts of prehnite (1.5 μm, 2.35 μm), a Ca-Al silicate hydroxide that forms in specific metamorphic environments (Ehlmann et al., 2009). The TIR is dominated by a broad absorption feature near 9 μm with variable quartz signatures and a lack of mafic mineral absorptions present at wavelengths between 10 μm and 12 μm. When convolved to orbital bandpasses, the VNIR spectra of granites and granodiorites are relatively featureless with a steady increase in reflectance to 1.65 μm, whereas the TIR exhibits low emissivity values short of 10 μm followed by a rapid increase in emissivity beyond 10 μm (green spectrum, Fig. 8). Most outcrop-forming exposures of the Beacon Supergroup consist of quartzites with occasional shale, siltstone, and mudstone interbeds (Isaac et al., 1995). The quartzites exhibit a similar spectral shape to the granites and granodiorites in the VNIR, exhibiting a relatively flat spectrum that steadily increases in reflectance until a maximum at approximately 1.7 μm (blue spectrum, Fig. 10). The vibrational absorption 137 features associated with OH- and H2O are much stronger than those observed in the granites and can be explained by the presence of opaline silica (1.4 μm, 1.45 μm, 1.9 μm, 2.2 μm) and illite (1.4 μm, 1.9 μm, sharp 2.2 μm). The TIR emission spectra are dominated by the diagnostic quartz absorptions centered near 8.4 μm and 8.9 μm with an emissivity peak between the two absorptions near 8.62 μm. The remainder of the TIR spectrum is relatively featureless until approximately 12.5 μm, where a second pair of absorption features unique to quartz is present. Convolved to the orbital bandpasses, the quartzites exhibit a similar VNIR spectral shape to that of granites and granodiorites, except that the increase in reflectance up to 1.65 μm and the decrease in reflectance beyond 1.65 μm are both typically of greater magnitude. In the TIR, the first three ASTER bands are able to capture the absorption doublet and emission peak unique to quartz, while the last two bands exhibit significantly higher emissivity values (blue spectrum, Fig. 8). Two distinct classes of the Ferrar Dolerite are evident in the laboratory VNIR dataset. The first class of dolerites exhibits a low albedo and a relatively weak 1 μm and 2 μm absorption features associated with opx (Adams, 1974) (purple spectrum, Fig. 10). Additionally, the presence of a relatively broad absorption feature at 1.2 μm due to the Fe present in the M1 site of pyroxenes (Klima et al., 2008) causes the reflectance peak beyond 1 μm to be located at approximately 1.6 μm. The second class of dolerites is characterized by strong 1 μm and 2 μm absorption features and a masking of the weaker 1.2 μm absorption feature that is present in the first class of dolerites, causing the local reflectance maximum to be located near 1.3 μm (orange spectrum, Fig. 10). When convolved to orbital bandpasses, the spectral shapes of these classes are easily 138 distinguished by (1) the strength of the broad 1 μm and 2 μm opx absorption features (regarded as VNIR mafic band strength (MBS), see Table 3) and (2) the position of the local reflectance maximum at either 1.25 μm or 1.65 μm. The TIR signatures of these dolerite classes are also unique. The emissivity spectra from the first class of dolerites exhibit a broad and complex absorption feature between 8 μm and 12 μm with evidence for quartz, plagioclase, opx, and other minor phases (purple spectrum, Fig. 8). The second class of dolerites, however, exhibits stronger opx absorptions centered near 9.1 μm and 11 μm. When convolved to orbital bandpasses, the second class of dolerites exhibit a stronger decrease in emissivity between 8.6 μm and 9.1 μm, in addition to a less pronounced increase in emissivity between 9.1 μm and 10.65 μm, which reflect the additional opx contribution (orange spectrum, Fig. 8). While plagioclase fractionation and variability has been previously studied (e.g., Fleming et al., 1995), this component is difficult to assess using our spectroscopic techniques. In the VNIR, crystalline plagioclase exhibits a relatively weak and broad crystal field absorption near 1.25 μm due to the substitution of trace amounts of Fe2+ for Ca2+ (Adams and McCord, 1971). This feature, however, is commonly masked by the 1.2 μm pyroxene absorption feature (Klima et al., 2008). The minor TIR spectral variations expected for varying degrees of plagioclase fractionation are also difficult to observe in our analyses due to the broad and complex absorptions caused by multiple overlapping silicate mineralogies. However, the strong and diagnostic pyroxene absorption features are readily distinguishable in both VNIR and TIR spectral regions. The altered surfaces of many fine grained dolerites exhibit unique TIR spectral signatures. These signatures are dominated by a strong decrease in emissivity between 139 8.6 μm and 9.1 μm, followed by a sharp increase in emissivity from 9.1 μm to 10.65 μm (red spectrum, Fig. 8). This spectral shape is diagnostic of the breakdown of mineral structures at the rock surface as a result of surface oxidation and alteration and will be discussed further below. 3.2 Lithological mapping from orbit Laboratory spectra provide the necessary validation for interpreting orbital spectral signatures. Spectral parameters were heavily used to exploit unique spectral features (Table 3). In Figure 1, MBS is mapped in red, the intensity of the reflectance increase between 1.25 μm and 0.79 μm is mapped in green, and the height of the quartz emissivity peak at 8.62 μm relative to the depth of the two adjacent absorption features is mapped in blue. When combined into a single image, these parameters prominently highlight the lithologic diversity throughout the MDV (Fig. 1). Figure 11 compares the MBS relative to the strength of the quartz emissivity maximum for all of the pixels in the final spectral mapping product. Dolerites plot towards stronger MBS, whereas granites and quartzites plot at intermediate and strong quartz emissivity maximum values, respectively. The dense data cloud representative of weak values for each parameter represents the widespread and homogeneous sediments present in the valley floors and along mixed talus slopes, which comprise most of the image. When values for representative in-scene endmembers (boxes with widths and heights of one standard deviation) are plotted, it is evident that the representative laboratory measurements (circles) accurately represent the lithologies present throughout the MDV. The largest offset between laboratory and in-scene endmembers is associated with the dolerites, although there is a slight offset with quartzite measurements as well. 140 Sub-pixel mixing of quartz- and opx-rich material with the Mg-rich dolerites and quartzites, respectively, can explain the observed offset between laboratory and in-scene endmembers. The Mg-poor dolerite laboratory endmembers measured in this study were obtained from Beacon Valley, which is composed largely of quartz-normative dolerites, whereas portions of the lower sills are composed of hypersthene-normative dolerites (Fleming et al. 1995). As a result, the Mg-poor dolerites selected for laboratory measurements are expected to be the quartz-rich dolerite endmembers, as is confirmed in Figure 11. 3.3 Spectral variability of pure dolerite Purely doleritic pixels show a range of spectral variability associated with diagnostic compositional properties. Mapping the MBS in ALI reveals widespread variability throughout the Labyrinth, Victoria Valley, and Central Wright Valley, whereas Beacon Valley exhibits uniformly low values with little variability (Fig. 12). The strong MBS values are restricted to the middle of the lower dolerite sills and are absent from any surfaces dominated by dolerites from the upper sills. A similar distribution can be identified by mapping the location of the local reflectance maximum at either 1.25 μm or 1.65 μm, which was shown earlier to be diagnostic of pyroxene content. The centers of the lower sills exhibit the reflectance maximum at 1.25 μm, whereas the margins of the lower sills and the entirety of the upper sills exhibit the reflectance maximum at 1.65 μm (Fig. 13). While ALI only has one spectral band located in the region dominated by OH- combination tones (band 10, 2.215 μm), its broad full width at half maximum (0.135 μm) and the lack of other nearby spectral bands also make the identification of hydrated 141 alteration phases difficult. As a result, in the absence of additional mineralogical information, ALI cannot be used to determine the presence or abundance of hydrated alteration phases. However, none of the dolerites investigated in this study exhibit vibrational absorption features between 2.0 μm and 2.5 μm. All dolerite surfaces instead exhibit strong absorption features at wavelengths shorter than 0.7 μm that are associated with Fe3+. Unfortunately, these features are also difficult to characterize using ALI due to the unavoidable influences of Rayleigh scattering in the remote investigations of high latitudes. As a result, we have not considered quantitatively assessing the degree of surface oxidation using this spectral region. Significant variability in TIR spectra is observed throughout the Ferrar Dolerite, as is evident from the linear unmixing of purely doleritic pixels (Fig. 14). The low average RMS error (0.0043 ± 0.0016) confirms the goodness of fit of the model. In Beacon Valley, the most significant spectral contributor is the altered Mg-poor dolerite, with only minor contributions from the unaltered endmembers. In the Labyrinth, unaltered mafic dolerite signatures dominate the central regions with perhaps the strongest signatures present along the scree slopes. Altered dolerite signatures are modeled along the western, northern, and southern margins. The Labyrinth shows the largest RMS errors associated with the unmixing algorithm, although the values still represent good spectral fits. These high RMS errors are likely to be a result of the Mg- rich dolerite endmember spectrum being derived from samples largely collected from Victoria Valley and Bull Pass, with only a few samples collected from the Labyrinth. Central Wright Valley and Bull Pass are also dominated by unaltered mafic dolerites, with less mafic dolerite contributing significantly to the dolerite lobe along the 142 southeastern portion of Central Wright Valley and altered dolerite signatures modeled along the eastern edge of Bull Pass. Lastly, Victoria Valley is largely characterized by unaltered mafic materials, while substantial altered components are modeled along the northwestern portion of Victoria Valley as well as along the central portion of the exposed sill. The alteration signatures observed in the Labyrinth are particularly intriguing due to their distribution only along the western, northern, and southern margins (Fig. 14d), where the current surface elevations are highest. To test the relationship between alteration signatures and surface elevation, an average of fifteen south-to-north profiles was made across the Labyrinth with the surface elevation (as measured by airborne LIDAR measurements (Schenk et al., 2004)) and the modeled abundance of altered dolerite values extracted. There is a clear relationship between higher elevations and higher modeled abundances of altered dolerites (Fig. 15a). The Pearson correlation coefficient of the relationship between these two parameters is 0.56, with a Student’s t- test value confirming to a 95% confidence level that the elevation of the surface provides information to the prediction of the modeled altered surface abundance. In addition, the sum of the chi-square value is equal to 35.5 with 181 degrees of freedom, verifying that there is a probability of less than 1% that the data can be explained by randomness alone. Together, these statistical tests conclude that areas of higher elevation in the Labyrinth are correlated with regions of higher modeled altered dolerite abundances. A single representative topographic profile is provided in Figure 15b to highlight the topographic variability within the Labyrinth and along its margins. Background colors are consistent 143 with the stratigraphic profile in Figure 2 and demarcate the approximate locations of the sill chilled margins and the opx-enriched interior. 3.4 Chemical variability within the Ferrar Dolerite Bulk rock MgO and CaO concentrations follow similar trends to those identified in Marsh (2004), with more evolved magmas showing an increase of CaO with increased MgO below ~ 7 wt.% MgO, representing the near-liquid compositions of the upper sills and the sill margins of the lower sills (Fig. 16a). At MgO concentrations greater than ~ 7 wt.%, CaO decreases with increasing MgO concentration, representing the addition of more primitive opx-bearing magmas. A similar relationship is also seen when plotting the MBS against MgO (Fig. 16b); below ~ 7 wt.%, the strength of the MBS remains relatively constant, whereas samples with MgO concentrations greater than 7 wt.% show a systematic increase in MBS. Because ALI bandpasses were used to calculate the MBS in laboratory data, this relationship can be used in the analysis of orbital datasets to approximate the MgO concentration in different doleritic regions throughout the MDV by applying the equation in Figure 16b to the map shown in Figure 12. This equation converts the low and high MBS values identified in Figure 12 to 6.6 wt.% MgO and 32.5 wt.% MgO, respectively, which are broadly consistent with MgO abundances measured in rocks from Central Wright Valley presented by Marsh (2004). These values should be regarded as estimates, as several potential sources of error exist, including the effects of topography, illumination angle, and shadows, although these effects are likely to be minor (Cord et al., 2005; Domingue and Vilas, 2007). 144 4.0 Discussion 4.1 Identification and distribution of doleritic signatures The spectral signatures of purely doleritic regions of the MDV can be effectively characterized using an endmember library derived from laboratory measurements of dolerite samples documented and collected in key areas of the MDV. Variations in both primary mineralogies and secondary alteration products are identified in laboratory measurements, which can then be linked to spectral signatures observed from orbit. For example, TIR orbital data indicates that the majority of the variability in the lower sills is due to variations in the primary mineralogy of the dolerite (Fig. 14a-c). However, in the upper sills, the presence and abundance of alteration products account for the majority of the observed spectral variability (Fig. 14d). In the VNIR, the lower sills exhibit a range of MBS values that are associated with the presence and abundance of opx-rich dolerites (Fig. 12a-c). However, the upper sills exhibit little variability in MBS, as these dolerites consist largely of fine-grained dolerites of minimal chemical variability (Fig. 12d). Variations in primary igneous compositions are in good agreement with previous studies that have identified major chemical variations within the Ferrar Dolerites exposed throughout the MDV. The zones of opx-enrichment identified by Marsh (2004) are clearly visible in VNIR orbital data as the regions of heightened MBS values. Significant exposures of opx-rich dolerites that were not detailed in Marsh (2004) can also be observed and characterized from orbit, particularly in Victoria Valley and the Labyrinth (Fig. 12). The identification of these variations in primary mineralogy add spatial context to the studies of Marsh (2004), Bédard et al. (2007), and other works that use laboratory investigations to identify local mineralogical and chemical heterogeneities. Spectral 145 effects associated with silicic segregations were not observed in our orbital datasets due to their small spatial scales and extents (typically ≤ 2 m thick (Zavala et al., 2011)). The distribution of secondary alteration products is also in good agreement with previous studies of chemical weathering in the MDV. The VNIR and TIR spectral signatures of dolerite surfaces from Beacon Valley exhibit unique spectral signatures, as compared to their unaltered interiors (Fig. 3), that represent anhydrous oxidation in response to the oxidizing Antarctic environment (Salvatore et al., unpublished data). While Fe3+ absorption features in the VNIR are difficult to characterize from orbit, the shape and characteristics of ASTER TIR spectra are consistent with the presence of altered dolerites throughout Beacon Valley (Fig. 6). These signatures are strongest along the valley floor and weakest along the western walls, suggesting that the exposed walls of Beacon Valley are younger and less altered than the floors, which have had sufficient time to develop and preserve alteration products. Why are TIR chemical alteration signatures almost exclusively concentrated in Beacon Valley? The development of alteration products is not likely to be limited to certain rock chemistries; opx-rich lithologies are just as (if not more) susceptible to chemical alteration than those of near liquid composition (Lasaga, 1984). The maturation and preservation of alteration products is more likely to be related to variations in sill properties as exposed in the different valleys. The upper sills, which are devoid of mafic intrusions and were intruded into cold sedimentary rocks, are characterized by fine grained igneous textures. As suggested by Glasby et al. (1981), fine grained dolerites are the best hosts for alteration rinds due to their resistance to physical weathering. The lower dolerite sills were both intruded at a greater depth and were subject to multiple 146 episodes of magmatic injection, providing a heat source and ample time for prolonged crystal growth. Whereas some coarse grained dolerites do effectively preserve alteration rinds and their associated spectral signatures, most coarse grained dolerites are easily weakened by aeolian abrasion, thermal cycling, freeze-thaw cycling, and other means of physical breakdown and erosion (Marchant et al., 2013). As a result, alteration products that form on coarse grained dolerites are easily lost to flaking or disintegration before they can become significant spectral components of the rock surfaces. The western, northern, and southern margins of the Labyrinth also show evidence of altered dolerite signatures in ASTER data (Fig. 14a). These areas are associated with the upper margin of the Peneplain Sill, which is relatively fine grained (as compared to the central regions of the Peneplain Sill) and has a composition similar to the near liquid dolerites from Beacon Valley (Marsh and Wheelock, 1994). Transitioning to lower elevations and into the opx-enriched portion of the Peneplain Sill, alteration signatures are modeled at lower abundances due to the difficulties associated with preserving alteration rinds (Fig. 16). The other localized area of altered TIR signatures includes portions of Victoria Valley. The exposure of the Basement Sill in Victoria Valley is bisected by a narrow valley that connects the topographically higher Bull Pass to Lake Vida in Victoria Valley (Fig. 1). The margins of this valley exhibit TIR alteration signatures that may be associated with erosion from this ancient channel, which masks the underlying mafic compositions. However, no samples were collected from this location and so identifying the cause of the narrow reststrahlen bands is purely speculative. The northwestern margin of Victoria Valley also exhibits narrow reststrahlen bands typical of altered 147 dolerites (Fig. 14b). This locale appears to be a portion of the lower margin of the Basement Sill, which is thought to be associated with finer grained rocks of near liquid compositions. As a result, these signatures are likely to be associated with the preferential preservation of alteration rinds on fine grained dolerites. Lastly, a portion of the center of the Basement Sill exhibits evidence of TIR alteration signatures where the MBS values are particularly high (Fig. 12c and Fig. 14c). No samples were collected from this particular region in Victoria Valley, and only one sample collected from Victoria Valley exhibits both alteration signatures in the TIR as well as a strong 1 μm opx absorption feature, although the 2 μm feature is absent (W10_VV_D1_008, Fig. 17). This sample, although coarse grained, has a well-preserved alteration rind on its surface. A possible explanation for these orbital VNIR and TIR signatures is that the surface is dominated by rocks similar to W10_VV_D1_008, where alteration rinds are able to develop and remain preserved on the surfaces of mafic, coarse grained dolerites. Why this portion of Victoria Valley is unique, however, has yet to be constrained and will likely require future in situ investigations. The spectral signatures in Victoria Valley were further investigated using a second ASTER scene obtained over Victoria Valley. This additional scene is in agreement with the one used in the MDV spectral map regarding the distribution of altered dolerites (Fig. 18). This observation confirms that the identification of alteration signatures is not an instrumental artifact or due to the presence of transient sub-pixel ice, snow, or clouds. Rather, these spectral signatures represent fundamental mineralogical and structural properties of the doleritic surfaces. 148 4.2 Geochemical evolution of the Ferrar Dolerite The geochemical and mineralogical signatures associated with the emplacement of dolerite sills, and the chemical weathering following exposure to the Antarctic environment, both produce distinct spectral signatures that can be identified from orbit. During emplacement, the parental magmas of the Ferrar Dolerite were intruded into the subsurface at various depths, resulting in a range of cooling histories and initial grain sizes (e.g. Marsh, 2004; Bédard et al., 2007; Elliot and Fleming, 2008). The lower sills were then intruded with additional, more primitive magmatic slurries of liquid and opx crystals, which also acted to reheat the surrounding doleritic material and create unique crystallization patterns and cryptic banding within these sills (Marsh and Wheelock, 1995; Heyn et al., 1995). The two upper sills were never modified by subsequent injections of magmatic slurry, resulting in a preservation of the initial stages of magma intrusion, near-liquid compositions, rapid quenching, and the resultant fine grained crystals (Marsh, 2004). As we have shown in our spectroscopic investigations, the influence and distribution of these primary magmatic processes can be readily observed from orbit using both VNIR and TIR multispectral datasets due to the spectrally unique signatures of opx. These spectral data provide valuable information regarding the spatial distribution of opx enrichment and chemical variability throughout the sills. Long after emplacement, burial, and exhumation (Fitzgerald et al., 2006), the dolerite sills were exposed throughout the MDV through a series of physical processes dominated by fluvial and glacial erosion (Sugden et al., 1995, and references therein). Once exposed to these hyper-arid and hypo-thermal environmental conditions (Marchant and Head, 2007), chemical alteration of the dolerites was able to commence. Recent 149 studies suggest that anhydrous alteration products dominate dolerite surfaces (Salvatore et al., unpublished data). These processes, which can proceed in the absence of liquid water, are the only known explanation for the observed geochemical and spectral signatures. Whereas the majority of the VNIR spectral modifications are difficult to quantify due to the residual effects of Rayleigh scattering, TIR spectral variations are very sensitive to these alteration processes and readily capture their variability and distribution throughout the MDV. Localized aqueous alteration has also been observed throughout the MDV (e.g., Allen and Conca, 1991; Head et al., 2011), although the preservation of mature alteration products on rock surfaces appears to be the exception rather than the norm. The products of this chemical alteration are best preserved on fine grained dolerites, which are less susceptible to physical erosion, and result in unique spectral and chemical signatures. In contrast, coarse grained dolerites, including most of the opx-rich dolerites that underwent slow cooling at depth, lack alteration signatures because of their susceptibility to physical erosion. Regardless of grain size, rock ventifaction and disintegration as a result of freeze-thaw and thermal cycling (Glasby et al., 1981; Marchant et al., 2013) are widespread throughout the MDV and confirm the dominance of physical erosion over chemical alteration. 5.0 Conclusions We have presented the results of a combined laboratory and orbital investigation to identify and interpret geochemical signatures of the Ferrar Dolerite throughout the MDV. Our analyses conclude that: 150 (1) Dolerites exhibit unique VNIR and TIR spectral signatures as a result of both primary geochemical properties as well as secondary chemical alteration; (2) Linear unmixing of ASTER data using a laboratory-derived endmember library is able to identify spectrally pure dolerite pixels in orbital datasets based on their diagnostic TIR spectral signatures; (3) Laboratory investigations reveal an association between the strength of the strength of opx absorption features in the VNIR and the bulk MgO content of the dolerites. When applied to ALI data, the measured MgO contents throughout the dolerite sills are consistent with previous studies. Additionally, this analysis is the first complete assessment of the spatial distribution of exposed opx-rich sill interiors throughout the MDV; (4) TIR signatures of altered dolerites are largely restricted to Beacon Valley and the margins of the Labyrinth. Only fine grained dolerites are capable of preserving mature alteration rinds that result in these spectral signatures. This observation explains the scarcity of altered Mg-rich dolerites in our collected sample suite. Future use of additional multispectral and hyperspectral datasets can provide critical information regarding the presence, nature, and distribution of crystalline alteration products throughout the MDV. For example, ASTER shortwave-infrared (SWIR) datasets can provide additional spectral resolution between 2.0 – 2.5 μm, which could help to identify the presence and distribution of phyllosilicates, sulfates, and carbonates throughout the MDV. These data were excluded from this study largely due to the incomplete spatial coverage of cloud-free images. While absorption features have not been identified in this wavelength region as a result of dolerite alteration processes, 151 the analysis of glacial till and the other prominent lithologies may benefit greatly from the addition of these spectral bands. The acquisition of additional cloud-free ASTER SWIR imagery would be beneficial to these types of studies. Additional in situ reflectance and emissivity measurements of doleritic surfaces would help to reduce some of the short wavelength scattering and aerosol contributions associated with remote sensing at high latitudes. These in situ measurements may help to better study the nature and distribution of Fe3+ phases and could help to assess the effects of oxidation outside of Beacon Valley. Our analyses demonstrate that multispectral orbital datasets can be used to better characterize the magmatic, climatic, and alteration histories of the Ferrar Dolerite within the MDV. The identification and characterization of pure doleritic terrains throughout the MDV has helped to constrain the spatial distribution of complex magmatic and alteration products, which has significant implications for the geologic and weathering histories within the Transantarctic Mountains. Acknowledgements This work was funded by the National Science Foundation Antarctic Science Division (Office of Polar Programs) through grants to James W. Head (ANT-0739702) and David R. Marchant (ANT-0944702), which are gratefully acknowledged. Logistical support for this project was provided by the U.S. National Science Foundation through the U.S. Antarctic Program. The authors would also like to thank Raytheon Polar Services Company, the United States Air Force 62nd Airlift Wing, and PHI, Inc., for their assistance and support during the 2009-2010 and 2010-2011 austral summer field 152 expeditions. We thank James Dickson, Laura Kerber, Gareth Morgan, Brandon Boldt, Sylvain Piqueux, David Hollibaugh Baker, J. R. Skok, Sean Mackay, Jennifer Lamp, Jack Seeley, Sandra Wiseman, Tim Goudge, Rebecca Greenberger, Kevin Cannon, Paul Morin, Tim Glotch, Deanne Rogers, Takahiro Hiroi, Dave Murray, Joe Orchardo, Andrea Weber, the Keck/NASA Reflectance Experiment Laboratory (RELAB) at Brown University, and the Vibrational Spectroscopy Laboratory at Stony Brook University for their assistance with field work, orbital analyses, and laboratory measurements. This manuscript benefitted greatly from the reviews by Christian Haselwimmer, Teal Riley, and Alan Vaughan, for which we are sincerely grateful. References Adams J. B. (1974), Visible and near-infrared diffuse reflectance spectra of pyroxenes as applied to remote sensing of solid objects in the solar system. J. Geophys. Res. 79, 4829-4836. Adams J. B. and McCord T. B. 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Geophys. Res. 88, 9534-9544. Ramsey M. S. and Christensen P. R. (1998), Mineral abundance determination: Quantitative deconvolution of thermal emission spectra. J. Geophys. Res. 103, 577-596. 158 Schenk T., Csatho B., Ahn Y., Yoon T., Shin S. W. and Huh K. I. (2004), DEM generation from the Antarctic LIDAR data: Site report. Available from: http://usarc.usgs.gov/lidar/lidar_pdfs/Site_reports_v5.pdf, 49 pp. Schwerdtfeger W. (1984), Weather and climate of the Antarctic. Amsterdam: Elsevier, 327 pp. Sugden D. E., Denton G. H. and Marchant D. R. (1995), Landscape evolution of the Dry Valleys, Transantarctic Mountains: Tectonic implications. J. Geophys. Res. 100, 9949-9967. Zavala K., Leitch A. M. and Fisher G. W. (2011), Silicic segregations of the Ferrar Dolerite sills, Antarctica. J. Petrol. 52(10), 1927-1964. Figure and Table Descriptions Figure 1. Spectral parameter map of the McMurdo Dry Valleys. Mafic band strength (MBS) is mapped in red, NIR spectral slope is mapped in green, and the strength of the quartz emissivity peak is mapped in blue (Table 3). Dark object subtraction- regression (DOS-R) locations are marked by orange stars, in situ spectral grid locations are marked by blue stars, and the locations of the four primary study regions in this work are outlined in yellow. Figure 2. Stratigraphy of the McMurdo Dry Valleys in the area of this study, adapted from Marsh (2004). The stratigraphy of the four primary doleritic sills is shown in purple, whereas the approximate location of the opx-enriched magmatic slurry signatures are shown in yellow. The stratigraphic location of the four study regions are also approximated on the left side of the section. 159 Figure 3. (a) Visible/near-infrared and (b) thermal infrared spectra of averaged unaltered dolerite interiors (purple) and dolerite surfaces (red) from Beacon Valley. Dolerite surfaces are characterized by strong Fe2+-Fe3+ intervalence charge-transfer absorptions at wavelengths shorter than 0.7 μm and an overall higher albedo in the near- infrared. They are also characterized by narrow reststrahlen features in the thermal infrared centered near 1100 cm-1 (9.1 μm) and 465 cm-1 (21.3 μm), which represent the breakdown of silicate mineralogy into metastable alteration products. Figure 4. (a) Frequency distributions of measured spectral radiances in each ALI band of image EO1A0581152008022110KG. Data are derived for 3,372 pixels of shadowed regions within the scene, and the plotted frequencies are individually scaled to facilitate comparisons between bands. The measured radiances represent the effect of scattered atmospheric downwelling. Dotted vertical line at 2 W/(m2 sr μm) is magnified in (b). (b) Frequency distributions of ALI bands 8 – 10. The majority of pixels in band 10 record scattered downwelling radiances of less than 0.1 W/(m2 sr μm), which is the foundation for our assumption that the scattered radiance component in ALI band 10 is negligible. (c) An example DOS-R regression scatterplot of 42 spectra. The y-intercepts of the modeled regressions for each band represent the scattered atmospheric downwelling radiance values. A total of 18 scattered downwelling radiance spectra were created using this method, which were used in the DOS-R atmospheric removal technique. Figure 5. Comparison between the dark object subtraction (DOS) atmospheric removal technique used in our spectral mapping (dashed lines) and the use of in situ calibration targets to correct for atmospheric effects in a corresponding Landsat image 160 (solid lines). Despite the different bandpass positions, the DOS spectra are comparable to the in situ calibration technique, emphasizing the utility of this in-scene atmospheric correction. The absorption features located near 1 μm and 2 μm are associated with the presence of opx and are resolvable only in ALI data and not Landsat data. Figure 6. (a) VNIR laboratory spectra (dark solid lines) and characteristic ALI spectra (light dashed lines) of different lithologic units. The spectral shapes are largely consistent between laboratory and orbital datasets, while offsets are likely due to sub- pixel mixing and imprecise atmospheric removal. (b) TIR laboratory spectra (dark solid lines) and characteristic ASTER spectra (light dashed lines) of different lithologic units. Data have been scaled and offset for clarity. As with the VNIR data, minor offsets are likely due to sub-pixel mixing and imprecision in the TES atmospheric removal algorithm. Figure 7. (a) VNIR and (b) TIR spectra of ice and assorted lithologies from throughout the MDV, highlighting the ease of spectrally identifying regions influenced by significant abundances of ice, snow, water, and clouds. Figure 8. Laboratory TIR emissivity spectra of five rock endmembers in the MDV. The spectra are also resampled to ASTER bandpasses (dots and dashed lines) and plotted with the hyperspectral laboratory data. The top four lithologies were used as spectral endmembers in the linear unmixing algorithm to identify uncontaminated doleritic terrains. The bottom three doleritic spectral endmembers highlight the range of known spectral variation in the dolerite based on laboratory measurements and were used in the linear unmixing of pure doleritic pixels. 161 Figure 9. The results of a linear unmixing algorithm on the full spectral map of the MDV. The root-mean-square (RMS) error, indicating the goodness of fit of the modeled spectra, shows an overall good fit to the data using the provided endmember spectra. However, slightly increased RMS errors are present in Beacon Valley and other doleritic regions and highlight regions of altered dolerite spectral signatures. Figure 10. VNIR laboratory spectra of different lithologies found throughout the MDV. The spectra are also resampled to ALI bandpasses (dots and dashed lines) and plotted with the hyperspectral data. The unique shapes of the spectra and positions and strengths of absorption features allows for the identification of individual mineral constituents as well as the discrimination between major lithologic classes. Figure 11. Scatterplot derived from the spectral map, plotting the strength of the mafic band strength versus the quartz emissivity peak strength. Values derived for representative rock samples measured in the laboratory are shown as colored dots (colors identical to those in Fig. 10; quartzite in blue, granite in green, Mg-poor dolerite in purple, and Mg-rich dolerite in orange). Values derived from type-locations of these lithologies as observed in our spectral dataset are plotted as shaded boxes that are one standard deviation wide in both directions. The offset between the quartzite and Mg-rich laboratory- and orbital-derived values can be explained by sub-pixel mixing, while the offset for the Mg-poor dolerite can be explained by the measurement of quartz-normative dolerites in the laboratory. Figure 12. VNIR mafic band strength (MBS) maps of (a) the Labyrinth, (b) Victoria Valley, (c) Central Wright Valley, and (d) Beacon Valley. The location of the opx-enriched zones are clearly defined by the areas containing stronger mafic signatures. 162 Figure 13. Mapping the position of the NIR reflectance peak in (a) the Labyrinth, (b) Victoria Valley, (c) Central Wright Valley, and (d) Beacon Valley. The position of this reflectance peak is associated with the enrichment of opx and nicely maps the distribution of the zones of opx-enrichment identified by Marsh (2004). Figure 14. Results of linear unmixing of ASTER TIR data of the pure doleritic regions of (a) the Labyrinth, (b) Victoria Valley, (c) Central Wright Valley, and (d) Beacon Valley. Altered doleritic signatures are extensively identified throughout Beacon Valley and are limited elsewhere throughout the MDV. Figure 15. (a) Mean topographic and mean modeled altered surface abundance profiles of the Labyrinth of Upper Wright Valley. A strong correlation exists between the elevation and the modeled altered surface abundance. (b) A representative topographic profile through the Labyrinth. Background colors are consistent with Figure 2 and represent the approximate elevations and exposures of the Peneplain Sill upper chilled margin and opx-rich interior. Figure 16. (a) CaO vs. MgO concentrations in rock interiors, as measured by ICP-AES. Samples from the upper sills (represented by the Beacon Valley samples) consistently contain < 7 wt.% MgO and display a positive relationship with CaO, representing more evolved magmatic chemistries. However, in the portions of the lower sills that are influenced by the addition of opx-enriched magmatic slurries, the MgO concentration increases and the relationship with CaO becomes negative, indicating the contribution of more primitive magmatic components. These trends were originally observed by Marsh (2004). (b) VNIR mafic band strength vs. MgO concentration. With the addition of a more primitive magmatic component, a linear relationship exists 163 between the strength of the 1 μm and 2 μm VNIR mafic bands and the concentration of MgO. Figure 17. (a) VNIR and (b) TIR laboratory measurements of the surface of sample W10_VV_D1_008. Spectra downsampled to ALI and ASTER bandpasses are also shown. Despite the relatively strong VNIR mafic band strength, TIR data show significantly altered doleritic signatures. These spectral signatures are also found throughout a large portion of central Victoria Valley, which might indicate a region of uniquely altered Mg-rich dolerites. Figure 18. Comparison of two different ASTER scenes of Victoria Valley, showing the consistency between modeled alteration signatures. This test confirms the spectral variability throughout this region and proves that these signatures are not the result of spectral artifacts present in one particular ASTER image. Table 1. List of images and information used in the creation of the spectral map of the McMurdo Dry Valleys. Table 2. Dark object subtraction (DOS) information for the atmospheric correction in Advanced Land Imager data. Table 3. Spectral parameters used in the creation of the spectral mapping product featured in Figure 1, including the Mafic Band Strength (MBS) parameter. 164 Chapter 3, Figure 1. 165 Chapter 3, Figure 2. 166 Chapter 3, Figure 3. 167 Chapter 3, Figure 4. 168 Chapter 3, Figure 5. 169 Chapter 3, Figure 6. 170 Chapter 3, Figure 7. 171 Chapter 3, Figure 8. 172 Chapter 3, Figure 9. 173 Chapter 3, Figure 10. 174 Chapter 3, Figure 11. 175 Chapter 3, Figure 12. 176 Chapter 3, Figure 13. 177 Chapter 3, Figure 14. 178 Chapter 3, Figure 15. 179 Chapter 3, Figure 16. 180 Chapter 3, Figure 17. 181 Chapter 3, Figure 18. 182 Chapter 3, Table 1. Date of Instrument Image ID Location Acquisition Taylor V., ALI EO1A0581152008022110KG 22 Jan 2008 Beacon V. Victoria V., Bull EO1A0581152010038110KK 07 Feb 2010 Pass EO1A0581152009339110K0 05 Dec 2009 Wright V. EO1A0581152010041110K9 10 Feb 2010 Wright V. EO1A0581152011027110P1 27 Jan 2011 Wright V. ASTER AST_05_00312082002210402 08 Dec 2002 Wright V. AST_05_00312112003210330 11 Dec 2003 Wright V. Victoria V., Bull AST_05_00312032001211845 03 Dec 2001 Pass AST_05_00311292000204446 29 Nov 2000 Taylor V. AST_05_00312032001211854 03 Dec 2001 Beacon V. Taylor V., Beacon V., Landsat LE70561162012020ASN00 20 Jan 2012 Wright V., Victoria V. 183 Chapter 3, Table 2. Image # of B2 B3 B4 B5 B6 B7 B8 B9 B10 Lat, Lon ID Pixels Corr. Corr. Corr. Corr. Corr. Corr. Corr. Corr. Corr. -77.328, KK 23 +39.396 +32.464 +18.116 +10.066 +5.6566 +4.0031 +0.6465 -0.0312 0 161.275 -77.419, KK 43 +39.451 -33.030 +19.196 +10.613 +5.4282 +3.4578 +0.5577 -0.0430 0 161.719 -77.514, KK 27 +35.924 +29.802 +16.321 +9.0441 +5.1925 +3.6344 +0.7672 -0.0113 0 161.012 -77.376, P1 36 +57.661 +46.342 +27.043 +15.431 +8.984 +6.4466 +1.1988 +0.0451 0 162.909 -77.454, P1 40 +49.394 +39.895 +22.502 +12.144 +6.7079 +4.6801 +0.8977 +0.0289 0 162.535 -77.487, P1 41 +49.384 +40.060 +22.847 +12.528 +7.0322 +5.0108 +0.9542 +0.0715 0 162.431 -77.665, KG 53 +44.708 +36.051 +20.581 +11.672 +6.6564 +4.8594 +0.8893 -0.0823 0 162.689 -77.780, KG 48 +49.596 +41.463 +23.411 +13.194 +7.4379 +5.0455 +1.0418 +0.1338 0 161.752 -77.747, KG 42 +48.886 +40.774 +22.661 +12.444 +6.4901 +4.5694 +0.7379 -0.0624 0 160.645 -77.814, KG 55 +42.242 +34.726 +19.344 +10.707 +6.0513 +4.2571 +0.8599 +0.0034 0 160.774 -77.770, KG 42 +46.460 +38.129 +21.106 +11.686 +6.3849 +4.4096 +0.9566 +0.0337 0 160.564 -77.871, KG 76 +45.082 +35.840 +19.716 +10.746 +5.9421 +4.2567 +0.8239 -0.0175 0 160.662 -77.419, K0 24 +46.987 +37.133 +20.892 +11.735 +6.3409 +4.5537 +1.0300 -0.0213 0 161.719 -77.814, K0 46 +49.419 +39.481 +21.851 +12.461 +7.4512 +5.3469 +1.0241 +0.0260 0 160.774 -77.741, K0 38 +48.622 +39.869 +22.409 +12.949 +7.6412 +5.5942 +1.2831 +0.0741 0 161.395 -77.419, K9 36 +36.415 +29.663 +16.758 +10.032 +5.8238 +3.9391 +0.6466 -0.0072 0 161.719 -77.898, K9 21 +40.897 +33.743 +18.691 +10.720 +6.2827 +4.3797 +0.7412 +0.0080 0 161.461 -77.845, K9 22 +40.548 +32.199 +17.948 +10.051 +5.3748 +3.7179 +0.7420 +0.0032 0 161.016 184 Chapter 3, Table 3. Mapped Parameter Name Equation Color Mafic Band Strength ([0.79 μm] / [0.8675 μm]) + ([1.25 μm] / [1.65 μm]) Red (MBS) NIR Spectral Slope [1.25 μm] / [0.79 μm] Green Quartz Emissivity [8.65 μm] / (((([9.1 μm] – [8.3 μm]) / 0.80) * 8.65) + Blue Peak Strength ([9.1 μm] – (11.375 * ([9.1 μm] – [8.3 μm])))) 185 Chapter Four: Oxidative weathering in Antarctica and evidence for a cold and dry Amazonian Mars. M. R. Salvatore1, J. F. Mustard1, J. W. Head III1, and R. F. Cooper1 1 Department of Geological Sciences, Brown University, Providence, RI 02912, USA In review in its current form to: Nature Geoscience NGS-2013-03-00584 186 Main Text Orbital visible/near-infrared (VNIR) reflectance spectroscopy has been used to suggest that global-scale aqueous alteration on Mars ceased near the beginning of the Amazonian epoch (~3.1 Ga; Hartmann and Neukum, 2001), transitioning to an oxidative weathering regime with little or no aqueous alteration (Bibring et al., 2006). Investigations utilizing thermal infrared (TIR) emission spectroscopy, however, have suggested that widespread, latitude-dependent aqueous alteration has occurred during this era (Wyatt and McSween, 2002; Kraft et al., 2003; Michalski et al., 2003; Minitti and Hamilton, 2010; Rampe et al., 2012). Researchers have, until now, been unable to reconcile these seemingly disparate interpretations through a single process that is consistent with our current understanding of martian surface and environmental evolution. Here we show that regional surface spectroscopy of martian mafic terrains spanning the VNIR and TIR wavelength regions (pan-spectral) are consistent with pan- spectral observations of mafic lithologies observed in Beacon Valley of the McMurdo Dry Valleys, Antarctica. In Beacon Valley, oxidative weathering processes are the dominant form of surface alteration, while more mature aqueous alteration phases are absent (Fig. 1) (Salvatore et al., 2012). Significantly, these products of alteration are uniquely preserved in the Mars-like hyper-arid, hypo-thermal, and stable climate of Beacon Valley (Marchant and Head, 2007). The identification of these products of oxidative weathering on Mars and the associated link to a process that is dominant on Mars indicates that substantial amounts of widespread aqueous activity were not present during the Amazonian epoch and provides definitive mineralogical evidence for a cold, dry, and stable martian climate during this time. 187 High-resolution global spectroscopic studies using the Thermal Emission Spectrometer (TES) instrument (Christensen et al., 2001) on Mars Global Surveyor have identified two widespread surface compositions. Surface Type 1 (ST1) is defined as largely basaltic and minimally altered (Bandfield et al., 2000), while Surface Type 2 (ST2) has been characterized as basaltic with variable amounts of altered materials and is more common at higher latitudes (Wyatt and McSween, 2002; Kraft et al., 2003; Michalski et al., 2003; Minitti and Hamilton, 2010; Rampe et al., 2012). Although substantial TIR spectral variability has been observed within these two regions, their broad distribution has been used to demarcate the extent of post-Noachian alteration across the martian surface. The alteration phases that have been proposed to satisfy these spectral signatures include smectite clays (Wyatt and McSween, 2002), zeolites (Minitti and Hamilton, 2010), allophane (Rampe et al., 2012), and Si-rich mineraloids (Michalski et al., 2003), polymorphs (Michalski et al., 2003), surface coatings (Kraft et al., 2003), and glasses (Fig. 2b) (Koeppen and Hamilton, 2005). The presence of these components implies that significant aqueous alteration has occurred on the martian surface following the emplacement of these Hesperian-aged basaltic units. Our analyses integrate pan-spectral data for the Syrtis and Northern Acidalia- Utopia spectral regions (Rogers et al., 2007; Rogers and Christensen, 2007), the type localities for ST1 and ST2, respectively (Fig. 2). These locations underscore some of the most significant spectral differences observed in regional-scale thermal emission compositional mapping (Rogers and Christensen, 2007). Using data from the Observatoire pour la Minéralogie, l’Eau, les Glaces et l’Activité (OMEGA) instrument (Bibring et al., 2004) on Mars Express, we generated representative VNIR spectra of 188 these spectral regions and compare them to their regional TIR emissivity spectra (see Methods section) to assess the nature and composition of primary and secondary phases that may be present. The OMEGA data for Syrtis exhibit broad 1 μm and 2 μm absorption bands associated with pyroxene, while data for Northern Acidalia-Utopia exhibit a distorted 1 μm band with a significantly weaker 2 μm absorption (Fig. 1c). The strength of the Fe3+ crystal field and charge-transfer absorptions in the Syrtis data is weaker than that observed in the Northern Acidalia-Utopia observations, while the Northern Acidalia- Utopia data exhibit an overall higher albedo in the near-infrared in addition to a significant negative slope. These observations are consistent with previous VNIR orbital analyses (e.g. Mustard et al., 2005). Importantly, neither spectrum exhibits vibrational overtones or combination tones near 1.4 μm, 1.9 μm, nor between 2.1 μm and 2.5 μm, indicating that hydrated species are not spectrally abundant phases in these regions. The lack of evidence for hydrated mineral phases in VNIR reflectance data is seemingly at odds with TIR emission data that have been previously interpreted as containing abundances of these phases at amounts sufficient to be modeled above the detection limits with linear unmixing methods. The recent identification and characterization of oxidative weathering products (OWPs) observed on mafic lithologies in Beacon Valley, Antarctica, though, presents a spectral analog that simultaneously satisfies the key VNIR reflectance and TIR emission spectral properties associated with martian low albedo regions in Syrtis and Northern Acidalia-Utopia (Fig. 1) (Salvatore et al., 2012). 189 Beacon Valley (77.84º S, 160.63º E) is one of the coldest (mean annual air temperature of -22º C; Doran et al., 2002), driest (mean annual water equivalent precipitation of < 10 mm; Fountain et al., 2009), and most stable (erosion rates of ~15 cm Myr-1 and landscape ages of several million years old; Summerfield et al., 1999; Sugden et al., 1995) ice-free surfaces on the planet. The valley surface is dominated by clasts of the Ferrar Dolerite, a shallow intrusive quartz- and hypersthene-normative basaltic unit that has previously been investigated as an analog to martian surface and meteorite compositions (Harvey, 2001; Chevrier et al., 2006). The surfaces of the Ferrar Dolerite are characterized by thin (~0.5 – 5 mm), red alteration rinds that grade into the underlying unaltered rock (Fig. 3). VNIR spectroscopy (Fig. 1c) shows that, compared to their unaltered interiors, altered rock surfaces exhibit weaker 2 μm pyroxene absorptions, stronger Fe3+ crystal field and charge-transfer absorptions at wavelengths less than 0.6 μm, and higher albedo and a more pronounced negative spectral slopes in the near- infrared. However, reflectance spectra of dolerite surfaces are not accompanied by significant changes to the strength or presence of absorption features near 1.4 μm, 1.9 μm, or between 2.1 μm and 2.5 μm related to hydrated alteration phases. In the TIR (Fig. 1d), altered surfaces exhibit a narrowing of the reststrahlen features near 1100 cm-1 and 470 cm-1, while no evidence exists for the presence of smectite clays in this spectral region. Importantly, mineralogical analyses of these alteration rinds indicate no significant changes in bulk mineralogy as compared to their unaltered interiors, with only subtle variations in chemistry that indicate the migration of cations in response to a dry, oxidizing environment (Salvatore et al., 2012). The process of cation migration and subsequent Fe oxidation modifies the electronic, vibrational, and structural state of the 190 minerals present at the rock surfaces to significantly modify the reflectance and emission properties. Thus, the OWPs formed in the hyper-arid and hypo-thermal Beacon Valley do not represent a pure mineralogic or alteration endmember, but rather a distinct alteration trend associated with oxidative weathering processes and is a function of the unaltered compositions, environmental conditions, and duration of exposure. The alteration rinds found ubiquitously throughout the valley represent a metastable phase between unaltered mafic compositions and more mature alteration phases. The hyper-arid and hypo-thermal environmental conditions present in Beacon Valley have effectively arrested chemical alteration at this metastable phase due to the scarcity of liquid water and thermal barriers to alteration processes. Warmer and/or wetter environmental conditions would quickly alter these metastable phases to more mature alteration products, including phyllosilicates. In fact, more mature alteration phases have been found within small pits on dolerite surfaces where liquid water is able to pond following minor snowmelt events, indicating that the ubiquitous rinds are the metastable precursors to these more mature alteration phases (Allen and Conca, 1991). The sensitivity of VNIR reflectance spectroscopy to the presence of hydrated mineral phases makes this technique an important and requisite tool to constrain the range of possible spectral endmembers present on the martian surface. Our results show that the pan-spectral properties of OWPs are the only known materials that satisfy diagnostic spectral properties in both the VNIR and TIR wavelength regions (Fig. 2). To quantify the contributions of OWPs using regional TIR spectra, we ran a least-squares linear unmixing algorithm (Ramsey and Christensen, 1998) with an endmember library modified from Rogers and Christensen (2007) that is consistent with our regional VNIR 191 data (Table 1) (see Methods section). Smectite clays, zeolites, high-Si phases, and other hydrated materials were excluded from the endmember library because they were not detected in OMEGA data in these regions of investigation. The unmixing model results suggest that OWPs contribute significantly to the mixing models for both the Syrtis and Northern Acidalia-Utopia TIR emissivity spectra, accounting for roughly 14% and 37% of the modeled mineral abundances, respectively, if the OWPs are treated as a mineral endmember (Fig. 2b, Table 2). The abundances of other modeled endmembers are consistent with previous studies and suggest that the surfaces are largely basaltic in composition (Rogers and Christensen, 2007). The observed goodness of fit of the model results, the absence of coherent signatures in the residual spectra, and the low root-mean- square (RMS) errors confirm that the linear unmixing models provide appropriate fits (Fig. 2b). Based on analyses from rover landing sites, geologically recent erosion rates of the martian surface have been estimated to be four orders of magnitude slower than those observed in Beacon Valley (Summerfield et al., 1999; Golombek et al., 2006). The widespread distribution and preservation of OWPs throughout Beacon Valley indicate that hyper-arid and hypo-thermal environmental conditions have dominated this valley for an extended period of time. Cosmogenic age dating of dolerite clasts that exhibit well-developed alteration rinds have revealed uncorrected minimum exposure ages of 2.3 Ma and suggest that cold and dry conditions comparable to modern conditions have been present for at least that duration (Schäfer et al., 2000). With similar cold, dry, stable, and oxidizing (Bibring et al., 2006) conditions on Mars, the martian surface is also ideal for the formation and preservation of these early chemical alteration products (during the 192 proposed “siderikian” era of alteration; Bibring et al., 2006). The identification of OWPs on the martian surface and the dearth of hydrated alteration phases present in VNIR data of post-Noachian basalts requires comparable or more severe hyper-arid and hypo- thermal environmental conditions to be present since their formation. As a result, the preservation of these OWPs on Mars is compelling spectroscopic and mineralogic evidence for the long-term stability of the martian surface as well as the persistent cold and dry conditions that must have been present. These results elucidate the pan-spectral observations of these critical low albedo regions and resolve the conundrum between previous pan-spectral interpretations. On a regional scale, our results suggest that neither the Syrtis nor Northern Acidalia-Utopia spectral regions have undergone significant post-Noachian aqueous alteration, despite evidence for localized aqueous alteration at or near the surface during this geologic timeframe (e.g. Milliken et al., 2008; Skok et al., 2010). The absence of diagnostic water- and hydroxyl-bearing mineral signatures in VNIR reflectance data suggest that hydrated phases are not present at sufficiently high volume abundances that can be detected using spectroscopic datasets. Additionally, the preservation of the metastable products of oxidative weathering on the martian surface is only possible in the absence of significant aqueous alteration, regardless of pH. Our study suggests that, from a mineralogical and geochemical perspective, liquid water has been an inconsequential component of Amazonian surface processes. The deficiency of aqueous activity during the later stages of martian geologic history provides additional constraints on the evolution of the martian climate and hydrologic system. 193 Methods Spectral analyses of dolerite samples Details regarding sample preparation and analyses can be found in Salvatore et al. (2012). Fourteen dolerite interior and surface fragments were spectrally analyzed using VNIR and TIR spectrometers at the Keck/NASA Reflectance Experiment Laboratory (RELAB) at Brown University and the Vibrational Reflectance Laboratory at Stony Brook University, respectively. VNIR measurements were acquired using a bidirectional reflectance (BDR) spectrometer, which acquires spectra between 0.32 µm and 2.55 µm at a 5 nm spectral sampling interval using a photomultiplier and InSb detectors. Illumination and emergence angles were fixed at 30° and 0°, respectively. Samples were slowly rotated to reduce artifacts associated with viewing or illumination geometries. TIR measurements were acquired using a Nicolet 6700 FTIR Spectrometer, which utilizes a deuterated L-alanine doped triglycine sulfate (DLaTGS) detector and CsI window. Measurements were acquired between 2000 cm-1 and 200 cm-1 at a sampling interval of 4 cm-1 using a CsI beamsplitter. The VNIR spectra presented in this manuscript are of sample MS10_BV_12 and the TIR spectra are the average interior and surface measurements of all fourteen samples (Salvatore et al., 2012). Orbital data retrieval and calibration In a fashion similar to TIR data aggregation by Rogers et al. (2007) and Rogers and Christensen (2007), OMEGA data were acquired over broad spectral regions that were classified as belonging to either the N. Acidalia-Utopia or Syrtis surface emissivity groups. All OMEGA data acquired prior to orbit 1600 were consolidated, processed to I/F, corrected for solar incidence angle, and atmospherically calibrated in the same 194 fashion as Mustard et al. (2005) over the Syrtis and Northern Acidalia-Utopia spectral regions (Fig. 3a). In total, 61,050 and 401,831 OMEGA spectra were acquired and processed over the Syrtis and Northern Acidalia-Utopia spectral regions, respectively. These data were averaged within a single image and then weighted to their appropriate spatial coverage and resolution to produce a single spectrum for each of these two spectral regions (Fig. 3b). This methodology produces VNIR spectra that are comparable to those produced using TIR data over the same spectral regions (Rogers et al., 2007; Rogers and Christensen, 2007), allowing for a pan-spectral investigation of these spectral regions. TIR data were provided by A. D. Rogers and are identical to those derived for TIR spectral investigations of these particular regions (Rogers et al., 2007; Rogers and Christensen, 2007). Following data acquisition, atmospheric constituents were removed using a linear deconvolution surface-atmosphere separation strategy, as described in Rogers et al. (2007). In this method, an endmember library is built to include both potential surface and atmospheric components; atmospheric components include low- and high-opacity dust, small and large water ice grains, and synthetic CO2 and water vapor spectra. After the algorithm is run, the atmospheric components are scaled according to their modeled concentrations and removed from the spectrum, producing a surface-only emissivity spectrum. The benefits of this technique, as well as a more detailed description of this and other atmospheric removal techniques, are provided in Rogers et al. (2007). For our study, we utilize the surface-only emissivity spectra of the Syrtis and Northern Acidalia-Utopia surface emissivity groups derived by Rogers et al. (2007). 195 Assembly of endmember library and linear unmixing The endmember library used in our linear unmixing models is provided in Table 1. This library is identical to the skeleton library used in Rogers and Christensen (2007) with the addition of quartz and alteration rind endmembers and the exclusion of illite, montmorillonite, K-rich glass, and opal-A endmembers. Justification for the exclusion of these endmembers is provided in the main text. Our models were run between the range of 350 cm-1 and 1300 cm-1, excluding the excluded atmospheric CO2 bands between 518 cm-1 and 815 cm-1. All values presented in this manuscript have been normalized to their modeled blackbody components, which are provided in Table 2 along with the modeled endmember abundances. References Allen C. C. and Conca J. L. (1991), Weathering of basaltic rocks under cold, arid conditions: Antarctica and Mars. Proc. Lunar Planet. Sci. 21, 711-717. Bandfield J. L., Hamilton V. E. and Christensen P. R. (2000), A global view of martian surface compositions from MGS-TES. Science 287, 1626-1630. Bibring J.-P., Soufflot A., Berthé M., Langevin Y., Gondet B., Drossart P., Bouyé M., Combes M., Puget P., Semery A., Bellucci G., Formisano V., Moroz V., Kottsov V. and the OMEGA team (2004), OMEGA: Observatoire pour la Minéralogie, l’Eau, les Glaces et l’Activité. Eur. Space Agency Spec. Pub. 1240, 37 pp. Bibring J.-P., Langevin Y., Mustard J. F., Poulet F., Arvidson R., Gendrin A., Gondet B., Mangold N., Pinet P., Forget F. and the OMEGA Team (2006), Global 196 mineralogical and aqueous Mars history derived from OMEGA/Mars Express data. Science 312, 400-404. Chevrier V., Mathé P.-E., Rochette P. and Gunnlaugsson H. P. (2006), Magnetic study of an Antarctic weathering profile on basalt: Implications for recent weathering on Mars. Earth Planet. Sci. Lett. 244, 501-514. Christensen P. R., Bandfield J. L., Hamilton V. E., Ruff S. W., Kieffer H. H., Titus T. N., Malin M. C., Morris R. V., Lane M. D., Clark R. L., Jakosky B. M., Mellon M. T., Pearl J. C., Conrath B. J., Smith M. D., Clancy R. T., Kuzmin R. O., Roush T., Mehall G. L., Gorelick N., Bender K., Murray K., Dason S., Greene E., Silverman S. and Greenfield M. (2001), Mars Global Surveyor Thermal Emission Spectrometer experiment: Investigation description and surface science results. J. Geophys. Res. 106(E10), 23823-23871. Cooper R. F., Fanselow J. B. and Poker D. B. (1996), The mechanism of oxidation of a basaltic glass: Chemical diffusion of network-modifying cations. Geochim. Cosmochim. Acta 60, 3253-3265. Doran P. T., McKay C. P., Clow G. D., Dana G. L., Fountain A. G., Nylen T. and Lyons W. B. (2002), Valley floor climate observations from the McMurdo dry valleys, Antarctica, 1986-2000. J. Geophys. Res. 107, doi:10.1029/2001JD002045. Fountain A. G., Nylen T. H., Monaghan A., Basagic H. J. and Bromwich D. (2009), Snow in the McMurdo Dry Valleys, Antarctica. Int. J. Climatol. 30(5), 633-642. Golombek M. P., Grant J. A., Crumpler L. S., Greeley R., Arvidson R. E., Bell J. F., Weitz C. M., Sullivan R., Christensen P. R., Soderblom L. A. and Squyres S. W. 197 (2006), Erosion rates at the Mars Exploration Rover landing sites and long-term climate change on Mars. J. Geophys. Res. 111, doi:10.1029/2006JE002754. Hartmann W. K. and Neukum G. (2001), Cratering chronology and the evolution of Mars. Space Sci. Rev. 96, 165-194. Harvey R. P. (2001), The Ferrar Dolerite: An Antarctic analog for martian basaltic lithologies and weathering processes. Wkshp. Mart. Highl. & Moj. Desert Anal., abst. 4012. Hurowitz J. A., McLennan S. M., Tosca N. J., Arvidson R. E., Michalski J. R., Ming D. W., Schröder C. and Squyres S. W. (2006), In situ and experimental evidence for acidic weathering of rocks and soils on Mars. J. Geophys. Res. 111, doi:10.1029/2005JE002515. Koeppen W. C. and Hamilton V. E. (2005), Discrimination of glass and phyllosilicate minerals in thermal infrared data. J. Geophys. Res. 110, doi:10.1029/2005JE002474. Kraft M. D., Michalski J. R. and Sharp T. G. (2003), Effects of pure silica coatings on thermal emission spectra of basaltic rocks: Considerations for martian surface mineralogy. Geophys. Res. Lett. 30(24), doi:10.1029/2003GL018848. Marchant D. R. and Head J. W. (2007), Antarctic dry valleys: Microclimate zonation, variable geomorphic processes, and implications for assessing climate change on Mars. Icarus 192, 187-222. Michalski J. R., Kraft M. D., Diedrich T., Sharp T. G. and Christensen P. R. (2003), Thermal emission spectroscopy of the silica polymorphs and considerations for remote sensing of Mars. Geophys. Res. Lett. 30(19), doi:10.1029/2003GL018354. 198 Milliken R. E., Swayze G. A., Arvidson R. E., Bishop J. L., Clark R. N., Ehlmann B. L., Green R. O., Grotzinger J. P., Morris R. V., Murchie S. L., Mustard J. F. and Weitz C. (2008), Opaline silica in young deposits on Mars. Geology 36(11), 847- 850. Minitti M. E. and Hamilton V. E. (2010), A search for basaltic-to-intermediate glasses on Mars: Assessing martian crustal mineralogy. Icarus 201, 135-149. Mustard J. F., Poulet F., Gendrin A., Bibring J.-P., Langevin Y., Gondet B., Mangold N., Bellucci G. and Altieri F. (2005), Olivine and pyroxene diversity in the crust of Mars. Science 307, 1594-1597. Rampe E. B., Kraft M. D., Sharp T. G., Golden D. C., Ming D. W. and Christensen P. R. (2012), Allophane detection on Mars with Thermal Emission Spectrometer data and implications for regional-scale chemical weathering processes. Geology 40(11), 995-998. Ramsey M. S. and Christensen P. R. (1998), Mineral abundance determination: Quantitative deconvolution of thermal emission spectra. J. Geophys. Res. 103(B1), 577-596. Rogers A. D. and Christensen P. R. (2007), Surface mineralogy of martian low-albedo regions from MGS-TES data: Implications for upper crustal evolution and surface alteration. J. Geophys. Res. 112, doi:10.1029/2006JE002727. Rogers A. D., Bandfield J. 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L., Milliken R. E. and Murchie S. L. (2010), Silica deposits in the Nili Patera caldera on the Syrtis Major volcanic complex on Mars. Nature Geosci. 3(12), 838-841. Sugden D. E., Marchant D. R., Potter N., Souchez R. A., Denton G. H., Swisher C. C. and Tison J.-L. (1995), Preservation of Miocene glacier ice in East Antarctica. Nature 376, 412-414. Summerfield M. A., Stuart F. M., Cockburn H. A. P., Sugden D. E., Denton G. H., Dunai T. and Marchant D. R. (1999), Long-term rates of denudation in the Dry Valleys, Transantarctic Mountains, southern Victoria Land, Antarctica based on in-situ- produced cosmogenic 21Ne. Geomorph. 27, 113-129. Wyatt M. B. and McSween H. Y. (2002), Spectral evidence for weathered basalt as an alternative to andesite in the northern lowlands of Mars. Nature 417, 263-266. 200 Figure and Table Descriptions Figure 1. Lithologic and spectral comparisons between Mars and Beacon Valley, Antarctica. (a) Typical basaltic clast in Gusev Crater, Mars (Spirit Pancam P2542_Sol14_L456_zoom-A16R1). (b) Typical doleritic clast in Beacon Valley, Antarctica. Subset shows the unaltered (grey) interior and the thin alteration rind (red). (c) Orbital VNIR reflectance spectra from OMEGA (Bibring et al., 2004) and laboratory VNIR reflectance spectra of dolerite interiors and rinds. (d) Orbital TIR emission spectra from TES (Rogers and Christensen, 2007) and laboratory TIR emission spectra of dolerite interiors and rinds. Figure 2. Comparison of orbital and laboratory TIR and VNIR spectra. (a) The geographic locations used to derive the regional VNIR reflectance and TIR emission data (Rogers et al., 2007). (b) Martian TIR emission spectra (Rogers and Christensen, 2007) overlain with unmixing model results (green). Model residuals (difference between data and model results) indicate that no significant absorptions fail to be modeled during unmixing. Several laboratory emission spectra are also provided for comparison of spectral features and shapes. References can be found in Rogers and Christensen (2007) and Minitti and Hamilton (2010). (c) Martian VNIR reflectance spectra with a suite of analog materials proposed by this study and by previous studies. Strong hydration bands (marked by vertical dashed lines) are present in all of these analog materials with the exception of the dolerite alteration rind. Spectra from the RELAB spectral database (planetary.brown.edu/relabdocs/relab.htm). Figure 3. Explanation of oxidative weathering processes. (a) A dolerite alteration rind in thin section. Primary crystal structure is maintained throughout the rind 201 with no evidence for depositional coatings. (b) A schematic of the alteration process, where divalent cations migrate towards the rock surface – a flux compensated by electron transfer in the mineral valence band – as Fe2+ is converted to Fe3+. Friable oxides created during this process are readily removed through erosion, dissolution, and abrasion upon exposure to the environment. Modified from Salvatore et al. (2012) and Cooper et al. (1996). Table 1. Spectral library of geologically relevant endmembers used in this study. Source information can be found in Rogers and Christensen (2007). Table 2. Modeled surface abundances for Syrtis and Northern Acidalia-Utopia spectral regions. Statistical errors associated with the reported concentrations are derived from the square root of the diagonal of the estimated vector coefficients covariance matrix (Rogers and Aharonson, 2008). Italicized components are modeled at abundances less than 10%, which is the approximate detection limit of most geological materials. Also included are the blackbody contributions and the root-mean-square (RMS) error, indicative of the goodness of fit of the model. 202 Chapter 4, Figure 1. 203 Chapter 4, Figure 2. 204 Chapter 4, Figure 3. 205 Chapter 4, Table 1. Material (Sample ID or Source) Classification Albite (WAR-0244) Plagioclase Andesine (BUR-240) Plagioclase Anorthite (BUR-340) Plagioclase Bronzite (NMNH-93527) Low-Ca Pyroxene Enstatite (HS-9.4B) Low-Ca Pyroxene Pigeonite (D. Lindsley) High-Ca Pyroxene Diopside (WAR-6474) High-Ca Pyroxene Augite (NMNH-9780) High-Ca Pyroxene Augite (NMNH-122302) High-Ca Pyroxene Hedenbergite (DSM-HED01) High-Ca Pyroxene Forsterite (BUR-3720A) Olivine Fayalite (WAR-RGFAY01) Olivine Olivine Fo60 (V. Hamilton) Olivine Biotite (BUR-840) Phyllosilicate Serpentine (HS-8.4B) Phyllosilicate Magnesiohastingsite (HS-115.4B) Amphibole Calcite (C40) Carbonate Dolomite (C20) Carbonate Anhydrite (ML-S9) Sulfate Gypsum (ML-S6) Sulfate Dolerite Rind (M. Salvatore) Oxidative Weathering Product Quartz (BUR-4120) Quartz Hematite (TES-derived) Oxide 206 Chapter 4, Table 2. Endmember Group Syrtis Northern Acidalia-Utopia OWPs 14.1% ± 3.7% 37.0% ± 2.9% Plagioclase 27.3% ± 5.4% 28.7% ± 4.6% Pyroxene 29.9% ± 4.7% 11.2% ± 3.1% Olivine 5.8% ± 3.3% 3.3% ± 1.9% Quartz 0.6% ± 0.8% 0.0% Amphibole 3.1% ± 3.4% 0.0% Phyllosilicate 6.6% ± 2.5% 9.4% ± 2.6% Sulfate 6.2% ± 1.7% 7.7% ± 1.8% Carbonate 5.7% ± 0.7% 2.6% ± 0.7% Oxide 0.7% ± 5.9% 0.0% Blackbody 35.4% ± 5.3% 67.19% ± 1.3% RMS Error 0.139% 0.150% 207 Chapter Five: The spectral influence of oxidative weathering on martian low albedo terrain. M. R. Salvatore1, J. F. Mustard1, J. W. Head III1, R. F. Cooper1, and M. B. Wyatt1 1 Department of Geological Sciences, Brown University, Providence, RI 02912, USA 208 Abstract Thermal infrared (TIR) investigations of the martian surface have revolutionized our understanding of both the primary and secondary mineralogical constituents present at regional spatial scales, revealing a largely basaltic surface with variable amounts of secondary phases. However, the TIR spectral signatures of many alteration phases, including smectites, zeolites, opaline silica, allophane, hydrated glasses, and oxidative weathering products, are indistinguishable in Thermal Emission Spectrometer (TES) investigations. Fortunately, the spectral signatures of these phases in the visible/near- infrared (VNIR) spectrum are distinctive and can provide additional evidence as to the compositions of these martian terrains. In this study, we investigate the VNIR spectral signatures associated with typical martian low albedo regions to constrain the primary and secondary phases that may be present. We also characterize the spectral trends associated with oxidative weathering products, which are uniquely preserved in the hyper-arid and hypo-thermal environments of the McMurdo Dry Valleys. Our results indicate that (1) oxidative weathering of basaltic compositions results in unique VNIR spectral signatures that are indistinguishable from several other alteration phases in the TIR; (2) hydrated alteration phases are not spectrally significant components across regional low albedo terrains on Mars; (3) variations in VNIR spectral shape between 1.5 μm and 2.6 μm are likely to result from the combination of true variations in primary composition as well as spectral indications of chemical weathering; and (4) evidence suggests that oxidative weathering processes and variations in primary composition can account for the majority of observed regional spectral signatures. New linear unmixing models of regional TIR spectra are consistent with the presence of oxidative weathering 209 products in exchange for hydrated alteration phases. We further explore and substantiate these conclusions by local investigations of surface and subsurface spectral signatures in Acidalia Planitia and Syrtis Major, where unaltered basaltic subsurfaces undergo a similar spectral evolution to more oxidized and less mafic signatures. These analyses confirm the strong spectral influence of hyper-arid and hypo-thermal environmental conditions on remote compositional analyses of the martian surface. Additionally, the ubiquity of oxidative weathering products across the martian surface indicates that the martian climate has been cold and dry for the last ~3.0 Ga of its geologic history. 1.0 Introduction The dominantly basaltic nature of the martian surface was initially identified through telescopic investigations (e.g. Adams and McCord, 1969; McCord and Adams, 1969) and has been since been confirmed by orbital analyses (e.g. Erard et al., 1990; Mustard et al., 1993; Christensen et al. 2000a). Subsequently, a variety of altered compositions have been identified using orbiting spectroscopic observations (e.g. Poulet et al., 2005; Bibring et al., 2006), analyses of martian meteorites (e.g. Bridges et al., 2001), and landed datasets (e.g. Squyres et al., 2008). This diversity of alteration mineralogies, however, appears to be localized in the oldest geologic terrains (Bibring et al., 2006). Younger and more globally homogeneous units, including martian dust, soils, and post-Noachian (~3.7 Ga to present) volcanic plains, exhibit less spectral and compositional variability than is observed in locally exposed ancient landscapes. Nonetheless, considerable spectral variations have been observed from orbit across martian low albedo surfaces (Mustard et al., 1993; Mustard and Sunshine, 1995; 210 Mustard et al., 1997; Bandfield et al., 2000; Christensen et al., 2000a; Bibring et al., 2005; Mustard et al., 2005; Rogers et al., 2007; Rogers and Christensen, 2007). Early thermal infrared (TIR) investigations using the Thermal Emission Spectrometer (TES) instrument identified two unique spectral shapes referred to as Surface Type 1 (ST1) and Surface Type 2 (ST2) (Fig. 1a; Bandfield et al., 2000). These two spectral signatures have since been expanded into 11 unique spectral groups throughout martian low albedo terrain (Rogers et al., 2007; Rogers and Christensen, 2007). While ST1-like signatures have been interpreted as minimally altered basalt, the nature of spectral signatures resembling ST2 has been debated. Initial hypotheses of an andesitic composition (Bandfield et al., 2000) have been largely abandoned in favor of one or several spectrally distinct alteration phases. Wyatt and McSween (2002) initially proposed smectites as a principal ST2 component due to their narrow absorption feature at 1100 cm-1, although later work contested the presence of smectites based on the lack of diagnostic smectite absorption features present at 530 cm-1 (Ruff and Christensen, 2007). Other possible alteration components (commonly referred to as “high-silica phases”) include thin amorphous silica coatings (Kraft et al., 2003; Minitti et al., 2007), palagonite (Morris et al., 2003), zeolites (Minitti and Hamilton, 2010), Al- or Fe-rich opaline silica (Michalski et al., 2005), Si-rich mineraloids (Michalski et al., 2005), and allophane (Rampe et al., 2012); these have all been proposed as potential contributors to the TIR spectra of ST2 (Fig. 1b). Oxidative weathering processes were recently identified in the McMurdo Dry Valleys of Antarctica, and the resulting spectral signatures were invoked as yet another possible explanation for these unique TIR spectral signatures (Salvatore et al., 2011; 2012; 2013). The anhydrous nature of these oxidative weathering products (OWPs) 211 precludes the formation of strong vibrational absorption features in the visible/near- infrared (VNIR) associated with hydration and hydrated mineral species, allowing for the remote detection of these phases using a combined VNIR and TIR spectral investigation. By examining the composition and distribution of the primary and secondary phases modeled across the martian surface at a variety of spatial resolutions, we can begin to assess the associated primary and secondary processes that led to their formation as well as the evolution of the martian geologic and climatic systems. This study focuses on answering the following questions: (1) What are the regional VNIR spectral signatures associated with typical martian low albedo terrains? (2) What process(es) can best explain the observed spectral signatures? (3) What are the associated chemical and mineralogical consequences associated with these spectral signatures? (4) What can be inferred about the evolution of the martian climate system based on the distribution of spectral signatures across the surface? Within the past decade, global VNIR and TIR spectral datasets have been obtained from martian orbit, providing the ability to study these spectral variations across wavelength regions at moderate to high spatial resolutions. In this study, we re- investigate the nature of the low albedo regions initially investigated by Rogers and Christensen (2007) (Fig. 2) using both VNIR and TIR spectroscopic wavelength regions to assess the observed primary and secondary compositions. Data from the Mars Express Observatoire pour la Minéralogie, l’Eau, les Glaces et l’Activité (OMEGA) instrument (Bibring et al., 2004) are regionally averaged to match the low albedo regions studied in Rogers et al. (2007). These data were then subjected to visual inspection and modified Gaussian modeling (MGM; Sunshine et al., 1990) analyses to identify the presence of 212 spectrally diagnostic phases. Similar analyses are performed on the suite of Antarctic samples discussed in Salvatore et al. (2011; 2012; 2013), which represent the effects of oxidative weathering on basaltic compositions. Linear unmixing of the regional TIR spectra presented in Rogers and Christensen (2007) was revisited using a subset endmember library that is consistent with regional VNIR observations. Constraining the possible TIR spectral endmembers using VNIR datasets helps to clarify potentially ambiguous spectral signatures. In tandem, these two spectral regions provide complimentary information regarding the potential compositional phases that are present. Higher resolution spectral analyses of Syrtis Major and Acidalia Planitia were performed to determine the local heterogeneity associated with the observed regional spectral signatures. These analyses supplement previous spectral investigations, which identify small-scale variations in the VNIR spectral signatures throughout both of these regions (Mustard et al., 2005; Baratoux et al., 2007; Salvatore et al., 2010; Skok et al., 2010). 2.0 Methods 2.1 Laboratory spectroscopy VNIR reflectance spectra of the oxidized alteration rinds and the unaltered interiors of Antarctic dolerites (shallow intrusive basalts) were acquired at the Brown University Keck/NASA Reflectance Experiment Laboratory (RELAB) using a bidirectional reflectance spectrometer, which acquires data between 0.32 and 2.55 μm at a 5 nm sampling interval using a photomultiplier and InSb detectors (Pieters, 1983; 213 Mustard and Pieters, 1989). Illumination and emergence angles were fixed at 30º and 0º, respectively. MGM analyses were performed on the VNIR spectra of dolerites to identify the relative intensities of the broad crystal field absorptions in the 2 μm region caused by the presence and abundance of pyroxenes. The MGM is an objective analytical technique that does not require a priori information or assumptions about the composition of the material under investigation. In this particular application, the MGM defines and removes a continuum for each individual spectrum and then models the continuum- removed spectrum with a series of modified Gaussian curves (Sunshine et al., 1990). In this study, we utilize the methodology described by Gendrin (2004) and Skok et al. (2010) by which the 2 μm spectral region is subset and modeled using only two modified Gaussians centered at 1.9 μm and 2.3 μm with fixed full width half maximums (FWHM). Spectra are first clipped to include only those data at wavelengths longer than their local reflectance maximum near 1.5 μm. Next, a continuum is defined and removed for each spectrum, and the model is then run until the modeled root-mean-square (RMS) error is below a tolerance of 10-5. These two Gaussians at 1.9 μm and 2.3 μm represent the spectral absorption features of low-calcium pyroxene (LCP) and high-calcium pyroxene (HCP), respectively, and their modeled relative strengths indicate the proportion of each pyroxene endmember to the provided spectrum. The strength, shape, and position of this 2 μm crystal field absorption band can be influenced by several different factors, most notably the concentration and composition of the pyroxenes present. This absorption feature is caused by the presence of Fe2+ in the highly distorted pyroxene M2 site (Burns, 1993). Transitioning from HCP to LCP results in the continued replacement of Ca by Fe2+, causing the M2 site to contract in response to 214 the presence of a smaller cation and the subsequent shift of the 2 μm band to higher frequencies (shorter wavelengths) (Burns, 1993). As a result, the location of the 2 μm absorption feature shifts from 2.3 μm in HCP to 1.9 μm in LCP, permitting the retrieval of approximate pyroxene composition from the analysis of the relative position and shape of this absorption feature. This methodology is consistent with previous MGM investigations of martian surface compositions (e.g. Gendrin, 2004; Skok et al., 2010). The 1 μm region was excluded from MGM modeling due to the possible overlapping contributions from several different compositions, including pyroxene, olivine, crystalline plagioclase, ferric iron oxides, and basaltic glass (Kanner et al., 2007). Fortunately, pyroxene is the only common mafic mineral in the dolerite and on Mars that exhibits a significant 2 μm absorption feature. Concern over the influence of strong 1.9 μm vibrational absorption features prompted the exclusion of all dolerite spectra with a 1.9 μm band strength greater than 10% from these analyses. TIR emission measurements were acquired at the Vibrational Spectroscopy Laboratory at Stony Brook University using a Nicolet 6700 FTIR Spectrometer, which utilizes a deuterated L-alanine doped triglycine sulfate (DLaTGS) detector and CsI window. Measurements were made between 2000 cm-1 and 200 cm-1 at a resolution of 4 cm-1 using a CsI beamsplitter. Linear unmixing was performed used a spectral endmember library that is identical to the skeleton library used in Rogers and Christensen (2007) to ensure consistency between laboratory and orbital analyses. Additional information regarding TIR measurements and calibrations can be found in Ruff et al. (1997). 215 TIR data were linearly unmixed to determine the abundances of compositional phases present within the samples. The linear unmixing algorithm used in this study is identical to that of Ramsey and Christensen (1998) and consists of a numerical least squares fitting algorithm using a chi-squared minimization (Ramsey, 1996), where the matrix of unknown endmember fractions is solved using a linear regression analysis (Press et al., 1988). Linear unmixing is possible in the TIR due to the high absorption coefficients of most geologically relevant materials, resulting in the dominance of emitted energy from the uppermost surface and the reduction of volumetric interactions and scattering (Ramsey and Christensen, 1998). As a result of this surface interaction, the observed emission spectrum is a linear combination of the areal abundance of phases present on the surface within a given field of view. Unmixing of this spectrum is possible given an endmember library that contains all of the applicable spectral endmembers (Ramsey and Christensen, 1998; Rogers and Christensen, 2007). The spectral unmixing of dolerites was performed using the full wavelength range between 1400 cm-1 and 400 cm-1. 2.2 Visible/Near-infrared orbital spectroscopy To study the observed spectral variability throughout martian low albedo regions and to determine whether significant vibrational absorption features are present throughout these terrains, regional VNIR data were collected, calibrated, and averaged into the same geographic regions described in Rogers et al. (2007). VNIR data were obtained using the OMEGA instrument, which is an imaging reflectance spectrometer that spans the wavelength range of 0.35 μm to 5.1 μm at a sampling resolution of 8 nm – 14 nm and a spatial resolution of 0.3 – 5 km pix-1, depending on the position of the 216 spacecraft within its highly eccentric orbit (Bibring et al., 2004). Data were acquired from all 61 atmospherically and spectrally clean images obtained over the nine representative spectral regions analyzed in Rogers and Christensen (2007) prior to orbit 1600. Radiance data were corrected to the ratio between the observed radiance and the incoming solar flux (I/F) using the techniques of Bellucci et al. (2006). Atmospheric contributions were removed following the methodologies described in Bibring et al. (2005), where an atmospheric spectrum is derived from spectral observations at the base and summit of Olympus Mons and is scaled by the strength of the CO2 atmospheric absorption feature measured in the observation. All pixels within these geographic regions were averaged within their individual scene and single channel spikes that are too narrow to be associated with mineralogy were filtered (Ehlmann et al., 2009). Lastly, the average spectrum from each image was weighted according to the area of the footprint of that particular image relative to the total area of the entire spectral region. This process results in nine VNIR spectra, representing the average spectral signature for these representative spectral regions as measured by the OMEGA instrument. Additional high quality OMEGA data up to orbit 2500 were acquired and processed for the detailed investigation of Acidalia Planitia and Syrtis Major. VNIR data were visually inspected for the presence of electronic and vibrational absorption features associated with primary and secondary compositions. In addition to these visual inspections, MGM was applied to each average spectrum to derive the relative contributions of LCP and HCP in the 2 μm wavelength region in addition to calculating magnitude of the near-infrared spectral slope. 217 2.3 Thermal infrared orbital spectroscopy TIR data were gathered from the TES instrument on the Mars Global Surveyor spacecraft to investigate regional and local variations in primary silicate and alteration mineralogy. The TES instrument consists of three subsections, one of which is a Michelson interferometer covering a spectral range from 1650 cm-1 to 200 cm-1 with a sampling resolution of 5 cm-1 – 10 cm-1 and an individual pixel size of 3 km by 6 km (Christensen et al., 2001). The emissivity spectra of the nine spectral regions analyzed in this study are identical to those analyzed in Rogers and Christensen (2007) and include Northern Acidalia (NA), Syrtis (SM), Tyrrhena (TT), Cimmeria-Iapygia (CI), Aonium- Phrixi (AP), Hesperia (HP), Mare Sirenum (MS), Meridiani (MP), and Solis (SP). The TIR spectra used in the local investigations of Acidalia Planitia and Syrtis Major were acquired using the TES Data Tool (tes.asu.edu/data_tool; accessed on 26 September 2012) for the spectral regions of interest (Table 1). The local Acidalia Planitia study region was defined as 18º N – 70º N and 310º E – 335º E, whereas the local Syrtis Major study region was defined as 2º S – 28º N and 58º E – 83º E. TES data were acquired between mapping phase orbits 1 to 5317 with a scan length of 10 cm-1 and were subset based on target temperature (≥ 255 K), lambert albedo (< 0.15), emission angle (≤ 30º), total ice (≤ 0.04) and dust (≤ 0.15) extinctions, and no solar panel or high gain antenna motions. Following acquisition, only data with sufficient spectral contrast were used (defined as a ratio between emissivity values at 1238 cm-1 and 1100 cm-1 greater than 10%). The high spectral contrast criterion limited the number of spectra to 9627 for Acidalia Planitia and 32616 for Syrtis Major, which were then individually inspected to identify and remove spectra that exhibited anomalous spectral shapes. Data were then 218 aggregated into 2 pixel per degree (ppd) bins, where only bins containing 5 or more individual spectra were kept for additional analyses. The resultant data products are two spectral grids (2 ppd) of high quality TES data with high spectral contrast. The average number of spectra included in each bin for Acidalia Planitia and Syrtis major were 14.0 and 27.3, respectively. Unbinned spectra were also used for more detailed spectral investigations and are discussed further in Section 3.3. Surface emissivity was derived for each of the binned pixels through the use of the linear deconvolution atmospheric removal technique (Ramsey and Christensen, 1998; Smith et al., 2000). This technique uses an additional atmospheric endmember library to distinguish and remove atmospheric components present in the emission spectra. The additional library is forced to fit each individual spectrum (negative values permitted) to return an emissivity spectrum representing only the observed surface. This technique was shown to be effective at removing atmospheric constituents from TES spectra, allowing for the modeling and interpretation of spectral signatures derived from the surface itself (e.g. Wyatt et al., 2003; Rogers et al., 2007). These derived surface emissivity spectra are concurrently unmixed using an endmember library containing geologically pertinent endmembers (Christensen et al., 2000b). Linear unmixing of TES data was performed between 1300 cm-1 and 350 cm-1 with the exclusion of the wavenumber region of atmospheric CO2 opacity between 518 cm-1 and 815 cm-1. 219 3.0 Results 3.1 Laboratory analyses (Table 2) MGM analyses performed on dolerite VNIR reflectance spectra (Fig. 3, Table 2) indicate a systematic decrease in near-infrared spectral slope in dolerite surfaces relative to their interiors, strengthening the negative slope by an average of 9.4º. In addition, the apparent spectral contribution of LCP (indicated by the LCP#, which is calculated as the proportion of LCP relative to total pyroxene, where a value of 1 indicates all LCP and a value of 0 indicates all HCP) is greater in all dolerite surfaces (average LCP# value of 0.46) than for their corresponding interiors (average LCP# value of 0.19). In tandem, there is a clear spectral trend that shows a systematic decrease in spectral slope and increase in LCP# from dolerite interiors to their corresponding surfaces (Fig. 4). Lastly, the strength of the Fe3+ intervalence charge transfer (IVCT) absorption feature in the visible wavelengths (<0.6 μm), calculated as the average reflectance surrounding 0.73 μm relative to that near 0.35 μm, is stronger in dolerite surfaces (2.16) relative to dolerite interiors (1.44), indicating a higher degree of oxidation in dolerite surfaces. Linear unmixing was performed on the same subset of dolerites used in the MGM analyses described above (Fig. 5). The unmixing of these dolerite interiors and surfaces utilizing the skeleton library described in Rogers and Christensen (2007) reveal average LCP# values of 0.25 for dolerite interiors and 0.31 for dolerite surfaces. While the magnitude of modeled LCP enrichment is not equivalent between our VNIR and TIR investigations, it is clear that the oxidation and alteration process at work on dolerite surfaces creates an apparent decrease in the magnitude of HCP spectral contributions relative to that of LCP. This can be observed in the average TIR dolerite spectra (Fig. 5), 220 which show stronger absorption features between 900 cm-1 and 1000 cm-1 in the interior spectrum relative to the surface spectrum. These absorptions are due to the second and third critical absorption features in CPX, which are typically weaker than the first characteristic absorption feature in OPX centered near 1050 cm-1 (Hamilton, 2000). The reduced strength of these absorption features in the average dolerite surface spectrum results in an apparent decrease in HCP abundance relative to LCP. Additionally, there is a significant spectral misfit between our unmixing model and the measured dolerite surface spectrum in this pyroxene critical absorption region (black arrow, Fig. 5). Emissivity is underestimated between 900 cm-1 and 1000 cm-1, indicating that the library may be missing a relevant spectral endmember. Furthermore, it is possible that the modeled pyroxene (particularly HCP) abundances in dolerite surfaces are overestimated, and the inclusion of additional endmembers could potentially increase the LCP# value modeled for dolerite surfaces. In the unmixing models for both interior and surface spectra, silica- and potassium-rich glass (SiK Glass; Wyatt et al., 2001) is modeled as the most significant “high-silica phase.” Dolerite surfaces are also modeled as containing 15.6% smectites. While hydrated interstitial glass may account for the presence of the 1.4 μm and 1.9 μm hydration bands observed in VNIR spectra of both dolerite interiors and surfaces (Fig. 3), its physical abundance at > 15 vol.% in both interiors and surfaces is not supported by this or previous investigations (Salvatore et al., 2013). Additionally, despite these significant spectral differences between dolerite interiors and surfaces, laboratory analyses of the Beacon Valley dolerites using X-ray diffraction reveal no substantial changes in bulk mineralogy (Salvatore et al., 2013). Inductively coupled plasma-atomic 221 emission spectroscopy via the flux fusion method of sample preparation (Murray et al., 2000) reveals subtle yet diagnostic chemical variations between dolerite interiors and their surfaces that are indicative of the outward migration of divalent cations in response to an oxidation gradient (Salvatore et al., 2013; Cooper et al., 1996) and are not consistent with the presence of significant abundances of hydrated alteration phases. The modeling of these alteration phases at anomalously high abundances, the significant spectral misfit observed in the unmixing model of dolerite surfaces, and the doubling of the measured RMS error (indicative of the overall goodness of fit of the model; Ramsey and Christensen, 1998), all suggest that the current endmember library is not capable of accurately modeling the components present in dolerite surfaces. The weak to absent chemical and mineralogical variations observed between dolerite interiors and surfaces also imply that a unique compositional endmember is not being excluded from our endmember library at spectrally, chemically, or mineralogically significant abundances. Therefore, we consider dolerite alteration rinds to be unique compositional and spectral endmembers, representing OWPs that form in cold and dry environments. This representative spectrum of oxidative weathering products was added to our linear unmixing library to represent a plausible spectral component of martian low albedo surfaces. 3.2 Orbital analyses (Regional) VNIR reflectance data of the nine spectral regions reveal the presence of two broad absorption features centered near 1 μm and 2 μm (Fig. 6). These absorptions are the result of crystal field transitions caused primarily by the presence of ferrous iron in the M2 octahedral site in pyroxenes. Additional structure may be present near or within 222 the 1 μm band due to contributions by Fe2+ in the M1 and/or M2 octahedral sites in olivines, Fe3+-bearing components, and basaltic glass (Kanner et al., 2007). All of the spectra also exhibit a strong absorption feature at visible wavelengths (< 0.6 μm) as a result of an Fe3+ IVCT absorption. This feature, however, is readily influenced by minute quantities of surface dust (< 1%) and therefore should be interpreted with caution (Roush et al. 1993). Lastly, none of the regional spectra exhibit vibrational absorption features near 1.4 μm (OH- stretching overtone and combination tones of H2O), 1.9 μm (stretching and bending combination of H2O), or between 2.1 and 2.5 μm (structural metal-OH stretching and bending combination). Absorption features at these wavelengths would indicate the presence of hydrated geologic materials, and the absence of these signatures suggests that hydrated phases are not present at spectrally significant abundances. The MGM-derived outputs indicate substantial spectral variability associated with the 2 μm pyroxene absorptions and the modeled spectral slope (Fig. 7). Most of the regional VNIR spectra exhibit a near-uniform mixture of both the 1.9 μm and 2.3 μm absorption features, as indicated by LCP# values near 0.5. However, the LCP# is substantially higher in the NA spectral region (0.84) and lower in the SM spectral region (0.39). These model results indicate that the majority of the low albedo martian surface is spectrally consistent with a mixture of LCP and HCP, while locales enriched in both LCP and HCP are also present. This observation is consistent with previous regional VNIR investigations of the martian surface (e.g., Mustard et al., 2005). These laboratory and VNIR spectral investigations indicate that not all of the phases included in the Rogers and Christensen (2007) skeleton library are potential candidates for the observed compositions in martian low albedo regions. Based on the 223 lack of diagnostic spectral features in the VNIR, we are able to exclude several hydrated phases that are not abundant at spectrally identifiable quantities (~10%, Ehlmann et al., 2012), including illite (IMt-2), montmorillonite (STx-1), SiK Glass, and opal-A (01-011) (Table 3). The non-detection of these phases in the VNIR suggests that their greatest possible abundances are still lower than the estimated TES detection limit of 10% (Ehlmann et al., 2012; Christensen et al., 2000). Their exclusion was also due to their spectral similarity in the TIR, which results in ambiguous model results. Other hydrated phases, including carbonates, sulfates, and amphiboles, were kept in the endmember library because of their unique spectral shapes in the TIR and for their reduction of model RMS errors when modeled at or below TES detection limits. Additionally, a spectrum of enstatite (HS-9.4B; Christensen et al., 2000b) was added to augment the spectral diversity of potential LCP endmembers within the spectral library. Lastly, the spectrum of OWPs (Salvatore et al., 2013) was also included to represent a potential oxidative weathering phase. Linear unmixing results of the nine low albedo regions utilizing this modified spectral library are presented in Table 4 and are shown graphically in Figure 8. The low RMS errors and the lack of coherent spectral signatures present in residual spectra indicate that our model results appropriately fit the input spectra. In addition, the modeled primary mineral components are largely consistent with previous studies, suggesting largely basaltic substrates with variable amounts of secondary materials. Several differences exist between our modeled endmember components and those of previous investigations. First, LCP is modeled at much higher abundances than HCP in all of our unmixing models, with the exception of the SM spectrum. This result is at 224 odds with previous studies, which suggest that the majority of martian low albedo terrains are dominated by HCP (e.g., Bibring et al., 2005; Mustard et al., 2005; Rogers and Christensen, 2007). Second, the modeled plagioclase/pyroxene ratios range from 0.6 (TT) to 2.6 (NA), which is outside the range of those identified in martian meteorites (0.1 – 0.3; Hamilton et al., 1997) and is broader than the range previously modeled by Rogers and Christensen (2007). Third, OWPs are modeled at abundances ranging from 14% to 37%, with an average of 27.9%. This modeled component largely substitutes for the high-silica phases in the endmember libraries of previous studies. On a plagioclase–(pyroxene + olivine)–OWP ternary diagram (Fig. 9a), all nine regions are widely spread below the 40% plagioclase line, with those regions modeled with higher OWP abundances (e.g., NA, SP, MP) also modeled with less pyroxene and olivine. On a HCP–LCP–olivine ternary diagram (Fig. 9b), most of the regions fall along or near the LCP and olivine join, with TT and SM modeled as having higher HCP abundances. While SM has the lowest modeled LCP abundance, TT has an intermediate modeled LCP abundance, implying that the relative proportion of HCP is not directly associated with the relationship between LCP and olivine abundances. Lastly, on a HCP–LCP–OWP ternary diagram (Fig. 9c), most data plot along the LCP and OWP join. With the exception of MP, those regions modeled with HCP abundances greater than zero are also modeled as having the lowest OWP contributions. This is particularly true for TT and SM, which are the only two regions where HCP is modeled above the traditional TIR detection limits. This suggests that the relative proportion of HCP is linked to the relationship between modeled LCP and OWP abundances. This relationship can also be seen when plotting modeled OWP abundance against LCP# (Fig. 10). Similar to the 225 trend observed in Figure 9c, the relationship between these two variables does not appear to be linear, although there is a significant logarithmic relationship (R2 = 0.87) that strongly suggests that high OWP abundances are related to high LCP#. Caution must be taken when interpreting TIR-derived LCP#, however, because OWPs are modeled as complex mixtures that contain primary mineral phases that include higher HCP abundances relative to LCP. As a result, HCP spectral signatures may be preferentially masked in OWP spectral signatures. Both VNIR and TIR spectral signatures must be interpreted concurrently to identify where these apparent variations in LCP# are due to either primary igneous or secondary alteration processes. 3.3 Orbital analyses (Local) Syrtis Major and Acidalia Planitia have long been regarded as spectral endmembers of martian low albedo regions (e.g. Mustard et al., 2005). Our regional analyses confirm the disparities between these two regions in both the visible, near-, and thermal-infrared. Characterization of subsurface compositions throughout these regions was also performed using high resolution VNIR data from the OMEGA and Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) instruments (Baratoux et al., 2007; Salvatore et al., 2010; Skok et al., 2010). These analyses supplement regional surface studies by utilizing impact craters as probes into the shallow subsurface where subaerial alteration processes have likely been minimized relative to the regional surface. Below, we incorporate these detailed investigations of subsurface compositions into our regional surface analyses in an effort to better constrain their relationship. 226 3.3.1 Acidalia Planitia In Acidalia Planitia, Salvatore et al. (2010) identified the presence of discrete olivine- and HCP-bearing basaltic components in the shallow subsurface through their identification in crater rims and ejecta deposits. The intact HCP-bearing stratigraphic units are small in scale, on the order of 102 m in thickness, precluding the use of the OMEGA instrument to investigate these units in their pristine geologic settings. However, MGM analyses of the CRISM observations presented in Salvatore et al. (2010) confirm the dominance of HCP over LCP (LCP# of 0.34) and suggests the presence of spectrally similar pyroxenes to those observed in Syrtis Major by Skok et al. (2010) (Salvatore et al., unpublished data). This MGM modeling, however, was performed on surface spectra that were ratioed to nearby spectrally neutral terrain (to remove spectral artifacts and remnant atmospheric components; Mustard et al., 2005) and is therefore not equivalent to the MGM analyses performed on the regional unratioed OMEGA data presented elsewhere in this study. Surface emissivity data for Acidalia Planitia were derived for the binned TES data concurrent with atmospheric removal process and were spectrally unmixed using the modified endmember library. Average model RMS errors were 0.00246 with a standard deviation of 0.00069, and are comparable to the errors associated with the global mineral distributions modeled by Bandfield (2002). Both the shape of the derived surface emissivity spectra as well as the modeled mineral abundances suggest the presence of two distinct terrains within Acidalia Planitia separated north and south of 42º N latitude (hereby referred to as South Acidalia and North Acidalia) (Fig. 11). In South Acidalia, the derived average surface emissivity spectrum exhibits low spectral contrast (~ 4%) and 227 a slight concave-down feature centered near 950 cm-1, while the derived average surface emissivity spectrum of North Acidalia has higher spectral contrast (~ 6%) and no concave-down feature near 950 cm-1 (Fig. 11a). These observations were also made by Rogers et al. (2007), who interpreted the spectral differences to likely be related to small amounts of dust in South Acidalia. Compositionally, total pyroxene, OWP, and carbonate abundances differ between South Acidalia and North Acidalia, although these variations are within the estimated detection limits of the TES instrument (10%, Christensen et al., 2000a) (Fig. 11b, Table 5). The modeled carbonate contribution is due to an unresolved problem associated with linear unmixing of TES data (Fig. 11a; Stockstill-Cahill et al., 2008). Consequently, interpreting these modeled mineral differences is likely inappropriate. Despite these uncertainties, it is evident that LCP is preferred over HCP as the dominant pyroxene phase present in Acidalia Planitia (Fig. 11c). Higher resolution spectral investigations, however, may be fruitful given the extent of VNIR spectral diversity observed in impact ejecta throughout Acidalia and Chryse planitiae (Tornabene et al., 2006; Salvatore et al., 2010). Several olivine-rich ejecta blankets were identified by Salvatore et al. (2010) and are larger in spatial extent than the discrete subsurface horizons, which permits the use of OMEGA data in their analysis. Grindavik crater (25.4º N, 321.0º E), an 11.7 km crater in southern Acidalia Planitia, is an archetypal example of these olivine-rich ejecta blankets. Ratios of large spectral averages from OMEGA image ORB2079_7 exhibit characteristic olivine absorption features in the VNIR (Fig. 12b), and the absence of olivine absorption features in the surrounding terrain is confirmed through spectral parameterization (Fig. 12a). 228 In the TIR, fourteen individual TES spectra were extracted from over the ejecta blanket, atmospherically corrected, and unmixed using the methodologies described above. These data were then compared to the regionally binned spectra extracted for the regional terrain south of the crater (Fig. 12c). Although the TES spectra do not overlap entirely with the corresponding OMEGA data, the uniformity of the crater ejecta in Thermal Emission Imaging System (THEMIS) (Christensen et al., 2004) nighttime infrared imagery and its distinct properties relative to the surrounding terrain indicates that the entirety of the ejecta blanket is spectrally distinct. Unmixing results for the crater ejecta confirm the presence of olivine at abundances greater than the estimated detection limits of TES (12.3%), in addition to OWPs (42.9%), plagioclase (18.8%), and other minor phases. On the other hand, binned spectra of the surrounding regional terrain are modeled with olivine at below the TES detection limit (4.0%), while OWPs (51.6%), plagioclase (17.0%), and LCP (11.0%) are the most dominant spectral phases (Table 5). 3.3.2 Syrtis Major Baratoux et al. (2007) and Skok et al. (2010) characterized the distribution of spectrally distinct ejecta (SDE) in the VNIR across Syrtis Major, which exhibit stronger spectral signatures associated with HCP relative to the surrounding terrain and are largely clustered to the east of Nili Patera (Fig. 13). These data were used to suggest that a regional or global transition in the martian climate occurred roughly 2 Gyr ago (based on extensive crater counting), resulting in the chemical alteration of surface materials prior to this event and the preservation of surface materials exposed since this transition. To further characterize these spectral variations, we assess the regional TIR variability associated with Syrtis Major and compare this with previous VNIR investigations. We 229 then utilize both VNIR OMEGA and TIR TES data to analyze two archetypal SDEs and compare them to the surrounding regional terrain to compare the modeled mineralogy at a higher spatial resolution. The average RMS errors associated with atmospheric removal, surface emissivity derivation, and linear unmixing for the 2 ppd TIR Syrtis Major data was 0.00170 with a standard deviation of 0.00028. Two distinct terrains were also identified on the volcanic shield of Syrtis Major, separated by the 69º E line of longitude (hereby referred to as West Syrtis and East Syrtis) (Fig. 14). Both terrains exhibit similar average RMS errors, with West Syrtis modeled at 0.00169 and a standard deviation of 0.00028 and East Syrtis modeled at 0.00170 and a standard deviation of 0.00029. While within the estimated error associated with TES unmixing models, West Syrtis is modeled with 4.6% less pyroxene (primarily HCP) and 4.5% more OWP than East Syrtis (Fig. 14a, Table 5). The modeled LCP# associated with West Syrtis is 0.60, whereas this value is modeled as 0.52 in East Syrtis. The average TIR spectrum of East Syrtis exhibits a stronger absorption between 900 cm-1 and 1000 cm-1, similar to that observed in the average dolerite interior TIR spectrum, which indicates a stronger HCP spectral contribution (Fig. 14a, Hamilton 2000). A simple model of adding 5% augite (HCP) to the average West Syrtis spectrum verifies that the addition of an HCP component results in a strengthened absorption feature in this region (Fig. 15). As a result, despite being below the previously accepted detection limits for linear unmixing models, we interpret these mineralogical variations as justifiable. To investigate these local spectral variations, we acquired 6,527 OMEGA pixels over two SDE in Syrtis Major (associated with craters centered at 8.9º N, 74.3º E, and 230 5.9º N, 70.5º E, black dashed circles in Fig. 13) from OMEGA images ORB2316_4 and ORB0284_2, respectively. These data were compared to 7,623 OMEGA pixels of the regional terrain near 8.5º N, 68.75º E (grey dashed box, Fig. 13). MGM analyses (Fig. 16) indicate an average LCP# of 0.39 and 0.31 for the regional terrains and the SDE, respectively, which are largely consistent with the values and magnitude of variability observed in Syrtis Major by Skok et al. (2010). The negative VNIR spectral slope of the surrounding terrain is also 0.7º stronger than that of the SDE, which is consistent with the spectral trends observed in the dolerites. TES spectra were acquired over these two SDE deposits and compared to the surrounding terrain within Syrtis Major. In total, 185 TES spectra were averaged and compared to the TIR spectra of the archetypal regional terrain acquired near 8.5º N, 68.75º E during our regional investigation of binned 2 ppd TES spectra. The results of this study are generally consistent with both previously reported VNIR investigations as well as our analyses of OMEGA data. TIR-derived LCP# is modeled as 0.83 for the surrounding regional terrain and 0.16 for the SDE deposits. While this range of values far exceeds our other analyses as well as those derived from other studies, the trend is identical and indicates the spectral masking of HCP signatures in the surrounding terrains. The spectral variations between SDEs and the surrounding terrain are reported in Figure 17. Particular emphasis is drawn to the modeled 10.8% higher HCP and 4.8% lower OWP abundances in SDE relative to the surrounding regional terrain (Table 5). These modeled trends are consistent with those observed in TIR analyses of dolerite surfaces and interiors, suggesting that similar weathering and resultant spectral processes are at work. 231 3.4 Summary VNIR laboratory analyses of weathered dolerites from Beacon Valley, Antarctica, exhibit systematic decreases in NIR spectral slopes. Apparent shifts in the position of the broad 2 μm crystal field absorption band suggests a stronger spectral contribution of LCP relative to HCP, despite no such variations observed in laboratory compositional analyses (Salvatore et al., 2013). Identical VNIR spectral variations are observed regionally across martian low albedo terrains, where regions exhibiting more HCP-dominated spectral signatures have the least negative NIR spectral slopes and regions exhibiting more LCP-dominated spectral signatures have the most negative spectral slopes. Local VNIR analyses are also subject to much more spectral variability than is observed regionally, but where observed, local pyroxene spectral trends appear to be consistent with regional observations. In particular, regional intercrater plains in both Acidalia Planitia and Syrtis Major systematically exhibit more LCP-dominated spectral signatures in the VNIR than the ejecta and subsurface layers exposed in younger impact craters. TIR spectral measurements of dolerite surfaces are also modeled as being more enriched in LCP than their corresponding unaltered interiors. The significant narrowing of reststrahlen features in the absence of evidence for significant hydration in the VNIR suggests that OWPs are a unique spectral endmember. When added to martian TIR unmixing libraries in exchange for unobserved hydrated phases, OWPs are modeled at spectrally significant abundances in all martian low albedo terrains. Local analyses in Acidalia Planitia and Syrtis Major show identical TIR spectral trends that correspond with VNIR analyses at the same spatial scales. In particular, intercrater plains are 232 modeled as more enriched in OWPs and exhibit higher LCP# values than younger ejecta deposits. 4.0 Discussion 4.1 Assumptions regarding oxidative weathering products and processes The oxidation products described in Salvatore et al. (2013) and discussed throughout this manuscript do not represent a pure mineralogic or alteration endmember, but rather a distinct alteration trend associated with the oxidative weathering process observed in Beacon Valley, Antarctica. Additionally, the observed alteration signatures may be strongly dependent upon the composition of the unaltered lithologic material as well as the environment under which oxidation is proceeding. As a result, the applicability of our OWP spectral endmember across the varying primary lithologies observed on Mars is uncertain. Future work must seek to investigate the dependency of the observed spectral signatures of OWPs on the composition of the underlying lithology and the environmental conditions present. The study by Salvatore et al. (2013) was unable to identify new alteration phases within dolerite alteration rinds, nor were they able to observe the destruction or removal of primary materials inherent to the dolerite within the alteration rind. Based on these analyses, two possibilities exist for the cause of the observed spectral differences between dolerite interiors and alteration rinds. First, the oxidative weathering process results in substantial modification to the electronic and vibrational environment of the dolerite surface, significantly altering the observed spectral signatures in the absence of new phase formation. This possibility is most consistent with the results of Salvatore et al. 233 (2013). The second possibility is that alteration products are being produced at the sub- micron scale and at abundances below the detection limits of the analytical techniques performed in Salvatore et al. (2013). Possible alteration products include small abundances of hydrated glass replacing plagioclase feldspar or interstitial basaltic matrix materials within the alteration rind, hydrated silica replacing quartz, or small amounts of smectite clays forming within the interstitial basaltic matrix. While current analytical results are unable to definitively rule out any of these possibilities, the combination of x- ray diffraction data, electron microprobe analyses, Mössbauer spectroscopy, and bulk chemical analyses all require the abundances of these phases to be extremely minor with respect to the composition of the unaltered dolerite interiors. As mentioned previously, additional work is required at different relevant field sites to assess the effects of different parent lithology on the observed oxidation products. These additional analyses, including x-ray diffraction at the micron-scale, can also help to potentially identify whether more mature or hydrated alteration products are present at scales that were previously unobservable. With these caveats aside, our assumption in this analysis that the OWPs observed throughout Beacon Valley are applicable across the martian surface allows us to systematically and uniformly assess each spectral region using the same unmixing library and techniques. The consistency in spectral trends observed throughout the dolerite suite suggests that the result of oxidative weathering is predictable for these specific compositions, which justifies the inclusion of OWPs in our linear unmixing models. Populating our unmixing library with additional OWPs derived from different starting compositions (e.g., dunite, pyroxenite, andesite) is the goal of future research endeavors. 234 4.2 Effects of oxidative weathering on apparent surface composition Detailed laboratory characterization of dolerites from Beacon Valley reveals diagnostic spectral trends associated with the production and development of OWPs. In the VNIR, dolerite surfaces exhibit stronger negative spectral slopes than their respective interiors. In addition, MGM analyses of the 2 μm region indicate an apparent enrichment in LCP relative to their interiors. In the TIR, dolerite surfaces are best modeled by a significant increase in amorphous aluminosilicate materials and smectite clays, exhibiting narrowing of the reststrahlen features centered near 1100 cm-1 and 465 cm-1. These spectral signatures are not accompanied by mineralogical changes with respect to their unaltered interiors, demonstrating that the observed variations in LCP# are not indicative of bulk mineralogical variations. This laboratory characterization of OWPs provides a means for remotely assessing the effects of these anhydrous alteration processes where accompanying information about the unaltered lithologies exist. In Acidalia Planitia and Syrtis Major, high-resolution VNIR studies have identified the presence of unaltered olivine- and HCP- bearing basalts in the shallow subsurface (Salvatore et al., 2010; Baratoux et al., 2007; Skok et al., 2010). These identifications were thought to be at odds with broader VNIR and TIR analyses, which reveal spectral signatures that are more enriched in LCP relative to the immediate subsurface. However, the highest modeled abundances of OWPs in these two regions are correlated with the largest apparent enrichment in LCP (Fig. 10). This strong relationship suggests that the observed spectral signatures in these two geographic regions are the result of oxidative weathering processes. 235 Our understanding of the recent martian climate suggests that oxidative weathering is currently the dominant chemical alteration process on the surface of Mars, which is supported by the spectroscopic variations observed in this study. The lack of hydrated signatures in the VNIR and the abundance of OWPs modeled across martian low albedo terrains confirms that these resultant spectroscopic products are globally distributed. The apparent increase in LCP# in oxidized surfaces relative to their unoxidized interiors is also observed spectroscopically over large geographic regions on Mars. Local VNIR and TIR measurements are also consistent with the laboratory analyses of oxidized and unoxidized dolerite samples. In Acidalia Planitia, regional spectral signatures reveal a negative slope and weak (if any) mafic signatures in the VNIR, as well as high modeled OWP and LCP# in the TIR, respectively. However, less weathered olivine-rich ejecta blankets exhibit strong olivine spectral signatures in both the VNIR and TIR wavelength regions and a reduction in the apparent LCP#. In Syrtis Major, areas exhibiting spectrally distinct ejecta also reveal low LCP# values, while the surrounding terrain is modeled as having a higher LCP# in the VNIR (Baratoux et al., 2007; Skok et al., 2010) and TIR (this study) in addition to a higher modeled abundance of OWPs. These local spectral observations substantially bolster the argument that the production and distribution of OWPs is a global phenomenon, yet is dependent upon regional and local factors that likely include underlying compositions and regional climate. As mentioned previously, TIR-derived LCP# values may be significantly influenced by the modeled spectral components within OWPs themselves (Fig. 5). HCP 236 is modeled as the most abundant pyroxene phase in OWPs, which would likely result in higher LCP# values being modeled for terrains that exhibit strong OWP signatures. The concurrent interpretation of both VNIR and TIR spectral data is necessary to differentiate between spectral artifacts and actual observed mineralogical signatures. Because MGM analyses do not require a priori information about the composition of the material under investigation, these analyses in the VNIR wavelength region provide an objective look into the observed spectral signatures. In tandem with the abilities to estimate modal mineralogy using remote TIR datasets, these two datasets and remote analytical techniques are capable of assessing and clarifying both real and apparent spectral signatures. Our analyses of both laboratory and remote TIR datasets assume the dominance of linear spectral mixing, which is a fundamental assumption when estimating modal mineralogy. However, the possibility exists that non-linear processes are influencing the observed TIR spectral signatures. Specifically, the minor mineralogical and chemical variations measured during laboratory investigations (e.g. Salvatore et al., 2013) are much smaller than the observed spectral influences. If OWPs are not a true spectral endmember, then the observed spectral signatures are likely the product of non-linear mixing, making the reported modal mineralogies inaccurate. Further spectral and laboratory investigations are currently being designed to assess the assumption of linearity with regards to these spectral signatures. 237 4.3 Distribution of oxidative weathering products on Mars Possible explanations for the observed distribution of OWPs across the martian surface include (1) regional- and global-scale climatic variations, (2) age and preservation of the uppermost observable surface, and (3) composition of the underlying substrate: The substitution of OWPs for smectites, amorphous silica, zeolites, glasses, and other significantly hydrated phases in TIR spectral libraries has important implications for the nature of martian surface materials and the evolution of the martian climate. Our results suggest that hydrated alteration products are not as widespread across the martian surface as were previously hypothesized. This observation relaxes previous climatic constraints that were required to explain their presence across both old and young surfaces. Additionally, while previous TIR studies argued for varying degrees of latitudinal dependence on the distribution of TES ST2 (e.g., Bandfield et al., 2000; Wyatt and McSween, 2002; Rogers et al., 2007), the dependence on latitude observed in our study is unclear. Although the only high-latitude spectral region analyzed in this study is NA, the modeled abundances of OWPs in NA (37%) is not significantly enriched relative to some of the equatorial regions, including MP (35%) and MS (32%). The modeled abundances of OWPs at low latitudes alone varies by more than 20% and can vary considerably even at local scales (e.g., within Syrtis Major), suggesting that OWP abundances are not strictly controlled by regional or latitude-dependent climatic processes. Could the large variations in OWP abundance be related to discrete shifts in the global climate system? Baratoux et al. (2007) and Skok et al. (2010) found that craters exhibiting spectrally distinct HCP-rich ejecta in Syrtis Major were formed more recently 238 than ~2 Ga, while older craters exhibit less of a HCP enrichment. They propose that the observed spectral signatures in the Syrtis plains relative to the younger crater ejecta could be the result of “superficial and long-term weathering occurring under the present environmental conditions” (Baratoux et al., 2007). If craters with spectrally distinct ejecta deposits are present in other low albedo terrains, and if these craters are also estimated to be younger than 2 Ga, then evidence for a global-scale shift in climate and alteration history may be preserved. Testing this hypothesis requires (1) identifying whether the presence of SDE is a global phenomenon beyond Syrtis Major and Acidalia Planitia; if so, (2) determining whether the ages of all SDE deposits are younger than 2 Ga; and (3) identifying whether the compositional trends between SDE deposits and the surrounding terrain follow the same tendencies as those observed in Syrtis Major. The disparate subsurface compositions between Syrtis Major and Acidalia Planitia suggests that oxidation processes produce similar spectral results regardless of primary composition, and supports the hypothesis that a shift in global-scale climatic conditions has resulted in the deceleration of oxidative weathering since 2 Ga. However, different trends are observed in crater ejecta in the Tyrrhena Terra region (Rogers, 2011), and the relationship between these different geographic regions must be further investigated. The identification of OWPs from orbit requires both their formation across the surface as well as the preservation of these materials in the harsh martian environment. As is observed in Beacon Valley, aeolian abrasion effectively scours alteration rinds from the rock surfaces, exposing fresh and unaltered rock in the process (Glasby et al., 1981; Salvatore et al., 2013). The weaker OWP signatures observed in Syrtis Major relative to Acidalia Planitia could potentially indicate greater amounts of physical erosion (likely 239 related to aeolian abrasion) in Syrtis Major. Evidence exists for widespread and persistent aeolian activity in Syrtis Major based largely on the presence of wind streaks pointing west of most impact craters. The rapid removal of dust in Syrtis Major following global dust storms is also a testament to the heightened aeolian activity (Bell et al., 2012). Therefore, the accumulation of OWPs may be hindered across Syrtis Major relative to other low albedo regions. Regions like Acidalia Planitia and Meridiani exhibit fewer wind streaks than are present in Syrtis Major, indicating that aeolian activity may not be as strong of an erosive force and may explain the higher modeled abundances of OWPs observed in these regions. Thin coatings of amorphous silica have been previously proposed as contributors to TES ST2 spectral signatures (Kraft et al., 2003; Minitti et al., 2007). However, the preservation of these silica coatings throughout the Amazonian epoch is unlikely in the abrasive martian environment. Whereas oxidative weathering products are able to form under current climatic conditions, the ubiquity of silica-rich coatings across the martian surface would imply either their preservation despite aeolian abrasion and reworking throughout the Amazonian, or the continual renewal and redevelopment of leached layers on rock surfaces and sand grains throughout the Amazonian epoch and into the present. While some studies have shown that silica-rich coatings are moderately resistant to physical erosion (e.g., Kraft and Greeley, 2000), the identification of such coatings on Mars would imply that aqueous activity (which is necessary to produce these types of silica-rich coatings) was present on the martian surface in the very recent geologic past. Variations in the modeled abundances of OWPs and their relationship to LCP# may be related to differences in primary underlying compositions. Both NA and SM 240 were previously shown to host olivine- and HCP-bearing basalts in the immediate subsurface (Salvatore et al., 2010; Baratoux et al., 2007; Skok et al., 2010), which may explain their similar alteration pathways and resultant spectral signatures. These other low albedo regions, however, have not been fully investigated using high resolution spectral datasets, and so their subsurface compositions remain largely unconstrained. Instruments on the Mars Exploration Rover Opportunity have been used to identify the dominance of LCP at the Meridiani Planum exploration sites, which are located north and west of the locations used to derive the regional Meridiani (MP) VNIR and TIR spectra (Rogers and Aharonson, 2008). This substrate is unique from those identified in NA and SM (e.g., Salvatore et al., 2010; Baratoux et al., 2007; Skok et al., 2010), and the relationship between this disparate starting composition and the observed regional spectral signatures remains uncertain. 4.4 Implications for Amazonian climate The high modeled abundances of OWPs across the martian surface have implications for the evolution and stability of the martian climate system during the Amazonian epoch. Previous studies (e.g., Cooper et al., 1996; Burkhard and Müller- Sigmund, 2007; Salvatore et al., 2013) have described the metastability and transient nature of these oxidative weathering species, which are far from equilibrium in their current environment and are susceptible to further weathering under most terrestrial conditions. The evidence for similar metastable products on the martian surface implies that conditions on Mars have not been sufficiently warm and/or wet to result in the production of more mature alteration phases since the formation of the OWPs. 241 Theoretical modeling and geomorphic evidence suggests that the Amazonian climate is akin to that of a cold polar terrestrial desert (e.g., Montmessin, 2006; Marchant & Head, 2007; Carr & Head, 2010). Geochemically, the regional to global production of pre-Amazonian carbonate (e.g. Ehlmann et al., 2008), phyllosilicate (e.g. Poulet et al., 2005), sulfate (e.g. Gendrin et al., 2005; Langevin et al., 2005), and hematite (e.g. Christensen et al., 2000c) represents alteration conditions that are significantly different from those observed during the Amazonian epoch. However, the geochemical effects of Amazonian-era chemical alteration have not been previously studied in detail. This work represents the first attempts at constraining the global geochemical and spectral influences of cold and dry environmental conditions on the alteration of the martian surface. The ubiquity of these alteration processes are substantiated through the agreement between laboratory experiments and orbital observations, particularly the global distributions of OWPs. Given our current understanding of martian climate and geochemical evolution, the effects of surface oxidation were likely overwhelmed by the production of more mature weathering products through aqueous alteration early in martian history. The formation of carbonates and phyllosilicates epitomize the complex aqueous weathering processes at work during the Noachian epoch (the “Phyllosian” era; Bibring et al., 2006), and required the prolonged contact of geologic materials with liquid water in a variety of chemical environments and at a range of temperatures (Ehlmann et al., 2009). Following a global shift in aqueous geochemistry and alteration environment, martian surface conditions favored the formation of sulfates and other evaporites (the “Theiikian” era; Bibring et al., 2006). Surprisingly, this transition, which approximately coinciding with 242 the Noachian-Hesperian boundary, also coincides with the formation of valley networks across the martian surface (Fassett & Head, 2008). This association may represent the waning stages of an active hydrologic system, the transition to a desiccating environment, and the termination of extensive physical erosion by fluvial processes. The later Hesperian-Amazonian boundary, therefore, may represent the transition from a water-limited and evaporite-dominated geochemistry to the hyper-arid, hypo- thermal, and oxidation-dominated environment observed today (the “Siderikian” era; Bibring et al., 2006). This transition would enable the preservation of transient OWPs that would otherwise be overprinted by aqueous processes. The Theiikian-Siderikian boundary was initially thought to have formed rapidly as the last remaining liquid water was sequestered (Bibring & Langevin, 2008). However, more recent studies have suggested that many of the sulfate deposits observed on the martian surface formed episodically in response to a variety of different triggering events (e.g. King & McLennan, 2010; Andrews-Hanna et al., 2007; Murchie et al., 2009; Halevy & Head, 2012), although the average age of these units is thought to be clustered near 3.5 Ga. Finally, should the climate change at ~2 Ga proposed by Baratoux et al. (2007) and Skok et al. (2010) be global in scale, the proposed Theiikian-Siderikian boundary may be much more diffuse and prolonged than previously hypothesized. Together, these studies suggest that the geochemical evolution of Mars, from the Theiikian to the Siderikian, was prolonged and potentially episodic (Head, 2012). The timing and duration of this transition has important implications regarding the cessation of aqueous activity on the martian surface and the duration of oxidative weathering processes modifying the currently observed surface units. Studies to further constrain the martian cratering record 243 and erosion and weathering rates are required to augment our current understanding of the martian geologic and geochemical history. 5.0 Conclusions The availability of global VNIR and TIR spectral datasets allows, for the first time, the combined VNIR and TIR spectral analysis of martian low albedo terrain. These investigations ensure that the resultant geologic and geochemical interpretations are consistent throughout both wavelength regions. Regional and local studies provide unique information regarding the abundance and distribution of both primary and secondary phases: (1) Laboratory VNIR and TIR investigations capture unique spectral properties associated with oxidative weathering products (OWPs), which result from exposure of basaltic compositions to hyper-arid and hypo-thermal terrestrial environments. The characterization of these spectral signatures allows for comparable investigations to be undertaken using martian orbital spectroscopic datasets. These unique spectral properties include an increase in the negative spectral slope in the near-infrared, in addition to an apparent shift to higher LCP abundances relative to their unaltered interiors. (2) Orbital VNIR spectroscopy of martian low albedo terrains exhibit variability in the strength of the Fe2+-Fe3+ charge transfer absorption at wavelengths <0.6 μm, the near-infrared spectral slope, and the position and strength of the 2 μm absorption feature associated with Fe2+ in pyroxenes. No vibrational absorption features were observed at 1.4 μm, 1.9 μm, or between 2.0 μm and 2.5 μm, 244 confirming the absence of hydrated minerals at spectrally observable quantities. MGM analyses of these spectra suggest nearly equal proportions of HCP and LCP throughout these study regions, with the exception of LCP-dominated Northern Acidalia and HCP-dominated Syrtis Major. Northern Acidalia also exhibits the strongest negative spectral slope in the VNIR. (3) Regional TIR investigations of the martian surface were performed using a modified spectral endmember library, which includes the TIR spectrum of OWPs and excludes spectral phases that are inconsistent with VNIR observations and that are spectrally indistinguishable from OWPs. Linear unmixing models of these TIR spectra exhibit good fits (low RMS errors) and substantial abundances of OWPs, which primarily replace high-silica phases modeled in previous TIR investigations. Other modeled mineralogies are largely consistent with previous studies of these low albedo regions, and indicate that the surfaces are largely basaltic in nature. However, considerable differences in modeled mineral compositions are present and may be a spectral consequence of oxidative weathering. (4) Localized VNIR spectroscopic investigations uncovered subsurface compositions in both Acidalia Planitia (Salvatore et al., 2010; this study) and Syrtis Major (Baratoux et al., 2007; Skok et al., 2010; this study) identify subsurface compositions that are more enriched in olivine and HCP relative to their apparent surface signatures. Additionally, the distinct spectral signatures in many ejecta deposits confirm that the shallow subsurfaces and observable surfaces of these regions are spectrally inconsistent. 245 (5) Localized TIR investigations of Acidalia Planitia and Syrtis Major are consistent with our local VNIR investigations. Olivine-bearing ejecta in Acidalia Planitia were identified using OMEGA are also identified in TIR investigations. The surrounding terrains, however, contain higher abundances of OWPs, lower olivine abundances, and higher modeled LCP abundances. Similar trends are observed in Syrtis Major, where HCP-enriched ejecta blankets in East Syrtis contain lower OWP abundances and a lower modeled LCP# than the surrounding regional terrains. (6) The spectral influences of OWPs are consistent with the observed martian regional and local spectral signatures. The identification of these products indicates that cold and dry conditions have dominated Amazonian Mars, preserving these metastable alteration products. The transition from the Theiikian to the Siderikian climatic eras was likely more gradual than previously thought, based on the spectral and temporal sequences identified in this study and previous studies. Determining regional variations in primary mineralogy through the use of VNIR and TIR spectroscopy must account for the influence of oxidative weathering on the apparent surface mineralogy. 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(2008), Detection of silica-rich deposits on Mars. Science 320, 1063-1067. 257 Stockstill-Cahill K. R., Anderson F. S. and Hamilton V. E. (2008), A study of low-albedo deposits within Amazonis Planitia craters: Evidence for locally derived ultramafic to mafic materials. J. Geophys. Res. 113, doi:10.1029/2007JE003036. Sunshine J. M., Pieters C. M. and Pratt S. F. (1990), Deconvolution of mineral absorption bands: An improved approach. J. Geophys. Res. 95(B5), 6955-6966. Tornabene L. L., Moersch J. E., McSween Jr. H. Y., Piatek J. L., Milam K. A. and Christensen P. R. (2006), The subsurface geology of Mars via remote sensing of impact craters. GSA Ann. Mtg. SE Sect. 38(3), p. 81. Wyatt M. B. and McSween H. Y. (2002), Spectral evidence for weathered basalt as an alternative to andesite in the northern lowlands of Mars. Nature 417(6886), 263- 266. Wyatt M. B., Hamilton V. E., McSween Jr. H. Y., Christensen P. R. and Taylor L. A. (2001), Analysis of terrestrial and martian volcanic compositions using thermal emission spectroscopy: 1. Determination of mineralogy, chemistry, and classification strategies. J. Geophys. Res. 106(E7), 14711-14732. Wyatt M. B., McSween H. Y., Moersch J. E. and Christensen P. R. (2003), Analysis of surface compositions in the Oxia Palus region on Mars from Mars Global Surveyor Thermal Emission Spectrometer observations. J. Geophys. Res. 108(E9), doi:10.1029/2002JE001986. Figure and Table Descriptions Figure 1. (a) Representative Surface Type 1 (ST1) and Surface Type 2 (ST2) TIR spectra (from Bandfield et al. 2000). The origin of the narrow reststrahlen feature in ST2 258 has been widely debated. (b) Proposed spectral contributors to ST2 TIR spectra, including hydrated minerals and mineraloids, Si-rich glasses, and oxidative weathering products (OWPs). Zeolite spectrum from Ruff et al. (2007), OWP spectrum from Salvatore et al. (2013), Si-K glass from Wyatt et al. (2001), montmorillonite spectrum from Christensen et al. (2000b), and opaline silica spectrum from Michalski et al. (2003). Figure 2. A map of the 9 low albedo regions identified by Rogers et al. (2007) and subsequently analyzed in Rogers and Christensen (2007) and in this study. Regions include Aonium-Phrixi (AP), Cimmeria-Iapygia (CI), Hesperia (HP), Meridiani (MP), Mare Sirenum (MS), N. Acidalia-Utopia (NA), Syrtis (SM), Solis (SP), and Tyrrhena (TT). Background is TES bolometric albedo. The locations of Figure 11 and Figure 14 are outlined by dashed white boxes. Figure 3. Average dolerite interior (a) and surface (b) that were subset for modified Gaussian model (MGM) analyses. Original data from Salvatore et al. (2013). MGM analysis fits (light grey) and continua (dark grey) are also shown, along with the relative strengths of the modeled 1.9 μm (black, circles) and 2.3 μm (black, squares) absorption features associated with LCP and HCP, respectively. The average dolerite surface is modeled as having a higher LCP abundance relative to HCP (defined as LCP#) than the average dolerite interior. Figure 4. VNIR spectral slope plotted against LCP# for dolerite interiors (black circles) and surfaces (grey circles), as modeled using MGM techniques. Grey joins and arrows link the interior and surface measurements of the same sample. All pairs show a systematic decrease in spectral slope and increase in LCP# in the sample surface relative to its unaltered interior. 259 Figure 5. Average TIR emission spectra of the same subset of dolerite interiors (black) and surfaces (light grey) used in MGM analyses. The dolerite surface spectrum is offset by -0.05. The results of linear unmixing are reported and are graphically represented as dashed, dark grey lines. A region of substantial misfit between the measured and modeled surface spectra is highlighted (black arrow). Figure 6. Average OMEGA data for the 9 spectral regions outlined in Figure 2. Also shown are the MGM fits (light grey), the MGM continua (dark grey), and example LCP (circles, black line) and HCP (squares, black line) modeled Gaussians. Figure 7. VNIR spectral slope plotted against LCP# for the 9 martian low albedo regions, as modeled using MGM. There is an apparent relationship between the magnitude of the VNIR spectral slope and the modeled LCP#, implying that the two are likely related. Figure 8. Average TES spectra for the 9 spectral regions outlined in Figure 2 and presented in Rogers and Christensen (2007). Results from our modified endmember library and unmixing analyses are shown as dashed dark grey lines and are presented in Table 4. Figure 9. Model mineralogy for each spectral region as derived from linear unmixing of TIR data. (a) Plot of plagioclase, pyroxene + olivine, and OWPs, showing a largely even mix between all three components with no clear trends between regions. (b) Plot of HCP, LCP, and olivine. Most regions fall near or along the LCP-olivine join, while SM and TT are significantly enriched in HCP relative to the other spectral regions. (c) Plot of HCP, LCP, and OWPs. Most spectral regions fall along the LCP-OWPs join. However, the regions modeled as having the highest abundances of HCP are also 260 modeled as having the lowest abundances of OWPs, although the relationship appears to be nonlinear. Figure 10. Modeled OWP abundance plotted against modeled LCP#, as derived from TIR linear unmixing. There exists a significant logarithmic trend between these two variables (R2 = 0.87), implying that a higher OWP abundance is correlated to a higher modeled LCP#. Figure 11. (a) Mean spectra of South Acidalia (black) and North Acidalia (grey), as derived from binned TES data. Modeled spectral fits are also shown as dashed dark grey lines and are presented in Table 5. (b) TES data binned at 2 ppd, showing variability in the modeled abundances of pyroxene (red), OWPs (green), and carbonate (blue). The spectral dichotomy can be observed both north and south of roughly 42º N by a transition from dominantly blue colors in the south, to dominantly red colors in the north. (c) Modeled LCP# binned at 2 ppd as derived from TES data, indicating high values across the entirety of Acidalia Planitia and implying the dominance of LCP over HCP. Figure 12. (a) THEMIS daytime infrared image of Grindavik crater (25.4º N, 321.0º E), overlain with the OLINDEX2 olivine parameter (Salvatore et al. 2010) for OMEGA image ORB2079_7. Cold colors indicate weak olivine VNIR absorption features, while warm colors indicate strong features. Also shown are OMEGA regions of interest (dashed light green and red regions) and the locations of TES data analyses (solid dark green and red regions), the spectra of which are presented in (b) and (c), respectively. (b) OMEGA VNIR spectra of Grindavik ejecta and the regional terrain. The ratioed spectrum (blue) reveals a broad absorption centered near 1 μm and no 261 absorption feature observed near 2 μm, consistent with a forsterite library spectrum (orange) and the absence of pyroxene within the crater ejecta. (c) TES TIR spectra of Grindavik ejecta and regional terrain. A forsterite library spectrum (orange) is also shown to highlight its consistency with the absorption feature centered near 920 cm-1 in the Grindavik ejecta spectrum, as highlighted in the ratioed spectrum (blue). Modeled unmixing results also confirm a stronger olivine contribution in Grindavik ejecta relative to the surrounding terrain, and are presented in Table 5. Figure 13. A map of LCP# throughout Syrtis Major, highlighting the locations of spectrally distinct ejecta (SDE) blankets concentrated in East Syrtis. Modified from Skok et al. (2010). Black dashed circles highlight the SDE analyzed in Figures 16 and 17, and the grey dashed box highlights the regional terrain to which these SDE were compared. Figure 14. (a) Mean spectra of West Syrtis (black) and East Syrtis (grey), as derived from binned TES data. Modeled spectral fits are shown as dashed dark grey lines and are presented in Table 5. (b) TES binned data at 2 ppd, showing variability in the modeled abundances of HCP (red), OWPs (green), and olivine (blue). West Syrtis appears more green (stronger OWP signatures), while East Syrtis appears more red (stronger HCP signatures). (c) Modeled LCP# binned at 2 ppd as derived from TES data, showing higher LCP# values in West Syrtis and lower LCP# values in East Syrtis. These results are consistent with VNIR analyses performed by Baratoux et al. (2007) and Skok et al (2010) (Fig. 13). Figure 15. Average TES spectra of West Syrtis (black) and East Syrtis (light grey), as derived from binned TES data. An additional 5% spectral contribution from augite (HCP) to the West Syrtis spectrum shows good agreement with the East Syrtis 262 spectrum, suggesting that a slight enrichment in HCP in East Syrtis can account for the majority of the spectral variability observed between these two regions. This is consistent with concurrent and previous VNIR analyses. Figure 16. Average VNIR spectra of regional terrain (a, grey dashed box in Fig. 13) and SDE deposits (b, black dashed circles in Fig. 13) in Syrtis Major from OMEGA images ORB0284_2 and ORB2316_4. MGM fits and continua are shown as light grey and dark grey lines, respectively. The relative strengths of the LCP (circles, black lines) and HCP (squares, black lines) absorption features are also shown. The regional terrain exhibits a higher LCP# value (0.39) relative to the SDE (0.31) and can be seen as the relative strengths of the LCP and HCP absorptions. Figure 17. TES TIR spectra derived from archetypal regional terrain in Syrtis Major (grey, grey dashed box in Fig. 13) and the same SDE deposits analyzed in Figure 16 using OMEGA data (black, black dashed circles in Fig. 13). Linear unmixing model results are shown as dashed dark grey lines, and the modeled mineral concentrations are provided in Table 5. SDE are modeled as having higher HCP abundances, lower LCP#, and lower OWP abundances than the archetypal regional terrain. Table 1. The regions, locations, and number of TES spectra used in local TIR investigations. Table 2. Modified Gaussian modeling (MGM) results for dolerite interiors and surfaces. Table 3. Modified skeleton library from Rogers and Christensen (2007). Endmembers in grey were removed due to their non-detection in VNIR wavelengths and 263 their spectral similarities in the TIR. Italicized endmembers were added to the Rogers and Christensen (2007) skeleton library to provide additional spectral characterization. Table 4. Modeled mineralogical abundances for the 9 martian low albedo regions, derived from linear unmixing of TIR emission spectra using the modified endmember library provided in Table 3. Abundances, statistical errors, and RMS errors are reported in percent. Statistical errors for the modeled abundances are derived from the square root of the diagonal of the estimated covariance matrix (see Rogers and Aharonson (2008)). Table 5. Linear unmixing results for Acidalia Planitia and Syrtis Major. Regional 2 ppd unmixing results are highlighted in grey and represent the TIR spectral dichotomy observed in both of these regions. Localized spectrally distinct ejecta deposits in Acidalia Planitia (associated with Grindavik crater) and Syrtis Major (associated with two craters located at 8.9º N, 74.3º E and 5.9º N, 70.5º E) are also modeled. Abundances, statistical errors, and RMS errors are reported in percent. 264 Chapter 5, Figure 1. 265 Chapter 5, Figure 2. 266 Chapter 5, Figure 3. 267 Chapter 5, Figure 4. 268 Chapter 5, Figure 5. 269 Chapter 5, Figure 6. 270 Chapter 5, Figure 7. 271 Chapter 5, Figure 8. 272 Chapter 5, Figure 9. 273 Chapter 5, Figure 10. 274 Chapter 5, Figure 11. 275 Chapter 5, Figure 12. 276 Chapter 5, Figure 13. 277 Chapter 5, Figure 14. 278 Chapter 5, Figure 15. 279 Chapter 5, Figure 16. 280 Chapter 5, Figure 17. 281 Chapter 5, Table 1. Region Latitude Longitude # of Spectra Acidalia Planitia 18º N – 70º N 310º E – 335º E 20422 Syrtis Major 2º S – 28º N 58º E – 83º E 38699 282 Chapter 5, Table 2. Slope Slope y- RMS Fe3+ 1.9 μm 2.3 μm Sample (x10- (º) intercept Error LCP# IVCT Strength Strength 5 ) (x10-1) (%) Strength MS10_BV_02_int 0.09031 0.08966 2.63 1.65 0.41 0.896 0.502 1.45 MS10_BV_02_sur 0.07927 0.00655 1.58 1.00 0.62 1.097 0.924 1.74 MS10_BV_03_int 0.07889 0.10464 0.12 0.08 0.87 0.916 0.430 1.58 MS10_BV_03_sur 0.09251 0.06639 -0.58 -0.37 1.11 1.496 0.582 2.38 MS10_BV_06_int 0.00331 0.06626 -0.53 -0.33 0.87 1.047 0.048 1.25 MS10_BV_06_sur 0.01714 0.00737 -3.36 -2.12 1.75 1.685 0.699 2.00 MS10_BV_07_int 0.00345 0.09208 -0.50 -0.32 0.83 1.335 0.036 1.34 MS10_BV_07_sur 0.07340 0.10049 -3.25 -2.05 1.78 1.671 0.422 2.41 MS10_BV_09_int -0.02703 0.02252 -1.37 -0.86 1.08 1.509 0.000 1.25 MS10_BV_09_sur 0.00913 0.07440 -1.90 -1.20 1.29 1.847 0.109 1.99 MS10_BV_10_int -0.00367 0.07931 -0.86 -0.54 0.93 1.655 0.000 1.44 MS10_BV_10_sur 0.00562 0.04882 -0.90 -0.57 0.64 1.210 0.103 1.64 MS10_BV_11_int 0.00725 0.07102 -0.88 -0.56 0.90 0.984 0.093 1.46 MS10_BV_11_sur 0.03242 0.06277 -3.11 -1.96 1.44 2.041 0.341 2.19 MS10_BV_12_int 0.11646 0.15275 -0.99 -0.62 1.15 2.050 0.433 1.74 MS10_BV_12_sur 0.08068 0.09295 -3.79 -2.39 1.91 1.770 0.465 2.89 Interior Average 0.03362 0.08478 0.30 -0.19 0.88 1.30 0.193 1.44 Surface Average 0.04877 0.05747 1.92 -1.21 1.32 1.60 0.456 2.16 283 Chapter 5, Table 3. Endmember Mineral Group Source Albite WAR-0244 Plagioclase Christensen et al. (2000b) Andesine BUR-240 Plagioclase Christensen et al. (2000b) Anorthite BUR-340 Plagioclase Christensen et al. (2000b) Bronzite NMNH-93527 Low-Ca Pyroxene Christensen et al. (2000b) Diopside WAR-6474 High-Ca Pyroxene Christensen et al. (2000b) Augite NMNH-9780 High-Ca Pyroxene Hamilton (2000) Augite NMNH-122302 High-Ca Pyroxene Hamilton (2000) Hedenbergite DSM-HED01 High-Ca Pyroxene Christensen et al. (2000b) Pigeonite Low-Ca Pyroxene Hamilton (2000) Forsterite BUR-3720A Olivine Christensen et al. (2000b) Fayalite WAR-RGFAY01 Olivine Christensen et al. (2000b) KI 3362 Fo60 Olivine Morse (1996) Biotite BUR-840 Phyllosilicate Christensen et al. (2000b) Serpentine HS-8.4B Phyllosilicate Christensen et al. (2000b) Illite IMt-2 Phyllosilicate Christensen et al. (2000b) Ca-Montmorillonite STx-1 Phyllosilicate Christensen et al. (2000b) Si-K Glass High-Si Phase Wyatt et al. (2001) Opal-A (01-011) High-Si Phase Michalski et al. (2003) Magnesiohastingsite HS-115.4B Amphibole Christensen et al. (2000b) Avg. Martian Hematite Oxide Glotch et al. (2004) Calcite C40 Carbonate Christensen et al. (2000b) Dolomite C20 Carbonate Christensen et al. (2000b) Anhydrite ML-S9 Sulfate Christensen et al. (2000b) Gypsum ML-S6 Sulfate Christensen et al. (2000b) OWP OWP Salvatore et al. (2013) Enstatite HS-9.4B Low-Ca Pyroxene Christensen et al. (2000b) Blackbody Blackbody Christensen et al. (2000b) 284 Chapter 5, Table 4. GROUP AP CI HP MP MS NA SM SP TT 29.3 ± 20.3 ± 18.9 ± 15.6 ± 20.4 ± 28.7 ± 27.3 ± 27.0 ± 18.0 ± Plagioclase 3.8 4.6 4.4 4.3 3.8 4.6 5.4 3.2 4.6 14.7 ± 23.7 ± 19.2 ± 16.1 ± 18.9 ± 11.2 ± 12.6 ± 17.6 ± 22.6 ± Low-Ca Pyx 4.7 3.4 3.2 3.7 4.0 3.1 4.3 3.7 3.1 17.3 ± High-Ca Pyx 0.0 1.7 ± 4.8 1.9 ± 4.4 0.9 ± 4.7 0.0 0.0 0.0 7.5 ± 3.6 5.1 13.3 ± 13.8 ± 16.7 ± 10.5 ± 14.3 ± Olivine 5.8 ± 1.9 3.3 ± 1.9 5.8 ± 3.3 4.1 ± 1.1 2.7 2.6 2.9 2.1 2.3 Phyllosilicate 4.6 ± 2.3 3.2 ± 3.0 4.5 ± 2.8 2.4 ± 1.5 6.2 ± 2.5 9.4 ± 2.6 6.6 ± 2.5 2.8 ± 0.8 3.1 ± 2.6 Amphibole 0.0 2.2 ± 2.9 0.3 ± 2.8 0.0 0.0 0.0 3.1 ± 3.4 3.9 ± 2.3 3.6 ± 2.6 Carbonate 4.0 ± 0.6 2.9 ± 0.6 3.6 ± 0.6 4.1 ± 0.6 3.3 ± 0.6 2.6 ± 0.7 5.7 ± 0.7 2.4 ± 0.5 2.3 ± 0.4 11.3 ± Sulfate 8.4 ± 1.5 8.2 ± 1.3 8.9 ± 1.2 9.4 ± 1.4 8.5 ± 1.6 7.7 ± 1.8 6.2 ± 1.7 8.8 ± 1.4 1.3 29.6 ± 24.5 ± 29.1 ± 34.7 ± 32.1 ± 37.0 ± 14.1 ± 30.8 ± 19.4 ± OWP 3.2 4.3 4.1 3.8 3.4 2.9 3.7 2.2 3.3 Quartz 0.1 ± 0.8 0.0 0.0 0.0 0.0 0.0 0.6 ± 0.8 0.0 0.4 ± 0.7 Oxide 3.4 ± 6.1 0.0 0.0 0.0 0.0 0.0 0.7 ± 5.9 0.0 0.0 Plag/Pyx 2.0 0.8 0.9 0.9 1.1 2.6 0.9 1.5 0.6 LCP# 1.00 0.93 0.91 0.95 1.00 1.00 0.42 1.00 0.75 52.2 ± 45.9 ± 50.7 ± 56.6 ± 53.8 ± 67.2 ± 35.4 ± 59.5 ± 46.8 ± Blackbody 4.6 1.9 1.6 1.5 1.7 1.3 5.3 1.3 1.7 RMS Error 0.104 0.118 0.111 0.113 0.136 0.150 0.139 0.160 0.108 285 Chapter 5, Table 5. North South Grindavik Regional West East SDE Regional GROUP Acidalia Acidalia Ejecta Terrain Syrtis Syrtis Deposits Terrain Plagioclase 28.6 ± 3.4 25.1 ± 4.6 18.8 ± 4.4 17.0 ± 6.2 27.7 ± 4.4 29.2 ± 4.4 31.7 ± 6.0 24.0 ± 5.7 Low-Ca Pyx 7.3 ± 2.6 1.9 ± 2.4 8.0 ± 3.3 11.0 ± 3.9 7.3 ± 3.0 8.7 ± 2.8 2.4 ± 2.8 7.5 ± 2.8 High-Ca Pyx 0.0 0.0 0.0 0.0 4.8 ± 5.1 8.0 ± 4.7 12.3 ± 6.9 1.5 ± 5.9 Olivine 2.1 ± 1.3 0.6 ± 1.9 12.3 ± 2.0 4.0 ± 2.7 10.8 ± 3.4 10.7 ± 3.0 8.1 ± 4.4 14.2 ± 4.2 Phyllosilicate 0.5 ± 0.7 0.0 1.5 ± 0.9 2.2 ± 3.0 0.6 ± 0.7 0.0 0.0 1.3 ± 1.1 Amphibole 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Carbonate 4.9 ± 0.6 8.0 ± 0.6 6.5 ± 0.7 8.6 ± 1.1 5.4 ± 0.7 5.5 ± 0.5 6.0 ± 0.7 5.5 ± 0.7 Sulfate 8.6 ± 1.5 8.4 ± 1.7 9.9 ± 1.9 5.5 ± 2.2 5.4 ± 1.5 4.2 ± 1.2 3.8 ± 1.3 5.3 ± 1.9 OWP 48.1 ± 2.5 56.1 ± 3.2 42.9 ± 3.2 51.6 ± 3.8 36.9 ± 3.8 32.4 ± 3.4 34.7 ± 4.5 39.5 ± 4.9 Quartz 0.0 0.1 ± 0.9 0.0 0.0 0.6 ± 0.9 1.3 ± 0.9 0.9 ± 1.2 1.2 ± 1.2 Oxide 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Plag/Pyx 3.9 13.2 2.3 1.5 2.3 1.7 2.2 2.7 LCP# 1.00 1.00 1.00 1.00 0.60 0.52 0.16 0.83 Blackbody 61.9 ± 0.9 71.7 ± 0.8 62.0 ± 1.2 69.1 ± 1.2 48.6 ± 1.1 46.6 ± 1.1 49.2 ± 1.7 52.9 ± 1.5 RMSE 0.153 0.150 0.195 0.185 0.169 0.170 0.196 0.163 286 Chapter Six: On the current and future investigation of pervasive oxidative alteration processes on Earth and Mars. M. R. Salvatore1 1 Department of Geological Sciences, Brown University, Providence, RI 02912, USA 287 1.0 Summary and Significance of Work This body of work aims to further our understanding of cold and dry chemical alteration processes through the use of terrestrial analogs, laboratory analyses, and remote sensing. We have been fortunate to root our investigations in fundamental laboratory analyses (e.g. Cooper et al., 1996) that thoroughly characterize and quantify the process of oxidative weathering in basaltic glasses at high temperatures. However, in natural settings, the ubiquity of oxidative weathering is typically overwritten by more mature alteration processes, such as the development of amorphous or crystalline alteration phases. As a result, in more than a decade since the process of oxidative weathering has been characterized, only a few studies have identified natural environments where this process is observed and the resultant products are preserved (e.g. Burkhard and Müller- Sigmund, 2007). Through extensive field work and the identification of these metastable terrestrial weathering products, it soon became obvious that Beacon Valley, Antarctica, experienced pervasive oxidative weathering without the development of more mature alteration phases. This represents the only natural laboratory where oxidative weathering processes are subaerially preserved. In Chapter Two, we characterize a subset of samples from Beacon Valley using a suite of laboratory techniques in an attempt to investigate the chemical, mineralogical, and spectral effects of oxidative weathering on these samples. Our investigations show that spectrally significant modifications occur to the rock surfaces in response to small chemical and immeasurable mineralogical variations. While the electronic and vibrational environments of these samples are clearly distorted 288 significantly upon weathering, the exact cause and nature of these changes remain uncertain. These distinct spectral signatures and their spatial distributions throughout the McMurdo Dry Valleys are further investigated in Chapter Three. A multitude of difficulties, largely with respect to atmospheric and geometric corrections, has precluded the widespread use of orbital and aerial spectral datasets over the McMurdo Dry Valleys. Using in-scene atmospheric correction techniques and a wealth of ground-truthed visible/near-infrared (VNIR) and thermal infrared (TIR) data, we have produced the first multispectral data product covering the majority of the McMurdo Dry Valleys (MDV). The first scientific results utilizing this valuable data product are presented in Chapter Three, where the spectral variability observed in the Ferrar Dolerite is characterized from orbit and linked to a range of primary compositions and secondary processes. In particular, variations in the abundance of orthopyroxene are readily observed using VNIR spectral datasets due to the strength of the 1 μm and 2 μm crystal field absorption features caused by Fe2+ in pyroxenes. Additionally, the distinct spectral signatures of oxidative weathering are observed in the thermal infrared, and their observed distribution throughout the MDV highlights their unique preservation in Beacon Valley and in only a few other localized regions throughout the MDV. These results confirm that while oxidative weathering is a global and pervasive phenomenon, preservation of these signatures and products is rare in terrestrial environments. The successful characterization of oxidative weathering products in Beacon Valley, using both laboratory and orbital techniques, has allowed us to apply our observations to martian surface investigations. The wealth of hyperspectral VNIR and 289 TIR data from orbit are well suited to characterize similar spectral signatures to those observed in the MDV. Chapter Four presents the initial results of our orbital investigation of the martian surface and the spectral similarities to signatures observed in Beacon Valley. The Syrtis and N. Acidalia-Utopia spectral regions, which represent the two distinct low albedo surface endmembers on Mars, can be uniquely characterized as basaltic surfaces that have undergone variable amounts of oxidative weathering. Not only is oxidative weathering a good analog to the spectral signatures observed in both the VNIR and TIR wavelength regions, but it is also consistent with our current understanding of martian surface and climate evolution. For example, thin silica-rich surface coatings have been shown to exhibit spectral similarities to the alteration rinds identified in Beacon Valley and hypothesized for the martian surface (Fig. 1; Kraft et al., 2003; Minitti et al. 2007; Chemtob et al., 2010). However, the dominance of physical erosion on the current martian surface, and ubiquity of these thin coatings that are necessary on the martian surface, makes the presence of these features on the martian surface less likely and supports our hypothesis of oxidative alteration processes being the primary cause of these spectral signatures at regional and global scales. This initial investigation highlights the observed spectral similarities and sets the stage for additional and more detailed VNIR and TIR analyses. Chapter Five builds upon and expands the research presented in Chapter Four. The nine characteristic low albedo regions initially identified by Rogers et al. (2007) and characterized by Rogers and Christensen (2007) in the TIR were investigated using data from the Observatoire pour la Minéralogie, l’Eau, les Glaces et l’Activité (OMEGA; Bibring et al., 2004) to derive regional hyperspectral VNIR signatures to further 290 characterize the near-surface mineralogy. Additionally, Syrtis Major and Acidalia Planitia were both investigated at higher spatial resolutions to relate the observed surface signatures to subsurface compositions using impact craters as geologic boreholes into the subsurface. The results from this investigation suggest that hydrated alteration products are not observed at spectrally significant abundances on regional spatial scales. Instead, oxidative weathering processes are capable of explaining the observed spectral signatures and are uniquely consistent across both VNIR and TIR wavelength regions. At higher resolutions, the subsurface compositions of both Syrtis Major and Acidalia Planitia appear to be dominated by high-Ca pyroxene- and olivine-bearing basalts. However, variable amounts of oxidative weathering result in an apparent weakening of these spectral signatures in exchange for an apparent enrichment in low-Ca pyroxene. This work suggests that the interpreted primary compositions of different low albedo regions on Mars may be significantly influenced by oxidative weathering processes. As a result, future spectral investigations of Mars must account for the effects of oxidative weathering processes on apparent surface compositions. 2.0 Outstanding Questions Although the work presented in this dissertation answers several fundamental questions regarding the alteration process associated with cold desert environments and the distribution of these alteration products on both Earth and Mars, many outstanding questions remain. Here, we highlight a handful of these remaining questions both as a means of organizing relevant future research, but also as a means of appreciating the diversity of the questions that we have worked so tirelessly to address. 291 2.1 What is the primary mechanism for the migration of cations to rock surfaces during oxidative weathering in Beacon Valley, Antarctica? The low temperatures in Beacon Valley are critical for the preservation of metastable oxidative weathering products and the retardation of more mature alteration processes. However, these low temperatures and associated slow kinetics raise another question: What are the relative roles of different diffusion mechanisms that result in cation migration and alteration rind formation? As mentioned in Chapter Two, simple extrapolation of high-temperature volume diffusion rates to ambient Antarctic temperatures result in extremely slow rates that are insufficient to generate the observed alteration rind thicknesses. It is likely that diffusion along grain boundaries, dislocations, and other fast paths play an important role in the formation of these alteration rinds via cation migration. Characterizing the relative roles of these different diffusion mechanisms during oxidative weathering can help to constrain the duration and rates of oxidative weathering in Antarctica and provide a more fundamental understanding of how geologic materials weather in oxidizing environments. Further extrapolation can then help to predict oxidative weathering mechanisms and rates on the martian surface. 2.2 What is the cause of the large amount of variability observed in X-ray diffraction data and what is the relationship to spectroscopic measurements? X-ray diffraction (XRD) is widely considered to be the standard method for mineralogical identification and quantification in geologic samples because it measures fundamental lattice parameters to assess crystal structures. Efforts to characterize powders of both dolerite interiors and surfaces are described in Chapter Two. Measurements were made at three different laboratories using three different preparation 292 and measurement techniques, none of which resulted in clean and reproducible patterns. Additionally, attempts at quantitative characterization using Reitveld refinements resulted in mineral abundances that were not consistent with other spectral and compositional measurements. For example, the Fe-bearing smectite clay nontronite was modeled at an abundance of roughly 30% in both the interior and surface of a particular dolerite sample. However, VNIR and TIR measurements do not reveal spectral signatures that correspond to the presence of nontronite at these abundances. Additionally, the presence of nontronite at 30 vol.% would result in diagnostic shifts in sample chemistry, although no such shifts are observed (Salvatore et al., 2013). As a result, XRD analyses appear to be incongruous with other laboratory techniques that are all consistent with each other. While XRD analyses were not critical towards our dolerite characterization described in Chapter Two, this inconsistency is of concern. In particular, while XRD analyses are a standard mineralogical assessment performed on terrestrial samples, the ability to characterize surface mineralogy on other planets, particularly Mars, relies heavily on remote spectroscopy. Disagreements between XRD analyses and spectral measurements on terrestrial samples, like those observed in Chapter Two, create concern regarding the ability to accurately assess sample mineralogy using either method. What is the true relationship between these XRD and spectral analyses? Are the disagreements between the two datasets the result of sample preparation or analytical errors, or is there a property that is fundamental to the Ferrar Dolerite (e.g., amount of interstitial glass or the morphology of individual grains) that precludes the ability to use either technique to accurately assess the mineralogical components that are present? Additional work is currently being designed to meticulously prepare and measure the same dolerite suite 293 discussed in Chapter Two (i.e., Salvatore et al., 2013) using techniques designed solely for XRD analyses. Should large disagreements continue between analytical techniques, the ability to link spectroscopic studies to mineralogical identifications derived via XRD analyses must be reevaluated. 2.3 What is the origin of the spectral variations observed in oxidative weathering products? The chemical, mineralogical, and spectral signatures of oxidative weathering described in the preceding chapters represents our current understanding of how basaltic lithologies alter where hyper-arid and hypo-thermal conditions dominate. The subtle yet systematic chemical signatures associated with the oxidized alteration rinds on dolerites are indicative of a unique process with a foundation in chemical diffusion, kinetics, and thermodynamics (Cooper et al. 1996). The cause of the observed spectral variability, however, is less constrained. VNIR reflectance spectroscopy is sensitive to both the electronic environment associated with transition metals (primarily Fe) as well as the vibrational overtones and combination tones associated with different anion groups and cation-anion pairings. In Chapter Two, we first characterize the VNIR spectral signatures of alteration rinds and the dominant spectral differences between dolerite surfaces and their interiors. To further compare these signatures to the regional VNIR spectral signatures observed across the martian surface, we revisit these VNIR spectra in Chapter Five, where modified Gaussian model (MGM; Sunshine et al., 1990) analyses reveal a systematic decrease in spectral slope and apparent shift in the 2 µm electronic transition associated with pyroxene. Higher H2O abundances could result in a stronger fundamental vibrational absorption 294 associated with water near 3 µm, which has been shown to result in decreased NIR spectral slopes in samples of heavily hydrated phases. While the dolerite surfaces are likely more enriched in H2O relative to their interiors, the slope of dolerite surfaces is more gradual and begins at shorter wavelengths than would be expected by the simple presence of a stronger H2O fundamental absorption. This imposed spectral slope may also be the cause of the apparent shift in the 2 µm band center. Definitive evidence for the cause of these spectral features, however, is lacking and requires additional macro- and micro-scale spectral measurements to supplement these initial studies. The narrowing of the reststrahlen features in thermal infrared (TIR) emission spectra of dolerite surfaces is similarly unconstrained with regards to the underlying vibrational processes involved in the production of these signatures. In silicates, absorptions in these wavelength regions are linked to the primary Si-O vibrational frequencies. Variations in these shapes imply that the Si-O vibrational environment has been modified (and, in this instance, simplified) to result in one dominant vibrational frequency (~1100 cm-1). Perhaps the removal of divalent cations, enrichment in monovalent cations, and the associated oxidation of ferrous iron can result in such Si-O homogenization? Additional work must also be undertaken at a variety of spatial scales to clearly identify the extent and cause of these spectral relationships. 2.4 How does oxidative weathering influence the spectral signatures of different primary compositions? We have shown that the spectral signatures associated with oxidative weathering in Beacon Valley, Antarctica, are comparable to those observed throughout the martian surface. However, while the Ferrar Dolerite is an appropriate analog for many martian 295 basaltic lithologies, its limited compositional range precludes direct comparison to all observed lithologies across the martian surface. Igneous compositions on Mars range from quartzofeldspathic to ultramafic on both local and regional scales, and understanding the spectral influences of oxidative weathering on these different primary compositions is critical. The chemical effects of oxidative weathering have been well documented in both laboratory (Cooper et al., 1996) and natural settings (Burkhard & Müller-Sigmund, 2007; Salvatore et al., 2013). In theory, the initial compositions of these materials should not influence the distinct alteration trends associated with the oxidation process, so long as the necessary chemical components (e.g., ferrous iron, divalent and monovalent cations) are present at significant abundances (Cook and Cooper, 2000). However, because the cause of the resultant spectral effects is not completely understood, the influence of primary composition must also be investigated. For example, TIR spectra of oxidized dolerite surfaces exhibit a significant narrowing of the reststrahlen features centered roughly at the same frequency as the dolerite interiors. However, if the primary dolerite were olivine-rich, the reststrahlen features of the unaltered dolerite would shift to lower frequencies. Would the resultant oxidative weathering signatures show a comparable shift to lower frequencies, or is the observed 1100 cm-1 center unique to oxidative weathering products regardless of the starting composition? In Chapter Three, we show that the Ferrar Dolerite has a range of compositions and textures that reflect multiple injections of pyroxene-laden magmatic slurries concurrent with sill emplacement. We also highlight how the preservation of alteration rinds on these more mafic dolerites is thwarted by their increased susceptibility to 296 physical erosion. The inherent variability and difficulties associated with these natural samples will likely require the identification of additional field sites that contain different primary lithologies exhibiting well-developed oxidation rinds. Care must be taken when selecting appropriate field sites, however, to ensure that oxidative weathering processes dominate over more common chemical alteration processes (e.g., fluvial, periglacial), which introduces our next outstanding question. 2.5 How does oxidative weathering progress under different climatic conditions? Beacon Valley represents the only known natural laboratory on Earth where such immature oxidative alteration rinds develop and are preserved under ambient climatic conditions. Lasaga (1984) and numerous additional studies have determined that the dominant style of alteration is determined in large part by the temperature and chemistry of the alteration environment. Therefore, one would expect the nature and dominance of oxidative alteration to be dependent upon environmental conditions. Figure 2 shows the location of Beacon Valley and other terrestrial, martian, and modeled martian environments with respect to mean annual temperature and precipitation. While oxidative weathering has been shown to dominate in Beacon Valley, what is the true extent of this alteration process in temperature-precipitation space? In other words, at what temperature do other alteration processes (e.g., thermal decomposition) begin to overshadow oxidative weathering? This bounding limit is useful for determining the ability to reproduce relevant weathering conditions in laboratory settings. Additionally, how much liquid water is necessary to overprint oxidative weathering products with hydrous alteration products? This information can help to define other potential field sites to investigate oxidative weathering. Should the 297 bounding environmental coordinates of oxidative weathering be fairly broad, the possibility of constraining the rate and extent of oxidation for many primary compositions is realistic. If not, cautious laboratory experiments may be the only way to study terrestrial oxidative weathering processes in further detail. 2.6 What is the rate of oxidative weathering in terrestrial and martian environments? The previously described outstanding question has clear implications for understanding the rate of oxidative weathering on Earth and Mars. In Chapter Two, our samples were collected along an age transect defined by Marchant et al. (2007) and represent surface ages of 0.6 Ma and older. We found no clear relationship between alteration rind properties and the position along the predefined age transect. This result is consistent with that of Marchant et al. (2013), who found that alteration rind thickness does not significantly increase beyond a surface exposure age of roughly 10,000 – 15,000 years. While their study was focused primarily on the processes of physical erosion in the MDV, additional work needs to be undertaken to determine the rates and kinetic mechanisms of oxidation, taking grain size and unaltered primary composition into account. Combining the rate of oxidation rind formation with the climatic conditions present within Beacon Valley will help to constrain oxidation rates in this hyper-arid and hypo-thermal natural environment. Together with previous laboratory studies, the kinetics of oxidative weathering can be estimated and applied to other natural terrestrial and martian environments. However, the rate of weathering rind formation is dependent on both environmental conditions as well as primary composition. In particular, the relative abundance of cations will change each individual transport coefficient and, 298 hence, the rates at which cations are able to migrate within the material. In terrestrial environments, the primary composition of samples can be easily constrained through field and laboratory studies. On Mars, however, primary mineralogy must be modeled using a variety of analytical datasets at a wide range of spatial resolutions. Therefore, the successful determination of oxidation rates on Mars is heavily dependent upon the successful determination of primary starting compositions. Nonetheless, relative rate estimations are valuable when assessing and comparing the evolutionary history of different martian landscapes. Determining oxidation rates will require the use of both laboratory analyses of naturally oxidized samples and the oxidation of pristine samples in controlled laboratory environments. While the textures of naturally oxidized materials can hold valuable information regarding the nature and extent of alteration (e.g., Cooper et al. 1996), the ability to study the evolution of these textures on human timescales is not a current possibility. Instead, the oxidation of unaltered samples in a controlled laboratory setting could potentially supplement the study of natural samples. Given the potential sensitivity of this alteration process to the unique environmental conditions found in Beacon Valley, however, caution must be taken to ensure that laboratory-derived oxidation products are comparable to those observed in nature. 3.0 Future Work and Concluding Remarks 3.1 Future work Future work to explore these outstanding questions will require a similar combination of field, laboratory, and orbital investigations. Graduate student Kevin 299 Cannon (Brown University, exp. 2017) has been analyzing the spectral, chemical, and mineralogical properties of basalts and basaltic sandstones from Carapace Nunatak, an isolated bedrock exposure along the eastern margin of the East Antarctic Ice Sheet that is located 110 km NNW of Beacon Valley. Preliminary measurements indicate that the samples from Carapace Nunatak have experienced more extensive aqueous alteration than the dolerites in Beacon Valley (Cannon et al., 2013). While mean annual temperatures are likely colder on Carapace Nunatak due to its exposure on top of the East Antarctic Ice Sheet, the amount of melting may be significantly higher due to the availability of snow and ice and the dark albedo of the rocks. The radiating effect of the dark rocks is manifested in the presence of an ice collar surrounding the nunatak (Fig. 3). The result of this effect is that liquid water is likely in more frequent contact with the rocks on Carapace Nunatak than in Beacon Valley. Determining whether these alteration products are the result of subaerial alteration in the current Antarctic environment or whether they are associated with deuteric alteration (volcanic rocks) or allogenic/authigenic alteration (sedimentary rocks) prior to exposure is of critical importance. Future work on the Carapace Nunatak sample suite will involve additional chemical and mineralogical analyses, including the use of micro-X-ray diffraction (μXRD), micro-X-ray fluorescence (μXRF), elemental mapping, and micro-X-ray Absorption Near Edge Structure (μXANES) analyses, which require the use of synchrotron radiation and has been accepted for study at Brookhaven National Laboratory. Additional work surrounding new field sites and new analytical techniques are also being considered: 300 3.1.1 Field studies Future field investigations will be necessary to identify the range of natural environments where oxidative weathering products are currently observed. One potential location for future research is the Nevada National Security Site (N2S2), located approximately 100 km northwest of Las Vegas. Hundreds of nuclear and conventional ordinances were detonated at this location beginning in 1951, creating well-developed and well-preserved craters that excavate underlying geologic materials. Of particular interest are the 81 m diameter crater created during Project Danny Boy resulting from a 0.42 kiloton (kt, of TNT) nuclear device buried at 33.5 m depth into basaltic substrate, and the 260 m diameter Schooner crater resulting from a 30 kt nuclear device buried at 108 m depth into basaltic substrate (DOE, 2000). The excavated and ejected material consists primarily of trachybasalt containing roughly 60% plagioclase, 15% pyroxene, 15% interstitial glass, and 10% olivine, with minor opaques (Nordyke and Wray, 1964; James, 1969). Studies of the exposed basaltic materials will help to constrain the degree to which oxidative weathering products are preserved in this environment, as well as the extent to which chemical alteration has progressed beyond the effects of oxidation. These types of studies are possible (and are likely better constrained than those performed in the McMurdo Dry Valleys) because of the detailed temporal and environmental records available for this location. For example, the exact times of exposure for the basaltic ejecta associated with the Danny Boy and Schooner craters are precisely known (DOE, 2000). This information provides unique information on the temporal role of chemical alteration in desert environments. Additionally, detailed 301 weather and climate records are available from both Las Vegas, NV (105 km southeast of N2S2), and Beatty, NV (41 km southwest of N2S2), which provide temperature and precipitation data through the date and time of basalt excavation. Therefore, the extent of alteration observed on these basaltic clasts will allow us to determine whether exposure to the subtropical desert climate of southern Nevada results in significantly different alteration products than those observed in Beacon Valley. 3.1.2 Laboratory analyses Additional laboratory analyses on the suite of dolerite samples from Beacon Valley can help to further constrain the properties and extent of oxidative weathering throughout each individual sample. One particular analysis that could potentially improve our understanding of the relationship between the spectral, chemical, and optical signatures observed in dolerite alteration rinds is the use of micro-thermal emission imaging, which is currently being developed at the Arizona State University Mars Space Flight Facility (Edwards and Christensen, 2012). This spectrometer is capable of achieving spatial resolutions of ~90 μm pix-1 on powders, whole rock, and sectioned samples. Further characterization of dolerite alteration rinds using this technology can help to constrain the depth of the observed thermal emission signatures as well as emissivity variations associated with different mineral groups. Similarly, preliminary analyses using hyperspectral VNIR imaging spectroscopy (with Dr. Ed Cloutis, University of Winnipeg) has been conducted by graduate student Rebecca Greenberger (Brown University, exp. 2015) on a subset of dolerites from Beacon Valley. These data have a spectral resolution of 5 nm between 0.42 μm and 1.10 μm, and a spectral resolution of 10 nm between 1.20 μm and 2.50 μm. Initial 302 investigations of the data between 0.42 μm and 1.10 μm show good agreement with measurements made at the Reflectance Experiment Laboratory (RELAB) at Brown University (Fig. 4). Given the sub-millimeter spatial resolution that can be achieved using this imaging system, characterization of the alteration rind and the transition into the unaltered rock interior can be carefully characterized. As of April of 2013, calibration of the near-infrared component of these data is still underway. Laboratory analyses utilizing transmission electron microscopy (TEM) can help to elucidate nanometer-scale textures within the dolerites. Graduate student Hillary O’Brien (Brown University, exp. 2016) has been spearheading the efforts of analyzing select dolerite samples using TEM analyses to search for new phases that may form within the alteration rinds. These analyses will help to refine the alteration model that we present in Chapter Two. Additional XRD analyses under optimal sample preparation and analytical conditions must also be performed in order to reconcile the conflicting results presented in Chapter Two, and to perform more robust Rietveld refinements on the measurements in order to derive reasonable quantitative mineral abundances. Future work is currently being planned for the summer of 2013. 3.1.3 Remote analyses Orbital investigations of additional terrestrial field sites will help to establish the link between the weathering processes and the observed spectral signatures. The utility of Advanced Land Imager (ALI; Mendenhall et al., 2000) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER; ERSDAC, 2005) datasets to study both primary and secondary compositions was shown in Chapter Three. The spatial coverage and proven utility of these datasets will be useful in future investigations 303 in other relevant terrestrial environments. Orbital and aerial datasets with higher spectral resolution, including Hyperion (220 spectral bands between 0.4 μm and 2.5 μm; Pearlman et al., 2001), Airborne Visible/Infrared Imaging Spectrometer (AVIRIS, 224 spectral bands between 0.4 μm and 2.5 μm; Green et al., 1998), and the Thermal Infrared Multispectral Scanner (TIMS, 6 spectral bands between 8.2 μm and 12.2 μm; Palluconi and Meeks, 1985), can potentially contribute to these analyses, provided appropriate atmospheric corrections can be applied. Chapters Four and Five of this dissertation focus primarily on the regional-scale spectral analyses of the martian surface, with the investigation of more localized spectral signatures limited only to Syrtis Major and Acidalia Planitia. A quick survey of other low albedo regions revealed little spectral variation observed at the spatial resolutions of the OMEGA and the Thermal Emission Spectrometer (TES) instruments in the VNIR and TIR, respectively. However, high resolution TIR imagery from the Thermal Emission Imaging System (THEMIS; Christensen et al., 2004) may be capable of identifying spectral signatures at high spatial resolutions that would otherwise be invisible using TES. For example, small impact craters in Mare Sirenum are dark in THEMIS daytime infrared imagery and bright in THEMIS nighttime infrared imagery, indicating that they exhibit a lower albedo and a higher thermal inertia than the surrounding terrain, respectively. These craters, which are several hundred meters in diameter and, hence, beyond the spatial resolution of TES, are prime candidates for investigation using the THEMIS multispectral TIR capabilities. Analysis of these craters could reveal both the underlying unaltered composition of Mare Sirenum as well as the potential role of oxidative weathering processes in this unique location. Higher resolution OMEGA and 304 Compact Reconnaissance Imaging Spectrometer for Mars (CRISM; Murchie et al., 2007) data would complement these THEMIS analyses and help to ascertain the present and absent mineral species. 3.2 Concluding remarks Since the earliest stages of planetary evolution, oxidative weathering has likely been an active and global component of the terrestrial and martian subaerial alteration regime. As the martian surface began to desiccate, liquid water became sequestered into its current solid surface and subsurface reservoirs. As widespread aqueous activity and alteration ceased, oxidative weathering processes developed into the dominant chemical alteration process on the martian surface. The low temperatures and paucity of liquid water in Beacon Valley has also led to the dominance of oxidative weathering without the subsequent obscuration by more mature chemical alteration. This represents the first natural laboratory where Amazonian-style chemical alteration has been investigated on Earth as well as the first thorough characterization of Amazonian-aged chemical weathering. By constraining the details of chemical alteration under modern martian surface conditions, our work provides a stable foundation upon which to investigate the nature, timing, and influences of climatic transitions on Mars. References Bibring J.-P., Langevin Y., Mustard J. F., Poulet F., Arvidson R., Gendrin A., Gondet B., Mangold N., Pinet P., Forget F. and the OMEGA team (2006), Global mineralogical and aqueous Mars history derived from OMEGA/Mars Express data. Science 312, 400-404. 305 Burkhard D. J. M. and Müller-Sigmund H. (2007), Surface alteration of basalt due to cation-migration. Bull. Volcanol. 69, 319-328. Cannon K. M., Salvatore M. R. and Mustard J. F. (2013), Weathering rinds on basalts and basaltic sandstones in the Antarctic climate: Spectroscopic implications for Mars. LPSC XLIV, abstract 1358. Christensen P. R., Jakosky B. M., Kieffer H. H., Malin M. C., McSween Jr. H. Y., Nealson K., Mehall G. L., Silverman S. H., Ferry S., Caplinger M. and Ravine M. (2004), The Thermal Emission Imaging System (THEMIS) for the Mars 2001 Odyssey mission. Space Sci. Rev. 110, 85-130. Cook G. B. and Cooper R. F. (2000), Iron concentration and the physical process of dynamic oxidation in an alkaline earth aluminosilicate glass. Am. Min. 85, 397- 406. Cooper R. F., Fanselow J. B. and Poker D. B. (1996), The mechanism of oxidation of a basaltic glass: Chemical diffusion of network-modifying cations. Geochim. Cosmochim. Acta 60, 3253-3265. DOE (2000), United States Nuclear Tests: July 1945 through September 1992. U.S. Dept. of Energy DOE/NV-209-REV 15, 162 pp. Edwards C. S. and Christensen P. R. (2012), Development of a microscopic thermal emission spectrometer: Analysis of primary igneous materials for planetary analogs. LPSC XLIII, abstract 2658. ERSDAC, SNM (2005), ASTER Users Guide, Part 1 General, Version 4. http://www.science.aster.ersdac.or.jp/en/documents/users_guide/part1/pdf/Part1_ 4E.pdf, Date Accessed: 12 June 2012. 306 Green R. O., Eastwood M. L., Sarture C. M., Chrien T. G., Aronsson M., Chippendale B. J., Faust J. A., Pavri B. E., Chovit C. J., Solis M. and Olah M. R. (1998), Imaging spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Rem. Sens. Of Env. 65(3), doi:10.1016/S0034-4257(98)00064-9. James O. B. (1969), Shock and thermal metamorphism of basalt by nuclear explosion, Nevada Test Site. Science 166, 1615-1620. Lasaga A. C. (1984), Chemical kinetics of water-rock interactions. J. Geophys. Res. 89(B6), 4009-4025. Marchant D. R., Phillips W. M., Fastook J. L., Head III J. W., Schaefer J. M., Shean D. E. and Kowalewski D. E. (2007), Dating the world’s oldest debris-covered glacier: Implications for interpreting viscous-flow features on Mars. LPSC 38, abstract 1895. Marchant D. R., Mackay S., Lamp J. L., Hayden A. T. and Head J. W. (2013), A review of geomorphic processes and landforms in the Dry Valleys of southern Victoria Land: Implications for evaluating climate change and ice-sheet stability. In Hambrey M. J., Barker P. F., Barrett P. J., Bowman V., Davies B., Smellie J. L. and Tranter M., eds. Antarctic Palaeoenvironments and Earth-Surface Processes. London: Geological Society Special Pub. 381, in press. http://dx.doi.org/10.1144/SP381.10. Mendenhall J. A., Bernotas L. A., Bicknell W. E., Cerrati V. J., Digenis C. J., Evans J. B., Forman S. E., Hearn D. R., Hoffeld R. H., Lencioni D. E., Nathanson D. M. and Parker A. C. (2000), Earth Observing-1 Advanced Land Imager: Instrument 307 and flight operations overview. Massachusetts Institute of Technology & Lincoln Laboratory Project Report EO-1-1. Minitti M. E., Weitz C. M., Lane M. D. and Bishop J. L. 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(1964), Cratering and radioactivity results from a nuclear cratering detonation in basalt. J. Geophys. Res. 69, 675-689. Palluconi F. D. and Meeks G. R. (1985), Thermal Infrared Multispectral Scanner (TIMS): An investigator’s guide to TIMS data. NASA STI/Recon Tech. Rep. N 85, 28286. Pearlman J., Carman S., Segal C., Jarecke P., Barry P. and Browne W. (2001), Overview of the Hyperion Imaging Spectrometer for the NASA EO-1 mission. IGARSS 2001. 308 Rogers A. D. and Christensen P. R. (2007), Surface mineralogy of martian low-albedo regions from MGS-TES data: Implications for upper crustal evolution and surface alteration. J. Geophys. Res., 112(E01003), doi:10.1029/2006JE002727. Rogers A. D., Bandfield J. L. and Christensen P. R. (2007), Global spectral classification of martian low-albedo regions with Mars Global Surveyor Thermal Emission Spectrometer (MGS-TES) data. J. Geophys. Res. 112(E02004), doi:10.1029/2006JE002726. Salvatore M. R., Mustard J. F., Head J. W., Cooper R. F., Marchant D. R. and Wyatt M. B. (2013), Development of alteration rinds by oxidative weathering processes in Beacon Valley, Antarctica, and Implications for Mars. Geochim. Cosmochim. Acta, in review. Sunshine J. M., Pieters C. M. and Pratt S. F. (1990), Deconvolution of mineral absorption bands: An improved approach. J. Geophys. Res. 95(B5), 6955-6966. Figure Descriptions Figure 1. Back-scattered electron (BSE) micrograph of a dolerite surface (a; sample MS10_BV_05A, see Chapter Two for additional sample details) compared to the silica-rich basaltic coatings studied in Minitti et al. (2007) (b; Figure 13a from Minitti et al., 2007). The dashed line in the scale bar of (a) indicates 20 μm, which is approximately the thickness of the silica-rich coating studied in Minitti et al. (2007). No evidence exists for the presence of thin coatings on dolerites from Beacon Valley, which would be observable should they be present at the same scale as those identified by Minitti et al. (2007). While spectral similarities exist between these two distinct surface 309 textures, the physical manifestations are drastically different. White arrows indicate sample surfaces. Figure 2. Mean annual precipitation plotted against mean annual temperature for three terrestrial analog locations (light and dark blue), current martian locations (dark green), and modeled martian environments (light green). Characterizing oxidative weathering in other analog environments will help to determine the rates and relative importance of this process under different climatic conditions. Figure 3. Oblique aerial photograph of Carapace Nunatak, looking towards the west. Considerable amounts of snow and ice are present on and around the exposed bedrock. The ice collar on the left portion of the image is largely due to thermal radiation emitted from the dark and high thermal inertia bedrock, which prevents significant ice accumulations from forming immediately adjacent to the exposed bedrock. For scale, the distance between the vertical cliff face and the summit of the annotated ice collar is approximately 75 meters. Photograph taken by M. R. Salvatore. Figure 4. (a) A hyperspectral image of dolerite sample MS10_BV_01 (see Chapter Two for additional chemical, mineralogical, and spectral information on this sample). The alteration rind, unaltered interior, and the transition between these two are clearly visible. Surface pitting is also visible on the rock surface. Boxes represent the locations of the spectra shown in (b), with colors corresponding to the respective spectra. (b) Spectra derived from the hyperspectral image. Shown for comparison are the laboratory-derived RELAB spectra, which are in good agreement with the spectra derived from the hyperspectral image. 310 Chapter 6, Figure 1. 311 Chapter 6, Figure 2. 312 Chapter 6, Figure 3. 313 Chapter 6, Figure 4. 314 Appendix A: Multispectral map of the McMurdo Dry Valleys: Description, methodology, and parameterization. M. R. Salvatore1 1 Department of Geological Sciences, Brown University, Providence, RI 02912, USA 315 Main Text The McMurdo Dry Valleys (MDV) of Antarctica are some of the most geologically diverse ice- and vegetation-free terrains on Earth. The geology of this unique region has been extensively studied since their discovery in the early 20th century and has revolutionized our understanding of the tectonic (e.g., Gleadow and Fitzgerald, 1987; Denton et al., 1993; Sugden et al., 1995), volcanic (e.g., Gunn, 1962; Armstrong, 1978; Marsh 2004), and climatic history (e.g., Denton et al., 1993; Marchant and Denton, 1996) of Antarctica. The United States Navy began a detailed aerial photographic campaign of key locations on the Antarctic continent in 1946 (including the MDV; PGC 2013), which was followed by rigorous geologic mapping of the region, completed in the mid-1990s (McElroy et al., 1987; Kirk et al., 1989; Allibone and Heron, 1991; Pocknall et al., 1994; Turnbull et al., 1994; Isaac et al., 1995). This mapping was substantiated with ground observations and use of aerial photography. While aerial photography and (more recently) orbital imagery have been used to investigate regional and local geomorphology, spectral datasets have not been thoroughly investigated. The likely reasons behind the limited use of these datasets are the geometric and atmospheric difficulties associated with polar observations. The low solar elevation (≤ 35.9º) and long solar path length through the atmosphere (proportional to cosine θ, where θ is the solar elevation in degrees) equate to low irradiances and large atmospheric contributions, respectively. In contrast, tropical remote sensing benefits from high solar elevations and short atmospheric path lengths, resulting in large solar irradiances and minimized atmospheric contributions (although heightened atmospheric H2O contents are often problematic). 316 Since the 1980s, radiative transfer modeling has been used to estimate atmospheric contributions so that they can be removed from remote datasets. However, these models require the input of atmospheric parameters coinciding with the time of image acquisition. Reasonable estimates of atmospheric information can be made across much of the populated landmasses, thanks in large part to the dense distributions of regional and international airports. The isolation of the MDV makes the frequent and robust collection of atmospheric information difficult. McMurdo Station is the closest location of consistent atmospheric data collection, but the volatility of atmospheric conditions along the Transantarctic Mountains makes these data largely inapplicable to the MDV (Doran et al., 2002). The difficulties in constraining atmospheric parameters throughout the MDV make traditional radiative transfer modeling unsuitable for atmospherically correcting remote datasets. This is especially true for the visible and near-infrared (VNIR) wavelengths, where both the incoming solar irradiance as well as the exiting radiance from the target of interest must pass through the atmosphere. To mitigate these issues, we used an in-scene hybrid dark object subtraction and regression (DOS-R) method to atmospherically correct our VNIR dataset (more information provided in Chapter Three). Thermal infrared (TIR) emission spectroscopy, on the other hand, does not have to correct for atmospheric effects on incoming solar irradiance which, due to the long path length of low-elevation solar irradiance, is the largest source of atmospheric contributions. As a result, after confirming the efficacy of the standard Temperature/Emissivity Separation (TES) algorithm (Gillespie et al., 1998) using laboratory-derived emissivity values of relevant lithological endmembers, it was 317 determined that the publically available atmospherically corrected data were suitable for use in our MDV spectral mapping product. The benefits of remote spectral mapping are prodigious. Spectral mapping supplements traditional geologic mapping through the addition of compositional information and unobstructed spatial coverage. VNIR data are sensitive to Fe2+-Fe3+ intervalence charge transfer absorptions at visible wavelengths, in addition to Fe2+ crystal field absorptions in the near-infrared. The TIR is sensitive to variations in silicate mineral structure in addition to the effects of oxidative chemical alteration processes. In tandem, these two wavelength regions are able to distinguish between all of the exposed primary lithologies throughout the MDV as well as select altered components. In the creation of this spectral mapping product, multispectral VNIR and TIR datasets were used due to their coverage, ease of access and processing, and high signal to noise. Advanced Land Imager (ALI; Mendenhall et al., 2000) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER; ERSDAC, 2005) datasets were utilized and provide broad spatial coverage at 30 m pix-1 and 90 m pix-1, respectively. In total, this combined spectral product contains 1.57 x 10-6 multispectral pixels of ice-, snow-, water-, and cloud-free terrain, providing geomorphic and compositional information to supplement traditional geologic mapping products. However, while the improved spatial coverage is an obvious benefit to geologic investigations of the MDV, the relatively coarse spatial footprint precludes the detailed investigation of sub-pixel features. For example, variations in mineralogy and texture are aggregated into a single spectral signature. Additionally, if contributing below the masking thresholds described in Chapter Three, the presence of sub-pixel ice, snow, 318 water, clouds, or shadows can substantially alter the observed spectral signature, resulting in misinterpretation. Nonetheless, in conjunction with traditional geologic mapping, multispectral orbital data provide an additional tool for geologic interpretations. Detailed sensor information and data calibration techniques are outlined in Chapter Three of this dissertation. In this Appendix, we present additional details regarding the images utilized in the production of the spectral map as well as additional calibration and atmospheric removal information. The completed spectral map can be downloaded from the following website: http://planetary.brown.edu/grad_pages/Salvatore/MDV_spectral_map_2013.zip (subject to change, please contact M. R. Salvatore for additional information), which includes an image file and a README file with additional information. Provided below are approximate true color images of the spectral map with the outlines of the individual ALI (Fig. 1) and ASTER (Fig. 2) images used in the final mosaic. Figure 3a through Figure 3n display single band images of the completed mosaic. Figure 4 is a contextual figure and represents the range of spectral diversity observed throughout the MDV (see Chapter 3, Figure 1). Table 1 lists the names, date of acquisition, and locations of each image used in the spectral map. Table 2 provides information necessary for the radiometric calibration of ALI data (see Chapter Three for additional details). Table 3 provides the hybrid dark object subtraction and regression (DOS-R) atmospheric removal values for each pixel used in the derivation of the VNIR atmospheric correction and supplements the averaged DOS-Rvalues found in Chapter Three, Table 2. Lastly, Table 4 lists the Earth-Sun distance (d) in astronomical units and the solar elevation (θ) in degrees for the date and time that each ALI image was acquired. 319 References Allibone A. H. and Heron D. W. (1991), Geology of the Thundergut area, southern Victoria Land, Antarctica. Scale 1:50,000. New Zeal. Geol. Surv., Misc. Map Series 21. Armstrong R. L. (1978), K-Ar dating: Late Cenozoic McMurdo Volcanic Group and dry valley glacial history, Victoria Land, Antarctica. New Zealand J. Geol. & Geophys. 21, 685-698. Chander G., Markham B. L. and Helder D. L. (2009), Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Rem. Sens. of Env. 113, 893-903. Denton G. H., Sugden D. E., Marchant D. R., Hall B. L. and Wilch T. I. (1993), East Antarctic Ice Sheet sensitivity to Pliocene climate change from a Dry Valleys perspective. Geograf. Annal. 75A, 155-204. Doran P. T., McKay C. P., Clow G. D., Dana G. L., Fountain A. G., Nylen T. and Lyons W. B. (2002), Climate observations from the McMurdo Dry Valleys, Antarctica, 1986-2000. J. Geophys. Res. 107, doi:10.1029/2001JD002045. ERSDAC, SNM (2005), ASTER Users Guide, Part 1 General, Version 4. http://www.science.aster.ersdac.or.jp/en/documents/users_guide/part1/pdf/Part1_ 4E.pdf, Date Accessed: 12 June 2012. Gillespie A., Rokugawa S., Matsunaga T., Cothern S., Hook S. and Kahle A. B. (1998), A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) images. Inst.Elect. & Electr. Eng. Trans. on Geosci. & Rem. Sens. 36, 1113-1126. 320 Gleadow A. J. W. and Fitzgerald P. G. (1987), Uplift history and structure of the Transantarctic Mountains – New evidence from fission track dating of basement apatites in the Dry Valleys area, southern Victoria Land. Earth & Planet. Sci. Lett. 82, 1-14. Gunn B. M. (1962), Differentiation in Ferrar Dolerites. New Zeal. J. Geol. & Geophys. 5, 820-863. Isaac M. J., Chinn T. J., Edbrooke S. W. and Forsyth P. J. (1995), Geology of the Olympus Range area, southern Victoria Land, Antarctica. Scale 1:50,000. N. Z. Inst. of Geol. & Nucl. Sci., geol. map 20. Kirk P. A., Sherwood A. M., Woolfe K. J., Allibone A. M., Anckorn J. F. and Morrison A. D. (1989), Geology of the Knobhead Area, southern Victoria Land, Antarctica. Scale 1:50,000. New Zeal. Geol. Surv., Misc. Map Series 19. Marchant D. R. and Denton G. H. (1996), Miocene and Pliocene paleoclimate of the Dry Valleys region, southern Victoria Land: A geomorphological approach. Marine Micropaleo. 27, 253-271. Marsh B. (2004), A magmatic mush column Rosetta Stone: The McMurdo Dry Valleys of Antarctica. Eos Trans. of the Amer. Geophys. Union 85, 497-508. McElroy C. T. and Rose G. (1987), Geology of the Beacon Heights area, southern Victoria Land, Antarctica. New Zeal. Geol. Surv., Misc. Map Series 15. Mendenhall J. A., Bernotas L. A., Bicknell W. E., Cerrati V. J., Digenis C. J., Evans J. B., Forman S. E., Hearn D. R., Hoffeld R. H., Lencioni D. E., Nathanson D. M. and Parker A. C. (2000), Earth Observing-1 Advanced Land Imager: Instrument 321 and flight operations overview. Massachusetts Institute of Technology & Lincoln Laboratory Project Report EO-1-1. PGC (2013), Polar Geospatial Center at the University of Minnesota. www.pgc.umn.edu, accessed on 04 January 2013. Pocknall D. T., Chinn T. J., Sykes R. and Skinner D. N. B. (1994), Geology of the Convoy Range area, southern Victoria Land, Antarctica. Scale 1:50,000. Inst. of Geol. & Nucl. Sci., geol. map 11. Sugden D. E., Denton G. H. and Marchant D. R. (1995), Landscape evolution of the Dry Valleys, Transantarctic Mountains: Tectonic implications. J. Geophys. Res. 100, 9949-9967. Turnbull I. M., Allibone A. H., Forsyth P. J. and Heron D. W. (1994), Geology of the Bull Pass-St. John Range area, southern Victoria Land, Antarctica. Scale 1:50,000. Inst. of Geol. & Nucl. Sci., geol. map 14. Figure and Table Descriptions Figure 1. Outlines of subset Advanced Land Imager (ALI) images used in the creation of the spectral mapping product. Image names are abbreviated to the final two characters. Figure 2. Outlines of subset Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images used in the creation of the spectral mapping product. Image names are abbreviated to the final four numbers. Figure 3. Single band images of the completed spectral mosaic of the McMurdo Dry Valleys. (a) Band 1 (0.4430 μm), (b) Band 2 (0.4825 μm), (c) Band 3 (0.5650 μm), 322 (d) Band 4 (0.6600 μm), (e) Band 5 (0.7900 μm), (f) Band 6 (0.8675 μm), (g) Band 7 (1.2500 μm), (h) Band 8 (1.6500 μm), (i) Band 9 (2.2150 μm), (j) Band 10 (8.2910 μm), (k) Band 11 (8.6340 μm), (l) Band 12 (9.0750 μm), (m) Band 13 (10.6570 μm), (n) Band 14 (11.3180 μm). Figure 4. Spectral parameter map of the McMurdo Dry Valleys. Mafic band strength (MBS) is mapped in red, NIR spectral slope is mapped in green, and the strength of the quartz emissivity peak is mapped in blue. Dark object subtraction-regression (DOS-R) locations are marked by orange stars, in situ spectral grid locations are marked by blue stars, and the locations of the four primary study regions highlighted in Chapter Three are outlined in yellow. Table 1. List of images used to create the spectral map of the McMurdo Dry Valleys. Table 2. Band-specific rescaling gain factor (Grescale, [(W/(m2 sr μm))/DN]), band-specific rescaling bias factor (Brescale, [W/(m2 sr μm)]), and mean exoatmospheric solar irradiance (ESUNλ, [W/(m2 μm)]) for each ALI band used in the production of this spectral map. Data from Chander et al. (2009). Table 3. Pixel values used in the hybrid dark object subtraction and regression (DOS-R) atmospheric removal technique. Table 4. Earth-Sun distance (d) in astronomical units and the solar elevation (θ) in degrees for the date and time of ALI image acquisition. 323 Appendix A, Figure 1. 324 Appendix A, Figure 2. 325 Appendix A, Figure 3a. 326 Appendix A, Figure 3b. 327 Appendix A, Figure 3c. 328 Appendix A, Figure 3d. 329 Appendix A, Figure 3e. 330 Appendix A, Figure 3f. 331 Appendix A, Figure 3g. 332 Appendix A, Figure 3h. 333 Appendix A, Figure 3i. 334 Appendix A, Figure 3j. 335 Appendix A, Figure 3k. 336 Appendix A, Figure 3l. 337 Appendix A, Figure 3m. 338 Appendix A, Figure 3n. 339 Appendix A, Figure 3. 340 Appendix A, Table 1. Instrument Image ID Date of Acquisition Location Taylor V., ALI EO1A0581152008022110KG 22 Jan 2008 Beacon V. Victoria V., EO1A0581152010038110KK 07 Feb 2010 Bull Pass EO1A0581152009339110K0 05 Dec 2009 Wright V. EO1A0581152010041110K9 10 Feb 2010 Wright V. EO1A0581152011027110P1 27 Jan 2011 Wright V. ASTER AST_05_00312082002210402 08 Dec 2003 Wright V. AST_05_00312112003210330 11 Dec 2003 Wright V. Victoria V., AST_05_00312032001211845 03 Dec 2001 Bull Pass AST_05_00311292000204446 29 Nov 2000 Taylor V. AST_05_00312032001211854 03 Dec 2001 Beacon V. 341 Appendix A, Table 2. Band Grescale Brescale ESUNλ B1P 0.045 -3.4 1857 B1 0.043 -4.4 1996 B2 0.028 -1.9 1807 B3 0.018 -1.3 1536 B4 0.011 -0.85 1145 B4P 0.0091 -0.65 955.8 B5P 0.0083 -1.3 452.3 B5 0.0028 -0.6 235.1 B7 0.00091 -0.21 82.38 342 Appendix A, Table 3. Image X-Pixel Y-Pixel B2 B3 B4 B5 B6 B7 B8 B9 B10 KK 1305 1238 41.645 36.579 24.868 17.312 12.394 8.750 3.116 1.455 0.372 KK 1304 1239 41.915 37.009 24.700 17.492 12.713 8.969 3.273 1.601 0.402 KK 1303 1239 42.185 36.880 24.784 17.312 12.460 8.750 3.174 1.483 0.372 KK 1303 1238 41.105 35.719 23.888 15.764 11.118 7.758 2.825 1.198 0.311 KK 1302 1238 41.375 35.676 23.188 15.566 10.843 7.658 2.576 1.164 0.300 KK 1302 1237 40.790 35.031 22.628 15.080 10.436 7.276 2.269 0.996 0.246 KK 1302 1236 40.655 34.472 22.012 14.684 10.018 6.912 2.244 0.920 0.237 KK 1301 1236 40.115 33.612 20.416 12.686 8.170 5.638 1.597 0.503 0.148 KK 1301 1235 40.295 34.042 21.312 13.154 8.599 6.157 1.879 0.657 0.165 KK 1300 1235 40.025 33.741 21.004 12.560 7.961 5.656 1.497 0.453 0.115 KK 1300 1236 39.935 33.612 20.220 12.560 7.939 5.602 1.597 0.498 0.119 KK 1299 1236 39.845 33.569 20.332 12.110 7.675 5.383 1.398 0.394 0.111 KK 1299 1237 40.700 34.816 21.760 13.712 9.094 6.475 1.962 0.755 0.185 KK 1298 1237 40.385 34.988 21.480 13.766 9.116 6.503 1.904 0.744 0.180 KK 1298 1236 40.205 33.526 20.332 12.308 7.862 5.483 1.381 0.442 0.122 KK 1297 1236 40.340 34.128 20.668 12.686 8.148 5.756 1.564 0.551 0.146 KK 1297 1237 40.925 34.945 21.704 13.838 9.050 6.357 1.862 0.761 0.189 KK 1296 1237 40.655 34.859 21.088 13.568 8.819 6.157 1.721 0.699 0.185 KK 1296 1236 40.475 34.859 20.472 13.388 8.709 6.275 1.721 0.638 0.166 KK 1296 1235 40.070 33.483 19.716 11.714 7.125 5.174 1.273 0.344 0.095 KK 1295 1235 40.160 33.612 19.296 11.930 7.466 5.220 1.215 0.391 0.099 KK 1295 1234 39.800 33.182 19.128 11.282 6.806 4.783 1.115 0.237 0.069 KK 1294 1234 40.250 33.440 19.100 11.156 6.751 4.710 1.057 0.206 0.067 KK 1692 1556 50.825 50.425 43.292 36.572 31.435 25.958 11.507 6.313 1.812 KK 1692 1557 50.690 50.425 43.180 36.374 31.259 25.849 11.681 6.285 1.799 KK 1691 1557 48.755 48.361 40.240 32.972 27.871 22.801 10.171 5.451 1.575 KK 1691 1558 49.790 48.619 39.876 32.738 27.552 22.500 10.096 5.378 1.562 KK 1690 1558 48.845 47.372 38.392 31.352 26.287 21.736 9.764 5.277 1.566 KK 1690 1559 49.565 48.619 40.660 33.548 28.454 23.492 10.727 5.608 1.623 KK 1689 1559 49.070 49.178 40.968 33.746 28.619 23.602 10.627 5.736 1.667 KK 1689 1560 48.800 47.587 39.456 32.378 27.442 22.619 10.411 5.574 1.618 KK 1688 1560 49.070 47.845 39.764 32.702 27.783 22.628 10.204 5.602 1.632 KK 1687 1560 48.080 46.340 37.496 30.002 25.231 20.881 8.610 5.174 1.519 KK 1687 1561 48.485 48.103 39.876 32.594 27.552 22.482 9.980 5.294 1.572 KK 1686 1561 47.765 45.953 37.944 31.190 26.144 21.691 9.573 5.227 1.539 KK 1686 1560 47.585 45.695 36.684 29.732 24.747 20.207 8.984 4.762 1.395 KK 1686 1559 47.360 46.082 36.712 29.300 23.999 19.434 8.785 4.448 1.306 KK 1685 1559 46.730 44.319 34.304 26.744 21.007 17.031 7.332 3.956 1.145 KK 1685 1560 46.055 44.405 34.444 27.410 22.503 18.333 7.921 4.216 1.203 343 KK 1684 1560 46.505 43.674 33.716 25.844 20.501 16.585 7.282 3.681 1.079 KK 1684 1559 46.505 43.330 33.660 25.880 20.666 16.995 7.515 4.180 1.228 KK 1683 1559 46.055 42.513 32.624 24.674 19.709 15.857 6.859 3.818 1.144 KK 1683 1560 45.830 43.244 33.184 25.826 20.710 16.777 7.282 3.883 1.138 KK 1682 1560 44.480 41.567 31.672 23.828 18.279 14.283 5.846 3.090 0.959 KK 1682 1559 44.570 41.309 30.468 22.424 17.333 13.901 5.797 3.202 0.998 KK 1682 1560 44.480 41.567 31.672 23.828 18.279 14.283 5.846 3.090 0.959 KK 1681 1560 42.950 38.729 27.528 19.184 14.033 10.989 4.327 2.340 0.756 KK 1681 1561 42.635 37.912 26.800 18.626 13.032 9.879 3.738 1.763 0.537 KK 1680 1561 42.275 37.224 25.512 17.348 12.097 9.333 3.398 1.847 0.580 KK 1680 1562 43.085 37.525 25.596 17.168 11.833 8.860 3.257 1.508 0.480 KK 1679 1562 43.130 37.912 25.932 17.510 12.471 9.524 3.431 1.769 0.554 KK 1679 1563 42.275 37.310 25.820 17.492 12.449 9.378 3.514 1.704 0.536 KK 1678 1563 41.420 36.149 23.748 15.620 10.205 7.758 2.634 1.116 0.355 KK 1678 1564 40.475 34.558 21.648 13.262 8.159 5.984 1.671 0.677 0.234 KK 1677 1564 40.295 33.827 20.584 12.182 6.960 5.001 1.074 0.397 0.108 KK 1677 1563 40.430 34.988 21.648 13.370 8.071 5.729 1.746 0.582 0.152 KK 1676 1563 40.115 34.386 20.808 11.750 7.268 4.983 1.464 0.366 0.098 KK 1676 1564 39.935 34.085 20.416 11.822 6.927 4.810 1.190 0.332 0.094 KK 1675 1564 39.665 33.655 20.304 12.092 6.905 4.701 1.256 0.321 0.087 KK 1675 1563 39.980 34.214 20.640 12.146 6.993 4.892 1.339 0.310 0.087 KK 1674 1563 40.160 34.386 20.584 12.236 6.872 4.783 1.373 0.321 0.088 KK 1674 1564 40.070 33.827 20.360 11.930 6.806 4.683 1.306 0.282 0.082 KK 1673 1564 40.295 34.042 20.332 11.948 6.861 4.737 1.232 0.304 0.080 KK 1673 1563 40.250 34.386 20.472 12.506 7.235 4.956 1.232 0.307 0.088 KK 1672 1563 40.250 34.601 20.640 12.326 7.301 4.983 1.323 0.327 0.087 KK 1672 1564 40.340 34.386 20.780 12.470 7.312 5.001 1.240 0.335 0.088 KK 1106 1912 40.925 35.805 25.540 18.644 14.253 10.661 3.531 1.657 0.476 KK 1105 1912 40.430 35.805 24.980 18.554 14.110 10.798 3.738 1.704 0.484 KK 1105 1911 39.575 35.074 23.580 17.294 12.603 9.396 3.174 1.366 0.404 KK 1105 1910 39.170 34.214 22.544 16.394 11.877 8.805 2.858 1.262 0.367 KK 1104 1910 39.755 34.386 23.020 16.412 12.108 8.887 2.991 1.209 0.343 KK 1104 1911 40.025 35.375 23.888 17.348 12.603 9.669 3.165 1.374 0.384 KK 1104 1912 40.520 35.848 24.896 18.176 13.736 10.316 3.605 1.609 0.463 KK 1104 1913 39.935 35.461 24.784 18.734 14.231 10.598 3.730 1.811 0.519 KK 1103 1913 40.115 35.332 24.280 17.942 13.527 10.124 3.697 1.716 0.474 KK 1103 1912 40.115 35.074 23.692 17.258 13.197 9.933 3.290 1.528 0.434 KK 1103 1911 38.990 34.085 22.236 15.512 11.437 8.477 2.734 1.150 0.325 KK 1103 1910 37.910 32.451 20.444 14.198 10.051 7.349 2.410 0.887 0.260 KK 1102 1910 37.100 31.333 18.876 12.434 7.983 5.884 1.705 0.582 0.162 KK 1102 1911 37.820 32.537 20.724 13.928 9.567 7.176 2.161 0.848 0.237 344 KK 1102 1912 38.945 33.397 22.012 15.710 11.415 8.659 2.867 1.265 0.369 KK 1102 1913 39.755 34.945 23.356 16.628 12.680 9.497 3.190 1.464 0.426 KK 1101 1913 39.125 34.472 22.516 15.818 11.602 8.541 2.709 1.167 0.339 KK 1101 1912 38.180 33.182 21.004 14.234 10.150 7.449 2.360 0.898 0.261 KK 1101 1911 37.955 32.494 20.024 12.866 9.072 6.694 2.003 0.708 0.205 KK 1101 1910 37.370 31.505 18.736 11.660 7.631 5.593 1.680 0.498 0.148 KK 1101 1909 37.100 30.989 17.896 10.994 6.861 4.901 1.339 0.304 0.098 KK 1100 1909 36.920 30.989 17.924 10.706 6.894 4.947 1.273 0.299 0.080 KK 1100 1908 36.830 31.075 17.896 10.814 6.553 4.737 1.356 0.282 0.086 KK 1099 1908 36.515 30.559 17.616 10.040 6.542 4.674 1.173 0.254 0.078 KK 1099 1907 36.920 30.989 17.756 10.526 6.575 4.646 1.124 0.243 0.074 KK 1098 1907 36.290 30.688 17.756 10.310 6.553 4.683 1.273 0.268 0.078 KK 1098 1906 36.425 30.473 17.532 10.562 6.542 4.746 1.124 0.268 0.073 P1 1660 1522 68.150 62.508 52.112 42.314 35.230 28.170 11.889 6.624 2.091 P1 1659 1522 68.015 61.605 50.572 40.892 33.932 27.524 11.598 6.375 1.985 P1 1659 1523 68.465 61.906 51.272 41.432 34.251 27.433 11.532 6.369 2.018 P1 1658 1523 66.890 60.229 48.220 38.372 31.424 25.340 10.171 5.641 1.798 P1 1658 1524 67.565 60.745 48.472 38.318 31.479 25.576 10.569 5.700 1.813 P1 1657 1524 66.710 59.154 46.876 36.500 29.565 23.875 9.507 4.978 1.583 P1 1657 1525 65.900 59.068 45.700 35.222 28.663 23.074 9.249 4.913 1.559 P1 1656 1525 65.810 57.778 45.084 34.520 27.486 21.873 8.452 4.376 1.392 P1 1656 1526 65.135 57.778 44.272 33.656 26.837 21.590 8.552 4.381 1.384 P1 1655 1526 65.090 57.305 44.580 33.440 26.089 20.617 7.697 3.984 1.261 P1 1655 1527 65.180 57.176 42.592 31.856 24.956 19.707 7.457 3.743 1.187 P1 1655 1528 64.505 57.090 42.144 31.082 23.889 18.897 6.942 3.502 1.102 P1 1654 1528 64.010 55.499 40.212 29.300 21.986 17.040 6.137 2.976 0.906 P1 1654 1529 63.020 54.209 38.532 27.374 20.314 15.712 5.597 2.642 0.814 P1 1654 1530 62.525 53.607 37.328 26.312 19.522 15.084 5.315 2.357 0.730 P1 1653 1530 61.265 52.231 35.732 24.602 17.674 13.755 4.701 2.049 0.655 P1 1653 1531 61.175 51.070 34.584 23.360 16.640 12.736 4.211 1.780 0.555 P1 1653 1532 60.905 50.425 32.848 21.560 14.803 11.244 3.497 1.424 0.437 P1 1653 1533 59.915 48.877 31.140 19.544 12.889 9.569 2.759 0.915 0.285 P1 1652 1533 58.970 48.533 29.852 18.302 11.756 8.778 2.427 0.752 0.220 P1 1652 1534 58.340 47.673 28.704 17.510 10.799 7.931 2.028 0.531 0.150 P1 1651 1534 58.160 48.318 28.872 17.456 10.777 7.968 2.053 0.489 0.139 P1 1651 1535 58.835 47.673 28.536 16.970 10.425 7.813 1.763 0.442 0.107 P1 1651 1536 58.295 46.899 28.004 16.574 10.084 7.558 1.771 0.383 0.115 P1 1650 1536 58.250 47.157 28.396 16.790 10.425 7.677 1.788 0.433 0.132 P1 1650 1537 58.025 47.286 28.396 16.808 10.271 7.549 1.713 0.397 0.122 P1 1649 1537 58.340 47.243 28.676 17.042 10.546 7.758 1.721 0.439 0.146 P1 1649 1538 58.340 47.071 28.284 16.592 10.293 7.576 1.663 0.402 0.128 345 P1 1649 1539 57.800 46.598 27.808 16.448 10.051 7.349 1.746 0.391 0.109 P1 1648 1539 58.115 46.727 27.780 16.538 10.150 7.413 1.713 0.402 0.127 P1 1648 1540 57.980 46.598 27.724 16.430 10.117 7.449 1.829 0.380 0.119 P1 1647 1540 57.980 46.899 28.004 16.574 10.194 7.449 1.788 0.428 0.102 P1 1647 1541 57.440 46.254 28.004 16.376 10.106 7.458 1.837 0.405 0.118 P1 1646 1541 57.665 46.727 27.724 16.286 10.095 7.476 1.572 0.422 0.099 P1 1646 1542 58.070 46.469 27.528 16.340 10.018 7.367 1.647 0.405 0.112 P1 1645 1542 56.990 45.910 27.696 16.160 9.974 7.212 1.622 0.397 0.098 P1 1367 1833 61.940 59.627 47.408 36.410 28.487 22.428 8.951 5.820 1.987 P1 1367 1834 60.815 58.208 46.008 35.384 27.706 21.809 8.826 5.683 1.968 P1 1366 1834 61.085 58.595 45.168 34.322 26.375 20.981 8.112 5.370 1.858 P1 1366 1835 60.500 57.434 44.580 34.124 26.309 20.817 8.295 5.302 1.832 P1 1365 1835 59.645 55.671 42.732 32.108 24.384 19.297 7.714 4.936 1.715 P1 1364 1835 57.980 53.564 39.568 28.706 21.810 17.159 6.477 4.222 1.499 P1 1363 1835 56.855 50.898 36.488 26.078 19.049 14.765 5.448 3.410 1.190 P1 1363 1836 55.550 50.210 35.452 24.872 18.345 14.219 5.257 3.236 1.143 P1 1362 1836 54.470 48.361 33.240 22.874 16.178 12.463 4.543 2.600 0.925 P1 1362 1837 55.280 48.318 32.344 21.866 15.705 12.108 4.327 2.502 0.888 P1 1361 1837 54.245 46.598 31.056 20.372 14.099 10.943 3.688 2.150 0.754 P1 1360 1837 53.030 45.437 29.516 18.680 12.493 9.588 3.091 1.665 0.579 P1 1360 1838 52.535 44.362 28.088 17.582 11.756 8.869 2.892 1.475 0.512 P1 1359 1838 51.860 43.846 27.108 16.430 10.777 8.050 2.460 1.153 0.412 P1 1359 1839 50.870 42.685 26.212 15.836 10.249 7.604 2.153 0.990 0.308 P1 1359 1840 50.960 42.298 25.204 14.990 9.270 7.076 2.086 0.803 0.292 P1 1359 1841 49.970 41.954 24.840 14.396 8.654 6.403 1.547 0.565 0.211 P1 1358 1841 49.970 41.008 23.916 13.838 8.159 6.048 1.663 0.506 0.162 P1 1358 1842 50.240 41.352 24.308 13.892 8.379 6.093 1.505 0.506 0.197 P1 1358 1843 50.330 41.782 24.784 14.198 8.511 6.202 1.182 0.517 0.189 P1 1358 1844 50.825 41.782 24.532 14.252 8.456 6.166 1.298 0.512 0.144 P1 1359 1844 49.610 41.610 24.672 14.090 8.533 6.166 1.431 0.503 0.142 P1 1359 1845 50.375 41.739 24.476 14.162 8.566 6.120 1.721 0.464 0.159 P1 1358 1845 50.240 41.696 24.504 14.144 8.456 6.102 1.505 0.509 0.145 P1 1357 1845 50.735 41.782 24.588 14.180 8.511 6.130 1.406 0.500 0.146 P1 1357 1846 49.880 41.696 24.532 14.072 8.324 6.111 1.489 0.481 0.139 P1 1357 1847 50.465 41.782 24.784 14.090 8.456 6.157 1.638 0.492 0.146 P1 1358 1847 50.870 41.696 24.588 14.396 8.467 6.120 1.738 0.500 0.168 P1 1358 1848 50.825 41.696 24.476 14.144 8.489 5.993 1.771 0.478 0.170 P1 1358 1849 50.420 41.309 24.308 14.018 8.412 6.093 1.464 0.509 0.162 P1 1357 1849 50.600 41.524 24.308 14.036 8.291 5.993 1.771 0.489 0.164 P1 1357 1850 50.285 41.438 24.280 13.946 8.456 5.957 1.705 0.492 0.150 P1 1358 1850 50.465 41.438 24.308 14.018 8.456 6.111 1.564 0.506 0.149 346 P1 1358 1851 50.240 41.567 24.560 14.252 8.467 6.184 1.680 0.470 0.136 P1 1359 1851 50.600 40.750 24.924 14.324 8.599 6.148 1.464 0.475 0.157 P1 1360 1851 50.915 41.782 24.364 14.180 8.357 6.066 1.514 0.433 0.167 P1 1360 1852 50.105 41.524 24.504 14.072 8.456 5.993 1.464 0.416 0.169 P1 1359 1852 50.240 41.266 24.616 14.126 8.511 6.039 1.373 0.478 0.153 P1 1358 1852 50.510 40.406 24.728 14.018 8.511 5.911 1.564 0.492 0.135 P1 1358 1853 50.150 40.664 24.140 14.054 8.434 5.948 1.464 0.475 0.143 P1 1277 1950 57.305 52.446 38.084 27.950 20.820 16.140 6.079 3.681 1.297 P1 1277 1951 57.800 52.145 37.664 26.906 20.160 15.712 6.004 3.552 1.265 P1 1278 1951 57.440 52.747 38.056 27.302 20.666 16.403 6.328 3.726 1.263 P1 1278 1952 57.305 53.048 38.420 28.112 21.260 16.804 6.469 3.984 1.366 P1 1279 1952 59.780 56.789 43.684 32.990 25.649 20.380 8.345 4.849 1.689 P1 1279 1953 59.375 53.994 42.396 31.568 24.274 19.143 7.656 4.558 1.581 P1 1280 1953 60.905 56.617 44.132 33.170 25.770 20.398 8.079 4.994 1.760 P1 1280 1954 59.690 56.015 42.508 31.334 24.076 19.124 7.614 4.583 1.654 P1 1281 1954 61.625 58.724 46.820 35.906 28.311 22.446 9.150 5.644 1.973 P1 1281 1955 61.490 58.638 45.840 34.880 27.508 21.727 8.643 5.392 1.908 P1 1280 1955 58.790 54.811 41.388 30.650 23.581 18.415 7.166 4.278 1.547 P1 1280 1956 58.160 53.607 39.680 28.670 21.986 17.277 6.560 3.939 1.423 P1 1279 1956 57.395 53.220 39.344 28.346 21.513 16.849 6.378 3.748 1.352 P1 1279 1957 56.315 51.500 36.936 26.042 19.357 15.220 5.730 3.320 1.210 P1 1278 1957 55.280 48.834 33.464 22.748 16.101 12.691 4.618 2.486 0.896 P1 1278 1958 53.570 47.028 31.896 20.930 14.979 11.635 3.813 2.091 0.709 P1 1277 1958 52.580 45.265 29.488 19.580 13.219 10.325 3.448 1.878 0.616 P1 1277 1959 51.140 43.115 26.548 15.818 9.853 7.331 1.846 0.803 0.262 P1 1276 1959 50.375 41.825 24.868 14.594 8.951 6.666 1.746 0.506 0.190 P1 1276 1958 51.095 42.341 26.380 16.088 9.996 7.422 1.854 0.904 0.323 P1 1276 1957 51.680 43.889 28.956 18.464 12.482 9.533 3.116 1.427 0.449 P1 1275 1957 51.095 42.771 25.848 15.620 9.644 7.276 2.211 0.806 0.241 P1 1275 1958 50.510 40.879 25.120 14.720 9.050 6.594 1.862 0.556 0.166 P1 1275 1957 51.095 42.771 25.848 15.620 9.644 7.276 2.211 0.806 0.241 P1 1274 1957 50.105 41.825 25.008 14.630 9.061 6.666 1.622 0.671 0.193 P1 1274 1958 50.240 41.524 24.924 14.432 8.863 6.475 1.821 0.548 0.170 P1 1274 1957 50.105 41.825 25.008 14.630 9.061 6.666 1.622 0.671 0.193 P1 1273 1957 50.375 41.610 24.588 14.450 8.797 6.512 1.688 0.534 0.166 P1 1273 1958 50.510 42.040 24.672 14.288 8.973 6.512 1.588 0.551 0.179 P1 1273 1959 50.825 41.739 24.868 14.486 8.830 6.466 1.680 0.542 0.177 P1 1272 1959 50.195 41.395 24.588 14.414 8.764 6.430 1.622 0.534 0.158 P1 1272 1960 49.835 41.266 24.532 14.360 8.731 6.348 1.647 0.573 0.157 P1 1273 1960 50.510 41.438 24.812 14.576 8.819 6.321 1.738 0.512 0.148 P1 1273 1961 50.060 40.535 24.840 14.486 8.775 6.439 1.572 0.503 0.172 347 P1 1274 1961 50.600 41.567 24.784 14.360 8.742 6.357 1.547 0.495 0.162 P1 1274 1962 50.645 41.997 24.868 14.288 8.687 6.302 1.638 0.475 0.144 P1 1273 1962 50.465 41.438 24.896 14.324 8.621 6.403 1.497 0.461 0.179 P1 1274 1962 50.645 41.997 24.868 14.288 8.687 6.302 1.638 0.475 0.144 P1 1275 1962 50.870 41.739 24.784 14.522 8.786 6.439 1.597 0.481 0.156 P1 1275 1963 51.365 42.255 24.812 14.234 8.643 6.284 1.439 0.461 0.151 P1 1276 1963 50.420 42.298 24.952 14.396 8.797 6.393 1.422 0.470 0.155 KG 2562 1503 49.097 42.528 30.801 22.911 17.200 13.498 4.821 2.262 0.758 KG 2563 1503 50.042 45.108 34.245 26.583 19.982 15.627 6.099 2.996 0.943 KG 2564 1503 49.997 45.108 34.021 26.277 20.016 15.754 5.825 2.755 0.911 KG 2565 1503 47.297 40.335 26.797 18.429 12.349 9.093 2.937 1.016 0.408 KG 2566 1503 45.407 37.368 22.401 13.641 8.543 6.354 1.750 0.367 0.168 KG 2567 1503 45.182 36.465 21.729 13.011 8.146 6.136 1.418 0.314 0.147 KG 2568 1503 44.912 37.067 21.953 13.101 8.191 6.136 1.492 0.308 0.127 KG 2569 1503 45.272 36.852 22.121 13.119 8.333 6.181 1.467 0.280 0.159 KG 2570 1503 45.092 37.153 22.037 13.209 8.191 6.172 1.227 0.280 0.150 KG 2571 1503 45.497 36.895 22.009 13.155 8.179 6.081 1.484 0.288 0.149 KG 2572 1503 45.497 36.852 22.009 13.173 8.224 6.163 1.625 0.283 0.145 KG 2573 1503 45.182 36.852 22.009 13.389 8.257 6.245 1.716 0.302 0.147 KG 2574 1503 44.867 36.637 21.953 13.389 8.224 6.218 1.609 0.322 0.162 KG 2574 1502 45.137 36.594 21.981 13.641 8.323 6.272 1.725 0.344 0.156 KG 2573 1502 44.822 36.852 21.813 13.155 8.036 6.099 1.609 0.283 0.145 KG 2572 1502 45.542 36.981 21.897 13.119 8.158 6.145 1.418 0.258 0.149 KG 2571 1502 45.632 37.368 21.925 13.245 8.234 6.181 1.227 0.297 0.151 KG 2570 1502 45.317 37.153 21.981 13.245 8.201 6.245 1.061 0.314 0.159 KG 2569 1502 45.227 36.637 21.981 13.119 8.113 6.145 1.393 0.300 0.110 KG 2568 1502 45.182 37.067 22.121 13.389 8.411 6.327 1.517 0.353 0.112 KG 2567 1502 46.037 37.798 23.353 14.343 9.059 6.654 1.907 0.456 0.232 KG 2566 1502 46.982 40.249 27.245 18.825 12.854 9.466 3.011 1.131 0.438 KG 2565 1502 48.827 43.173 31.193 23.559 17.827 13.716 4.821 2.260 0.800 KG 2564 1502 51.167 47.129 36.653 28.905 22.336 17.738 6.904 3.464 1.107 KG 2563 1502 50.312 45.237 34.077 26.169 20.126 15.818 6.223 3.058 0.992 KG 2562 1502 49.232 42.872 30.857 22.263 15.891 12.633 4.696 2.282 0.756 KG 2562 1501 48.917 42.528 30.129 21.705 16.176 12.779 4.746 2.139 0.738 KG 2563 1501 50.042 44.807 33.153 25.089 19.322 15.281 5.684 2.862 0.977 KG 2564 1501 50.267 45.667 35.029 27.123 21.016 16.655 6.688 3.346 1.090 KG 2565 1501 49.772 44.936 34.329 25.827 19.707 15.509 6.066 2.982 0.979 KG 2566 1501 49.367 43.087 31.417 23.055 17.089 13.215 4.538 2.170 0.740 KG 2567 1501 47.702 41.109 28.561 20.463 14.669 11.041 3.509 1.456 0.550 KG 2568 1501 46.712 39.131 24.921 16.233 10.413 7.637 2.414 0.647 0.285 KG 2569 1501 45.632 37.540 22.877 14.055 8.807 6.618 1.833 0.398 0.185 348 KG 2570 1501 45.497 37.411 22.233 13.425 8.366 6.172 1.443 0.316 0.095 KG 2571 1501 45.767 36.809 21.981 13.155 8.146 6.181 1.252 0.302 0.102 KG 2572 1501 45.317 36.895 21.953 13.245 8.125 6.127 1.534 0.300 0.158 KG 2573 1501 45.227 37.110 21.869 13.137 7.981 6.045 1.509 0.274 0.142 KG 2574 1501 45.362 37.196 21.785 13.137 8.234 6.145 1.526 0.288 0.160 KG 2575 1501 45.137 36.852 22.065 13.407 8.300 6.281 1.750 0.311 0.161 KG 2575 1500 45.137 36.981 22.177 13.533 8.300 6.299 1.550 0.325 0.166 KG 2574 1500 45.542 36.938 21.897 13.137 8.158 6.108 1.658 0.266 0.159 KG 2573 1500 45.407 37.067 21.981 13.155 8.003 6.172 1.858 0.252 0.131 KG 2572 1500 44.957 37.067 22.009 13.209 8.224 6.208 1.542 0.294 0.042 KG 2571 1500 45.632 37.712 22.989 14.037 8.642 6.472 1.633 0.389 -0.010 KG 2570 1500 45.767 39.088 23.969 15.549 10.038 7.564 2.389 0.689 0.252 KG 2569 1500 46.397 38.787 25.341 16.629 11.028 8.274 2.397 0.854 0.348 KG 2568 1500 47.747 40.550 27.553 18.717 13.427 10.513 3.451 1.434 0.496 KG 2567 1500 48.692 42.786 30.465 22.317 16.506 12.724 4.588 2.114 0.715 KG 2566 1500 49.772 44.850 33.321 24.855 18.575 14.662 5.609 2.649 0.846 KG 2565 1500 50.357 45.194 34.273 25.899 19.696 15.618 5.875 2.920 0.953 KG 2564 1500 50.582 45.968 35.001 26.853 20.192 15.700 6.157 3.080 1.002 KG 2564 1499 50.807 46.054 34.553 27.339 21.610 16.965 6.638 3.270 1.109 KG 2565 1499 50.267 45.237 34.525 26.709 20.379 15.955 6.049 3.108 1.029 KG 2566 1499 49.502 45.108 33.517 25.449 18.860 14.926 5.435 2.794 0.913 KG 2567 1499 49.097 43.302 31.025 22.551 16.484 12.815 4.696 2.204 0.725 KG 2568 1499 47.702 41.539 28.113 19.239 13.954 10.722 3.617 1.526 0.541 KG 2569 1499 47.387 40.980 27.441 18.843 12.800 10.058 3.235 1.389 0.457 KG 2570 1499 47.657 39.303 25.817 17.493 12.349 9.366 2.920 1.042 0.418 KG 2571 1499 46.487 38.658 25.285 16.989 11.722 8.920 2.779 1.000 0.367 KG 2572 1499 46.577 39.604 26.069 17.277 10.995 8.047 2.223 0.711 0.146 KG 2573 1499 45.407 37.927 22.485 13.389 8.290 6.281 1.617 0.330 0.034 KG 2574 1499 44.957 37.153 21.869 13.011 8.158 6.117 1.725 0.269 0.159 KG 2575 1499 45.992 37.325 22.205 13.407 8.311 6.309 1.517 0.328 0.169 KG 2576 1499 45.677 36.981 22.009 13.371 8.191 6.208 1.401 0.314 0.151 KG 2576 1498 44.867 37.153 21.925 13.389 8.378 6.281 1.509 0.322 0.167 KG 2575 1498 45.452 36.809 22.261 13.461 8.389 6.263 1.418 0.367 0.136 KG 2574 1498 46.262 38.056 23.269 14.469 8.630 6.345 1.584 0.370 0.027 KG 2573 1498 47.882 41.797 30.885 22.713 15.846 11.741 3.883 1.604 0.465 KG 2572 1498 47.837 41.281 28.645 20.931 15.561 12.396 4.331 2.044 0.673 KG 2571 1498 46.487 38.357 23.577 14.307 9.533 7.555 2.273 0.748 0.290 KG 2570 1498 45.992 39.389 25.537 17.043 11.326 8.529 2.746 1.098 0.383 KG 2569 1498 47.657 40.851 27.189 19.023 13.394 10.458 3.376 1.414 0.492 KG 2568 1498 48.017 41.539 28.925 20.409 14.637 11.459 3.908 1.747 0.589 KG 2567 1498 48.827 42.743 31.333 22.911 16.891 13.270 4.721 2.313 0.776 349 KG 2567 1497 49.142 43.646 31.137 22.533 16.980 13.106 4.804 2.226 0.746 KG 2568 1497 48.332 42.442 29.597 21.003 15.461 11.951 3.916 1.879 0.649 KG 2569 1497 47.792 41.066 27.889 19.113 13.207 10.203 3.318 1.534 0.517 KG 2570 1497 46.442 39.518 25.453 16.953 12.040 9.503 2.995 1.126 0.400 KG 2571 1497 46.397 39.776 26.489 18.069 12.172 9.111 2.970 1.064 0.402 KG 2572 1497 49.142 42.184 28.113 18.915 12.712 9.666 3.459 1.378 0.469 KG 2573 1497 50.177 44.291 32.649 24.063 18.091 14.189 5.294 2.400 0.850 KG 2574 1497 47.972 41.625 30.409 22.281 15.429 11.741 4.074 1.814 0.634 KG 2575 1497 46.532 39.045 24.697 15.675 9.698 7.109 1.866 0.546 0.044 KG 2576 1497 45.182 37.239 22.429 13.659 8.620 6.454 1.642 0.378 0.038 KG 2577 1497 44.867 37.153 22.289 13.389 8.521 6.299 1.750 0.305 0.168 KG 2578 1497 45.767 37.368 21.925 13.227 8.201 6.218 1.526 0.325 0.152 KG 1828 1874 54.200 48.748 34.696 26.654 20.655 15.776 5.846 2.760 0.756 KG 1828 1875 54.110 49.651 35.844 28.328 21.887 16.786 6.461 3.068 0.810 KG 1827 1875 54.380 49.092 35.704 27.590 21.326 16.021 6.037 2.917 0.803 KG 1827 1876 53.975 48.662 34.948 27.140 21.084 15.766 5.987 2.816 0.772 KG 1826 1876 53.615 48.576 34.752 26.528 20.237 15.157 5.813 2.757 0.772 KG 1826 1877 54.605 49.092 35.256 27.140 20.963 15.921 5.954 2.861 0.818 KG 1825 1877 54.155 49.178 35.732 27.734 21.040 15.703 6.162 2.998 0.901 KG 1825 1878 53.570 49.092 34.556 26.672 20.721 15.776 5.863 2.808 0.856 KG 1824 1878 53.165 48.232 33.632 25.088 18.290 13.755 5.373 2.581 0.779 KG 1824 1879 53.525 47.501 32.904 23.936 17.652 13.200 4.759 2.320 0.665 KG 1823 1879 56.045 51.371 38.588 30.164 23.086 17.486 6.842 3.426 0.816 KG 1823 1880 55.370 51.027 37.412 28.310 21.777 16.831 6.178 3.118 0.914 KG 1822 1880 55.370 50.941 37.524 29.678 22.690 17.386 6.693 3.278 0.927 KG 1822 1881 55.190 50.511 37.328 28.526 22.008 16.777 6.029 3.018 0.830 KG 1821 1881 53.165 47.630 33.100 24.926 18.675 14.056 5.033 2.424 0.726 KG 1821 1882 53.660 48.060 33.548 24.764 18.235 13.810 4.875 2.318 0.617 KG 1820 1882 53.300 48.189 33.744 24.998 18.290 13.501 4.676 2.351 0.642 KG 1820 1883 53.660 47.931 32.680 23.684 17.355 12.782 4.311 2.071 0.599 KG 1819 1883 52.625 47.458 32.372 23.288 17.014 12.536 4.477 2.150 0.579 KG 1819 1884 52.805 46.770 32.064 23.360 16.816 12.500 4.253 2.032 0.561 KG 1818 1884 53.525 47.587 33.212 24.692 18.026 13.619 4.875 2.390 0.658 KG 1818 1885 53.345 47.157 32.232 22.982 16.134 11.799 4.178 1.892 0.505 KG 1817 1885 52.355 46.426 30.720 21.668 14.880 11.053 3.531 1.662 0.468 KG 1817 1886 50.825 43.760 26.856 16.556 10.579 7.613 2.236 0.755 0.220 KG 1816 1886 51.140 43.373 25.960 16.052 9.809 7.131 1.887 0.649 0.181 KG 1816 1887 50.195 42.298 24.448 14.090 8.368 5.784 1.489 0.338 0.062 KG 1815 1887 50.510 43.889 27.108 17.222 10.755 7.413 2.302 0.817 0.118 KG 1815 1888 51.185 43.631 26.492 16.862 11.140 7.922 2.261 0.769 0.147 KG 1814 1888 50.960 43.717 26.632 16.700 10.568 7.549 2.244 0.769 0.082 350 KG 1814 1889 50.465 43.244 25.540 15.638 9.710 6.794 1.796 0.540 0.129 KG 1813 1889 49.835 42.169 24.504 14.360 8.555 5.857 1.547 0.363 -0.005 KG 1813 1890 49.835 42.040 24.028 13.838 8.225 5.647 1.273 0.282 0.066 KG 1812 1890 49.880 42.470 24.028 13.928 8.170 5.593 1.414 0.304 -0.042 KG 1812 1891 49.610 41.696 24.000 13.928 8.027 5.629 1.190 0.251 0.078 KG 1811 1891 49.385 41.825 24.112 13.874 8.049 5.520 1.306 0.279 -0.036 KG 1811 1892 49.475 41.395 23.608 13.640 7.895 5.493 1.165 0.248 0.058 KG 1810 1892 49.745 41.094 23.580 13.586 7.928 5.474 1.223 0.246 -0.013 KG 1810 1893 49.250 41.309 23.356 13.478 7.950 5.456 1.198 0.229 0.057 KG 1809 1893 49.745 41.567 23.496 13.352 7.785 5.402 1.248 0.218 0.039 KG 1809 1894 49.385 41.094 23.552 13.514 7.785 5.447 1.256 0.232 0.073 KG 1808 1894 49.565 40.750 23.412 13.316 7.719 5.256 1.182 0.226 0.063 KG 1808 1895 49.250 40.836 23.244 13.298 7.763 5.356 1.323 0.229 0.065 KG 1807 1895 49.160 41.567 23.468 13.388 7.763 5.429 0.900 0.243 0.060 KG 1807 1896 50.240 41.739 23.720 13.586 7.961 5.502 1.323 0.246 0.070 KG 1806 1896 50.195 42.169 23.720 13.730 7.829 5.411 1.223 0.220 0.070 KG 1806 1897 50.195 41.825 23.776 13.766 8.082 5.474 1.348 0.246 0.074 KG 1805 1897 50.330 42.126 23.748 13.730 7.950 5.493 1.157 0.237 0.079 KG 1805 1898 49.790 41.868 24.560 14.180 8.214 5.647 1.240 0.268 0.088 KG 936 1724 52.490 46.211 32.596 25.358 19.115 14.456 5.689 3.144 0.889 KG 937 1724 52.715 46.297 32.148 24.728 18.697 14.128 5.572 2.973 0.840 KG 938 1724 52.085 45.695 31.336 23.324 16.893 12.782 4.801 2.486 0.711 KG 939 1724 51.680 45.437 30.328 22.784 15.881 11.872 4.361 2.253 0.658 KG 940 1724 51.455 45.136 30.356 22.388 16.167 11.935 4.361 2.287 0.637 KG 941 1724 51.590 45.265 30.636 23.036 16.497 12.281 4.527 2.379 0.657 KG 942 1724 52.040 45.609 31.168 23.882 16.387 12.163 4.552 2.281 0.665 KG 943 1724 51.860 45.652 30.524 22.946 16.134 11.826 4.278 2.150 0.624 KG 944 1724 52.400 45.824 30.524 22.190 15.903 11.781 4.261 2.166 0.635 KG 945 1724 51.950 45.093 29.992 21.776 15.782 11.762 4.186 2.122 0.601 KG 946 1724 51.905 44.534 28.928 19.940 14.165 10.589 3.489 1.713 0.462 KG 947 1724 49.790 42.298 24.728 14.684 9.149 6.703 2.012 0.724 0.232 KG 948 1724 49.295 41.395 23.608 14.054 8.148 5.929 1.489 0.391 0.125 KG 949 1724 49.385 41.051 23.524 13.784 8.071 5.638 1.265 0.318 0.095 KG 950 1724 49.250 41.051 23.692 13.856 7.950 5.675 1.356 0.318 0.108 KG 951 1724 49.565 41.653 23.664 13.802 7.950 5.684 1.323 0.304 0.097 KG 952 1724 49.205 41.438 23.720 13.892 7.796 5.675 1.281 0.293 0.069 KG 952 1725 48.845 41.653 23.804 14.144 7.884 5.738 1.323 0.310 0.105 KG 953 1725 49.430 41.352 23.692 13.694 7.983 5.629 1.348 0.307 0.100 KG 953 1726 49.430 41.438 24.112 14.216 8.082 5.793 1.198 0.271 0.078 KG 952 1726 49.070 41.438 23.552 13.982 7.983 5.784 1.339 0.288 0.102 KG 951 1726 49.295 41.567 24.028 13.820 8.071 5.775 1.348 0.310 0.115 351 KG 950 1726 49.340 41.653 24.280 13.766 7.983 5.738 1.223 0.260 0.091 KG 949 1726 49.115 41.782 23.972 13.748 7.994 5.738 1.223 0.285 0.090 KG 948 1726 49.475 41.653 24.000 13.928 8.082 5.802 1.422 0.346 0.136 KG 947 1726 49.385 41.266 23.860 14.522 8.071 5.738 1.422 0.344 0.129 KG 946 1726 49.295 41.180 24.112 15.296 8.093 5.802 1.290 0.341 0.111 KG 945 1726 49.475 41.911 24.840 15.422 9.204 6.721 1.846 0.643 0.209 KG 944 1726 50.870 43.932 27.724 18.932 12.812 9.469 3.124 1.469 0.394 KG 943 1726 52.085 45.738 30.860 22.982 16.156 11.926 4.244 2.122 0.578 KG 942 1726 51.635 45.867 31.196 23.306 16.442 12.208 4.485 2.245 0.644 KG 941 1726 51.590 45.480 30.552 22.586 16.475 12.399 4.502 2.340 0.662 KG 940 1726 51.815 45.480 30.636 23.072 16.387 12.217 4.518 2.346 0.651 KG 939 1726 51.365 45.222 30.440 23.342 16.189 11.990 4.419 2.304 0.661 KG 938 1726 51.815 46.168 31.560 23.594 17.586 13.164 5.025 2.693 0.754 KG 937 1726 52.085 46.426 32.036 24.818 18.455 13.946 5.548 2.953 0.837 KG 936 1726 52.265 46.340 31.980 25.448 18.510 13.910 5.498 3.029 0.844 KG 935 1726 52.760 46.727 32.792 25.538 19.236 14.520 5.631 3.104 0.875 KG 934 1726 52.760 46.942 33.324 26.096 19.841 14.902 5.821 3.194 0.901 KG 934 1727 52.715 47.028 33.324 26.348 19.841 14.893 5.738 3.149 0.877 KG 933 1727 52.715 47.286 33.408 26.384 20.105 14.929 5.896 3.177 0.886 KG 933 1728 52.850 46.899 33.380 26.816 19.907 14.784 5.813 3.127 0.865 KG 1071 1982 45.290 39.546 26.688 19.922 15.221 11.171 4.062 2.169 0.571 KG 1071 1983 45.830 39.202 26.604 19.886 15.067 11.153 4.153 2.248 0.595 KG 1071 1984 45.290 39.761 26.940 20.426 15.617 11.963 4.469 2.483 0.674 KG 1071 1985 45.650 39.890 27.500 20.930 16.541 12.563 4.892 2.822 0.766 KG 1070 1985 45.380 39.417 26.492 19.940 15.342 11.508 4.394 2.410 0.667 KG 1070 1984 45.020 38.729 26.660 19.544 15.221 11.508 4.336 2.348 0.634 KG 1070 1983 44.705 39.202 26.856 20.030 15.265 11.235 4.195 2.278 0.600 KG 1069 1983 44.750 39.417 25.904 19.526 14.627 10.889 4.103 2.158 0.573 KG 1069 1984 44.795 38.643 25.428 18.770 13.956 10.397 3.697 1.984 0.527 KG 1069 1985 44.705 37.955 24.644 17.852 12.350 9.260 3.431 1.716 0.477 KG 1068 1985 43.400 36.106 22.012 13.334 9.534 6.930 1.929 0.850 0.236 KG 1068 1984 43.895 37.267 23.048 15.638 10.656 7.840 2.634 1.240 0.318 KG 1067 1984 43.355 35.848 20.920 12.254 8.060 5.766 1.688 0.512 0.132 KG 1067 1985 43.130 35.375 20.360 11.714 7.345 5.411 1.422 0.344 0.088 KG 1067 1986 42.680 35.031 20.248 10.202 7.323 5.238 1.339 0.352 0.088 KG 1067 1987 42.725 35.332 20.136 11.966 7.367 5.383 1.348 0.341 0.089 KG 1067 1988 42.455 35.375 20.220 11.858 7.356 5.329 1.356 0.335 0.096 KG 1066 1988 42.410 35.418 20.248 12.110 7.323 5.356 1.422 0.332 0.093 KG 1066 1987 42.860 35.418 20.416 11.912 7.367 5.320 1.331 0.341 0.089 KG 1066 1986 42.815 35.461 20.332 11.534 7.345 5.283 1.339 0.355 0.089 KG 1065 1986 42.905 35.633 20.528 12.236 7.246 5.320 1.331 0.318 0.097 352 KG 1065 1987 42.815 35.504 20.528 12.470 7.411 5.101 1.281 0.324 0.086 KG 1065 1988 42.725 35.289 20.360 12.380 7.312 5.229 1.414 0.307 0.091 KG 1064 1988 42.635 35.719 20.388 12.632 7.323 5.210 1.281 0.324 0.086 KG 1064 1987 43.175 35.848 20.472 12.182 7.389 5.229 1.339 0.316 0.087 KG 1063 1987 42.545 35.590 20.584 12.416 7.356 5.265 1.256 0.313 0.084 KG 1063 1988 42.995 35.418 20.528 12.290 7.389 5.201 1.290 0.313 0.078 KG 1063 1989 42.365 35.289 20.444 12.398 7.235 5.165 1.298 0.335 0.071 KG 1062 1989 42.590 35.418 20.472 12.290 7.455 5.320 1.248 0.352 0.082 KG 1062 1988 42.860 35.461 20.360 12.164 7.345 5.365 1.364 0.313 0.081 KG 1061 1988 43.085 35.891 20.360 12.164 7.246 5.265 1.281 0.299 0.073 KG 1061 1989 42.590 35.418 20.388 12.092 7.356 5.301 1.431 0.338 0.070 KG 1061 1990 42.635 35.461 20.668 12.722 7.642 5.538 1.522 0.436 0.108 KG 1060 1990 42.455 35.160 20.612 12.146 7.455 5.311 1.306 0.344 0.088 KG 1060 1991 42.410 35.246 20.192 11.948 7.290 5.138 1.232 0.324 0.078 KG 1060 1992 42.050 35.117 20.332 11.804 7.202 5.174 1.348 0.346 0.089 KG 1059 1992 42.320 35.332 20.192 12.020 7.048 5.156 1.265 0.302 0.093 KG 1059 1993 42.725 35.762 20.976 13.118 7.983 5.957 1.813 0.545 0.143 KG 1058 1993 43.310 36.708 22.404 15.116 10.777 7.986 2.576 1.184 0.337 KG 1057 1993 44.345 38.041 25.176 17.816 13.186 9.924 3.439 1.878 0.504 KG 1057 1992 44.435 38.041 24.784 17.726 13.032 9.642 3.390 1.688 0.457 KG 1057 1991 44.480 38.385 24.644 16.988 12.724 9.378 3.207 1.643 0.429 KG 1056 1991 44.435 38.643 26.100 18.734 14.275 10.325 3.838 2.043 0.503 KG 1056 1992 44.345 38.772 26.072 18.878 14.605 10.962 3.846 2.077 0.573 KG 1056 1993 44.390 38.170 24.924 18.086 12.768 9.906 3.564 1.833 0.517 KG 1056 1994 43.670 36.794 23.272 15.260 11.206 8.177 2.676 1.450 0.407 KG 1055 1994 42.635 35.676 20.612 12.470 7.851 5.857 1.572 0.478 0.170 KG 1055 1993 43.580 36.235 22.712 14.216 10.282 7.285 2.344 1.086 0.292 KG 1054 1993 42.545 35.289 20.220 11.588 7.411 5.329 1.414 0.321 0.121 KG 1053 1993 42.365 35.289 20.164 11.714 7.180 5.001 1.240 0.288 0.078 KG 1053 1994 42.995 34.902 20.304 11.516 7.224 5.138 1.298 0.279 0.078 KG 1053 1995 42.545 35.246 20.304 11.930 7.268 5.147 1.339 0.316 0.078 KG 1053 1996 42.545 34.988 20.108 12.020 7.290 5.119 1.331 0.307 0.085 KG 1052 1996 42.050 35.160 20.248 11.840 7.257 5.201 1.306 0.313 0.084 KG 1051 1996 42.500 35.246 20.332 11.786 7.191 5.156 1.265 0.299 0.084 KG 906 1773 49.385 41.782 26.632 18.068 12.944 9.679 3.356 1.508 0.441 KG 906 1774 48.890 42.513 26.744 18.266 12.922 9.588 3.423 1.475 0.434 KG 906 1775 48.755 41.997 26.184 17.708 12.240 9.123 2.983 1.298 0.368 KG 906 1776 48.935 41.653 25.680 17.132 11.657 8.486 2.941 1.195 0.351 KG 905 1776 48.710 40.707 24.644 16.178 10.557 7.786 2.377 0.934 0.262 KG 905 1777 48.485 40.578 24.196 15.476 9.809 7.313 2.286 0.856 0.270 KG 904 1777 47.900 40.879 24.224 15.368 9.974 6.867 2.261 0.836 0.232 353 KG 904 1776 47.900 40.621 24.168 15.296 9.831 7.258 2.269 0.853 0.260 KG 904 1775 48.035 40.707 24.532 15.890 10.128 7.649 2.510 0.951 0.306 KG 903 1775 48.530 41.137 24.924 16.088 10.546 7.768 2.402 1.010 0.274 KG 903 1776 48.170 40.664 24.196 15.440 10.205 7.376 2.385 0.926 0.283 KG 903 1777 48.350 40.922 24.504 16.016 10.711 7.940 2.427 0.948 0.282 KG 903 1778 49.025 40.879 24.784 16.538 10.612 7.931 2.560 0.926 0.291 KG 902 1778 48.170 40.191 23.636 14.828 9.314 6.776 2.053 0.657 0.184 KG 902 1779 47.675 39.761 23.132 14.018 8.731 6.330 1.804 0.565 0.166 KG 901 1779 47.765 39.675 23.552 14.792 8.907 6.557 1.970 0.702 0.223 KG 901 1780 47.855 40.062 24.000 14.990 9.490 6.666 2.028 0.685 0.224 KG 900 1780 49.115 41.868 26.324 17.438 12.460 9.651 3.033 1.452 0.441 KG 900 1781 48.395 40.191 23.804 14.396 8.940 6.148 1.896 0.545 0.169 KG 900 1782 47.495 39.417 22.768 13.388 8.126 5.820 1.580 0.411 0.109 KG 900 1783 46.910 39.116 22.628 13.424 8.027 5.911 1.580 0.425 0.123 KG 899 1783 46.820 39.159 22.516 13.280 8.005 5.793 1.505 0.386 0.109 KG 898 1783 47.180 39.245 22.600 13.334 8.104 5.820 1.597 0.433 0.121 KG 897 1783 47.090 39.460 22.432 13.316 8.104 5.857 1.588 0.428 0.131 KG 897 1784 47.045 39.073 22.348 13.226 8.115 5.784 1.597 0.388 0.121 KG 897 1785 47.315 39.331 22.376 13.532 8.027 5.811 1.481 0.411 0.120 KG 897 1786 47.405 39.460 22.824 13.712 8.621 6.266 1.804 0.514 0.159 KG 896 1786 47.405 39.503 22.936 13.892 8.379 6.139 1.671 0.478 0.139 KG 896 1787 47.135 39.675 22.964 13.856 8.720 6.330 1.896 0.554 0.153 KG 896 1788 47.135 39.245 22.572 13.496 8.005 5.756 1.489 0.400 0.112 KG 895 1788 47.405 39.589 22.656 13.658 8.313 6.139 1.705 0.484 0.136 KG 894 1788 47.540 39.288 22.600 13.586 8.236 6.011 1.680 0.447 0.140 KG 893 1788 46.910 38.987 22.432 13.316 8.016 5.665 1.555 0.405 0.103 KG 893 1787 47.135 39.159 22.712 13.316 8.049 5.829 1.655 0.428 0.105 KG 892 1787 47.090 38.987 22.516 13.244 7.950 5.784 1.580 0.414 0.114 KG 891 1787 47.135 39.030 22.460 13.298 8.005 5.738 1.530 0.405 0.101 KG 890 1787 46.910 39.030 22.460 13.424 8.082 5.747 1.580 0.405 0.101 KG 889 1787 47.000 39.073 22.600 13.406 8.137 5.693 1.638 0.425 0.107 KG 889 1788 47.405 39.030 22.600 13.478 8.049 5.747 1.406 0.402 0.106 KG 888 1788 47.180 39.245 22.628 13.442 8.181 5.702 1.588 0.461 0.133 KG 887 1788 47.360 39.202 22.824 13.496 8.280 5.875 1.630 0.470 0.139 KG 886 1788 47.450 39.288 22.656 13.352 8.346 5.957 1.597 0.461 0.134 KG 955 2220 50.735 44.448 32.008 25.358 20.237 15.202 5.697 2.903 0.804 KG 956 2220 50.330 44.061 31.560 24.818 19.115 14.320 5.406 2.721 0.763 KG 957 2220 50.060 44.319 31.924 25.142 19.423 14.647 5.398 2.735 0.749 KG 958 2220 50.555 43.975 31.364 25.178 19.555 14.229 5.307 2.768 0.762 KG 959 2220 49.745 42.599 29.348 21.452 15.749 12.308 4.352 1.970 0.542 KG 959 2219 46.910 38.858 24.336 15.980 9.776 7.294 2.493 1.058 0.242 354 KG 959 2218 46.055 36.923 21.004 12.794 7.840 5.465 1.265 0.369 0.129 KG 958 2218 47.450 39.245 24.672 16.088 10.293 7.886 2.609 1.007 0.250 KG 957 2218 48.935 41.782 27.948 20.966 15.210 10.752 3.979 1.914 0.519 KG 956 2218 49.790 43.717 31.336 23.846 18.433 14.110 5.299 2.533 0.717 KG 955 2218 50.510 43.932 31.280 25.412 19.445 14.411 5.506 2.819 0.756 KG 954 2218 50.510 44.491 32.204 25.304 19.588 14.947 5.581 2.712 0.766 KG 954 2217 50.555 43.846 31.756 24.494 18.422 14.028 5.423 2.631 0.723 KG 954 2216 49.475 41.911 29.348 22.568 16.387 11.808 4.352 2.208 0.576 KG 955 2216 46.550 38.858 23.944 15.044 10.469 8.059 2.468 0.906 0.287 KG 956 2216 45.605 36.880 21.116 12.722 7.466 5.229 1.539 0.436 0.090 KG 956 2215 45.515 36.923 20.668 12.002 7.345 5.156 1.182 0.195 0.095 KG 956 2214 45.785 36.665 20.808 12.074 7.290 5.247 1.298 0.285 0.095 KG 956 2213 45.515 36.536 20.836 12.164 7.301 5.238 1.348 0.265 0.092 KG 955 2213 45.650 36.536 20.612 12.074 7.158 5.210 1.207 0.234 0.087 KG 954 2213 45.650 36.450 20.584 12.038 7.224 5.201 1.198 0.248 0.078 KG 953 2213 45.155 36.579 20.696 12.002 7.466 5.183 1.190 0.288 0.087 KG 952 2213 45.290 37.181 21.648 12.794 7.752 5.866 1.647 0.436 0.119 KG 951 2213 47.675 39.374 24.252 16.916 11.404 7.804 2.452 1.181 0.337 KG 950 2213 48.620 42.126 29.012 21.020 15.397 11.972 4.203 1.979 0.539 KG 949 2213 49.475 43.287 30.916 24.044 18.752 13.728 5.282 2.606 0.716 KG 948 2213 49.115 43.717 31.000 24.224 19.379 14.574 5.373 2.718 0.740 KG 948 2212 48.035 41.997 29.236 21.362 15.683 11.881 4.485 2.152 0.550 KG 948 2211 45.650 38.385 24.140 16.214 10.799 7.922 2.692 1.105 0.275 KG 948 2210 47.540 40.320 25.568 17.492 13.065 9.724 2.975 1.147 0.353 KG 949 2210 45.470 37.439 22.572 14.234 9.468 6.985 1.846 0.590 0.167 KG 949 2209 48.440 40.492 25.764 18.374 13.417 10.079 3.298 1.419 0.430 KG 950 2209 46.100 37.826 22.460 13.856 9.028 6.939 1.954 0.523 0.179 KG 950 2208 47.675 40.062 25.960 18.410 13.472 10.379 3.597 1.606 0.472 KG 951 2208 47.315 39.288 23.888 15.530 10.920 8.095 2.269 0.702 0.229 KG 951 2207 49.295 41.825 28.004 20.804 16.046 12.126 4.161 2.029 0.607 KG 952 2207 47.675 38.901 23.608 15.098 10.117 7.749 2.344 0.747 0.231 KG 952 2206 47.360 38.815 24.308 16.664 11.437 8.004 2.601 1.055 0.305 KG 953 2206 46.010 36.536 20.724 12.056 7.400 5.456 1.256 0.274 0.105 KG 952 2206 47.360 38.815 24.308 16.664 11.437 8.004 2.601 1.055 0.305 KG 951 2206 49.025 42.169 29.600 21.470 15.914 12.081 4.236 2.032 0.553 KG 951 2205 47.675 39.589 25.484 17.582 11.448 8.314 2.933 1.343 0.323 KG 950 2205 48.755 42.040 28.872 21.344 16.266 12.181 4.352 2.116 0.619 KG 950 2204 46.910 39.632 25.876 17.006 11.459 8.896 3.041 1.240 0.312 KG 949 2204 49.070 42.427 29.376 21.902 16.618 12.381 4.485 2.178 0.580 KG 949 2203 49.070 41.825 28.788 21.326 15.562 11.499 4.095 1.909 0.486 KG 948 2203 49.745 44.147 31.084 23.396 17.949 13.428 4.709 2.228 0.629 355 KG 948 2202 49.925 43.889 30.720 22.442 16.750 12.945 4.527 2.066 0.583 KG 947 2202 50.195 42.943 29.572 23.000 17.520 13.046 4.676 2.320 0.656 KG 947 2201 48.980 42.298 29.432 21.758 16.310 12.381 4.435 2.066 0.576 KG 947 2200 48.170 40.707 27.080 19.400 13.043 9.706 3.597 1.522 0.369 KG 947 2199 45.965 37.095 22.068 13.658 8.291 5.729 1.638 0.559 0.158 KG 948 2199 45.605 36.536 21.060 12.218 7.312 5.456 1.256 0.282 0.054 KG 948 2200 46.325 38.428 22.656 14.324 9.611 6.885 1.896 0.772 0.190 KG 949 2200 45.020 36.966 21.172 12.146 7.037 5.220 1.290 0.276 0.045 KG 949 2201 46.190 37.396 22.152 13.298 8.863 6.348 1.555 0.528 0.172 KG 950 2201 45.830 36.751 20.976 12.164 6.993 5.083 1.348 0.260 0.065 KG 950 2202 46.190 37.826 22.376 13.370 8.302 6.357 1.763 0.453 0.112 KG 951 2202 46.235 36.665 20.836 12.254 7.136 5.074 1.232 0.260 0.055 KG 951 2203 45.650 36.794 20.920 11.912 7.213 5.274 1.256 0.240 0.069 KG 952 2203 45.740 36.837 20.920 11.894 7.257 5.238 1.273 0.248 0.074 KG 952 2204 46.010 36.493 20.808 12.038 6.960 5.292 1.323 0.240 0.066 KG 953 2204 45.650 36.794 20.724 12.002 7.092 5.156 1.339 0.226 0.084 KG 953 2205 45.380 36.278 21.004 12.020 7.114 5.038 1.256 0.237 0.061 KG 954 2205 45.605 36.450 20.640 12.056 7.169 5.101 1.190 0.223 0.055 KG 954 2206 45.335 36.407 20.696 12.074 7.103 5.183 1.198 0.240 0.083 KG 954 2207 45.290 36.192 20.752 12.056 7.235 5.283 1.232 0.274 0.061 KG 953 2207 45.605 36.536 21.004 12.416 7.598 5.429 1.315 0.316 0.083 KG 952 2207 47.675 38.901 23.608 15.098 10.117 7.749 2.344 0.747 0.231 KG 952 2208 45.830 36.579 21.340 12.776 8.148 5.948 1.630 0.419 0.129 KG 951 2208 47.315 39.288 23.888 15.530 10.920 8.095 2.269 0.702 0.229 KG 951 2209 45.695 36.622 20.864 12.236 7.620 5.474 1.456 0.360 0.116 KG 950 2209 46.100 37.826 22.460 13.856 9.028 6.939 1.954 0.523 0.179 KG 950 2210 45.515 36.493 20.948 12.308 7.554 5.356 1.406 0.335 0.092 KG 949 2210 45.470 37.439 22.572 14.234 9.468 6.985 1.846 0.590 0.167 KG 948 2210 47.540 40.320 25.568 17.492 13.065 9.724 2.975 1.147 0.353 K0 1745 1367 54.065 47.845 35.032 27.104 20.182 15.120 5.855 2.743 0.699 K0 1745 1368 53.210 46.985 34.052 26.528 19.533 14.456 5.315 2.500 0.614 K0 1744 1368 53.075 46.555 33.128 25.034 18.004 13.319 5.199 2.270 0.552 K0 1744 1369 51.680 44.921 31.616 23.432 16.563 12.154 4.610 2.015 0.475 K0 1745 1369 53.030 45.867 32.288 24.368 17.839 13.355 5.008 2.197 0.544 K0 1745 1370 52.490 45.308 31.924 23.324 16.453 11.954 4.560 1.802 0.458 K0 1744 1370 51.590 44.104 30.636 21.938 15.331 10.971 4.020 1.539 0.371 K0 1744 1369 51.680 44.921 31.616 23.432 16.563 12.154 4.610 2.015 0.475 K0 1743 1369 50.960 43.029 28.732 20.336 13.780 10.097 3.522 1.503 0.390 K0 1743 1370 49.160 41.739 26.884 18.230 12.174 9.069 3.041 1.175 0.299 K0 1742 1370 50.105 41.438 26.884 17.906 11.701 8.723 2.883 1.077 0.286 K0 1742 1369 50.240 41.739 27.472 18.932 12.944 9.406 3.248 1.354 0.334 356 K0 1741 1369 49.340 41.180 26.716 17.870 11.778 8.587 2.875 1.186 0.341 K0 1741 1370 49.475 40.234 25.652 16.790 10.733 7.704 2.203 0.822 0.235 K0 1741 1371 49.025 39.073 23.384 14.558 8.621 6.575 1.896 0.542 0.151 K0 1741 1372 47.360 38.901 23.020 14.180 8.643 6.211 1.597 0.447 0.107 K0 1742 1372 48.530 39.288 23.972 14.882 9.061 6.585 1.970 0.517 0.130 K0 1743 1372 49.160 39.804 24.700 16.124 10.524 7.995 2.800 0.747 0.195 K0 1743 1373 48.485 39.503 24.532 15.548 10.007 7.176 2.203 0.548 0.152 K0 1742 1373 48.170 38.686 22.908 14.000 8.335 6.075 1.671 0.327 0.079 K0 1742 1374 47.765 38.729 22.684 13.712 8.016 5.738 1.647 0.302 0.056 K0 1741 1374 47.945 38.772 22.712 13.676 8.137 6.029 1.763 0.369 0.091 K0 1741 1375 47.585 38.643 22.908 14.144 8.467 6.048 1.738 0.366 0.092 K0 1740 1375 48.170 38.643 22.404 13.622 7.994 5.784 1.721 0.310 0.076 K0 927 2803 50.105 42.341 25.764 16.736 11.415 8.514 2.618 0.853 0.234 K0 927 2804 49.880 41.954 25.652 16.484 11.228 8.350 2.626 0.803 0.198 K0 926 2804 50.195 42.126 25.792 16.754 11.239 8.450 2.626 0.820 0.221 K0 926 2805 49.835 41.868 25.428 16.466 11.162 8.304 2.601 0.786 0.214 K0 927 2805 49.790 41.825 25.260 16.268 10.986 8.141 2.477 0.775 0.196 K0 927 2806 49.790 41.739 25.008 16.070 10.832 8.077 2.194 0.764 0.189 K0 926 2806 49.565 41.825 24.896 16.124 10.898 8.086 2.418 0.713 0.203 K0 926 2807 48.800 41.180 24.392 15.260 10.238 7.504 1.854 0.593 0.166 K0 925 2807 48.710 40.922 24.028 14.846 9.754 7.185 2.145 0.495 0.129 K0 925 2808 49.160 40.707 23.468 14.432 9.182 6.894 1.580 0.405 0.110 K0 924 2808 49.340 40.664 23.244 14.126 9.061 6.566 1.705 0.332 0.096 K0 924 2809 49.295 40.449 23.300 14.036 8.973 6.539 1.572 0.366 0.087 K0 923 2809 48.890 40.234 23.132 14.036 8.984 6.448 1.804 0.271 0.093 K0 922 2809 49.385 40.492 23.580 13.892 8.830 6.475 1.613 0.307 0.085 K0 922 2808 49.430 40.664 23.552 14.414 9.160 6.776 1.638 0.372 0.099 K0 922 2807 49.385 40.922 23.888 14.864 9.776 7.103 1.896 0.428 0.139 K0 922 2806 49.250 41.395 24.000 15.026 9.963 7.376 1.995 0.531 0.174 K0 922 2805 49.970 41.696 24.840 15.800 10.612 7.868 2.178 0.663 0.218 K0 922 2804 50.555 42.470 25.596 16.790 11.624 8.514 2.518 0.870 0.248 K0 922 2803 50.735 43.545 26.744 17.762 12.548 9.424 2.875 1.114 0.317 K0 922 2802 51.320 43.975 27.864 18.986 13.648 10.297 3.323 1.315 0.374 K0 923 2802 51.005 43.502 27.864 18.500 13.252 10.070 3.265 1.242 0.331 K0 923 2801 51.185 43.545 27.444 18.572 13.076 9.815 3.232 1.184 0.325 K0 924 2801 50.690 42.986 26.352 17.510 12.130 9.078 2.750 0.985 0.266 K0 924 2800 51.275 43.201 26.520 17.708 12.361 9.178 2.684 1.030 0.277 K0 925 2800 50.465 42.556 26.044 17.096 11.899 8.960 2.402 0.926 0.246 K0 926 2800 49.970 42.040 25.120 16.052 10.942 8.204 2.344 0.741 0.209 K0 927 2800 49.025 40.750 23.692 14.666 9.644 7.103 1.497 0.458 0.158 K0 927 2799 49.385 40.836 23.748 14.666 9.688 7.158 1.937 0.458 0.159 357 K0 928 2799 49.025 40.879 23.720 14.450 9.270 6.748 1.223 0.374 0.143 K0 929 2799 49.070 41.438 24.784 15.854 11.052 8.405 2.394 0.814 0.250 K0 929 2798 49.835 41.868 25.456 16.448 11.063 8.204 2.294 0.794 0.251 K0 930 2798 50.375 42.599 26.632 18.338 13.164 9.942 3.174 1.212 0.365 K0 930 2797 50.330 43.158 26.604 17.888 12.427 9.396 2.883 1.094 0.336 K0 931 2797 49.835 42.642 25.792 16.844 11.668 8.850 2.651 0.912 0.268 K0 931 2796 49.475 42.341 25.680 16.844 11.602 8.623 2.427 0.862 0.260 K0 932 2796 49.295 41.739 25.260 16.322 11.118 8.523 2.468 0.822 0.200 K0 932 2795 50.465 42.943 27.108 18.194 12.790 9.660 3.016 1.178 0.352 K0 933 2795 50.870 44.276 28.676 20.804 15.518 11.772 4.054 1.573 0.448 K0 933 2794 51.365 44.792 28.676 19.796 14.451 11.034 3.697 1.497 0.461 K0 934 2794 51.500 43.803 28.088 19.220 14.044 10.534 3.456 1.290 0.387 K0 934 2793 51.050 43.717 27.780 18.932 13.593 10.197 3.439 1.279 0.392 K0 935 2793 50.780 43.717 27.696 19.076 13.714 10.343 3.381 1.307 0.389 K0 935 2792 51.185 44.147 28.480 19.814 14.198 10.825 3.605 1.396 0.430 K0 935 2791 51.275 44.448 28.900 20.336 14.902 11.326 3.755 1.503 0.436 K0 936 2791 51.635 44.792 29.684 21.290 15.782 11.954 4.020 1.724 0.493 K0 1418 2521 53.345 47.114 33.324 25.952 20.072 15.011 5.971 2.906 0.781 K0 1418 2522 53.210 47.157 33.184 26.096 19.984 15.211 6.062 2.992 0.788 K0 1417 2522 53.570 47.372 33.492 26.222 20.039 15.011 5.863 2.850 0.802 K0 1416 2522 53.750 48.103 34.052 26.672 20.479 15.612 5.888 2.990 0.851 K0 1416 2523 52.220 45.953 30.916 23.378 17.300 13.255 4.908 2.379 0.625 K0 1416 2524 51.050 43.760 28.144 19.688 14.154 10.834 3.846 1.671 0.430 K0 1416 2525 49.970 42.427 26.044 17.744 11.998 8.941 3.024 1.035 0.251 K0 1416 2526 50.870 42.728 26.184 16.970 11.217 8.450 2.759 0.965 0.232 K0 1416 2527 50.645 42.341 25.988 17.474 11.932 8.951 2.643 1.046 0.262 K0 1416 2528 50.195 41.997 25.652 16.574 10.799 7.804 2.460 0.730 0.173 K0 1416 2529 49.880 41.524 24.560 15.728 10.194 7.431 2.128 0.649 0.167 K0 1416 2530 50.195 41.911 24.812 15.800 10.205 7.576 2.053 0.677 0.178 K0 1417 2530 50.285 41.868 24.700 15.692 10.282 7.595 2.103 0.643 0.123 K0 1417 2531 50.510 42.685 25.680 16.682 11.239 8.341 2.402 0.800 0.179 K0 1417 2532 50.915 43.029 26.912 18.392 12.746 9.560 3.058 1.158 0.321 K0 1417 2533 51.545 43.975 28.256 19.796 14.110 10.479 3.572 1.371 0.378 K0 1418 2533 51.410 43.975 28.480 20.318 14.198 10.534 3.746 1.480 0.419 K0 1418 2534 51.365 44.448 28.844 20.282 14.396 10.962 3.829 1.629 0.453 K0 1418 2535 51.320 44.448 28.648 19.922 14.253 10.825 3.921 1.570 0.452 K0 1418 2536 51.455 44.061 28.060 19.796 13.868 10.316 3.365 1.441 0.397 K0 1419 2536 51.455 45.050 28.844 20.606 14.990 11.408 3.780 1.758 0.485 K0 1419 2537 50.600 43.373 27.192 19.580 13.967 10.407 3.705 1.385 0.400 K0 1420 2537 51.095 43.416 27.640 19.346 13.714 10.243 3.431 1.430 0.402 K0 1420 2538 49.340 41.266 25.232 16.556 11.107 8.213 2.377 0.864 0.258 358 K0 1421 2538 49.970 41.696 24.924 16.160 10.645 7.895 2.493 0.867 0.220 K0 1422 2538 49.385 41.266 25.064 16.052 10.337 7.667 2.103 0.775 0.145 K0 1422 2539 48.890 40.535 23.412 13.982 8.621 6.657 1.829 0.338 0.113 K0 1423 2539 50.150 41.696 24.056 14.738 9.270 6.894 2.078 0.444 0.149 K0 1423 2540 48.800 40.320 23.160 13.982 8.654 6.448 1.837 0.391 0.118 K0 1423 2541 49.070 40.750 23.636 14.414 9.083 6.867 1.979 0.388 0.109 K0 1424 2541 48.890 40.406 23.580 14.576 9.105 6.721 1.837 0.419 0.114 K0 1425 2541 48.125 39.804 23.132 14.072 8.720 6.512 1.912 0.450 0.053 K0 1426 2541 48.260 40.234 24.028 14.648 9.578 6.730 1.871 0.408 0.118 K0 1426 2542 49.295 41.782 24.840 15.710 10.568 7.977 2.576 0.822 0.205 K0 1427 2542 50.645 42.857 27.220 18.626 12.790 9.415 3.074 1.172 0.299 K0 1428 2542 51.365 44.319 28.760 20.030 14.572 11.098 3.763 1.590 0.389 K0 1428 2543 51.545 44.835 29.096 20.696 14.803 11.171 3.672 1.693 0.446 K0 1429 2543 51.635 45.695 30.076 21.866 15.309 11.735 4.244 1.982 0.483 K9 1717 639 39.080 33.741 22.992 16.736 12.097 8.750 3.024 1.380 0.353 K9 1716 639 38.675 33.268 21.816 15.620 10.986 7.786 2.526 1.116 0.283 K9 1716 640 38.225 32.924 20.164 14.756 10.106 7.149 2.252 0.918 0.228 K9 1717 640 38.225 32.881 21.340 15.116 10.513 7.558 2.410 1.038 0.260 K9 1717 641 38.000 31.892 19.716 12.938 8.467 5.984 1.754 0.635 0.180 K9 1718 641 38.495 33.010 21.424 15.836 11.261 7.849 2.750 1.156 0.290 K9 1718 642 38.180 32.021 20.444 14.198 9.809 6.976 2.178 0.884 0.228 K9 1717 642 37.685 31.591 19.744 13.172 8.687 5.902 1.680 0.562 0.149 K9 1716 642 37.730 31.247 19.044 12.344 7.939 5.593 1.406 0.484 0.122 K9 1715 642 37.280 30.860 18.512 11.462 7.026 4.856 1.132 0.262 0.062 K9 1715 643 36.785 30.645 18.372 11.138 6.696 4.755 0.924 0.246 0.060 K9 1714 643 36.785 30.559 17.588 10.904 6.553 4.628 0.958 0.234 0.061 K9 1714 644 36.785 30.473 17.700 10.814 6.630 4.601 1.007 0.206 0.068 K9 1715 644 37.055 30.215 17.504 10.994 6.762 4.701 1.107 0.237 0.069 K9 1715 643 36.785 30.645 18.372 11.138 6.696 4.755 0.924 0.246 0.060 K9 1716 643 37.010 30.860 18.400 11.264 6.839 4.728 1.099 0.237 0.068 K9 1717 643 38.090 31.505 19.828 13.118 8.819 6.221 1.771 0.621 0.159 K9 1717 642 37.685 31.591 19.744 13.172 8.687 5.902 1.680 0.562 0.149 K9 1718 642 38.180 32.021 20.444 14.198 9.809 6.976 2.178 0.884 0.228 K9 1719 642 40.295 35.805 25.316 21.038 15.848 11.453 3.971 1.732 0.429 K9 1719 641 39.935 35.117 25.120 19.778 14.803 10.498 3.763 1.702 0.432 K9 1720 641 42.410 39.030 30.720 24.260 18.752 13.592 5.191 2.441 0.624 K9 1721 638 42.725 39.288 30.272 24.566 19.060 13.901 5.456 2.570 0.673 K9 1721 637 42.275 38.686 29.180 23.576 18.048 13.137 5.166 2.519 0.645 K9 1722 637 42.815 39.159 30.160 24.314 18.807 13.701 5.531 2.768 0.702 K9 1722 638 43.040 39.589 30.608 25.070 19.533 14.238 5.780 2.836 0.713 K9 1723 638 42.860 39.847 31.728 25.790 20.391 14.856 6.178 3.071 0.781 359 K9 1723 637 43.265 39.417 30.748 25.034 19.467 14.411 5.797 3.015 0.770 K9 1724 637 42.815 39.804 31.392 25.448 19.995 14.784 6.004 3.202 0.817 K9 1724 636 42.995 39.460 30.720 24.764 19.368 14.310 5.780 3.130 0.796 K9 1725 636 42.635 40.191 31.728 25.844 20.424 15.184 6.203 3.432 0.894 K9 1443 2365 43.355 38.213 24.840 17.564 12.834 9.305 3.016 1.542 0.400 K9 1443 2366 42.860 38.084 24.336 17.528 12.680 9.278 2.726 1.494 0.387 K9 1442 2366 42.995 37.181 23.776 17.024 12.064 8.896 2.858 1.391 0.360 K9 1441 2366 42.545 37.181 23.468 16.214 11.558 8.368 2.551 1.237 0.305 K9 1440 2366 42.590 36.665 22.768 15.494 10.689 7.622 1.896 1.021 0.260 K9 1440 2367 42.410 36.235 22.040 15.026 10.238 7.313 1.945 0.906 0.236 K9 1440 2368 42.320 36.364 21.956 14.504 9.644 7.040 2.020 0.845 0.222 K9 1439 2368 42.320 35.891 21.228 13.784 9.116 6.448 1.688 0.666 0.169 K9 1439 2369 41.555 34.945 20.556 12.956 8.346 5.857 1.514 0.475 0.125 K9 1438 2369 41.285 34.558 20.108 12.092 7.510 5.402 1.306 0.313 0.078 K9 1437 2369 41.285 34.429 19.604 12.002 7.521 5.338 1.306 0.282 0.073 K9 1437 2370 41.060 34.128 19.380 11.696 7.334 5.201 1.049 0.271 0.058 K9 1436 2370 41.240 34.773 19.828 11.804 7.345 5.201 0.841 0.251 0.069 K9 1103 2124 49.070 43.975 33.548 26.924 21.876 17.341 7.008 3.967 1.151 K9 1102 2124 48.125 42.470 31.140 24.800 19.874 15.448 6.137 3.379 1.034 K9 1101 2124 47.855 41.868 30.608 23.990 18.928 14.693 5.390 3.026 0.906 K9 1101 2125 47.450 41.309 30.020 23.270 18.345 14.165 5.423 2.984 0.883 K9 1101 2126 47.945 41.180 29.908 22.856 17.674 13.737 5.124 2.718 0.815 K9 1100 2126 46.370 40.105 28.368 21.182 16.387 12.882 4.635 2.416 0.716 K9 1100 2127 46.280 39.718 27.752 20.462 15.133 11.571 4.045 2.088 0.642 K9 1099 2127 44.165 37.353 24.700 17.744 13.043 9.806 3.406 1.699 0.517 K9 1098 2127 43.085 35.848 22.488 15.350 10.491 7.904 2.717 1.217 0.349 K9 1098 2128 42.455 34.644 21.256 14.198 9.303 6.858 1.879 0.890 0.279 K9 1097 2128 42.455 34.128 20.808 13.370 8.467 6.221 1.929 0.705 0.196 K9 1097 2129 42.095 33.655 19.884 11.840 7.246 5.156 1.215 0.433 0.125 K9 1096 2129 42.230 33.526 19.576 11.552 6.729 4.874 1.398 0.341 0.096 K9 1096 2130 41.645 33.569 19.576 11.696 6.894 4.828 1.165 0.335 0.095 K9 1095 2130 41.825 33.440 19.408 11.444 6.740 4.965 1.381 0.355 0.103 K9 1095 2131 40.745 33.397 19.296 11.426 6.883 4.810 1.132 0.346 0.101 K9 1094 2131 41.375 32.967 19.044 11.300 6.542 4.801 1.306 0.304 0.102 K9 1094 2132 40.925 33.053 19.128 11.462 6.839 4.856 1.140 0.324 0.094 K9 1093 2132 41.735 32.881 19.016 11.318 6.586 4.846 1.331 0.316 0.089 K9 1093 2133 40.385 33.225 18.988 11.282 6.696 4.801 1.290 0.318 0.082 K9 1092 2133 40.565 33.053 19.044 11.282 6.564 4.801 1.414 0.296 0.098 K9 1092 2134 40.700 32.838 19.268 11.354 6.718 4.774 1.248 0.321 0.101 360 Appendix A, Table 4. Image ID Date of Acquisition d θ EO1A0581152008022110KG 22 Jan 2008 0.98419 20.759 EO1A0581152010038110KK 07 Feb 2010 0.98628 17.600 EO1A0581152009339110K0 05 Dec 2009 0.98547 26.761 EO1A0581152010041110K9 10 Feb 2010 0.98680 17.425 EO1A0581152011027110P1 27 Jan 2011 0.98472 21.773 361 Appendix B: Database of samples collected during the 2009-2010 and 2010-2011 field seasons supporting National Science Foundation grant ANT-0739702. M. R. Salvatore1 1 Department of Geological Sciences, Brown University, Providence, RI 02912, USA 362 Main Text The following data were collected as a component of the National Science Foundation grant entitled “Orbital Spectral Mapping of Surface Compositions in the Antarctic Dry Valleys: Regional Distributions of Secondary Mineral-Phases as Climate Indicators” (ANT-0739702, James Head (Principal Investigator), Michael Wyatt (Former Principal Investigator), and John Mustard (Co-Principal Investigator)). Additional information regarding the objectives of this award can be found at the following website: www.nsf.gov/awardsearch/showAward?AWD_ID=0739702. More than 600 rock and sediment samples (totaling more than 4,200 lbs) were collected for the primary purpose of ground-truthing orbital spectral signatures observed across the McMurdo Dry Valleys (MDV) of Antarctica. This appendix includes a description of the samples collected for the purposes of ground-truthing remote sensing datasets in addition to the complete database of all samples collected from the MDV and returned to Brown University. As per the objectives of the funded grant, the majority of the samples were collected to ground-truth orbital spectroscopic datasets. Fifty-five sampling grids and 4 sampling transects were collected in regions that were designated unique based on ASTER imagery. Aside from a select few spectral grids, each grid consists of 9 individual sampling locations in a square-shaped pattern, with each sample located 30 meters from its neighboring sample; sampling transects were also optimally designed with 30 meter spacing between sampling locations. Some grids were designed to contain 25 samples in a square-shaped pattern to better characterize a large and spectrally homogeneous area. In addition, few sampling grids in Beacon Valley were designed with 60 meter spacing between sampling locations to test whether grids with higher spatial 363 coverage yet lower spatial resolution can better characterize the average spectral properties of the surfaces under investigation. The naming designation for the grid and transect samples was developed to help to quickly identify the season, geographic location, and lithology under investigation. Each sample name follows the following format: W##_XX_$$_@@@. The initial “W” designates the samples as belonging to (former) Principal Investigator Michael Wyatt. The numbers ##, either “09” or “10”, indicate the year that the samples were collected; all samples labeled “09” were collected during the 2009-2010 field season, while all samples labeled “10” were collected during the 2010-2011 field season. The letters “XX” were used to designate the geographic location within the MDV where the samples were collected. For example, “BV” indicates that the samples were collected in Beacon Valley, while “BP” indicates that the samples were collected in Bull Pass. The alphanumeric “$$” were used to designate the lithology under investigation and a unique identifier for that particular sampling grid or transect. For example, “Gd2” indicates the second granodiorite grid, “D3” indicates the third dolerite grid, and “T1” indicates the first transect. In some rare occasions, the indicated lithology incorrectly represents the lithology that was observed in the field. For example, the samples that begin with “W10_VV_S…” were labeled as indicating a sandstone (quartzite) sampling location. This interpretation was based on initial ASTER investigations that indicated a quartz-rich spectral signature. However, in situ field investigations indicated that this unit is a quartz-rich granitic lithology. However, to maintain consistency within our naming rubric, the sample names were not changed. Lastly, the numbers “@@@” were used to designate the unique sample identifier within that particular grid or transect. To 364 summarize this naming scheme, sample “W10_BP_D1_003” indicates the third sample of the first dolerite grid in Bull Pass during the 2010-2011 field season, while “W09_WV_T3_004” indicates the fourth sample of the third sampling transect in Wright Valley during the 2009-2010 field season. Samples collected for purposes other than ground-truthing were designated with other names and labels. All names are consistent with those written on the sampling bags. The strategic goal at each sampling location was to collect a clast and sediment sample that was representative of the surface in the immediate vicinity of the sampling location. Therefore, samples collected for ground-truthing purposes typically consist of a single clast in addition to approximately 500 cm3 of surface sediments. Clast sizes vary, but are typically representative of the average clast size on the surface. Where only massive clasts or exposed bedrock exists, however, sample sizes can vary depending on the size of the clast fractured using a rock hammer or the size of the only loose rock fragments in the vicinity of the sampling location. The amount of collected sediment also varies depending on the abundance of sediment near the sampling location. Each sample is typically accompanied by four photographs (Fig. 1): one low- magnification image of the sample before collection, one high-magnification image of the sample before collection, one low-magnification image of the sample location after collection, and one high-magnification image of the sample location after collection. Each of the four photographs also contains the labeled sampling bag within the field of view, providing both confirmation of the sample being collected as well as a means of determining scale within the image. Lastly, the date and time of collection are also indicated on the sampling bag. In the absence of time to identify the geographic 365 orientation of each sample, we chose to include the date and time of each measurement in our sampling photographs to provide the information necessary to calculate solar azimuth using measurements of shadows present within the image. As of the time of writing, there has been no need to determine the geographic orientation of each sample or image, but the necessary data are available should the necessity arise. In total, nearly 2,300 sample photographs were acquired, totaling 5.59 GB of data. As a result of this large file size, sample photographs are available upon request to the Principal Investigator and are not currently stored online. All of the samples returned to Brown University from McMurdo Station, Antarctica, are listed in the table below. Where available, the latitude and longitude of the sampling location and the date and time of collection are also provided. The numerical identifier of the box that each sample was transported in is also provided, in addition to any comments regarding sampling, handling, or documentation. All samples are currently stored in Metcalf Laboratory at Brown University and are available upon request to the Principal Investigator. Figure and Table Descriptions Figure 1. A typical photographic documentation sequence for the collected spectral grids. This sequence is for sample W09_BV_F05_006. (a) Low magnification, before collection. (b) High magnification, before collection. (c) Low magnification, after collection. (d) High magnification, after collection. 366 Table 1. Sample database with sample name, latitude and longitude of the sample, date and time of collection, and storage box name. Additional comments are provided in the “comments” field. 367 Appendix B, Figure 1. 368 Appendix B, Table 1. SAMPLE NAME LAT (ºN) LON (ºE) DATE TIME BOX COMMENTS W09_WV_Gd2_001 -77.564357 161.303184 11/23/2009 1542 1 W09_WV_Gd2_002 -77.564895 161.303282 11/23/2009 1603 1 W09_WV_Gd2_003 -77.565432 161.30338 11/23/2009 1600 1 W09_WV_Gd2_004 -77.564336 161.305678 11/23/2009 1545 1 W09_WV_Gd2_005 -77.564873 161.305776 11/23/2009 1606 1 W09_WV_Gd2_006 -77.565411 161.305874 11/23/2009 1558 1 W09_WV_Gd2_007 -77.564315 161.308172 11/23/2009 1547 1 W09_WV_Gd2_008 -77.564852 161.30827 11/23/2009 1552 1 W09_WV_Gd2_009 -77.565389 161.308368 11/23/2009 1555 1 W09_WV_T1_001 -77.564972 161.309999 11/23/2009 1804 1 W09_WV_T1_005 -77.566759 161.310825 11/23/2009 1750 1 W09_WV_T1_007 -77.567652 161.311239 11/23/2009 1743 1 W09_WV_T1_010 -77.568992 161.311859 11/23/2009 1735 1 W09_WV_T1_013 -77.570332 161.312479 11/23/2009 1727 1 W09_WV_T1_016 -77.571671 161.313099 11/23/2009 1719 1 W09_WV_T1_017 -77.572118 161.313306 11/23/2009 1716 1 W09_WV_T1_018 -77.572565 161.313513 11/23/2009 1713 1 W09_WV_T1_019 -77.573011 161.31372 11/23/2009 1710 1 W09_WV_T1_020 -77.573258 161.313926 11/23/2009 1706 1 W09_WV_Gd1_001 -77.56347 161.244122 11/22/2009 1645 2 W09_WV_Gd1_002 -77.563738 161.24417 11/22/2009 1647 2 W09_WV_Gd1_003 -77.564007 161.244217 11/22/2009 1707 2 W09_WV_Gd1_004 -77.564275 161.244265 11/22/2009 1709 2 W09_WV_Gd1_005 -77.564544 161.244313 11/22/2009 1735 2 W09_WV_Gd1_006 -77.563459 161.245369 11/22/2009 1643 2 W09_WV_Gd1_007 -77.563728 161.245417 11/22/2009 1649 2 W09_WV_Gd1_010 -77.564534 161.24556 11/22/2009 1733 2 W09_WV_Gd1_011 -77.563449 161.246616 11/22/2009 1641 2 W09_WV_Gd1_012 -77.563718 161.246664 11/22/2009 1651 2 W09_WV_Gd1_013 -77.563986 161.246711 11/22/2009 1702 2 W09_WV_Gd1_015 -77.564524 161.246807 11/22/2009 1731 2 W09_WV_Gd1_016 -77.563439 161.247863 11/22/2009 1639 2 W09_WV_Gd1_017 -77.563707 161.247911 11/22/2009 1654 2 W09_WV_Gd1_018 -77.563976 161.247958 11/22/2009 1700 2 W09_WV_Gd1_019 -77.564245 161.248006 11/22/2009 1716 2 W09_WV_Gd1_020 -77.564513 161.248054 11/22/2009 1729 2 W09_WV_Gd1_022 -77.563697 161.249157 11/22/2009 1656 2 W09_WV_Gd1_023 -77.563966 161.249205 11/22/2009 1658 2 369 W09_WV_Gd1_025 -77.564503 161.249301 11/22/2009 1721 2 BV alt? 11/16/09 11/16/2009 3 BV G-070 collected soils 3 BV Mullins alteration? 3 BV north/south rocks 3 BV representative surface samples 3 BV surface fines 3 BV Uly core tubes / syringes 3 BV Unlabelled whirl pack 3 W09_WV_D3_001 -77.569302 161.279349 11/26/2009 1326 4 W09_WV_D3_002 -77.569839 161.279446 11/26/2009 1257 4 W09_WV_D3_003 -77.570376 161.279543 11/26/2009 1250 4 W09_WV_D3_004 -77.569281 161.281844 11/26/2009 1322 4 W09_WV_D3_005 -77.569818 161.281941 11/26/2009 1302 4 W09_WV_D3_006 -77.570355 161.282038 11/26/2009 1245 4 W09_WV_D3_007 -77.56926 161.284339 11/26/2009 1314 4 W09_WV_D3_008 -77.569797 161.284436 11/26/2009 1306 4 W09_WV_D3_009 -77.570334 161.284533 11/26/2009 1240 4 W09_WV_G2_003 -77.548257 161.216229 11/27/2009 1209 4 W09_WV_G2_004 -77.548526 161.216276 11/27/2009 1206 4 W09_WV_G2_008 -77.548247 161.217474 11/27/2009 1157 4 W09_WV_G2_009 -77.548516 161.217521 11/27/2009 1159 4 W09_WV_G2_010 -77.548784 161.217568 11/27/2009 1201 4 W09_WV_G2_015 -77.548774 161.218814 11/27/2009 1139 4 W09_WV_T3_001 -77.5453 161.262763 11/27/2009 1313 4 W09_WV_T3_002 -77.545563 161.263516 11/27/2009 1316 4 W09_WV_T3_003 -77.545826 161.26427 11/27/2009 1318 4 W09_WV_T3_005 -77.546351 161.265777 11/27/2009 1323 4 W09_WV_T3_006 -77.546614 161.266531 11/27/2009 1325 4 W09_BV_F01_002 -77.80232 160.70711 11/11/2009 1455 5 W09_BV_F01_003 -77.80205 160.70707 11/11/2009 1457 5 W09_BV_F01_004 -77.80258 160.70842 11/11/2009 1503 5 W09_BV_F01_005 -77.80231 160.70838 11/11/2009 1501 5 W09_BV_F01_007 -77.80258 160.70969 11/11/2009 1505 5 W09_BV_F01_008 -77.80231 160.70965 11/11/2009 1506 5 W09_BV_F03_001 -77.81209 160.69004 11/11/2009 1327 5 W09_BV_F03_002 -77.81182 160.69 11/11/2009 1324 5 W09_BV_F03_003 -77.81155 160.68996 11/11/2009 1316 5 W09_BV_F03_004 -77.81208 160.69131 11/11/2009 1330 5 W09_BV_F03_005 -77.81181 160.69127 11/11/2009 1344 5 W09_BV_F03_006 -77.81154 160.69124 11/11/2009 1342 5 370 W09_BV_F03_008 -77.81181 160.69254 11/11/2009 1336 5 W09_BV_F03_009 -77.81154 160.69251 11/11/2009 1339 5 W09_BV_F04_002 -77.81895 160.66549 11/11/2009 1226 5 W09_BV_F04_003 -77.81868 160.66546 11/11/2009 1222 5 W09_BV_F04_004 -77.81921 160.6668 11/11/2009 1214 5 MRS misc. loose rocks 5 W09_WV_D1_001 -77.55063 161.13527 11/20/2009 1153 6 W09_WV_D1_002 -77.5509 161.13532 11/20/2009 1156 6 W09_WV_D1_003 -77.55116 161.13536 11/20/2009 1158 6 W09_WV_D1_004 -77.55143 161.13541 11/20/2009 1201 6 W09_WV_D1_005 -77.5517 161.13545 11/20/2009 1203 6 W09_WV_D1_006 -77.55062 161.13652 11/20/2009 1150 6 W09_WV_D1_007 -77.55088 161.13656 11/20/2009 1147 6 W09_WV_D1_008 -77.55115 161.13661 11/20/2009 1145 6 W09_WV_D1_009 -77.55142 161.13665 11/20/2009 1142 6 W09_WV_D1_010 -77.55169 161.1367 11/20/2009 1139 6 W09_WV_D1_011 -77.55061 161.13776 11/20/2009 1122 6 W09_WV_D1_012 -77.55088 161.13781 11/20/2009 1124 6 W09_WV_D1_013 -77.55114 161.13785 11/20/2009 1127 6 W09_WV_D1_014 -77.55141 161.1379 11/20/2009 1128 6 W09_WV_D1_015 -77.55168 161.13794 11/20/2009 1132 6 W09_WV_D1_016 -77.5506 161.13901 11/20/2009 1118 6 W09_WV_D1_017 -77.55087 161.13905 11/20/2009 1116 6 W09_WV_D1_018 -77.55113 161.1391 11/20/2009 1112 6 W09_WV_D1_021 -77.55059 161.14025 11/20/2009 1054 6 W09_WV_D1_022 -77.55086 161.1403 11/20/2009 1058 6 W09_WV_D1_023 -77.55112 161.14034 11/20/2009 1100 6 W09_WV_D1_024 -77.55139 161.14039 11/20/2009 1102 6 W09_WV_D1_025 -77.55166 161.14044 11/20/2009 1105 6 Points mislabeled in ArcMap W09_BV_M1_001 -77.90202 160.59067 11/16/2009 1205 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M1_002 -77.90226 160.59097 11/16/2009 1202 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M1_003 -77.90269 160.59176 11/16/2009 1144 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M1_004 -77.90191 160.59154 11/16/2009 1207 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M1_005 -77.90224 160.59229 11/16/2009 1159 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M1_006 -77.90257 160.59272 11/16/2009 1148 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M1_007 -77.90182 160.59246 11/16/2009 1209 7 and Excel. Other data 371 correct. Points mislabeled in ArcMap W09_BV_M1_008 -77.9022 160.59342 11/16/2009 1157 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M1_009 -77.90244 160.59377 11/16/2009 1151 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_001 -77.89739 160.5825 11/16/2009 1330 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_002 -77.89767 160.58339 11/16/2009 1327 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_003 -77.89799 160.58351 11/16/2009 1313 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_004 -77.89728 160.58364 11/16/2009 1333 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_005 -77.8976 160.5849 11/16/2009 1325 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_006 -77.89788 160.58484 11/16/2009 1316 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_007 -77.8972 160.58486 11/16/2009 1336 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_008 -77.89748 160.58619 11/16/2009 1321 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M2_009 -77.89777 160.58645 11/16/2009 1318 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M3_003 -77.89207 160.5692 11/16/2009 1440 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M3_002 -77.89176 160.56849 11/16/2009 1432 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M3_004 -77.89138 160.56903 11/16/2009 1438 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M3_005 -77.89165 160.56944 11/16/2009 1429 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M3_006 -77.89192 160.57019 11/16/2009 1421 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M3_008 -77.8915 160.57043 11/16/2009 1427 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M3_007 -77.89124 160.56986 11/16/2009 1418 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M4_001 -77.88833 160.5565 11/16/2009 1521 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M4_002 -77.88851 160.55728 11/16/2009 1518 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M4_003 -77.88877 160.55797 11/16/2009 1505 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M4_004 -77.88818 160.55737 11/16/2009 1524 7 and Excel. Other data correct. 372 Points mislabeled in ArcMap W09_BV_M4_005 -77.88839 160.5584 11/16/2009 1516 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M4_006 -77.88859 160.55889 11/16/2009 1508 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M4_007 -77.88803 160.55899 11/16/2009 1526 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M4_008 -77.88826 160.55921 11/16/2009 1513 7 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M4_009 -77.88847 160.56015 11/16/2009 1510 7 and Excel. Other data correct. UWV North Fork Coatings 12/4/2009 8 UWV North Fork Dolerite 12/4/2009 8 Coatings UWV North Fork Salt Lake -77.53295 161.16464 12/4/2009 8 Samples UWV South Slope Orientation -77.53234 161.14431 12/3/2009 8 Study Site 1 UWV South Slope Orientation -77.53121 161.15907 12/3/2009 8 Study Site 2 UWV South Slope Orientation -77.53215 161.14951 12/3/2009 8 Study Site 3 UWV Unlabelled 8 UWV "Dol Top Tongue Soil" -77.57827 161.2725 11/30/2009 9 UWV "Top Gully Dol" -77.57827 161.2725 11/30/2009 9 UWV Dolerite "Ashtray" 9 UWV Site 1J Transects -77.56859 161.2905 11/30/2009 9 UWV Site 2J Transects -77.56719 161.29009 12/6/2009 9 UWV Site 5G Transects -77.5659 161.29491 12/6/2009 9 UWV "Dol TOP Gareth Gully" -77.57992 161.28033 11/30/2009 10 UWV JWH South Fork Eolian 10 Samples UWV JWH_09_DJP_01 10 UWV North Slope Orientation -77.56961 161.28707 12/4/2009 10 Study Site 1 UWV North Slope Orientation -77.56997 161.2863 12/4/2009 10 Study Site 2 UWV North Slope Orientation -77.56998 161.28893 12/4/2009 10 Study Site 3 W09_BV_F06_001 -77.8405 160.6156 11/10/2009 1518 11 W09_BV_F06_002 -77.84023 160.61556 11/10/2009 1522 11 W09_BV_F06_003 -77.83996 160.61553 11/10/2009 1525 11 W09_BV_F06_004 -77.84049 160.61688 11/10/2009 1539 11 W09_BV_F06_005 -77.84022 160.61684 11/10/2009 1535 11 W09_BV_F06_006 -77.83996 160.6168 11/10/2009 1531 11 W09_BV_F06_007 -77.84049 160.61815 11/10/2009 1544 11 W09_BV_F06_008 -77.84022 160.61812 11/10/2009 1550 11 W09_BV_F06_009 -77.83995 160.61808 11/10/2009 1553 11 W09_BV_F07_001 -77.84697 160.58491 11/10/2009 1336 11 W09_BV_F07_002 -77.8467 160.58487 11/10/2009 1333 11 373 W09_BV_F07_003 -77.84643 160.58484 11/10/2009 1330 11 W09_BV_F07_004 -77.84696 160.58618 11/10/2009 1319 11 W09_BV_F07_005 -77.84669 160.58615 11/10/2009 1322 11 W09_BV_F07_006 -77.84642 160.58611 11/10/2009 1326 11 W09_BV_F07_007 -77.84696 160.58746 11/10/2009 1316 11 W09_BV_F07_008 -77.84669 160.58742 11/10/2009 1312 11 W09_BV_F07_009 -77.84642 160.58739 11/10/2009 1308 11 W09_BV_F09_001 -77.87098 160.52731 11/9/2009 1343 11 W09_BV_F09_002 -77.87071 160.52728 11/9/2009 1347 11 W09_BV_F09_003 -77.87044 160.52724 11/9/2009 1349 11 W09_BV_F09_004 -77.87098 160.52859 11/9/2009 1331 11 W09_BV_F09_005 -77.87071 160.52855 11/9/2009 1336 11 W09_BV_F09_006 -77.87044 160.52852 11/9/2009 1338 11 W09S_BV_001B 11/9/2009 1213 11 W09S_BV_003 11/9/2009 11 W09S_BV_006 11/9/2009 11 W09S_BV_008 11/9/2009 11 UWV JWH_09_JG_600_0 12 UWV JWH_09_JG_600_10 12 UWV JWH_09_JG_600_20 12 UWV JWH_09_JG_650_0 12 UWV JWH_09_JG_650_10 12 UWV JWH_09_JG_650_14 12 UWV JWH_09_JG_790_Channel 12 UWV JWH_09_JG_790_Fan 12 UWV JWH_09_JG_790_Gravel 12 UWV JWH_09_JG_796.2_16 12 UWV JWH_09_SS_01_21 12 UWV JWH_09_SS_01_5 12 UWV JWH_DJP_01 12 UWV JWH_DJP_02 12 UWV JWH_DJP_03 12 UWV JWH_NF_G5_01 12 UWV JWH_S1_09 12 UWV LK09_TwnPks_A+B+C 12 UWV LK09_TwnPks_D+E 12 JLS001-007 sed. samples for 12 GWC LWV AP2 -77.52695 162.16405 12/20/2009 13 2 halves of lava bomb. LWV BP1 -77.52542 162.16112 12/20/2009 13 LWV CC2 -77.5255 162.16851 12/20/2009 13 374 LWV CP1 -77.52532 162.16858 12/20/2009 13 BV Unlabelled dolerite 14 W09_BV_BF2_001 -77.87563 160.48548 11/12/2009 1253 14 W09_BV_BF2_002 -77.87536 160.48544 11/12/2009 1251 14 W09_BV_BF2_003 -77.87509 160.48541 11/12/2009 1248 14 W09_BV_BF2_004 -77.87562 160.48676 11/12/2009 1256 14 W09_BV_BF2_005 -77.87535 160.48672 11/12/2009 1304 14 W09_BV_BF2_006 -77.87508 160.48669 11/12/2009 1246 14 W09_BV_BF2_007 -77.87561 160.48804 11/12/2009 1259 14 W09_BV_BF2_008 -77.87534 160.488 11/12/2009 1302 14 W09_BV_BF2_009 -77.87508 160.48797 11/12/2009 1242 14 W09_BV_F10_001 -77.88552 160.50738 11/12/2009 1448 14 W09_BV_F10_002 -77.88525 160.50735 11/12/2009 1446 14 W09_BV_F10_003 -77.88498 160.50731 11/12/2009 1443 14 W09_BV_F10_004 -77.88552 160.50866 11/12/2009 1451 14 W09_BV_F10_005 -77.88525 160.50863 11/12/2009 1453 14 W09_BV_F10_006 -77.88498 160.50859 11/12/2009 1456 14 W09_BV_F10_007 -77.88551 160.50994 11/12/2009 1503 14 W09_BV_F10_008 -77.88524 160.50991 11/12/2009 1500 14 W09_BV_F10_009 -77.88497 160.50987 11/12/2009 1458 14 W09_BV_M7_001 -77.87867 160.53509 11/12/2009 1632 14 W09_BV_M7_002 -77.8784 160.53506 11/12/2009 1630 14 W09_BV_M7_003 -77.87813 160.53502 11/12/2009 1622 14 W09_BV_M7_004 -77.87866 160.53637 11/12/2009 1644 14 W09_BV_M7_005 -77.87839 160.53634 11/12/2009 1646 14 W09_BV_M7_006 -77.87812 160.5363 11/12/2009 1634 14 W09_BV_M7_007 -77.87865 160.53765 11/12/2009 1642 14 W09_BV_M7_008 -77.87838 160.53762 11/12/2009 1639 14 W09_BV_M7_009 -77.87812 160.53758 11/12/2009 1637 14 W09S_BV_001A 11/9/2009 14 BV Central/East Taylor Moraine -77.80704 160.69931 11/11/2009 1428 15 Samples BV Unlabelled whirl pack 15 W09_BV_F01_001 -77.80259 160.70715 11/11/2009 1453 15 W09_BV_F01_006 -77.80204 160.70834 11/11/2009 1459 15 W09_BV_F01_009 -77.80204 160.70962 11/11/2009 1508 15 W09_BV_F03_007 -77.81155 160.68996 11/11/2009 1332 15 W09_BV_F04_001 -77.81922 160.66553 11/11/2009 1228 15 W09_BV_F04_005 -77.81894 160.66676 11/11/2009 1217 15 W09_BV_F04_006 -77.81868 160.66673 11/11/2009 1219 15 W09_BV_F04_007 -77.81921 160.66807 11/11/2009 1209 15 375 W09_BV_F04_008 -77.81894 160.66804 11/11/2009 1206 15 W09_BV_F04_009 -77.81867 160.668 11/11/2009 1204 15 W09_BV_F05_001 -77.826 160.64485 11/11/2009 1129 15 W09_BV_F05_002 -77.82574 160.64482 11/11/2009 1126 15 W09_BV_F05_003 -77.82547 160.64478 11/11/2009 1123 15 W09_BV_F05_004 -77.826 160.64613 11/11/2009 1116 15 W09_BV_F05_005 -77.82573 160.64609 11/11/2009 1118 15 W09_BV_F05_006 -77.82546 160.64606 11/11/2009 1121 15 W09_BV_F05_007 -77.82599 160.6474 11/11/2009 1114 15 W09_BV_F05_008 -77.82572 160.64737 11/11/2009 1111 15 W09_BV_F05_009 -77.82545 160.64733 11/11/2009 1108 15 W09_BV_MT3_001 -77.80633 160.69445 11/11/2009 1427 15 LWV AP4 -77.52713 162.16343 12/20/2009 16 LWV BC2 -77.52552 162.16132 12/20/2009 16 LWV DC1 -77.53147 162.18308 12/21/2009 16 LWV AC1 -77.52682 162.16317 12/20/2009 17 LWV BC1 -77.52488 162.15835 12/20/2009 17 W09_LWV_D1_003 -77.51984 162.1375 12/19/2009 1352 17 W09_LWV_D1_007 -77.5187 162.1422 12/19/2009 1338 17 W09_BV_F08_001 -77.86266 160.55244 11/9/2009 1727 18 W09_BV_F08_002 -77.86239 160.55241 11/9/2009 1732 18 W09_BV_F08_003 -77.86212 160.55238 11/9/2009 1734 18 W09_BV_F08_004 -77.86265 160.55372 11/9/2009 1724 18 W09_BV_F08_005 -77.86238 160.55369 11/9/2009 1721 18 W09_BV_F08_006 -77.86212 160.55365 11/9/2009 1716 18 W09_BV_F08_007 -77.86264 160.555 11/9/2009 1704 18 W09_BV_F08_008 -77.86238 160.55497 11/9/2009 1706 18 W09_BV_F08_009 -77.86211 160.55493 11/9/2009 1712 18 W09_BV_F09_007 -77.87097 160.52986 11/9/2009 1327 18 W09_BV_F09_008 -77.8707 160.52983 11/9/2009 1323 18 W09_BV_M8_001 -77.87087 160.54938 11/9/2009 1521 18 W09_BV_M8_002 -77.8706 160.54935 11/9/2009 1517 18 W09_BV_M8_003 -77.87033 160.54932 11/9/2009 1453 18 W09_BV_M8_004 -77.87086 160.55066 11/9/2009 1524 18 W09_BV_M8_005 -77.87059 160.55063 11/9/2009 1528 18 W09_BV_M8_006 -77.87032 160.5506 11/9/2009 1531 18 W09_BV_M8_007 -77.87086 160.55194 11/9/2009 1541 18 W09_BV_M8_008 -77.87059 160.55191 11/9/2009 1538 18 W09_BV_M8_009 -77.87032 160.55188 11/9/2009 1535 18 W09S_BV_001B 11/9/2009 1213 18 W09S_BV_002 11/9/2009 1246 18 376 W09S_BV_004 11/9/2009 1321 18 W09S_BV_007 11/9/2009 1806 18 Bag ID: W09S_BV_2nd ash W09S_BV_005 11/9/2009 18 deposit LWV "Upslope Vent" -77.52738 162.30093 12/16/2009 19 LWV Unlabelled 19 LWV Unlabelled soil & rocks in 19 whirl packs (3) W09_LWV_D1_001 -77.51876 162.13723 12/19/2009 1359 19 W09_LWV_D1_002 -77.5193 162.13736 12/19/2009 1356 19 W09_LWV_D1_008 -77.51924 162.14233 12/19/2009 1335 19 W09_LWV_D1_009 -77.51978 162.14246 12/19/2009 1331 19 LWV AP3 -77.527 162.16352 12/20/2009 20 LWV BP2 -77.52533 162.16095 12/20/2009 20 LWV Unlabelled canvas bags (2) 20 W09_LWV_D1_004 -77.51873 162.13971 12/19/2009 1341 20 W09_LWV_D1_005 -77.51927 162.13984 12/19/2009 1345 20 W09_LWV_D1_006 -77.51981 162.13998 12/19/2009 1348 20 W09_WV_D5_001 -77.53124 161.13374 12/4/2009 1358 21 W09_WV_D5_002 -77.53177 161.13384 12/4/2009 1354 21 W09_WV_D5_003 -77.53231 161.13393 12/4/2009 1350 21 W09_WV_D5_004 -77.53122 161.13623 12/4/2009 1337 21 W09_WV_D5_007 -77.5312 161.13872 12/4/2009 1330 21 W09_WV_D5_008 -77.53173 161.13881 12/4/2009 1326 21 W09_WV_D5_009 -77.53227 161.1389 12/4/2009 1322 21 W09_WV_T8_001 -77.53132 161.15269 12/4/2009 1131 21 W09_WV_T8_002 -77.5316 161.15407 12/4/2009 1135 21 W09_WV_T8_003 -77.53187 161.15544 12/4/2009 1142 21 W09_WV_T8_004 -77.53215 161.15682 12/4/2009 1146 21 W09_WV_T8_005 -77.53242 161.15819 12/4/2009 1150 21 W09_WV_T8_006 -77.5327 161.15957 12/4/2009 1155 21 W09_WV_T8_007 -77.53298 161.16094 12/4/2009 1200 21 W09_WV_T8_008 -77.53325 161.16232 12/4/2009 1208 21 W09_WV_T8_009 -77.53353 161.1637 12/4/2009 1212 21 W09_WV_T8_010 -77.5338 161.16507 12/4/2009 1215 21 W09_WV_T8_011 -77.53408 161.16645 12/4/2009 1218 21 LWV "Upslope Vent" -77.52738 162.30093 12/16/2009 22 LWV CC3 -77.52555 162.16875 12/20/2009 22 LWV AP5 -77.52686 162.16442 12/20/2009 23 LWV Unlabelled 23 LWV CC1 -77.52543 162.16835 12/20/2009 23 Mike <3 Air 23 377 JLD Hand Samples 23 LK09-WV JFS-creep 23 LWV AP1 -77.52698 162.16358 12/20/2009 24 LWV AP6 -77.52652 162.16337 12/20/2009 24 LWV DC2 -77.53317 162.1854 12/21/2009 24 UWV Top Dais Weird 25 UWV Sandstone Level 3 -77.58727 161.28229 25 UWV Highest up dolerite tongue 25 rocks UWV Dolerite in stream on lobe 12/5/2009 25 with algae UWV Don Juan lobe fine 12/5/2009 25 dolerite? UWV Walk from Don Juan to 12/5/2009 25 camp, fine grained dol UWV Eastern dolerite tongue 12/7/2009 25 UWV High up dolerite tongue 25 UWV Eastern dolerite tongue 12/7/2009 25 FAN L-09 26 L-07 26 L-06 26 L-01 26 L-08 26 L-05 26 L-04 26 L-10 26 L-03 26 L-02 26 L-11 26 GMT-1-4 26 GMT-1-3 26 GMT-1-0 26 GMT-1-2 26 GMT-1--2 26 GMT-1--1 26 GMT-1-5 26 GMT-1-1 26 GMT-2-1 26 GMT-2-3 26 GMT-2-2 26 GMT-2-5 26 GMT-2-1 26 GMT-2-0 26 GMT-2--2 26 378 GMT-2-4 26 GMT-3-3 26 GMT-3-1 26 GMT-3-5 26 GMT-3--2 26 GMT-3-1 26 GMT-3-0 26 GMT-3-2 26 GMT-3-4 26 LVS-01 27 LVS-04 27 LVS-03 27 LK WV Sample #3 27 LK WV Sample #4 27 LVS-02 27 LK WV Sample #5 27 LK09 WV Sample #8 27 Whirl Paks labelled Unlabelled canvas bag 27 "JWH09-##" UWV-Dolerite outcrop 1 27 (column) LK Saltation Trap 28 LK Beacon Samples 1 28 LK Coarse Grained Ripple 28 Experiment LK N.F. Samples Dais Rocks 28 LK Beacon Samples #2 28 LK09 Labyrinth Box Sample 28 GRANO 28 LVS-08 28 LVS-10 28 LVS-06 28 LVS-05 28 LVS-07 28 LVS-09 28 UWV-Dolerite outcrop 28 (weathered) W09_WV_D2_004 -77.55438 160.74805 11/25/2009 1412 29 W09_WV_D2_005 -77.55491 160.74805 11/25/2009 1420 29 W09_WV_D2_001 -77.55439 160.74548 11/25/2009 1407 29 W09_WV_D2_007 -77.55436 160.75047 11/25/2009 1443 29 W09_WV_D1_020 -77.55167 161.13919 11/20/2009 1107 29 W09_WV_D1_019 -77.5514 161.13914 11/20/2009 1110 29 W09_WV_Gd1_014 -77.56426 161.24676 11/22/2009 1714 29 379 W09_WV_Gd1_009 -77.56426 161.24551 11/22/2009 1711 29 W09_WV_Gd1_008 -77.564 161.24546 11/22/2009 1704 29 W09_WV_Gd1_021 -77.56343 161.24911 11/22/2009 1635 29 W09_WV_Gd1_024 -77.56423 161.24925 11/22/2009 1718 29 UWV Dais Special Rocks 11/20/2009 29 W09_WV_T2_005 -77.54809 161.14685 11/20/2009 1504 29 W09_WV_T2_001 -77.54903 161.14202 11/20/2009 1516 29 W09_WV_T2_003 -77.54856 161.14444 11/20/2009 1510 29 W09_WV_T2_008 -77.54739 161.15048 11/20/2009 1456 29 W09_WV_T2_002 -77.54879 161.14323 11/20/2009 1512 29 W09_WV_T2_004 -77.54833 161.14565 11/20/2009 1507 29 W09_WV_T2_006 -77.54786 161.14806 11/20/2009 1501 29 W09_WV_T2_009 -77.54716 161.15168 11/20/2009 1453 29 W09_WV_T2_007 -77.54762 161.14927 11/20/2009 1459 29 W09_WV_T2_010 -77.54692 161.15289 11/20/2009 1445 29 UWV Labyrinth pitted rock Lat/Lon of Labyrinth Helo -77.555163 160.74604 11/25/2009 30 surface & orange alt. Pad UWV Seussville dolerites -77.41783 161.41783 11/24/2009 30 Lat/Lon of Labyrinth Helo UWV Labyrinth surface till -77.555163 160.74604 30 Pad Lat/Lon of Labyrinth Helo UWV Labyrinth core bags -77.555163 160.74604 30 Pad UWV Dais alt. pebbles & soil 12/1/2009 30 UWV Special soils 12/1/2009 30 Lat/Lon of Labyrinth Helo UWV Labyrinth orange rocks -77.555163 160.74604 11/25/2009 30 Pad LWV camp dolerite -77.52698 162.16763 12/22/2009 30 W09_WV_T3_009 -77.5474 161.26879 11/27/2009 1332 31 W09_WV_T3_008 -77.54714 161.26804 11/27/2009 1329 31 W09_WV_G2_025 -77.54875 161.2213 11/27/2009 1113 31 W09_WV_G2_002 -77.54799 161.21618 11/27/2009 1211 31 W09_WV_G2_014 -77.5485 161.21877 11/27/2009 1142 31 W09_WV_G2_018 -77.54823 161.21996 11/27/2009 1131 31 W09_WV_G2_005 -77.54879 161.21632 11/27/2009 1204 31 W09_WV_G2_012 -77.54797 161.21867 11/27/2009 1146 31 W09_WV_G2_007 -77.54798 161.21743 11/27/2009 1154 31 W09_WV_G2_013 -77.54824 161.21872 11/27/2009 1144 31 W09_WV_G2_011 -77.5477 161.21863 11/27/2009 1149 31 W09_WV_G2_021 -77.54768 161.22112 11/27/2009 1123 31 W09_WV_G1_008 -77.57265 161.31186 11/26/2009 1721 31 W09_WV_G1_002 -77.57269 161.30687 11/26/2009 1648 31 W09_WV_G1_006 -77.5732 161.30946 11/26/2009 1713 31 W09_WV_G1_003 -77.57323 161.30696 11/26/2009 1707 31 W09_WV_G1_004 -77.57213 161.30926 11/26/2009 1729 31 380 W09_WV_G1_009 -77.57318 161.31196 11/26/2009 1717 31 LK09 Saltation Experiment 31 UWV Site 1G Transects -77.57835 161.27957 32 UWV Site 5J Transects (x2) -77.56335 161.28033 12/6/2009 32 UWV Site 4J Transects -77.56342 161.28921 12/6/2009 32 Boldt Samples 32 LK09 Saltation Trap 32 LK09 Sample #7 33 Boldt Beacon Valley Samples 33 Boldt Upper Wright Water 33 Samples W09_WV_G1_001 -77.57215 161.30677 11/26/2009 1642 33 W09_WV_G1_005 -77.57267 161.30936 11/26/2009 1725 33 W09_WV_G1_007 -77.57211 161.31176 11/26/2009 1732 33 W09_WV_D2_003 -77.55547 160.74563 11/25/2009 1357 33 W09_WV_D2_009 -77.55544 160.75062 11/25/2009 1434 33 W09_WV_D2_002 -77.55493 160.74555 11/25/2009 1402 33 W09_WV_D2_006 -77.55545 160.74812 11/25/2009 1425 33 W09_WV_D2_008 -77.5549 160.75054 11/25/2009 1438 33 W09_WV_T3_007 -77.54688 161.26728 11/27/2009 1327 34 W09_WV_T3_004 -77.54609 161.26502 11/27/2009 1321 34 W09_WV_T3_010 -77.54766 161.26955 11/27/2009 1334 34 W09_WV_G2_022 -77.54795 161.22116 11/27/2009 1121 34 W09_WV_G2_019 -77.5485 161.22001 11/27/2009 1134 34 W09_WV_G2_017 -77.54796 161.21992 11/27/2009 1129 34 W09_WV_G2_020 -77.54876 161.22006 11/27/2009 1136 34 W09_WV_G2_023 -77.54822 161.22121 11/27/2009 1119 34 W09_WV_G2_016 -77.54769 161.21987 11/27/2009 1126 34 W09_WV_G2_024 -77.54848 161.22126 11/27/2009 1116 34 W09_WV_G2_001 -77.54772 161.21614 11/27/2009 1214 34 W09_WV_G2_006 -77.54771 161.21738 11/27/2009 1151 34 W09_WV_T1_004 -77.56631 161.31061 11/23/2009 1754 34 W09_WV_T1_015 -77.57122 161.31289 11/23/2009 1722 34 W09_WV_T1_002 -77.56541 161.3102 11/23/2009 1801 34 W09_WV_T1_008 -77.56809 161.31144 11/23/2009 1742 34 W09_WV_T1_012 -77.56988 161.31227 11/23/2009 1729 34 W09_WV_T1_011 -77.56943 161.31206 11/23/2009 1732 34 W09_WV_T1_009 -77.56854 161.31165 11/23/2009 1739 34 W09_WV_T1_003 -77.56586 161.31041 11/23/2009 1758 34 W09_WV_T1_014 -77.57077 161.31268 11/23/2009 1725 34 W09_WV_T1_006 -77.5672 161.31103 11/23/2009 1747 34 381 W09_WV_D4_008 -77.56491 161.14293 12/5/2009 1652 35 W09_WV_D4_006 -77.56439 161.14034 12/5/2009 1701 35 W09_WV_D4_005 -77.56493 161.14043 12/5/2009 1717 35 W09_WV_D5_005 -77.53175 161.13632 12/4/2009 1341 35 W09_WV_D5_006 -77.53229 161.13641 12/4/2009 1346 35 JWH-09 NF-R02 -77.5284 161.21716 35 JWH-09 NF_R01 -77.5285 161.20798 35 UWV unlabelled soil whirl pak -77.53113 161.13854 35 UWV unlabelled soil whirl pak 35 Lat/Lon of Labyrinth Helo UWV Labyrinth special salt -77.555163 160.74604 11/25/2009 35 Pad UWV Labyrinth alteration at Lat/Lon of Labyrinth Helo -77.555163 160.74604 11/25/2009 35 depth ~10-30 cm Pad JWH-09 DAIS-1 35 JWH-09 DAIS-2 35 Lat/Lon of Labyrinth Helo UWV Labyrinth surface Si -77.555163 160.74604 11/25/2009 35 Pad Beacon Valley cores 2 different 11/17/2009 36 Ice Lake 1 rock samples (under 12/7/2009 36 ice) Ice Lake 2 (rock under ice) 12/7/2009 36 Slope streaks "yes + no" 12/3/2009 36 Uly BV 1 surficial rocks with core 11/17/2009 36 1 Points mislabeled in ArcMap W09_BV_M3_001 -77.89148 160.56788 11/16/2009 1435 36 and Excel. Other data correct. Points mislabeled in ArcMap W09_BV_M3_009 -77.89179 160.57135 11/16/2009 1423 36 and Excel. Other data correct. W09_WV_D4_001 -77.56548 161.13803 12/5/2009 1724 36 W09_WV_D4_002 -77.56495 161.13794 12/5/2009 1728 36 W09_WV_D4_003 -77.56441 161.13785 12/5/2009 1732 36 W09_WV_D4_004 -77.56547 161.14052 12/5/2009 1721 36 W09_WV_D4_007 -77.56545 161.14302 12/5/2009 1645 36 W09_WV_D4_009 -77.56437 161.14283 12/5/2009 1657 36 UWV Site 1J Transects -77.56859 161.2905 11/30/2009 37 UWV Site 2J Transects -77.56719 161.29009 12/6/2009 37 UWV Site 3J Transects (x3) -77.56526 161.29021 12/1/2009 37 UWV Site 4G Transects -77.5673 161.29466 12/2/2009 37 Beacon Grain Size Variety 1001 Dolerite Weathering, Nussbaum -77.66886 162.80523 1001 Riegal MS10_BV_01 -77.85974 160.57317 1001 MS10_BV_03 -77.86214 160.56693 1001 MS10_BV_04 -77.8635 160.56302 1001 MS10_BV_06 -77.86619 160.55724 1001 MS10_BV_07 -77.86845 160.55149 1001 382 MS10_BV_08 -77.87171 160.54582 1001 MS10_BV_09 -77.87321 160.54404 1001 MS10_BV_10 -77.87539 160.54128 1001 MS10_BV_11 -77.8783 160.5354 1001 MS10_BV_12 -77.8795 160.53381 1001 MS10_BV_13 -77.88074 160.53367 1001 MS10_BV_SANDSTONE_ALT -77.58734 161.28286 1001 Taylor Valley Alteration Samples 1001 INT_GRID Soils -77.66031 162.81522 1002 INT2_GRID Soil -77.66014 162.9232 1002 MRS B3 & B4 Science 1002 MRS Granite Weathering 1002 MRS Nussbaum Dolerite Alt. 1002 Rind Mustard Sampling Alteration 1002 PQX Rhone 1002 PQX Rhone 1002 W10_TV_B4_001 -77.75792 162.11696 11/19/2010 1220 1002 W10_TV_B4_002 -77.75738 162.11683 11/19/2010 1223 1002 W10_TV_B4_003 -77.75684 162.1167 11/19/2010 1226 1002 W10_TV_B4_004 -77.75789 162.1195 11/19/2010 1214 1002 W10_TV_B4_005 -77.75735 162.11936 11/19/2010 1241 1002 W10_TV_B4_006 -77.75681 162.11922 11/19/2010 1232 1002 W10_TV_B4_007 -77.75786 162.12203 11/19/2010 1208 1002 W10_TV_B4_008 -77.75732 162.12189 11/19/2010 1238 1002 W10_TV_B4_009 -77.75679 162.12176 11/19/2010 1235 1002 W10_TV_DS001 -77.67587 162.79213 1002 W10_TV_DS002 -77.67587 162.79213 1002 W10_TV_DS003 -77.67587 162.79213 1002 W10_TV_DS004 -77.67587 162.79213 1002 W10_TV_DS005 -77.67587 162.79213 1002 W10_TV_DS006 -77.67587 162.79213 1002 W10_TV_DS007 -77.67587 162.79213 1002 W10_TV_DS008 -77.67587 162.79213 1002 JFM Wright Valley Samples 1003 JWH 2010 Samples - COMAIR 1003 LABY_GRID Rocks JFM -77.54884 160.95442 1003 W10_TV_B1_002 -77.69994 162.69626 11/27/2010 1204 1004 W10_TV_B1_003 -77.69941 162.6961 11/27/2010 1201 1004 W10_TV_B1_004 -77.70056 162.69894 11/27/2010 1211 1004 W10_TV_B1_006 -77.69937 162.69862 11/27/2010 1158 1004 383 W10_TV_B1_008 -77.69988 162.7013 11/27/2010 1218 1004 W10_TV_B1_009 -77.69934 162.70114 11/27/2010 1155 1004 W10_TV_U1_001 -77.67478 162.81472 11/27/2010 1418 1004 W10_TV_U1_002 -77.67425 162.81455 11/27/2010 1439 1004 W10_TV_U1_003 -77.67371 162.81439 11/27/2010 1434 1004 W10_TV_U1_005 -77.67421 162.81706 11/27/2010 1437 1004 W10_TV_U1_006 -77.67367 162.8169 11/27/2010 1431 1004 W10_TV_U1_009 -77.67364 162.81941 11/27/2010 1429 1004 W10_TV_U2_002 -77.68294 162.79512 11/27/2010 1329 1004 W10_TV_U2_003 -77.6824 162.79495 11/27/2010 1326 1004 W10_TV_U2_004 -77.68344 162.79779 11/27/2010 1334 1004 W10_TV_U2_005 -77.6829 162.79763 11/27/2010 1346 1004 W10_TV_U2_006 -77.68237 162.79747 11/27/2010 1344 1004 W10_TV_U2_008 -77.68287 162.80014 11/27/2010 1339 1004 W10_TV_U2_009 -77.68233 162.79998 11/27/2010 1342 1004 Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. Rhone Basalt -77.7 162.26357 1005 Location is approximate. BV_JFM 1006 BV_JFM 1006 BV_JFM 1006 CN 002 -76.8874 159.41236 1006 Location is approximate. INT_GRID Rocks -77.66031 162.81522 1006 INT2_GRID Pebbles from -77.66014 162.9232 1006 Surface Loose Rocks (x9) 1006 Taylor Valley Grid 1006 TV_JFM_03 1006 Unlabelled Bag 1006 MRS Basalt/Dolerite Fragments 1007 384 MRS Nussbaum Mntn. Samples 1007 MRS Random from Nussbaum 1007 MS_TV_003 1007 Salvatore KB 1007 W10_TV_B1_001 -77.70048 162.69642 11/27/2010 1207 1007 W10_TV_B1_005 -77.69991 162.69878 11/27/2010 1216 1007 W10_TV_B1_007 -77.70041 162.70146 11/27/2010 1213 1007 W10_TV_U1_004 -77.67475 162.81723 11/27/2010 1421 1007 W10_TV_U1_007 -77.67471 162.81974 11/27/2010 1423 1007 W10_TV_U1_008 -77.67418 162.81958 11/27/2010 1426 1007 W10_TV_U2_001 -77.68347 162.79528 11/27/2010 1331 1007 W10_TV_U2_007 -77.6834 162.80031 11/27/2010 1336 1007 Carapace Basalt -76.8874 159.41236 1008 Location is approximate. Carapace Basalt -76.8874 159.41236 1008 Location is approximate. Carapace Basalt -76.8874 159.41236 1008 Location is approximate. Carapace Basalt -76.8874 159.41236 1008 Location is approximate. Talyor Valley Basalt 1008 Talyor Valley Basalt 1008 Talyor Valley Basalt 1008 Talyor Valley Basalt 1008 Talyor Valley Basalt 1008 Talyor Valley Basalt 1008 Talyor Valley Basalt 1008 Talyor Valley Basalt 1008 Talyor Valley Basalt 1008 Victora Valley Dike Material 1008 Victora Valley Mafic Sample 1008 Victora Valley Mafic Sample 1008 Victora Valley Mafic Sample 1008 JFM South Fork 1009 MRS Rhone Glacier Volcanic 1009 Samples Mustard Alteration (Ship) 1009 Talyor Valley Basalt 1009 Carapace Basalt -76.8874 159.41236 1010 Location is approximate. Carapace Basalt -76.8874 159.41236 1010 Location is approximate. Carapace Basalt -76.8874 159.41236 1010 Location is approximate. Carapace Basalt -76.8874 159.41236 1010 Location is approximate. Carapace Basalt -76.8874 159.41236 1010 Location is approximate. Talyor Valley Basalt 1010 Talyor Valley Basalt 1010 385 Talyor Valley Basalt 1010 Talyor Valley Basalt 1010 Talyor Valley Basalt 1010 Talyor Valley Basalt 1010 Talyor Valley Basalt 1010 Talyor Valley Basalt 1010 Talyor Valley Basalt 1010 Upper Wright Mafic Sample 1010 Rhone Basalt -77.7 162.26357 1011 Location is approximate. Rhone Basalt -77.7 162.26357 1011 Location is approximate. Rhone Basalt -77.7 162.26357 1011 Location is approximate. Rhone Basalt -77.7 162.26357 1011 Location is approximate. Rhone Basalt -77.7 162.26357 1011 Location is approximate. Rhone Basalt -77.7 162.26357 1011 Location is approximate. Rhone Basalt -77.7 162.26357 1011 Location is approximate. Rhone Basalt -77.7 162.26357 1011 Location is approximate. Rhone Basalt -77.7 162.26357 1011 Location is approximate. Beacon Mafic Sample 1012 Carapace Basalt -76.8874 159.41236 1012 Location is approximate. Carapace Basalt -76.8874 159.41236 1012 Location is approximate. Carapace Basalt -76.8874 159.41236 1012 Location is approximate. Garnet-Bearing Dike -77.67587 162.79213 1012 Spectral Mix 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Talyor Valley Basalt 1012 Carapace Basalt -76.8874 159.41236 1013 Location is approximate. Carapace Basalt -76.8874 159.41236 1013 Location is approximate. Carapace Basalt -76.8874 159.41236 1013 Location is approximate. Carapace Basalt -76.8874 159.41236 1013 Location is approximate. Carapace Basalt -76.8874 159.41236 1013 Location is approximate. 386 Carapace Basalt -76.8874 159.41236 1013 Location is approximate. Carapace Basalt -76.8874 159.41236 1013 Location is approximate. Carapace Basalt -76.8874 159.41236 1013 Location is approximate. Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Talyor Valley Basalt 1013 Piqueux Victoria Dune Sand 1014 Sample Piqueux Victoria Dune Sand 1014 Sample W10_VV_D2_003 -77.40415 161.83224 11/7/2010 1323 1014 W10_VV_D2_007 -77.40518 161.8374 11/7/2010 1312 1014 W10_VV_D2_009 -77.4041 161.83717 11/7/2010 1328 1014 W10_VV_S1_001 -77.40425 161.8782 11/7/2010 1242 1014 W10_VV_S1_004 -77.40422 161.88066 11/7/2010 1235 1014 W10_VV_S1_005 -77.40368 161.88054 11/7/2010 1238 1014 W10_VV_S1_007 -77.4042 161.88312 11/7/2010 1232 1014 W10_LWV_F2_001 -77.47074 162.42657 10/28/2010 1344 1015 W10_LWV_F2_005 -77.47017 162.4289 10/28/2010 1408 1015 W10_LWV_F2_006 -77.46964 162.42876 10/28/2010 1352 1015 W10_LWV_F2_007 -77.47068 162.43152 10/28/2010 1402 1015 W10_LWV_F2_008 -77.47014 162.43137 10/28/2010 1359 1015 W10_LWV_F3_001 -77.47717 162.39627 10/28/2010 1258 1015 W10_LWV_F3_005 -77.4766 162.39861 10/28/2010 1253 1015 W10_LWV_F3_006 -77.47606 162.39846 10/28/2010 1250 1015 W10_LWV_F3_007 -77.4771 162.40122 10/28/2010 1314 1015 W10_LWV_F3_008 -77.47657 162.40108 10/28/2010 1311 1015 W10_LWV_F3_009 -77.47603 162.40094 10/28/2010 1308 1015 W10_LWV_F4_004 -77.47875 162.3585 10/28/2010 1149 1015 W10_LWV_F4_005 -77.47821 162.35836 10/28/2010 1145 1015 W10_LWV_F4_007 -77.47872 162.36098 10/28/2010 1152 1015 W10_LWV_F4_008 -77.47818 162.36083 10/28/2010 1154 1015 W10_LWV_F4_009 -77.47765 162.36069 10/28/2010 1157 1015 387 W10_LWV_F5_001 -77.49041 162.33731 10/27/2010 1227 1015 W10_LWV_F5_002 -77.48987 162.33717 10/27/2010 1230 1015 W10_LWV_F5_003 -77.48934 162.33703 10/27/2010 1206 1015 W10_LWV_F5_004 -77.49038 162.33979 10/27/2010 1224 1015 W10_LWV_F5_005 -77.48984 162.33965 10/27/2010 1234 1015 W10_LWV_F5_006 -77.48931 162.33951 10/27/2010 1210 1015 W10_LWV_F5_007 -77.49035 162.34226 10/27/2010 1220 1015 W10_LWV_F5_008 -77.48981 162.34212 10/27/2010 1216 1015 W10_LWV_F5_009 -77.48928 162.34198 10/27/2010 1213 1015 "Piqueux" 1016 "Piqueux" 1016 MRS TV Dolerite Alt. Rind #1 1016 MRS TV Dolerite Alt. Rind #2 1016 MRS TV Dolerite Alt. Rind #3 1016 MRS TV Dolerite Alt. Rind #4 1016 MRS TV Dolerite Alt. Rind #5 1016 MRS TV Dolerite Alt. Rind #6 1016 MRS TV Dolerite Alt. Rind #7 1016 MRS TV Dolerite Alt. Rind #8 1016 MRS TV Dolerite Alt. Rind #9 1016 PQX Nussbaum Riegal 1016 "PQX TV" 1017 "PQX TV" 1017 MRS Dunes Samples 1017 MRS VV Dolerite Trench #1 1017 MRS VV Dolerite Trench #2 1017 W10_BP_G2_002 -77.4998 161.91548 11/11/2010 1238 1017 W10_BP_G2_003 -77.49926 161.91536 11/11/2010 1234 1017 W10_BP_G2_006 -77.49923 161.91784 11/11/2010 1231 1017 W10_BP_G2_009 -77.49921 161.92032 11/11/2010 1229 1017 W10_BP_G3_001 -77.50457 161.8881 11/11/2010 1327 1017 W10_BP_G3_003 -77.50349 161.88785 11/11/2010 1312 1017 W10_BP_G3_004 -77.50454 161.89058 11/11/2010 1325 1017 W10_BP_G3_005 -77.504 161.89046 11/11/2010 1329 1017 W10_BP_G3_008 -77.50398 161.89294 11/11/2010 1321 1017 W10_BP_D1_001 -77.47781 161.83462 11/9/2010 1131 1018 W10_BP_D1_002 -77.47728 161.8345 11/9/2010 1133 1018 W10_BP_D1_003 -77.47674 161.83438 11/9/2010 1115 1018 W10_BP_D1_004 -77.47779 161.8371 11/9/2010 1128 1018 W10_BP_D1_005 -77.47725 161.83698 11/9/2010 1135 1018 W10_BP_D1_008 -77.47723 161.83945 11/9/2010 1123 1018 388 W10_BP_D1_009 -77.47669 161.83933 11/9/2010 1120 1018 W10_BP_D2_004 -77.45458 161.75072 11/9/2010 1312 1018 W10_BP_D2_006 -77.4535 161.75049 11/9/2010 1256 1018 W10_BP_G1_001 -77.47607 161.79772 11/9/2010 1205 1018 W10_BP_G1_002 -77.47554 161.7976 11/9/2010 1207 1018 W10_BP_G1_003 -77.475 161.79748 11/9/2010 1210 1018 W10_BP_G1_004 -77.47605 161.80019 11/9/2010 1202 1018 W10_BP_G1_005 -77.47551 161.80008 11/9/2010 1215 1018 W10_BP_G1_006 -77.47497 161.79996 11/9/2010 1212 1018 W10_BP_G1_007 -77.47602 161.80267 11/9/2010 1159 1018 W10_BP_G1_008 -77.47548 161.80255 11/9/2010 1156 1018 W10_BP_G1_009 -77.47495 161.80243 11/9/2010 1154 1018 W10_BP_U3_001 -77.47243 161.73308 11/9/2010 1113 1018 W10_BP_U3_002 -77.47189 161.73297 11/9/2010 1110 1018 W10_BP_U3_003 -77.47135 161.73285 11/9/2010 1106 1018 W10_BP_U3_005 -77.47187 161.73544 11/9/2010 1139 1018 W10_BP_U3_006 -77.47133 161.73533 11/9/2010 1136 1018 W10_LWV_F1_001 -77.46269 162.4638 10/27/2010 1626 1019 W10_LWV_F1_002 -77.46216 162.46365 10/27/2010 1629 1019 W10_LWV_F1_003 -77.46162 162.46351 10/27/2010 1632 1019 W10_LWV_F1_004 -77.46266 162.46627 10/27/2010 1623 1019 W10_LWV_F1_006 -77.46159 162.46598 10/27/2010 1635 1019 W10_LWV_F1_007 -77.46263 162.46874 10/27/2010 1619 1019 W10_LWV_F1_008 -77.46209 162.46859 10/27/2010 1641 1019 W10_LWV_F1_009 -77.46156 162.46845 10/27/2010 1638 1019 W10_LWV_F2_002 -77.47021 162.42643 10/28/2010 1347 1019 W10_LWV_F2_003 -77.46967 162.42628 10/28/2010 1350 1019 W10_LWV_F2_004 -77.470711 162.42904 10/28/2010 1404 1019 W10_LWV_F2_009 -77.46961 162.43123 10/28/2010 1355 1019 W10_LWV_F3_002 -77.47663 162.39613 10/28/2010 1302 1019 W10_LWV_F3_003 -77.47609 162.39599 10/28/2010 1304 1019 W10_LWV_F4_001 -77.47878 162.35603 10/28/2010 1141 1019 W10_LWV_F4_002 -77.47824 162.35588 10/28/2010 1206 1019 W10_LWV_F4_003 -77.47771 162.35574 10/28/2010 1204 1019 W10_LWV_F4_006 -77.47768 162.35822 10/28/2010 1201 1019 Piqueux Ash/Clay (Black Bag) 1020 W10_TV_D1_004 -77.65618 162.87367 11/14/2010 1455 1020 W10_TV_D1_006 -77.65511 162.87334 11/14/2010 1445 1020 W10_TV_D2_004 -77.64947 162.93686 11/14/2010 1240 1020 W10_TV_G1_001 -77.67269 162.75122 1020 W10_TV_G1_002 -77.67215 162.75106 1020 389 W10_TV_G1_005 -77.67212 162.75358 1020 W10_TV_G1_008 -77.67208 162.75609 1020 W10_TV_S1_002 -77.67748 162.7424 1020 W10_TV_S1_004 -77.67799 162.74508 1020 W10_TV_S1_008 -77.67742 162.74743 1020 W10_TV_S1_009 -77.67688 162.74727 1020 W10_TV_U3_004 -77.65953 162.7556 1020 W10_TV_U3_007 -77.65949 162.75811 1020 W10_LWV_F3_004 -77.47713 162.39875 10/28/2010 1255 1021 W10_TV_D1_002 -77.65568 162.871 11/14/2010 1440 1021 W10_TV_D1_005 -77.65565 162.87351 11/14/2010 1457 1021 W10_TV_D1_007 -77.65615 162.87618 11/14/2010 1452 1021 W10_TV_D2_005 -77.64894 162.93669 11/14/2010 1243 1021 W10_TV_D2_006 -77.6484 162.93652 11/14/2010 1232 1021 W10_TV_D2_007 -77.64944 162.93937 11/14/2010 1238 1021 W10_TV_D2_009 -77.64837 162.96903 11/14/2010 1234 1021 W10_TV_G1_004 -77.67265 162.75374 1021 W10_TV_G1_007 -77.67262 162.75625 1021 W10_TV_S1_003 -77.67695 162.74224 1021 W10_TV_S1_005 -77.67745 162.74492 1021 W10_TV_S1_006 -77.67691 162.74475 1021 W10_TV_S1_007 -77.67795 162.74759 1021 W10_TV_U3_002 -77.65902 162.75293 1021 W10_TV_U3_006 -77.65845 162.75528 1021 W10_TV_U3_008 -77.65896 162.75795 1021 W10_TV_U3_009 -77.65842 162.75778 1021 W10_TV_U4_001 -77.6618 162.92368 11/14/2010 1350 1021 W10_TV_U4_004 -77.66176 162.92619 11/14/2010 1348 1021 W10_TV_U4_007 -77.66172 162.9287 11/14/2010 1346 1021 W10_TV_U4_008 -77.66119 162.92853 11/14/2010 1344 1021 W10_TV_U4_009 -77.66065 162.92836 11/14/2010 1342 1021 MRS Dolerites (CTZ) 1022 W10_BP_D3_001 -77.50286 161.8541 11/11/2010 1058 1022 W10_BP_D3_002 -77.50233 161.85398 11/11/2010 1055 1022 W10_BP_D3_003 -77.50179 161.85386 11/11/2010 1053 1022 W10_BP_D3_004 -77.50284 161.85658 11/11/2010 1101 1022 W10_BP_D3_005 -77.5023 161.85646 11/11/2010 1114 1022 W10_BP_D3_007 -77.50281 161.85906 11/11/2010 1103 1022 W10_BP_D3_008 -77.50227 161.85894 11/11/2010 1105 1022 W10_BP_D3_009 -77.50174 161.85882 11/11/2010 1108 1022 W10_BP_G2_001 -77.50033 161.9156 11/11/2010 1218 1022 390 W10_BP_G2_004 -77.50031 161.91808 11/11/2010 1222 1022 W10_BP_G2_005 -77.49977 161.91796 11/11/2010 1236 1022 W10_BP_G2_007 -77.50028 161.92056 11/11/2010 1224 1022 W10_BP_G2_008 -77.49974 161.92044 11/11/2010 1226 1022 W10_BP_G3_002 -77.50403 161.88798 11/11/2010 1331 1022 W10_BP_G3_006 -77.50346 161.89034 11/11/2010 1317 1022 W10_BP_G3_007 -77.50451 161.89306 11/11/2010 1323 1022 W10_BP_G3_009 -77.50344 161.89282 11/11/2010 1319 1022 Carapace Nunatak 001 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 003 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 004 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 005 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 006 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 007 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 007B -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 010 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 0105 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 010A -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 010C -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 010E -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak 011 -76.8874 159.41236 1023 Location is approximate. Carapace Nunatak Float 1 -76.8874 159.41236 1023 Location is approximate. Garnets on Dike Swarm -77.67587 162.79213 1023 Unlabelled Bag 1023 MRS Carapace 1024 Sandstone/Conglomerate MS_CN_001 -76.8874 159.41236 1024 Location is approximate. MS_CN_002 -76.8874 159.41236 1024 Location is approximate. MS_CN_003 -76.8874 159.41236 1024 Location is approximate. MS_CN_004 -76.8874 159.41236 1024 Location is approximate. MS_CN_005 -76.8874 159.41236 1024 Location is approximate. MS_CN_006 -76.8874 159.41236 1024 Location is approximate. MS_CN_007 -76.8874 159.41236 1024 Location is approximate. MS_CN_008A -76.8874 159.41236 1024 Location is approximate. MS_CN_008B -76.8874 159.41236 1024 Location is approximate. MS_CN_010 -76.8874 159.41236 1024 Location is approximate. MS_CN_011 -76.8874 159.41236 1024 Location is approximate. MS_CN_012A-E -76.8874 159.41236 1024 Location is approximate. MS_CN_013 -76.8874 159.41236 1024 Location is approximate. MS_CN_014 -76.8874 159.41236 1024 Location is approximate. MS_CN_015 -76.8874 159.41236 1024 Location is approximate. 391 MS_CN_016 -76.8874 159.41236 1024 Location is approximate. MS_CN_017 -76.8874 159.41236 1024 Location is approximate. MS_CN_018 -76.8874 159.41236 1024 Location is approximate. MS_CN_019 -76.8874 159.41236 1024 Location is approximate. MS_CN_020 -76.8874 159.41236 1024 Location is approximate. MS_CN_021 -76.8874 159.41236 1024 Location is approximate. MS_CN_022 -76.8874 159.41236 1024 Location is approximate. MS_CN_023 -76.8874 159.41236 1024 Location is approximate. MS_CN_024 -76.8874 159.41236 1024 Location is approximate. MS_CN_025 -76.8874 159.41236 1024 Location is approximate. W10_VV_C1_001 -77.36862 161.8007 11/2/2010 1445 1025 W10_VV_C1_003 -77.36754 161.80046 11/2/2010 1449 1025 W10_VV_C1_008 -77.36803 161.80549 11/2/2010 1456 1025 W10_VV_C1_004 -77.36859 161.80315 11/2/2010 1501 1025 W10_VV_D1_001 -77.39529 161.7506 11/4/2010 1425 1025 W10_VV_D1_002 -77.39476 161.75049 11/4/2010 1422 1025 W10_VV_D1_003 -77.39422 161.75037 11/4/2010 1420 1025 W10_VV_D1_004 -77.39527 161.75306 11/4/2010 1428 1025 W10_VV_D1_005 -77.39473 161.75295 11/4/2010 1443 1025 W10_VV_D1_006 -77.3942 161.75283 11/4/2010 1441 1025 W10_VV_D1_007 -77.39524 161.75552 11/4/2010 1431 1025 W10_VV_D1_008 -77.39471 161.75541 11/4/2010 1434 1025 W10_VV_D1_009 -77.39417 161.75529 11/4/2010 1437 1025 W10_VV_DS1_002 -77.40008 161.92985 1025 W10_VV_DS1_001 -77.40264 161.92167 1025 W10_VV_DS1_006 -77.39859 161.9411 11/3/2010 1319 1025 W10_VV_S2_001 -77.40273 161.95554 11/3/2010 1245 1025 W10_VV_S2_002 -77.40219 161.95541 11/3/2010 1247 1025 W10_VV_S2_004 -77.4027 161.958 11/3/2010 1242 1025 W10_VV_S2_005 -77.40216 161.95788 11/3/2010 1239 1025 W10_VV_S2_006 -77.40163 161.95775 11/3/2010 1229 1025 W10_VV_S2_007 -77.40267 161.96046 11/3/2010 1236 1025 W10_VV_S2_008 -77.40214 161.96034 11/3/2010 1233 1025 W10_VV_S2_009 -77.4016 161.96021 11/3/2010 1231 1025 W10_LWV_F1_005 -77.46212 162.46612 10/27/2010 1644 1026 W10_LWV_U1_001 -77.42539 162.6838 10/30/2010 1251 1026 W10_LWV_U1_002 -77.42486 162.68365 10/30/2010 1243 1026 W10_LWV_U1_003 -77.42432 162.6835 10/30/2010 1240 1026 W10_LWV_U1_004 -77.42536 162.68627 10/30/2010 1248 1026 W10_LWV_U1_005 -77.42482 162.68611 10/30/2010 1246 1026 W10_LWV_U1_006 -77.42429 162.68596 10/30/2010 1238 1026 392 W10_LWV_U1_007 -77.42533 162.68873 10/30/2010 1230 1026 W10_LWV_U1_008 -77.42479 162.68858 10/30/2010 1232 1026 W10_LWV_U1_009 -77.42425 162.68842 10/30/2010 1235 1026 W10_LWV_U3_001 -77.41878 162.67222 10/30/2010 1115 1026 W10_LWV_U3_002 -77.41825 162.67206 10/30/2010 1135 1026 W10_LWV_U3_003 -77.41771 162.67191 10/30/2010 1132 1026 W10_LWV_U3_004 -77.41875 162.67468 10/30/2010 1118 1026 W10_LWV_U3_005 -77.41821 162.67452 10/30/2010 1138 1026 W10_LWV_U3_006 -77.41768 162.67437 10/30/2010 1129 1026 W10_LWV_U3_007 -77.41872 162.67714 10/30/2010 1121 1026 W10_LWV_U3_008 -77.41818 162.67699 10/30/2010 1123 1026 W10_LWV_U3_009 -77.41764 162.67683 10/30/2010 1126 1026 W10_VV_A1_001 -77.36784 161.7407 11/2/2010 1111 1027 W10_VV_A1_002 -77.3673 161.74059 11/2/2010 1114 1027 W10_VV_A1_003 -77.36677 161.74047 11/2/2010 1116 1027 W10_VV_A1_004 -77.36781 161.74316 11/2/2010 1109 1027 W10_VV_A1_005 -77.36728 161.74304 11/2/2010 1124 1027 W10_VV_A1_006 -77.36674 161.74293 11/2/2010 1118 1027 W10_VV_A1_007 -77.36779 161.74561 11/2/2010 1107 1027 W10_VV_A1_008 -77.36725 161.7455 11/2/2010 1122 1027 W10_VV_A1_009 -77.36672 161.74538 11/2/2010 1120 1027 W10_VV_C1_002 -77.36808 161.80058 11/2/2010 1447 1027 W10_VV_C1_005 -77.36806 161.80304 11/2/2010 1503 1027 W10_VV_C1_006 -77.36752 161.80292 11/2/2010 1451 1027 W10_VV_C1_007 -77.36857 161.80561 11/2/2010 1458 1027 W10_VV_C1_009 -77.36749 161.80537 11/2/2010 1454 1027 W10_VV_DS1_003 -77.3981 161.93597 11/3/2010 1323 1027 W10_VV_DS1_004 -77.40303 161.92621 11/3/2010 1307 1027 W10_VV_DS1_005 -77.39859 161.9411 11/3/2010 1313 1027 W10_VV_S2_003 -77.40165 161.95529 11/3/2010 1226 1027 W10_BP_D1_006 -77.47671 161.83686 11/9/2010 1117 1028 W10_BP_D1_007 -77.47776 161.83957 11/9/2010 1126 1028 W10_BP_D2_001 -77.4546 161.74825 11/9/2010 1310 1028 W10_BP_D2_003 -77.45353 161.74802 11/9/2010 1300 1028 W10_BP_D2_007 -77.45455 161.75319 11/9/2010 1247 1028 W10_BP_D2_008 -77.45402 161.75308 11/9/2010 1250 1028 W10_BP_D2_009 -77.45348 161.75296 11/9/2010 1253 1028 W10_BP_U3_004 -77.4724 161.73556 11/9/2010 1117 1028 W10_BP_U3_007 -77.47238 161.73803 11/9/2010 1120 1028 W10_BP_U3_008 -77.47184 161.73792 11/9/2010 1124 1028 W10_BP_U3_009 -77.4713 161.7378 11/9/2010 1133 1028 393 W10_VV_D2_001 -77.40523 161.83248 11/7/2010 1317 1028 W10_VV_D2_002 -77.40469 161.83236 11/7/2010 1320 1028 W10_VV_D2_004 -77.4052 161.83494 11/7/2010 1315 1028 W10_VV_D2_005 -77.40466 161.83482 11/7/2010 1332 1028 W10_VV_D2_006 -77.40413 161.83471 11/7/2010 1326 1028 W10_VV_D2_008 -77.40464 161.83729 11/7/2010 1309 1028 W10_VV_S1_002 -77.40371 161.87808 11/7/2010 1219 1028 W10_VV_S1_003 -77.40317 161.87796 11/7/2010 1222 1028 W10_VV_S1_006 -77.40315 161.88042 11/7/2010 1224 1028 W10_VV_S1_008 -77.40366 161.883 11/7/2010 1230 1028 W10_VV_S1_009 -77.40312 161.88288 11/7/2010 1227 1028 Loose Rocks (x2) 1029 PQX (B) 1029 Unbagged Sandstone with 1029 Layering W10_TV_D1_001 -77.65622 162.87116 11/14/2010 1438 1029 W10_TV_D1_003 -77.65515 162.87083 11/14/2010 1443 1029 W10_TV_D1_008 -77.65561 162.87601 11/14/2010 1450 1029 W10_TV_D1_009 -77.65508 162.87585 11/14/2010 1447 1029 W10_TV_D2_001 -77.64951 162.93435 11/14/2010 1248 1029 W10_TV_D2_002 -77.64897 162.93418 11/14/2010 1245 1029 W10_TV_D2_003 -77.64844 162.93402 11/14/2010 1230 1029 W10_TV_D2_008 -77.6489 162.9392 11/14/2010 1236 1029 W10_TV_G1_003 -77.67161 162.7509 1029 W10_TV_G1_006 -77.67158 162.75341 1029 W10_TV_G1_009 -77.67154 162.75593 1029 W10_TV_S1_001 -77.67802 162.74256 1029 W10_TV_U3_001 -77.65956 162.75309 1029 W10_TV_U3_003 -77.65849 162.75276 1029 W10_TV_U3_005 -77.65899 162.75544 1029 W10_TV_U4_002 -77.66126 162.92351 11/14/2010 1351 1029 W10_TV_U4_003 -77.66072 162.92334 11/14/2010 1338 1029 W10_TV_U4_005 -77.66122 162.92602 11/14/2010 1353 1029 DB Samples 1030 JLD Hand Samples 1030 JLD Hand Samples 1030 MRS TV Dolerite ("Genesis -77.66422 162.80101 1001 Rock") MS10_BV_02 -77.86028 160.57066 1001 MS10_BV_05A&B -77.86455 160.56027 1001