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The Application of Silica Δ'17o and Δ18o Towards Paleo- Environmental Reconstructions

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The Application of Silica Δ'17o and Δ18o Towards Paleo- Environmental Reconstructions The application of silica Δ'17O and δ18O towards paleo- environmental reconstructions The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Liljestrand, Frasier. 2019. The application of silica Δ'17O and δ18O towards paleo-environmental reconstructions. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:42013151 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA 0 The application of silica Δ 17O and δ18O towards paleo-environmental reconstructions a dissertation presented by Frasier L. Liljestrand to The Department of Earth and Planetary Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Earth and Planetary Sciences Harvard University Cambridge, Massachusetts August 2019 © 2019 - Frasier L. Liljestrand All rights reserved. Thesis advisor: David T. Johnston Frasier L. Liljestrand 0 The application of silica Δ 17O and δ18O towards paleo-environmental reconstructions Abstract The oxygen isotope composition of silica provides a valuable record of the temperature at which it precipitated and the isotopic composition of the fluid 18 with which it equilibrated. This temperature-δ OH2O pair, however, is non-unique. The chert δ18O record shows a robust quasi-linear increase through time, but this signal has been interpreted as reflecting either cooling oceans, 0 shifting marine δ18O composition, or diagenesis. We suggest that Δ 17O measurements may resolve this uncertainty. In chapter 2 we collect Precambrian chert from many well preserved Precambrian deposits and measure their δ18O 0 and Δ 17O. Given equilibrium thermodynamic predictions for chert O-isotope evolution as a function of precipitation temperature, ocean O-isotope evolution, and diagenesis, we applied a Monte Carlo re-sampling model to test these alternate hypotheses. The results indicate the chert O-isotope record is best described as a product of alteration with higher-temperature, meteoric-derived groundwater. Neither changes in seawater temperature nor changes in seawater O-isotope composition are required. While this result is applicable to the Precambrian, it may not be useful in interpreting Phanerozoic data. We must first determine whether biological 0 fractionation imposes a significant vital effect in Δ 17O. In chapter 3 we measure 0 the δ18O and Δ 17O of diatom frustules from semi-continuous cultures. To iii Thesis advisor: David T. Johnston Frasier L. Liljestrand ascertain the degree of natural variability we measured the O-isotope composition from two different diatom species across a range of growth rates and temperatures. Variations in the cultured growth rate and species produced no 0 significant signal in the frustule δ18O or Δ 17O. Temperature variations in the culture, however, do produce a measurable O-isotope fractionation. The absolute 0 value of the measured Δ 17O compositions were systematically negative with respect to the thermodynamic prediction. This offset we interpret to represent a vital effect which may be produced by the silica concentrating mechanisms diatoms use to precipitate their frustules. These results confirm the utility of 0 diatom δ18O in reconstructing temperature, but suggest that Δ 17O may not be a 0 suitable temperature proxy for diatomaceous sediment. Instead, Δ 17O may be used to distinguish biologically from abiologically precipitated silica. In chapter 4 we analyze carbon isotope fractionations from the stratigraphy immediately following the Neoproterozoic Marinoan snowball Earth event. We observe a temporary excursion where εp is anomalously small due to an interval 13 of heavy δ Corg deposition. This signal may reflect the unique biogeochemical conditions that persisted in the aftermath of snowball Earth. To explain this record, we developed a model that tracks the fluxes and isotopic values of carbon between the surface ocean, deep ocean, and atmosphere. From this, we conclude the post-Marinoan conditions will not intrinsically generate the observed 13 isotopic signal. Reproducing the heavy δ Corg requires the progressively diminishing contribution of an additional anomalous source of organic matter. iv Contents Abstract................................. iii Contents ................................ v Author List . vii ListingofFigures ............................ viii Dedication . x Acknowledgements . xi 1 Introduction 1 1.1 Ocean and geologic record . 2 1.2 Evolution of the Earth’s surface . 3 1.3 Isotope methods . 5 1.4 Carbon cycle . 9 1.5 Oxygen cycle . 10 1.6 Preservation of sedimentary isotope records . 11 1.7 Focus and summary of the current thesis . 12 2 The triple oxygen isotope composition of Precambrian chert 14 2.1 Abstract . 15 2.2 Introduction . 16 2.3 Methods . 18 2.4 Results and Discussion . 22 2.5 Geological Scenarios . 27 2.6 Conclusion . 44 v 2.7 Additional Information . 47 3 Calibrating the triple oxygen isotope vital effect in cul- tured diatoms 69 3.1 Abstract . 70 3.2 Introduction . 71 3.3 Methods . 75 3.4 Results and discussion . 85 3.5 Environmental significance . 96 3.6 Conclusion . 101 3.7 Additional Information . 102 4 Isotopically anomalous organic carbon in the aftermath of the Marinoan Snowball Earth 107 4.1 Abstract . 108 4.2 Introduction . 109 4.3 Geological setting . 111 4.4 Analytical methods . 114 4.5 Geochemical results . 115 4.6 Discussion . 117 4.7 Conclusion . 132 4.8 Additional information . 134 5 Conclusion and future directions 155 References 188 vi Author List The following authors contributed to Chapter 2: Frasier L. Liljestrand, Andrew H. Knoll, Nicholas J. Tosca, Phoebe A. Cohen, Francis A. Macdonald, Yongbo Peng, David T. Johnston. The following authors contributed to Chapter 3: Frasier L. Liljestrand, Anxhela Hania, Mario Giordano, David T. Johnston. The following authors contributed to Chapter 4: Frasier L. Liljestrand, Francis A. Macdonald, Daniel P. Schrag, Thomas A. Laakso, David T. Johnston. vii Listing of figures 2.4.1 Chert δ18O temporal trend . 23 2.4.2 Chert silica fraction . 25 2.5.1 Temperature change and ocean O-isotope change hypothesis . 28 2.5.2 Evolution of seawater Δ’17O................... 31 2.5.3 Model of diagenetic alteration . 33 0 2.5.4 Alteration of chert in δ18O-Δ 17O space . 36 2.5.5 Distribution of stochastic model . 39 2.5.6 Results of stochastic model . 41 2.5.7 Comparison of δ18O from stochastic prediction and measured value 43 2.7.1 Harvard-LSU oxygen isotope comparison . 57 2.7.2 Fifteenmile O-isotope stratigraphy . 58 2.7.3 Chert Δ17O equilibrium temperature prediction . 59 2.7.4 Monte Carlo best fit precipitation temperature . 59 2.7.5 Comparison of chert δ30Si to O-isotope compositions . 60 3.3.1 O2 pressure evolution during prefluorination . 82 3.3.2 O2 isotope evolution during prefluorination . 83 3.4.1 Carbon isotope composition of diatom biomass . 87 3.4.2 18 vs temperature relationship of diatom frustules . 91 0 3.4.3 Δ 17O sensitivity of diatom species and growth rate . 92 0 3.4.4 Δ 17O sensitivity of diatom temperature . 94 3.4.5 Relationship between measured θ and temperature . 95 viii 3.7.1 18O temperature sensitivity of each individual diatom species . 105 3.7.2 Residual of 18O with respect to temperature . 106 3.7.3 Residual of 18O with respect to temperature . 106 4.3.1 Stratigraphic and isotope data from the Sheepbed and Ol forma- tions ............................... 112 4.6.1 Structure of the carbon isotope model . 119 4.6.2 carbon isotope model results . 122 4.8.1 Literature C-isotope data . 135 4.8.2 Temporal evolution of carbon cycle model . 137 4.8.3 Temporal evolution of carbon cycle model . 142 4.8.4 Carbon model sensitivity testing part 1 . 146 4.8.5 Carbon model sensitivity testing part 2 . 149 4.8.6 Carbon model sensitivity testing part 3 . 151 4.8.7 Carbon model sensitivity testing part 4 . 153 ix To my mother Blinda. Who is never afraid to lead but at the same time taught me to explore my own path. To my father Howard. Who in quiet moments and when I need it the most supports me more strongly than anyone. To my sister Emily. My best friend who is always there for me, my closest companion with whom I always overcome obstacles and share triumphs. x Acknowledgments First and foremost I would like to thank my advisor Dave Johnston for guiding me through this process. He was always patient and considerate with me. He taught me how to think as a scientist and I am grateful for his efforts shaping the person I am today. I wish I had developed the habit of watching the Red Sox; our conversations would probably have flowed more easily if we’d had that to share. I want to deeply thank all the Lab members of the Johnston lab, present and former. Thank you Ben Cowie for mentoring me when I decided to study triple oxygen isotope systematics before I really understood how isotopes worked. You were sometimes so supportive of me that I thought you were maybe being sarcastic. Thank you Andy Masterson for showing me its possible to be bothan excellent grad student and a mature functioning adult. Thank you Erin Beirne for sharing your office with me, you made it a joy to come to work every day. Thank you Emma Bertran for every time you shared your food, growing up with a twin I am used to having someone with me experiencing life at the same pace, you being in the same year, along with me for the ride, helped me greatly over the course of my PhD.
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