Amino Acid Racemization of Planktonic Foraminifera

AMINO ACID RACEMIZATION OF PLANKTONIC FORAMINIFERA:

PRETREATMENT EFFECTS AND TEMPERATURE RECONSTRUCTIONS

Emily Watson

A thesis submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Master of Science in Marine Studies

Spring 2019

AMINO ACID RACEMIZATION OF PLANKTONIC FORAMINIFERA:

PRETREATMENT EFFECTS AND TEMPERATURE RECONSTRUCTIONS

Emily Watson

Approved: ______Katharina Billups, Ph.D. Professor in charge of thesis on behalf of the Advisory Committee

Approved: ______Mark Moline, Ph.D. Chair of the Department of Marine Science and Policy

Approved: ______Estella Atekwana, Ph.D. Dean of the College of Earth, Ocean, and Environment

Approved: ______Douglas J. Doren, Ph.D. Interim Vice Provost for Graduate and Professional Education ACKNOWLEDGMENTS

Very special thanks to my M.S. advisor Dr. Katharina Billups for providing me with this amazing opportunity and giving me her utmost support. Her willingness to give her time so generously has been indispensable during my Masters. She is my ultimate scientific role model. I am grateful for my collaborators from Northern Arizona University, Dr. Darrell Kaufman and Katherine Whitacre, who taught me the cleaning methods for this project and opened up their lab to me in January 2018. I would like to express my appreciation to Dr. Kaufman for his valuable and constructive suggestions during the planning and development of this research work. Data provided by Katherine was very valuable. I would also like to thank Dr. Doug Miller, and Dr. Andrew Wozniak, Dr. John

Wehmiller from the University of Delaware for their assistance with this project. Dr. Wozniak has been an important part of my committee, especially from the organic chemistry side of things. Dr. Miller gave advice on the development of the statistical tests used in this study. Input from Dr. John Wehmiller (Emeritus) was especially appreciated as he is well-known in the field of amino acid geochronology. I wish to acknowledge funding of this research and first thank the donors of the Petroleum Research Fund (PRF #56964-ND), administered by the American Chemical Society ACS. I also wish to acknowledge the School of Marine Science and Policy at the

University of Delaware for their continued support and travel funding over the past 2 years.

iii Nobody has been more important to me in the pursuit of this project than my friends and family. I would like to thank my parents, whose love and guidance are with me in whatever I pursue. Most importantly, I wish to thank my loving husband, TJ, who has provided me unending support and encouragement through this journey. I also would like to make a quick shout-out to my lab mates, Maoli Vizcaíno and Emily Kaiser, who always bring a positive atmosphere to the lab and plenty of laughs.

iv TABLE OF CONTENTS

LIST OF TABLES ...... vii LIST OF FIGURES ...... ix ABSTRACT ...... xiv

Chapter

1 INTRODUCTION ...... 1

2 BACKGROUND ...... 5

2.1 Amino Acid Racemization (AAR)...... 5 2.2 Application of Amino Acid Racemization ...... 7

2.2.1 Amino Acid Geochronology ...... 7 2.2.2 Amino Acid Thermometry ...... 10

2.3 Amino Acid Racemization Kinetics ...... 12 2.4 Determination of the EDT ...... 14 2.5 Pretreatment Methods ...... 16

3 RESEARCH STRATEGY ...... 19

3.1 Site Selection and Modern Hydrography ...... 19 3.2 Species Selection ...... 22 3.3 Sampling Strategy ...... 24 3.4 Analytical Methods ...... 28

3.4.1 Foraminiferal Picking ...... 28 3.4.2 Pretreatment Methods ...... 28

3.4.2.1 Non-bleached Method ...... 28 3.4.2.2 Bleached Method ...... 29

3.4.3 Analysis on HPLC ...... 29 3.4.4 Radiocarbon Dating ...... 30

4 COMPARISON OF 14C AGES AND PUBLISHED STRATIGRAPHY ...... 32

5 PRETREATMENT ANALYSIS ...... 37

v 5.1 Effect of Bleaching on the Subsample Rejection Rate ...... 37 5.2 Effect of Bleaching on the Concentration of Amino Acids ...... 40 5.3 Effect of Bleaching on the D/L Ratios by Species ...... 44 5.4 Effect of Bleaching on the Variability of D/L Ratios of Subsamples within a Sample ...... 53 5.5 Effect of Bleaching on Species Differences in D/L ...... 56 5.6 Down-Core Trend ...... 63 5.7 Discussion of Pretreatment Analyses ...... 65 5.8 Summary ...... 67

6 APPLICATION TO PALEOTHERMOMETRY ...... 69

6.1 Determination of the Effective Diagenetic Temperatures ...... 69 6.2 Paleotemperature Uncertainties and Trend Selection ...... 78 6.3 Temperature Histories ...... 83 6.4 Paleoceanographic Implications ...... 84

6.4.1 Comparison with Other Records of Bottom Water Temperature 84 6.4.2 Deep Water Circulation ...... 86

6.5 Summary ...... 88

7 CONCLUSION ...... 91

REFERENCES ...... 94

Appendix

A SUPPLEMENTARY TABLES AND FIGURES ...... 107

vi LIST OF TABLES

Table 1. Site information for ODP Cores 1056D, 1059A, and 1062B from the Blake-Bahama Outer Ridge...... 21

Table 2. Summary of interval, depth in core, and stratigraphic age for sites used in this study. Stratigraphic ages for Holocene and down-core samples are 18 determined from %CaCO3 orbitally tuned (Grützner et al. 2002) and δ O stratigraphy (Hagen and Keigwin 2002; Billups et al. 2004), respectively.26

Table 3. Rapid 14C age measurements compared to δ18O (Hagen and Keigwin 2002; Billups et al. 2004) and %CaCO3 orbitally tuned (Grützner et al. 2002) age models...... 36

Table 4. Percent of subsamples rejected. The species in red show higher rejection rates in the bleached samples than unbleached samples. Data used to determine the subsample rejection rate are shown in Table A2...... 39

Table 5. Mean D/L values for the unbleached (unbl) and bleached (bl) treatments with the statistical results of Welch’s independent t-tests...... 51

Table 6. Results of two-way replicated ANOVA models to determine the effects of the different pretreatments on the D/L ratios...... 52

Table 7. Average sample variability (coefficient of variation, CV) in Holocene and down-core sites for both pretreatments (unbleached = unbl and bleached = bl). Data used to calculate the average variability are shown in Table A6...... 55

Table 8. Results of Welch’s independent t-tests to determine the species effects on the D/L ratios...... 61

Table 9. Effective diagenetic temperatures (EDTs) and uncertainties in °C derived from amino acid paleothermometry of P. obliquiloculata and G. truncatulinoides for 2000 m (Site 1056) and 3000 m (Site 1059A/JPC- 37) water depths. Sample ages and D/L values for the bracketed time intervals used to calculate the EDTs are included...... 76

Table A1. Subsample D/L values used for bleached and unbleached comparison.109

vii Table A2. Data used to determine the effect of the bleaching pretreatment on the subsample rejection rate...... 124

Table A3. Average concentration of amino acids in pmol/test. Data are from Table A4...... 125

Table A4. Subsample amino acid abundances in pmol/test, excluding rejected subsamples and those with missing data...... 127

Table A5. Average aspartic acid (Asp) and glutamic acid (Glu) D/L values for both pretreatments, including the standard deviation of the subsamples. Subsample values are in Table A1...... 144

Table A6. Sample variability in Holocene and down-core sites represented as the coefficient of variation (CV)...... 147

viii LIST OF FIGURES

Figure 1. Mechanism of amino acid racemization modeled after Bada and Schroeder (1975). The α-proton is abstracted from the L-amino acid to form the carbanion intermediate. Upon the re-addition of the proton, the D-amino acid is formed. This process is reversible and can form the L- amino acid...... 4

Figure 2. Example Arrhenius plot for aspartic (Asp) and glutamic acids (Glu). Data was obtained from laboratory heated and 14C dated P. obliquiloculata tests from Kaufman (2006)...... 18

Figure 3. Map of the ODP sites at the Blake-Bahama Outer Ridge modified from Franz and Tiedemann (2002). Sites 1056, 1059, and 1062 (circled) are used in this study...... 20

Figure 4. Modern bottom water temperatures at depths of Sites 1056, 1059, and 1062 (Levitus and Boyer 1994), used in this thesis. The zonation of modern water masses in the western subtropical North Atlantic are modeled after Keigwin et al. (1998)...... 21

Figure 5. Scanning electron microscope (SEM) images of the foraminiferal species P. obliquiloculata (A), G. truncatulinoides (B), and G. tumida (C) by Kennett and Srinivasan (1983)...... 23

Figure 6. Carbonate content (% CaCO3) of the sediment records at Sites 1056, 1059, and 1062 (East) versus phase-adjusted age during the last 150 kyr obtained by Grützner et al. (2002). The red bars indicate the intervals of time in the Holocene sampled for this study. Gray boxes highlight the interglacial periods determined from the timing of Marine Isotope Stages after Lisiecki and Raymo (2005)...... 27

Figure 7. Average recovery of aspartic acid (Asp), glutamic acid (Glu), and the total amino acid (Asp, Glu, Ser, Ala, Val, Phe, Ile, and Leu) concentrations (pmol/test) from Holocene (A) and down-core (B) samples. Welch’s t-tests were used to determine whether there was a significant difference in the mean amino acid concentrations between the pretreatments. P-values < 0.05 are significant. Data are listed in Table A3...... 41

ix Figure 8. Average recovery of total amino acid (Asp, Glu, Ser, Ala, Val, Phe, Ile, and Leu) concentrations (pmol/test) for each foraminiferal species from Holocene (A) and down-core (B) samples. Data are listed in A3...... 42

Figure 9. Average amino acid composition in unbleached and bleached shells of P. obliquiloculata, G. truncatulinoides (sinistral), G. truncatulinoides (dextral), and G. tumida. The total fraction of amino acids comprises Ala, Asp, Glu, Ser, Val, and other (Phe, Ile, Leu). Data are in Table A3...... 43

Figure 10. Aspartic acid (Asp) D/L ratios from Sites 1056D (A-C), 1059A (D-F), and 1062B (G) comparing the effects of bleaching on sample mean and standard deviation within P. obliquiloculata, G. truncatulinoides (sinistral), and G. tumida. Mean Asp D/L values are shown as dashed lines for each treatment. The box is plotted from the first quartile to the third quartile. The whiskers extend from each quartile to the minimum or maximum values. Subsample values outside of the quartiles by more than 1.5 times the interquartile range are plotted as small circular data points. The numbers are the P-values from Welch’s independent t-tests (Table 5) of each interval individually that evaluate the significance of the treatment on the subsample mean D/L values. P-values < 0.05 are significant...... 47

Figure 11. Same as Figure 10 but for glutamic acid (Glu) D/L ratios...... 48

Figure 12. Down-core plots of the aspartic acid (Asp) D/L ratios from Sites JPC-37 (A-B) and 1056B (C-D) to compare the effect of bleaching on sample mean and standard deviation within P. obliquiloculata and G. truncatulinoides (dextral and sinistral). Mean Asp D/L values are shown as dashed lines for each treatment. The box is plotted from the first quartile to the third quartile. The whiskers extend from each quartile to the minimum or maximum values. Subsample values outside of the quartiles by more than 1.5 times the interquartile range are plotted as small circular data points. The numbers are the P-values from Welch’s independent t-tests (5) of each interval individually that evaluate the significance of the treatment on the subsample mean D/L values. P- values < 0.05 are significant...... 49

Figure 13. Same as Figure 12 but for glutamic acid (Glu) D/L ratios...... 50

x Figure 14. Aspartic acid (Asp) and glutamic acid (Glu) D/L ratios from Sites 1056D (A-D) and 1059A (E-H) showing the species effects of P. obliquiloculata, G. truncatulinoides (sinistral and dextral), and G. tumida on sample mean and standard deviation. In these box and whisker plots, mean D/L values are shown as dashed lines for each treatment. The box is plotted from the first quartile to the third quartile. The whiskers extend from each quartile to the minimum or maximum values. Subsample values outside of the quartiles by more than 1.5 times the interquartile range are plotted as small circular data points...... 59

Figure 15. Down-core plots of the aspartic acid (Asp) and glutamic acid (Glu) D/L ratios from Sites JPC-37 (A-B) and 1056B (C-D) to compare the species effects of P. obliquiloculata, G. truncatulinoides (sinistral and dextral), and G. tumida on sample mean and standard deviation. Mean D/L values are shown as dashed lines for each treatment. The box is plotted from the first quartile to the third quartile. The whiskers extend from each quartile to the minimum or maximum values. Subsample values outside of the quartiles by more than 1.5 times the interquartile range are plotted as small circular data points...... 60

Figure 16. Extent of racemization (D/L) for aspartic acid (A) and glutamic acid (B) measured in six coeval intervals of P. obliquiloculata and G. truncatulinoides. Data are listed in Table A5...... 62

Figure 17. Summary of down-core changes in average Asp (A-B) and Glu (C-D) D/L ratios spanning the past 410 kyr for unbleached and bleached P. obliquiloculata and G. truncatulinoides (sinistral and dextral values averaged) from Sites 1056 (~2000 m water depth) and JPC-37 (~3000 m water depth). Data are listed in Table A5 as well as the corresponding ±1σ for the average D/L values. Lines reflect the relative rates of racemization as a function of sample age for each species. In all samples, the Asp D/L ratio increases as a function of age in accordance with the underlying principles of AAR geochronology...... 64

Figure 18. Representation of the calculation of the Effective Diagenetic Temperature (EDT) where T is temperature and t is time. T1 is the entire post depositional history of the sample since t1 (t1 – 0 ka) and is calculated from Eq. 9. T2 is the EDT since t2 (t2 – 0 ka) and is also calculated from Eq 9. T(t2-t1) is the EDT for the bracketed interval between t2 and t1 and is calculated from Eq. 10...... 73

Figure 19. Comparison between the extent of racemization (D/L) in coeval samples (n=6) of P. obliquiloculata and G. truncatulinoides for aspartic acid (A) and glutamic acid (B)...... 74

xi Figure 20. Comparison of the down-core trends of aspartic acid (A) and glutamic acid (B) D/L ratios of G. truncatulinoides corrected to P. obliquiloculata from the BBOR (this study) and P. obliquiloculata from the Queensland margin (Hearty et al. 2004). The lines show the data fit with a power curve. Samples shown in red are the initial analyses for samples 15.4 ka and 30.8 ka. The sample at 51.5 ka is shown as an open circle because it no longer aligns with the BBOR trend of the new 30.8 ka Glu D/L value.75

Figure 21. Global benthic δ18O records (Lisiecki and Raymo 2005) spanning 410 kyr (A) and 150 kyr (B) provide a corresponding view of interglacial- glacial climate background. EDTs for ~2000 m and ~3000 m water depth at the Blake-Bahama Outer Ridge based on the average (C and D) and weighted average (E and F) of the extent of racemization in aspartic acid and glutamic acid of P. obliquiloculata and G. truncatulinoides (corrected to P. obliquiloculata using the species correction from Figure 19). Since EDTs are an average post-depositional temperature between intervals of time, they are represented as lines between the data points for the beginning and end of the intervals of interest. For the ~2000 m water depth trend, samples at 4.82 ka and 410 ka are from Sites 1056D and 1056B, respectively. For the ~3000 m water depth trend, the sample at 5.04 ka is from Site 1059A, and the samples at 15.4 ka, 30.8 ka, and 86.4 ka are from JPC-37. Data are in Table 9...... 82

Figure 22. Longitudinal profile of the potential temperature (°C) in the Atlantic Ocean at ~25°W. Water masses within the cross section include Antarctic bottom water (AABW), North Atlantic deep water (NADW), Antarctic intermediate water (AAIW), and Mediterranean intermediate sea water (MISW). Image from Libes (2009)...... 90

Figure A1. Schematic of the methodology for subsample preparation. Each site has multiple drill core intervals (labeled 1-12), which are then individually picked for the three foraminiferal species (P. obliquiloculata, G. truncatulinoides, and G. tumida) and coiling directions of G. truncatulinoides (labeled A-D). Each sample is made of a particular species from a single core interval. The samples were split for the two cleaning methods (NaOCl and H2O2) with 10 subsamples per cleaning method consisting of ~5 foraminiferal tests for hydrogen peroxide (nonbleached) subsamples and ~10 foraminiferal tests for bleached subsamples. Each core interval was subdivided into at most 80 subsamples with 20 subsamples per foraminiferal species...... 108

xii Figure A2. Cross plots of unbleached D/L values for aspartic acid (Asp) and glutamic acid (Glu) in subsamples of the foraminiferal species G. truncatulinoides dextral (A) and sinistral (B), G. tumida (C), and P. obliquiloculata (D). Data are shown in Table A1...... 122

Figure A3. Cross plots of bleached D/L values for aspartic acid (Asp) and glutamic acid (Glu) in subsamples of the foraminiferal species G. truncatulinoides dextral (A) and sinistral (B), G. tumida (C), and P. obliquiloculata (D). Data are shown in Table A1 ...... 123

xiii ABSTRACT

Amino acid racemization (AAR) is a geochronological method that uses the ratio of D- to L- configurations in optically active amino acids from carbonate-based fossils to determine the time elapsed since the death of an organism. In well-dated fossil samples, the extent of racemization can be used to calculate post-depositional temperatures (also known as the effective diagenetic temperature). Calculated post-depositional temperatures of bracketed time intervals have uncertainties ranging from ±2 to 4°C with the dominant source of error in the D/L ratios (Kaufman 2003). Here, I aim to reduce these uncertainties using a bleach pretreatment that isolates the intra-crystalline fraction of amino acids in order to reduce the variability in foraminiferal D/L values to improve the precision of environmental paleotemperature estimates. I investigate the effect of this pretreatment method on the D/L ratios in three species of planktic foraminifera

(Globorotalia tumida, Pulleniatina obliquiloculata, and Globorotalia truncatulinoides) from Holocene (~4-5 ka) deep sea sediments of similar environmental settings (Ocean Drilling Program Sites 1056, 1059, and 1062) and early Holocene to Pleistocene (~10.5- 410 ka) sediments down-core (Ocean Drilling Program Site 1056 and KNR140 JPC-37). Results are reported for aspartic acid (Asp) and glutamic acid (Glu) because they are among the most abundant amino acids in foraminiferal protein and are the best resolved chromatographically. I analyzed 42 samples, each with an average of 9 replicates per sample and 5-10 individual tests per replicate, depending on the pretreatment method. Comparing D/L ratios from bleached versus unbleached samples indicates that bleaching only slightly reduces the variability in D/L values within the same sample (i.e. same species from the same core interval) by, on average, 1.1% and 3.0% for Asp and Glu,

xiv respectively. Furthermore, comparison of D/L ratios from the same species found at more than one site does not show statistical differences whether bleached or not. Bleaching does not appear to reduce the rejection rate or variability among replicates from the same sample from core intervals of similar age and environmental setting enough to warrant adding the additional time required to pick more tests for the bleaching procedure. Post- depositional temperatures calculated from unbleached D/L measurements of P. obliquiloculata and species corrected G. truncatulinoides give an account of the thermal history at ~2000 m (ODP Site 1056) and ~3000 m (ODP Site 1059 and KNR140 JPC-37) water depth at the Blake-Bahama Outer Ridge in the Western Atlantic. Paleotemperature estimates for the bracketed time interval of the Last Glacial Maximum (LGM; 15.4-30.8 ka) at ~3000 m water depth indicate >4°C cooling between the LGM and Holocene, consistent with other paleoclimate proxies (benthic foraminiferal δ18O and Mg/Ca). Currently, uncertainties of effective diagenetic temperatures averaged for the amino acids are ≤ ±0.6°C for T and ≤ ±1.6°C for T(t2-t1) due to an average inter-shell variation in D/L

(±1σx) of ±1.6% and ±2.9% for Asp and Glu, respectively. Therefore, it is important to have minimal variability (standard deviation and standard error) in D/L values for temperature estimates that are reflective of less than 4°C uncertainties in bottom water temperature. For a more complete comparison of water temperatures at the ~2000 m and ~3000 m water depth, I would obtain a measurement on a 410 ka sample from JPC-37

(~3000 m water depth) in order to compare the effective diagenetic temperature of glacial-interglacial periods during the past 410 kyr in the Western Atlantic.

xv Chapter 1

INTRODUCTION

Paleotemperature proxies are indispensable tools in order to understand past distributions of ocean temperature, climate variability, changes in glacial-interglacial cycles, and deep water circulation. Proxies used most frequently for paleotemperature reconstructions include assemblages of planktonic foraminifera, foraminiferal δ18O values and Mg/Ca ratios, clumped isotopes in carbonates, and biomarkers such as alkenones. Although these proxies have been used to reconstruct marine temperatures, each has their own uncertainties that limit quantitative reconstructions. Due to these uncertainties, no single proxy used in isolation is ideal, and the addition of newer techniques is vital in order to find a reliable independent proxy for the determination of bottom water temperature. Within the past few decades, amino acid racemization (AAR) has been used to reconstruct environmental temperatures (Murray-Wallace et al. 1988; Oches et al. 1996; Kaufman 2003; Reichert et al. 2011). This proxy is not limited to marine archives and has the potential to provide temperature histories for a range of settings (marine, lacustrine, and fluvial) and samples (mollusks, foraminifera, corals, bones, teeth, and wood). In this study, I further explore the applicability of AAR to reconstruct deep-sea temperatures. AAR is the interconversion of amino acids from their L- to D- enantiomeric configuration upon the death of an organism and subsequent break down of proteins (Figure 1) (Wehmiller and Hare 1971; Bada and Schroeder 1975). The D- to L- ratio of amino acids (D/L) is a measure of the extent of racemization and increases with time and temperature from values of ~ 0 in modern tissues to equilibrium values of ~1. Deep sea

1 depositional sites are the most stable long-term temperature environments and the best place for determining the rate of racemization independently of temperature changes that influence fossils in terrestrial settings (Kaufman 2003; Kaufman 2006). Here, changes in D/L values are independent of whether the calcification site of the organism was in the surface or deep water. Therefore, amino acids record long-term climate changes by integrating the entire post-depositional temperature history of a deposit (effective diagenetic temperature), as opposed to the geologically instantaneous paleoenvironmental evidence contained within the deposit (Wehmiller 1977). Typically, AAR has been used as a geochronological tool that uses D/L in optically active amino acids from predominantly carbonate-based fossils (e.g. bivalves, gastropods, foraminifera, coral, avian eggshells, etc.) to determine the time elapsed since the death of an organism. The method is frequently applied to Quaternary materials, but studies have shown that complete racemization can be found in fossils older than the Pliocene (Wehmiller and Hare 1971). In independently dated fossil samples, the extent of racemization (D/L) can be used to calculate post-depositional temperatures by combining simple power law kinetics that model the rate of racemization (Chapter 2 Eq. 7) and the Arrhenius equation (Chapter 2 Eq. 8). Currently, calculated post-depositional temperatures from AAR have uncertainties up to ± 4°C with the dominant source of error in the D/L ratios (McCoy 1987a; Kaufman 2003). Possible causes of the variability in

D/L values are leaching and contamination by non-indigenous amino acids (Goodfriend et al. 1992). A study by Penkman et al. (2008) suggested using bleach to remove leachable matrix proteins and contaminating material. This pretreatment is focused on minimizing variability in D/L values by exposing powdered biogenic carbonate to concentrated bleach for 48 hours to effectively reduce the amino acid content to a residual level that represents the indigenous intra-crystalline fraction (Penkman et al.

2 2008). The organic material trapped within single crystals (intra-crystalline fraction) is less prone to environmental influences than inter-crystalline amino acids, and therefore is a better approximation of a closed system (Penkman et al. 2008). My study aims to assess amino acid racemization within three species of planktonic foraminifera (Pulleniatina obliquiloculata, Globorotalia tumida, and Globorotalia truncatulinoides) to reconstruct paleotemperature extending into the Pleistocene at the Blake-Bahama Outer Ridge in the Western Atlantic. I hypothesize that bleach (NaOCl) pretreatments can be used to reduce the variability in these foraminiferal D/L ratios and improve down-core trends in D/L, which will reduce current uncertainties and improve the precision of environmental temperature estimates using AAR. To test this hypothesis, I will compare the bleach pretreatment against traditional hydrogen peroxide (H2O2) cleaning methods in the three species studied here in order to constrain potential inter-species variability. Method testing will be conducted on Holocene intervals near the core top (~40-70 cm, ~4-5 ka) from three sites (ODP Sites 1056, 1059, and 1062) and early Holocene to Pleistocene down-core intervals (~10-410 ka) from two sites (ODP Site 1056 and KNR140 JPC-37) within the Blake-Bahama Outer Ridge, totaling 42 samples with an average of 9 replicates per sample and 5-10 individual tests per replicate. Independent dating techniques, including AMS 14C (obtained from this study) and δ18O stratigraphy (obtained from Hagen and Keigwin 2002 and Billups et al.

2004), are combined with the AAR data to quantitatively estimate temperatures for intervals of time since ~410 ka. Temperatures will be calculated based on the D/L values of aspartic acid and glutamic acid, resolved using reversed phase high performance liquid chromatography, and uncertainties will be derived with a bootstrap propagation.

4 Chapter 2

BACKGROUND

2.1 Amino Acid Racemization (AAR) All amino acids, with the exception of glycine, are chiral molecules that exhibit

“handedness,” meaning that they can exist in two different configurations or enantiomers (Walker 2005; Miller et al. 2013). Upon the death of an organism, biological constraints are removed and diagenetic reactions degrade proteins into their constituent amino acids, which then interconvert from the L- to D-configuration in a diagenetic process known as racemization (Bada and Schroeder 1975; Kaufman 2003; Miller et al. 2013) (Figure 1). For amino acids that have more than one chiral carbon (i.e. isoleucine), diastereoisomers are formed rather than enantiomers in the related process called epimerization (McCoy

1987a). The extent of such interconversions is proportional to the length of time elapsed since the organism died and the ambient temperature of the reaction medium (Kaufman 2003). In amino acid racemization, the extent of the reaction is measured by the D/L ratio, which increases with temperature and time until the abundance of D formed is compensated by the reverse reaction (formation of L), prompting the ratio to reach an equilibrium value of 1.0 (Kaufman 2003). Although the simplest amino acids are stable at ambient temperature for hundreds of millions of years, not all amino acids are suitable candidates for AAR (Miller 2013). Typical amino acids chosen for AAR have a single chiral carbon atom and exist in their D- or L- configurations with identical physical and chemical properties, except in their interaction with other chiral substitutes (Miller et al. 2013). Glycine, serine, threonine,

5 and alanine are amino acids not suitable for AAR analyses. Glycine is not chiral, and therefore does not exist in two configurations (Miller et al. 2013). Serine and threonine are thermodynamically unstable with half-lives too short for most geological applications (Miller et al. 2013). Alanine is created in fossils by the decomposition of other, more complex amino acids (Miller et al. 2013). Commonly used amino acids in AAR analyses are isoleucine, alloisoleucine, glutamic acid, and aspartic acid, depending on the analytical method chosen.

The separation and detection of amino acids within carbonate fossils can be accomplished by gas chromatography, ion-exchange liquid chromatography, and reverse- phase liquid chromatography. In the past when most labs used ion-exchange or gas chromatographic methods to resolve the D- and L- forms of amino acids, D- alloisoleucine and L-isoleucine ratios were most commonly used because they were easily separated with chromatography. Isoleucine is one of the slowest amino acids to epimerize, thus it can provide a context to the degree of racemization for other amino acids in a sample (Wehmiller and Hare 1971). While gas chromatography offers the advantage of separating at least six enantiomers in a single analysis, reagents are relatively expensive, sample preparation is time-consuming, and quantifying concentrations of amino acids is difficult (Miller and Brigham-Grette 1989). On the other hand, ion-exchange liquid chromatography uses inexpensive reagents, minimal sample preparation is required, the technique has high sensitivity, and quantifying concentrations of amino acids is easier (Miller and Brigham-Grette 1989). The disadvantage of ion- exchange liquid chromatography is that only D-alloisoleucine and L-isoleucine are easily resolved (Miller and Brigham-Grette 1989). For the more recent method of reverse-phase high performance liquid chromatography, aspartic acid and glutamic acid are the amino acids of choice. Aspartic acid is a relatively fast racemizing amino acid that is also

6 commonly used for young materials or cold deposition sites (McCoy 1987a; Goodfriend et al. 1996; Miller et al. 2013). More recent studies have focused on aspartic acid and glutamic acid because they are the most abundant amino acids in foraminiferal protein, are the best resolved chromatographically, elute during the first 30 minutes of the sample run, and span most of the range of racemization rates (Kaufman 2003; Kaufman et al. 2013). Reversed-phase liquid chromatography also has easy sample preparation and amino acid quantification, quick analysis time, inexpensive operation, and the ability to use chiral mobile phases to easily separate D and L amino acid enantiomers (Miller and Brigham-Grette 1989).

2.2 Application of Amino Acid Racemization

2.2.1 Amino Acid Geochronology Traditionally, AAR has been used as a relative dating tool (aminostratigraphy) or calibrated dating tool (aminochronology) to provide age estimations for Quaternary deposits (Kaufman and Miller 1992; Engel and Macko 1993). Within the literature, aminochronology has been often been used as an extension of aminostratigraphic studies in order to determine calibrated ages of the deposits. AAR is potentially one of the most useful techniques available in Quaternary dating because it can be applied to marine and non-marine fossiliferous deposits beyond the range of 14C dating (> 45,000 years) (Walker 2005). The method is applicable to a wide range of stratigraphic problems (correlations, reworking, and unconformities) and depositional environments (marine, lacustrine, and fluvial). Aminostratigraphy is perhaps the most reliable and least ambiguous application of amino acid enantiomeric (D/L) ratios, where D/L values from closely spaced but discontinuous deposits are grouped into aminozones in order to determine relative age

7 indices (Miller and Hare 1980; Wehmiller 1982; Miller et al. 2013). This method assumes that the deposits grouped into an aminozone have experienced identical or similar temperature histories; therefore, differences in D/L values are interpreted exclusively as indications of age differences (Wehmiller 1982; Wehmiller et al. 1988; Miller et al. 2013). Over the limited region, samples with similar D/L are the same age, those with lower D/L are younger, and those with higher D/L are older (Miller et al. 2013). The primary application of aminostratigraphy has been in studying the relative chronology of coastal sediments deposited during high-sea level (i.e. interglacial shorelines) of the late Pliocene and Pleistocene (Walker 2005; Kaufman and Miller 1992). Some of the many regional studies of the relative ages of such deposits have included European coasts (Miller et al. 1979; Andrews et al. 1979; Miller et al. 1983; Miller and Mangerud 1985; Bowen et al. 1985; Kaufman and Sejrup 1995; Meijer and Cleveringa 2009), the Canadian Arctic (Miller et al. 1977; Nelson 1981; Miller 1985; Refsnider et al. 2013), the U.S. Pacific coast (Wehmiller et al. 1977; Kennedy, 1978;

Lajoie et al. 1979; Atwater et al. 1981; Kennedy et al. 1982; Wehmiller 1984; Rockwell et al. 1992; Wehmiller 2013), the U.S. Atlantic Coast (Mitterer 1974; Mitterer 1975; Belknap 1979; Belknap and Wehmiller 1980; Wehmiller et al. 1988; York et al. 1989; Wehmiller et al. 1995; Wehmiller et al. 2010; Wehmiller 2013), the Alaskan coast (Brigham-Grette and Carter 1992; Kaufman 1992; Kaufman and Brigham-Grette 1993), the South American Atlantic coast (Aguirre et al. 1995), the Australian coast (Murray- Wallace et al. 1991; Murray-Wallace 2000; Murray-Wallace et al. 2005; Kosnik et al.

2009), the Mediterranean (Hearty et al. 1986), and the Bahamas (Hearty and Kaufman 2000). Aminostratigraphy has also been applied to studies of terrestrial deposits. A sampling of the literature includes studies in Europe (Miller et al. 1979; Bowen and Sykes 1988; Oches and McCoy 1990; Bates 1993), the Negev Desert (Goodfriend 1987a;

8 Goodfriend 1987b), the U.S. (Scott et al. 1983; McCoy 1987b; Miller et al. 1987; McCoy and Miller 1990), and Australia (Sloss et al. 2004). A clear demonstration between D/L and stratigraphic age come from aminostratigraphic studies of foraminifera from deep sea sediment cores from the equatorial Atlantic and Pacific Oceans (King 1977; Müller 1984; Wehmiller and Hall 1997), Arctic Ocean (Sejrup et al. 1984a), North Sea (Sejrup et al. 1987), and Gulf of Mexico (Johnson 1990). AAR results are typically used to determine relative ages within a study region, but when associated with independent age calibrations, AAR can provide absolute ages. Within aminochronology, there are two general approaches to convert the D/L of a fossil to an absolute age. The first option is to use D/L values to interpolate between or extrapolate beyond the known ages of dated aminozones (Kaufman and Miller 1992). The second approach is to use high temperature lab experiments of modern shells to determine the effects of time and temperature on the extent of racemization in conjuncture with a model of the kinetics in order to calculate the age of a sample when the D/L and post-depositional history are known (Kaufman and Miller 1992). However, these high temperature lab experiments may not precisely mimic the net effect of long- term diagenetic processes (Kaufman 2015). Therefore, most attempts to quantify the temperature sensitivity of long-term racemization include analyses of 14C dated Holocene samples whose temperature history can be inferred from instrumental measurements

(Kafuman 2015). Calibrating the rate of racemization with independently dated samples of a particular taxon from a region where temperature histories are uniform is a more secure approach to geochronology because it does not require assumptions about the temperature history (Kaufman 2015). These calibrated rates are then used to date samples of the same taxon of unknown age from the same environment (Kafuman 2015). Primarily, calibrated AAR has been used to study sediment mixing processes in Holocene

9 aged sediments. Some of the many regional studies of the absolute ages of deposits include the Arctic Ocean (Macko and Aksu 1986; Kaufman et al. 2008; Kaufman et al. 2013), the Atlantic Ocean (Carroll et al. 2003; Barbour-Wood et al. 2006; Kaufman et al. 2013), the Pacific Ocean (Harada and Handa 1995; Kaufman et al. 2013), the Bahamas (Goodfriend 1997; Hearty and Kaufman 2000), the Chesapeake Bay (Simonson et al. 2013), the Gulf of California and Mexico (Meldahl et al. 1997; Kowalewski et al. 1998; Kowalewski et al. 2000), the Caribbean (Kidwell et al. 2005), the Ubatuba Bay (Krause et al. 2010), the Negev Desert (Goodfriend 1989), the United States (Laabs and Kaufman 2003), Australia (Hearty et al. 2004; Sloss et al. 2004; Kosnik et al. 2007; Kosnik et al. 2009; Kosnik et al. 2013), Norway (Sejrup et al. 1984b), and Africa (Brooks et al. 1990; Miller et al. 1991).

2.2.2 Amino Acid Thermometry Since the extent of amino acid racemization is temperature and time dependent, the average post-depositional temperature, also defined as the effective diagenetic temperature (EDT), can be determined from the D/L ratio if the sample age is known independently (Wehmiller 1977). The EDT represents the integrated effect of all temperatures that samples at a specific depth has been exposed (Wehmiller 1977). It is further defined as the equivalent temperature needed to explain the extent of racemization if the sample experienced a constant post-depositional temperature (Miller et al. 2013). This temperature is always equal to or higher than the arithmetic mean temperature (Miller et al. 2013).

Within the past few decades, amino acid racemization (AAR) has been used to reconstruct environmental temperatures (Murray-Wallace et al. 1988; Oches et al. 1996; Kaufman 2003; Reichert 2009). One study by Oches et al. (1996) specifically looked at

10 amino acid paleothermometry for the time period encompassing the last glacial maximum (LGM) in the Mississippi Valley. They estimated that sometime during or following the last glaciation, the temperature gradient was 0.3-0.6°C/degree latitude, which is lower than the modern mean air temperature gradient of 0.9°C/degree latitude (Oches et al. 1996). This degree of cooling was used to determine the temperature gradient in the southern United States during the LGM (Oches et al. 1996). Kaufman (2003) used the extent of AAR in fossil ostracodes to reconstruct the temperature history of the

Bonneville Basin, Utah. The effective diagenetic temperature for the intervals 150-12 ka and 24-12 ka (during the last full-glacial interval) were calculated to be 3.3 ± 1.3°C and 1.1 ± 2.5°C, respectively, which are approximately 7.6°C and 9.8°C lower than during the Holocene (last 5.8 ka; 10.9 ± 1.3°C) (Kaufman 2003). Kaufman (2003) suggested that such low paleotemperatures indicated that reduced evaporation could have caused the increased effective moisture and growth of Lake Bonneville (Kaufman 2003). Closely related to this thesis, Hearty et al. (2004) explored the use of AAR using

Pulleniatina obliquiloculata from the Queensland Margin, Australia. When looking at D/L values from samples of the same age, the ratios were lower for cores taken from deeper water sites, due to reduced racemization rates within colder, deeper waters (Hearty et al. 2004). Therefore, the sensitivity of the rate of racemization to bottom water temperature for Asp was determined to be a D/L increase of 0.02 per 1°C for P. obliquiloculata dated to 10.5 ka (Hearty et al. 2004). This study indicated that AAR can be used to resolve paleotemperatures within 1°C for samples of known age and thermal history; however, resolving D/L ratios that differ by only 0.02 seems unattainable with the current analytical techniques and natural variability within marine sediment (Hearty et al. 2004).

11 2.3 Amino Acid Racemization Kinetics In early calculations, the racemization of amino acids in total hydrolysate of simple systems was considered a first-order reversible reaction (Eq. 1) (Wehmiller and Hare 1971). 푘1 → 퐿 ← 퐷 Eq. 1 푘2 The rate law for the interconversion of amino acids is therefore (Kvenvolden et al. 1973): 푑[퐿] − = 푘 [퐿] − 푘 [퐷] Eq. 2 푑푡 1 2 and the integrated rate expression is given by (Kvenvolden et al. 1973) with the derivation by Bada and Schroeder (1972): 1+퐷⁄퐿 푘2 ln [ ] = (1 + ) 푘1푡 + 퐶 Eq. 3 1−((푘2⁄푘1)(퐷⁄퐿)) 푘1

In this equation, k1 and k2 are the forward and reverse rate constants for a given temperature (yr-1), t is the age of a sample (yr), and C is a constant equivalent to calculations at t=0.

However, first-order reversible kinetics is known to overestimate the rate of racemization beyond the initial phases of the reaction (Kvenvolden et al. 1973; Bada and Schroeder 1975; Mitterer and Kriausakul 1989; Goodfriend 1992; Engel and Macko 1993; Kaufman 2006). The deviation of racemization kinetics from a predicted first-order reversible reaction arises because amino acids within a biomineral are comprised of various states (i.e. bound within a peptide chain, at the N-terminus, at the C-terminus, and free amino acid) and the amino acids contained in these various fractions racemize at different rates (Bada and Schroeder 1975; Demarchi and Collins 2015). In general, racemization proceeds at different rates according to 1) the chemical characteristics of the amino acid, 2) the position of the amino acid within the protein sequence, 3) burial temperature, 4) water availability for peptide bond hydrolysis, and 5) secondary

12 environmental factors (pH, presence of cations and anions, microbial degradation, etc.) (Demarchi and Collins 2015). Racemization kinetics is complicated because the proportion of amino acids in the various forms changes with time due to hydrolysis (Bada and Schroeder 1975). Initially, amino acids exist mainly in the form of proteins, and these proteins are slowly hydrolyzed to produce smaller peptides, which are in turn hydrolyzed to produce free amino acids (Bada and Schroeder 1975). For free amino acids that are solvated, the rate of racemization is based on the ability of R groups in an amino acid to stabilize a carbanion intermediate that is formed when the hydrogen side chain is removed from an amino acid (Bada and Schroeder 1975; Miller et al. 2013). R groups that have greater electron withdrawing capacity and resonance-stabilizing capacities will stabilize the carbanion intermediate and therefore racemize more quickly (Bada and Schroeder 1975; Miller et al. 2013; Demarchi and Collins 2015). This mechanism is also applicable to terminal amino acids bound in peptides and proteins due to the participation of the protonated amino group in resonance, which facilitates the loss of the hydrogen

(Demarchi and Collins 2015). However, peptide-bound amino acids have been shown to be unable to racemize until hydrolysis drives them to a terminal position (exceptions include asparagine, aspartic acid, and serine); therefore, the free amino acid fraction is more extensively racemized (Wehmiller 1980; Mitterer and Kriausakul 1984; Geiger and Clarke 1987; Demarchi et al. 2013).

Due to the reversible nature of L- and D-amino acid formation upon the readdition of the hydrogen atom on to the carbanion intermediate, the net racemization rate slows as the extent of racemization increases, which is characteristic of a curvilinear trend when D/L ratios are plotted against linear time (Miller et al. 2013). Because theoretical models of first-order kinetics typically overestimate the rate of racemization

13 (especially for aspartic acid), several nonlinear kinetic models have been developed (Oches et al. 1996; Kaufman 2003; Kaufman 2006). The most recent approaches to kinetic modeling of racemization is based on mathematical curve fitting in order to derive an equation that most closely describes the available data (Kaufman 2006; Kosnik et al. 2008; Allen et al. 2013). The three models attempted by Kaufman (2006) using foraminifera in line with this study were simple power law kinetics (Eq. 4), constrained power-law kinetics (Eq.5), and apparent parabolic kinetics (Eq. 6) (Kaufman 2006).

푛 푘1푡 + 퐶 = 퐷/퐿 Eq. 4 퐷 퐷 푘 푡 + 퐶 = [(1 + )⁄(1 − )]푛 Eq. 5 1 퐿 퐿 0.5 푘1푡 + 퐶 = 퐷⁄퐿 Eq. 6 -1 In these equations, k1 is the forward rate constant for a given temperature (yr ), t is the time (yr), and C is a constant equivalent to calculations at t=0 (Kaufman 2006). For D/L values < 0.5 for Asp and < 0.25 for Glu, the simple power law kinetics was determined to provide the best linearization with optimal n exponents of 3.0 and 2.4, for Asp and Glu, respectively (Kaufman 2006). The expression of the rate constant (k1) used within this study is from the simple power law kinetics of Kaufman (2006): 퐷⁄퐿푛−퐶 푘 = Eq. 7 1 푡 where C= D/Ln in modern samples. Initial D/L values (t=0) for Pulleniatina obliquiloculata are 0.040 and 0.020 for Asp and Glu, respectively (Hearty et al. 2004).

2.4 Determination of the EDT The temperature dependency of AAR can be described by the Arrhenius equation:

푘 = 퐴푒−퐸푎⁄푅푇 Eq. 8

14 -1 where A is the frequency factor (yr ), Ea is the activation energy (kcal/mol), R is the gas constant (0.001987 kcal/K mol), and T is the temperature (K). Kaufman (2006) used an Arrhenius plot of data from laboratory-heating experiments combined with 14C dated P. obliquiloculata to calculate the Arrhenius parameters (Ea and A) for racemization of Asp and Glu (Figure 2). The Arrhenius plots shows the linear relationship between the natural log of the rate constant (k) and the reciprocal of the absolute temperature (1/T) with -Ea/R as the slope and ln(A) as the intercept (Figure 2). The resulting Ea values for Asp and Glu racemization in P. obliquiloculata is 31.5 ± 0.2 kcal/mol and 31.2 ± 0.3 kcal/mol, respectively (Kaufman 2006). The intercepts yielded ln(A) values of 42.12 ± 0.31 yr-1 and 40.25 ± 0.34 yr-1 for Asp and Glu, respectively (Kaufman 2006). By combining the expression for the rate constant (Eq. 7) and Arrhenius equation (Eq. 8), two different types of temperature estimates can be made. The first is the EDT of the entire post depositional history of a single sample whose age is known (Kaufman 2006): 푘 퐷⁄퐿푛−퐶 푇 = −퐸 ⁄푅 [ln ( )] = −퐸 ⁄푅 [ln ( )] Eq. 9 푎 퐴 푎 퐴푡 The second is the effective diagenetic temperature of an interval of time bracketed by two samples of known age (McCoy 1987a; Kaufman 2003): 퐴 푡2−푡1 푇푡2−푡1 = 퐸푎⁄푅 [ln ( )] = 퐸푎⁄푅 ln (퐴 [ ]) Eq. 10 퐾(푡2−푡1) 푘2푡2−푘1푡1

In Eq. 10, the variables t2 and t1 are the ages of the older and younger sample, respectively, k2 and k1 are the rate constants for the older and younger samples, respectively calculated using Eq. 7, and K(t2-t1) is the simplified expression for the rate expression (Eq. 11). 푘2푡2−푘1푡1 퐾푡2−푡1 = Eq. 11 푡2−푡1 The temperature calculation in Eq. 10 yields the average temperature between the depositional time of the older and younger samples (Kaufman 2003). The EDT

15 calculations (Eq. 9, Eq. 10) represent an integrated thermal history that emphasizes warm periods due to the exponential dependence of the rate constant on temperature (Oches et al. 1996; Miller et al. 2013). Therefore, the calculated EDT will always be somewhat higher than the mean annual temperature experienced by the sample during its post- depositional history (Oches et al. 1996). The difference between effective and arithmetic mean temperatures is proportional to the amplitude of the seasonal or longer term temperature variations, which are relatively small for deep marine settings (Kaufman

2006; Miller et al. 2013).

2.5 Pretreatment Methods Studies have shown that pretreatment cleaning of samples is crucial in order to interpret small differences in D/L ratios with respect to time and temperature. Due to the high surface area-to-mass ratio of foraminifera, contamination by exogenous amino acids is a concern (Stathoplos and Hare 1993; Hearty et al. 2004). In the early days of AAR, samples (mostly shells) were broken up for cleaning, foreign material was mechanically removed, and the samples were sonically cleaned in distilled water and rinsed in ultrapure water (Oches et al. 1996). In 2004, Hearty et al. studied the effectiveness of using 3%

H2O2, 5% NaOCl, isopropyl alcohol, and methanol as cleaning reagents to remove secondary organic molecules adsorbed to the test. The effectiveness of these cleaning reagents was compared based on their inter-shell variation in D/L ratios. The 2 hour H2O2 treatment was the most effective at reducing the inter-shell variation in D/L calculated based on the coefficient of variation (Hearty et al. 2004), in line with results from

Kaufman (2000). Many studies have focused on using a closed-system fraction of amino acids (intra-crystalline) where the organic material experiences no chemical or physical

16 interaction with the external environment (e.g. Collins and Riley 2000; Penkman et al. 2008). Prolonged oxidation (e.g. bleach) has been shown to remove inter-crystalline proteins that are more prone to contamination and interaction/exchange with the environment, leaving the intra-crystalline fraction for analysis (Demarchi and Collins 2015). Within the inter-crystalline fraction, the retention of amino acids is a function of the degree of protein breakdown, the rate of loss from the biomineral, and any contribution from the external environment (Demarchi and Collins 2015). The kinetic rate of intra-crystalline amino acids is focused on the slower hydrolysis of the internally protected amino acids rather than the combined hydrolyses of the protein, peptide, and free amino acid fractions within the total hydrolysable amino acid content. Inter- crystalline amino acids are often lost quickly; therefore, isolation of the intra-crystalline fraction through chemical pretreatment is more important for younger samples (Demarchi and Collins 2015).

Figure 2. Example Arrhenius plot for aspartic (Asp) and glutamic acids (Glu). Data was obtained from laboratory heated and 14C dated P. obliquiloculata tests from Kaufman (2006).

18 Chapter 3

RESEARCH STRATEGY

3.1 Site Selection and Modern Hydrography This study focuses on cores from Ocean Drilling Program (ODP) Leg 172 Sites 1056 (32°29’N, 76°20’W), 1059 (31°40’N, 75°25’W), and 1062 (28°15’N, 74°24’W) and KNR140-2 JPC-37 (31°41’N, 75°26’W) drilled in the subtropical northwestern

Atlantic on the Blake-Bahama Outer Ridge (BBOR) (Figure 3; Table 1). The BBOR is a segment of sediment drifts influenced by the Deep Western Boundary Current (DWBC) system that presently flows southeast at ~3000-5000 m water depth (Keigwin et al. 1998; Hagen and Keigwin 2002). Sites 1056, 1059, and 1062 form a depth transect off the United States east coast that traces the deep western boundary currents (Figure 4). Due to their close proximity, Site 1059 and JPC-37 record identical climatic variations (Hagen and Keigwin 2002). Sites above ~4000 m water depth (Sites 1056, 1059, and JPC-37), are mostly bathed by a northern water source (North Atlantic Deep Water = NADW) carried by the DWBC, while sites at greater depths (Site 1062) have larger proportions of recirculated southern-sourced water (Antarctic Bottom Water = AABW) (Jenkins and Rhines 1980; Keigwin et al. 1998). More specifically, Site 1056 lies within Upper-North

Atlantic Deep Water (U-NADW) sourced from the Labrador Sea, and Sites 1059 and

JPC-37 lies within Lower-North Atlantic Deep Water (L-NADW) sourced from the Norwegian Sea (Keigwin et al. 1998). Due to the position of Sites 1056 and 1059 within the core of NADW, they should be insensitive to all but the largest changes in the mixing zone between the AABW and NADW. However, Site 1062 is well placed to trace distinctive changes in the relative fluxes of northern and southern sourced deep water through time because it is located near the mixing zone of NADW and AABW (Keigwin

19 et al. 1998; Poirier and Billups 2014). Presently, NADW forms with a temperature of ~2.5°C and AABW penetrates the deep Atlantic with a temperature close to -1°C (Martin et al. 2002). Current bottom water temperatures associated with Sites 1056, 1059, and 1062 are 3.6°C, 2.7°C, and 1.8°C, respectively (Table 1).

Figure 3. Map of the ODP sites at the Blake-Bahama Outer Ridge modified from Franz and Tiedemann (2002). Sites 1056, 1059, and 1062 (circled) are used in this study.

20 Table 1. Site information for ODP Cores 1056D, 1059A, and 1062B from the Blake- Bahama Outer Ridge.

Bottom Water Site Water Depth (m) Temperature (°C)* 1056D 2178 3.6 1059A 2997 2.7 1062B 4780 1.8

*Temperature from Levitus (1994) and Leg 172 Initial Results Volume from Keigwin (1998).

21 3.2 Species Selection I assess amino acid racemization within Pulleniatina obliquiloculata (Figure 5A), Globorotalia truncatulinoides (Figure 5B), and Globorotalia tumida (Figure 5C), which are three species of planktonic foraminifera abundant in the Atlantic Ocean. These three species were chosen because of their relatively large tests, common locality across a broad region of low latitudes, abundance within cores of the Blake-Bahama Outer Ridge, and previous use in AAR investigations (e.g. Wehmiller and Hall 1997; Hearty et al.

2004; Kaufman 2006; Kaufman et al. 2013). G. tumida has also been used in previous studies of bleaching pretreatments (e.g. Stathoplos and Hare 1993). By analyzing multiple species in AAR, I can assess the inter-species variability in the D/L ratios between the two pretreatments.

Figure 5. Scanning electron microscope (SEM) images of the foraminiferal species P. obliquiloculata (A), G. truncatulinoides (B), and G. tumida (C) by Kennett and Srinivasan (1983).

23 3.3 Sampling Strategy Age equivalent samples of ~6 kyr BP from Sites 1056, 1059, and 1062 were chosen for analysis. The ages are based on published Holocene ages from Grützner et al. (2002) who tuned the percent calcium carbonate within the sediment to orbital precession and obliquity (Figure 2). The shallower sites (Sites 1055-1058) display better developed precession cycles in the carbonate record and are thus tuned to precession, while the deeper sites (Sites 1060-1063) contain higher spectral density in the obliquity band and are thus tuned to obliquity (Grützner et al. 2002). In both cases, the final “phase adjusted” age model assumes a 5 kyr lag of the climate response (here %CaCO3) behind the forcing and is derived by subtracting 5 kyr from the tuned ages. As discussed by Grützner et al. (2002), the carbonate variability reflects glacial/interglacial variability due to the excellent parallel with the δ18O record, which indicates variations in global ice volume. For example, the current interglacial period of the Holocene (MIS 1; 0-14 ka) and the last interglacial period of the Pleistocene (MIS 5; 71-130 ka) show high carbonate content, while the most recent glacial period (14-71 ka) and the last glacial period of the

Pleistocene (MIS 6; 130-191 ka) show low carbonate content (Figure 6). Applying this age model shows excellent agreement in the %CaCO3 variations at the finer scale among the three study sites; therefore, we use it to identify age equivalent intervals (6 kyr BP) corresponding to the Holocene %CaCO3 maxima (Table 2; Figure 6). Ages for the down-core (Pleistocene-early Holocene) samples from KNR140-2 JPC-37 and Site 1056 were determined from δ18O stratigraphy (Hagen and Keigwin 2002; Billups et al. 2004; Table 2). Hagen and Keigwin (2002) correlated the JPC-37 planktic foraminiferal δ18O record to the δ18O record from nearby BBOR Site 1059, which is determined from a combination of 14C ages and planktic foraminiferal δ18O tuning to the Greenland ice core records. The Site 1056 age model is determined by

24 adjusting its planktic foraminiferal δ18O record to the orbitally tuned δ18O record from North Atlantic Site 980 (Billups et al. 2004).

25 Table 2. Summary of interval, depth in core, and stratigraphic age for sites used in this study. Stratigraphic ages for Holocene and down-core samples are 18 determined from %CaCO3 orbitally tuned (Grützner et al. 2002) and δ O stratigraphy (Hagen and Keigwin 2002; Billups et al. 2004), respectively.

Interval Depth Stratigraphic Core (cm) (mcd)a Age (ka)

Holocene

1056D 1H-1 62-64 0.62-0.64 6.00

1056D 1H-1 64-66 0.64-0.66 6.08

1056D 1H-1 66-68 0.66-0.68 6.17

1056D 1H-1 68-70 0.68-0.70 6.25

1056D 1H-1 70-72 0.70-0.72 6.33

1056D 1H-1 72-74 0.72-0.74 6.42

1059A 1H-1 44-46 0.44-0.46 6.08 1059A 1H-1 50-52 0.50-0.52 6.33

1059A 1H-1 54-56 0.54-0.56 6.49 1062B 1H-1 52-54 0.52-0.54 6.62 1062B 1H-1 57-59 0.57-0.59 6.84 1062B 1H-1 62-64 0.62-0.64 7.06

Down Core

KNR140 JPC-37 150-152 --- 10.5

KNR140 JPC-37 238-256 --- 15.4

KNR140 JPC-37 458-460 --- 21.8

KNR140 JPC-37 666-676 --- 30.8

KNR140 JPC-37 1112-1114 --- 51.5

KNR140 JPC-37 1615-1617 --- 86.4

26 Table 2 Continued

Interval Depth Stratigraphic Core (cm) (mcd)a Age (ka)

1056B 5H-7 44-46 35.34-35.36 410 a In the piston core (KNR140 JPC-37) depth in meters composite depth (mcd) do not apply. The intervals are depth in consecutive order.

27 3.4 Analytical Methods

3.4.1 Foraminiferal Picking About 20 cm3 of Holocene sediment from Sites 1056, 1059, and 1062 were obtained from the IODP core repository. The 12 sediment samples were processed following standard procedures. Each bulk sediment sample was disaggregated in a buffered sodium metaphosphate solution and washed through a 63 μm sieve using deionized water. The >63 μm fraction was then air dried and put in glass vials. All P. obliquiloculata, G. tumida, and G. truncatulinoides (separated based on sinistral and dextral coiling direction) from an interval were hand-picked from the >350 μm fraction using a dedicated paint brush and MilliQ water. Gloves were worn to minimize contamination with modern organics. The tests picked for each species were then placed into small plastic vials for shipping to the Amino Acid Geochronology Lab at Northern Arizona University for method testing and analysis.

3.4.2 Pretreatment Methods

All samples were soaked in hydrogen peroxide (H2O2) in order to remove any surface organics from the foraminifer tests. One hundred fifty tests of each species were placed into 16 mm OD glass culture tubes. Each tube was filled with DI water and sonicated to ensure that any surface organics had been loosened. The tests were soaked in

3% H2O2 for 2 hours, rinsed three times with reagent grade H2O, and dried under laminar flow. The dry tests were then divided for further method testing (100 tests for the bleached method and 50 tests for the non-bleached method).

3.4.2.1 Non-bleached Method The 50 cleaned tests for each species were divided among 10 hydrolysis tubes. For total acid hydrolysate analysis, cleaned samples were hydrolyzed by dissolving in 7

28 μL of 6 M HCl, sealing under N2 atmosphere, and heating at 110°C for 6 hours. This hydrolysis step breaks peptide bonds connecting the chains of amino acids so that the total amino acid population of the samples could be measured. Hydrolysates were evaporated to dryness in a vacuum desiccator. Samples were rehydrated with 4 μL of slightly acidic water with L-hArg synthetic amino acid used as an internal spike.

3.4.2.2 Bleached Method Samples were pretreated according to the method of Penkman et al. (2008) with slight modifications for smaller sample sizes. The 100 cleaned tests for each species were divided among 10 hydrolysis tubes. To reduce the amino acid content to a residual level and isolate the intra-crystalline fraction, tests were gently broken (rather than crushed using a mortar and pestle in Penkman et al. 2008) and 12% bleach (NaOCl) was added into each tube. The tubes were shaken, left for 24 hours, re-shaken to ensure complete exposure to the bleach, and soaked for another 24 hours. After the 48 hours, the bleach was pipetted off and samples were rinsed with water 3-5 times before being left to dry under laminar flow. Unlike the methods of Penkman et al. (2008), methanol was not added to assist in removing the bleach. The dry fragments were transferred to microreaction vials and hydrolyzed, rehydrated, and analyzed using the same procedure as the non-bleached samples.

3.4.3 Analysis on HPLC Total hydrolysable amino acid enantiomers were resolved by reversed phase liquid chromatography (HPLC) using the method of Kaufman and Manley (1998) with modifications by Kaufman (2000) for individual microfossils. Briefly, the procedure uses a C18 stationary phase (Hypersil BDS, 5 μm), pre-column derivatization with OPA/IBLC (N-isobutyryl-L-cysteine), and fluorescence detection. The detector response was

29 externally calibrated by analyses of an internal spike solution of L-hArg. Chromatographic peak areas for the amino acids of importance were divided by a single mean value for the external spike (2 µL injection = 2100 fluorescence units) measured to yield the amino acid abundance per foraminiferal test (Kaufman 2006).

3.4.4 Radiocarbon Dating In order to confirm the stratigraphic ages of intervals from Sites 1056, 1059,

1062, and JPC-37 (Table 2), rapid 14C AMS was used following previously established methods at the Keck AMS facility at the University of California Irvine (Bush et al. 2013). The rapid method provides radiocarbon dates with decreased precision at a lower cost than standard AMS procedures. Bush et al. (2013) determined that the rapid and high precision methods correlate well generally with an average deviation of 1.8% for samples <10 ka, but this deviation increases for older samples. Since the majority of samples sent for radiocarbon dating was Holocene in age, the 14C ages from the rapid method should be akin to AMS procedures.The rapid method uses powdered carbonate for the AMS target thereby avoiding the time consuming step of producing filamentous graphite (Bush et al. 2013). Most importantly for studies involving foraminifera, the sample size required for the rapid AMS procedure is much smaller (< 1 mg) compared with standard AMS (typically several milligrams). Holocene samples for radiocarbon dating were selected to bracket the top and bottom intervals at each site. Sample preparation for rapid radiocarbon dating at the Keck AMS facility was conducted at Northern Arizona University. Untested foraminiferal tests were rinsed in reagent grade water, soaked in peroxide, and rinsed again before being left to dry. The dry tests were then broken, mixed with iron powder, and pressed into aluminum target holders for direct 14C accelerator mass spectrometry measurements.

30 Sample preparation backgrounds were subtracted based on measurements of 14C-free marble. All results have been corrected for isotopic fractionation according to the conventions of Stuiver and Polach (1977).

31 Chapter 4

COMPARISON OF 14C AGES AND PUBLISHED STRATIGRAPHY

In order to confirm the stratigraphic ages of the samples obtained for this study, I

14 compared the low precision C ages with published ages from CaCO3 stratigraphy for Holocene samples (Grützner et al. 2002) and δ18O stratigraphy for down-core samples (Hagen and Keigwin 2002; Billups et al. 2004) (Table 3). Overall, seven of the nine

Holocene samples display excellent agreement between the initial, CaCO3 orbitally tuned ages and the low precision 14C ages, with an average difference of only 0.92 ka (Table 3). This difference is small in comparison to the potential 5 kyr uncertainty related to the tuning procedure of Grützner et al. (2002) at these sites. Within the 62 cm interval from Sites 1056, 1059, and 1062, the average differences are 1.26 ka, 1.06 ka, and 0.28 ka respectively. The outlier is the 52 cm interval from Site 1062, with an average difference of 2.06 ka between the age models, which is significantly greater than those observed at the other Holocene samples. Within the down-core site (JPC-37), the radiocarbon age for the 238 cm interval agrees with the δ18O stratigraphy, while the radiocarbon age for the 666 cm interval does not. The 238 cm interval (expected to be 15.4 ka from the δ18O stratigraphy) displays a difference of 1.31 ka between the age models (14C and δ18O), and the 666 cm interval (expected to be 30.8 ka from δ18O) shows a difference of 8.87 ka between the age models. The 666 cm interval shows a 14C age that is younger than can be accounted for by the uncertainty in the tuned age model, which is approximately 500-2000 years based on 14C dating of the core (Hagen and Keigwin 2002). It may be that the discrepancy is

32 due to the increasingly larger uncertainty in low precision 14C ages with samples older than 10 ka and/or the high variation in carbonate blanks that has a large effect on samples older than 30 ka (Bush et al. 2013). While the successive intervals from Sites 1056 and 1059 show radiocarbon dates in line with stratigraphic principles, there is an age reversal in the 14C ages between the two intervals of Site 1062 (Table 3). Sample 1062B 52 cm gives an older age (8.48 and 8.87 ka from 14C analyses of G. truncatulinoides and P. obliquiloculata, respectively) than the sample ~10 cm lower in the core (6.68 and 7.23 ka, P. obliquiloculata and G. truncatulinoides, respectively). This is surprising because ages calculated from the orbital tuning of %CaCO3 in the cores are stratigraphically consistent at 6.62 ka and 7.06 ka for the 52 cm and 62 cm intervals, respectively. The two ages for the 62 cm interval are within ~170-380 years (7.06 ka from orbital tuning vs. 6.68 and 7.23 ka from 14C), which is well within the error due to tuning and/or the 14C analysis. On the other hand, the two ages for the 52 cm interval are offset by ~1.86-2.25 ka (6.62 ka from orbital tuning vs.

8.48 and 8.87 ka from 14C). I also observe that ages determined from the rapid 14C method, although within error, are consistently younger than those of %CaCO3 orbital tuning except for the Site 1062B 52 cm interval where they are significantly older. Therefore, I surmise that it is the 52 cm interval that is the outlier and that the low precision 14C ages for this interval are older than expected.

There are a number of possible explanations for the age discrepancy apparent at the 52 cm interval from Site 1062B. First, it would be theoretically possible that foraminiferal tests at the 52 cm interval were contaminated through secondary addition of older carbon within the sediment or the lab. These types of contaminations go unnoticed during the inspection of tests under an optical microscope (Ausín et al. 2019). Since there is no chemical pretreatment prior to low precision 14C analyses (Bush et al. 2013), any

33 carbon contaminations on the outer shell would have been included in the AMS analysis. However, the 14C analyses were repeated at this interval; therefore I can rule out lab contamination because the duplicates show the same amount of older carbon. Second, it is possible that the sample incorporates older foraminifera reworked up into the younger sediment. However, in order to explain radiocarbon ages that are approximately 2 ka too old, transport and deposition of a large number of older foraminifera would have been necessary (Ausín et al. 2019). If the abundance of foraminifera in the 52 cm interval decreased relative to adjacent intervals, bioturbation would be expected to up-mix some of the older, more robust foraminifera (P. obliquiloculata and G. truncatulinoides), resulting in an enrichment of older specimen in the 52 cm interval and deviation in expected radiocarbon ages (Ausín et al. 2019). Yet, the effect of bioturbation on mixing tests of different ages is usually dampened at sites of high sediment accumulation such as Site 1062B (Peng and Broecker 1984; Mekik 2014). Furthermore, bioturbation homogenizes sediments within an average sediment depth of 8-10 cm (Peng and

Broecker 1984; Teal et al. 2008); therefore, I should see the ages affected similarly at the 62 cm interval. However, the radiocarbon age for the 62 cm interval is closer to the phase adjusted age than the 14C age of the 52 cm interval, thereby effectively reducing bioturbation as a likely method causing the older radiocarbon age at the 52 cm interval. Due to the position of Site 1062B 400 m downslope on the east side of a 37 m high mud wave (Keigwin et al. 1998), reworked specimens could have been introduced to the 52 cm interval by advection and along-slope/downslope sedimentary processes

(Broecker et al. 2006; Mekik 2014; Ausín et al. 2019). This type of transport occurs when sediment is physically transported from the original site of deposition (Mekik 2014). Sediment instability due to bottom currents can result in the transport and redistribution of sediments supplied to the slope by downslope flows and vertical settling (Weaver et al.

34 2000). If there was a change in bottom current flow velocity, turbidity currents, or advection, sediment could have been transported downslope causing debris flows and mixing of the sediments (Weaver et al. 2000). Debris flows transport granular solids on a low slope with small runout distances, meaning that less sediment is transported towards the bottom of a mud wave (Weaver et al. 2000). A potential problem with this explanation is that we only see the old age for the 52 cm interval, meaning that the reworked sediment does not extend past 62 cm in the core. Since I do not have any samples from higher up the core in 1062B, I do not know how the core top could have been affected by potential down-slope movement. While sediment transport can explain the reversed stratigraphy, I do not see any evidence of disturbances associated with mud waves in the shipboard core photos (Keigwin et al. 1998) or the %CaCO3 record (Grützner et al. 2002). The excellent agreement between the stratigraphic ages and the 14C ages in all but one of the Holocene intervals supports using the rapid 14C AMS method for the purpose of confirming the initial age control. Site 1062B 52 cm is the only interval out of the seven Holocene samples where 14C ages indicate a discrepancy from the established stratigraphy. Because of the potential for an otherwise undetected core disturbance, I have not obtained further D/L data from this interval. Holocene 14C ages here are based primarily on the foraminiferal species P. obliquiloculata, while those for the down-core site are based on G. truncatulinoides. Different species have been shown to give varying radiocarbon dates within a single sample interval due to differences in calcifying depth, robustness, and dissolution resistance (Ausín et al. 2019; Broecker et al. 2006; Mekik 2014). No significant species differences in the radiocarbon dates (average difference of ±0.54 ka; n = 4) were shown at Site 1062 where 14C ages were obtained for both species. Thus potential species related

35 bias can be ruled out, which is particularly important where we only have G. truncatulinoides.

Table 3. Rapid 14C age measurements compared to δ18O (Hagen and Keigwin 2002; Billups et al. 2004) and %CaCO3 orbitally tuned (Grützner et al. 2002) age models.

Interval 14C Age Stratigraphic Core (cm) (ka) Age (ka)

Holocene

1056D 1H-1 62-64 4.82 ± 0.140a 6.00

1056D 1H-1 64-66 4.82 ± 0.120a 6.08

1056D 1H-1 70-72 5.00 ± 0.130a 6.33 1059A 1H-1 44-46 5.04 ± 0.090a 6.08

1059A 1H-1 54-56 5.42 ± 0.100b 6.49

8.48 ± 0.080b 1062B 1H-1 52-54 6.62 8.87 ± 0.240a 6.68 ± 0.150a 1062B 1H-1 62-64 7.06 7.23 ± 0.120b

Down Core KNR140 JPC-37 238-256 13.990 ± 0.110b 15.4

KNR140 JPC-37 666-676 21.930 ± 0.270b 30.8 a, b 14C ages determined from P. obliquiloculata and G. truncatulinoides, respectively.

36 Chapter 5

PRETREATMENT ANALYSIS

5.1 Effect of Bleaching on the Subsample Rejection Rate I followed the three step screening procedure from Kosnik and Kaufman (2008) to systematically identify subsample outliers due to the potential of exogenous amino acids to contaminate foraminifera and skew the results of D/L analyses (Kaufman et al. 2013). Each sample contains only one species from within a core interval and is made up of an average of 9 subsamples (i.e. replicate measurements) (Figure A1). First, the concentration of serine (Ser), a labile amino acid that is present only in low concentrations within fossils due to its rapid decomposition, was used to identify subsamples with aberrantly high levels of this amino acid, thereby indicating contamination by modern amino acids (Kaufman 2006; Kosnik and Kaufman 2008; Kaufman et al. 2013). Subsamples with high Ser content almost always have D/L values that are lower than other subsamples, effectively skewing the mean D/L value for a sample (Kaufman et al. 2013). The abundance of L-Ser was assessed with respect to L- Asp, whose concentration also decreases with sample age. I rejected individual subsamples with L-Ser/L-Asp values ≥ 0.9 (rejection criteria 1 in Table A1). Second, the covariance between the D/L ratios of glutamic acid (Glu) and aspartic acid (Asp) was used to identify subsamples with D/L values that deviate from the trend of other subsamples within a sample (Kaufman 2006; Kaufman et al. 2013) (Figure A2, Figure A3, rejection criteria 2 in Table A1). Third, subsamples with D/L Asp or Glu values that

37 fell beyond ±2σ of the mean of the rest of the group were rejected (Kaufman 2006; Kaufman et al. 2013) (rejection criteria 3 in Table A1). Of the 382 subsamples measured from the 21 core intervals and species, 27 (7.1 %) were rejected. Of these, 13 (3.4%) were rejected based on high serine content, 3 (0.8%) were rejected due to falling off the Asp D/L vs Glu D/L trend of the sample, and 11 (2.9%) were rejected due to falling beyond the ±2σ of the mean of the group (Table A1). Unbleached and bleached subsamples for all species (n=382) show 7.6% and 7.0% subsample rejection, respectively, indicating no decrease in the rejection rate based on the bleaching pretreatment (Table 4). For the Holocene samples specifically (n=291), the bleached method shows a decrease in the rejection rate by 0.3%, while the down-core samples (n=91) show a decrease of 1.9% (Table 4). The rejection rate of down-core samples for both pretreatments is approximately two times higher (11.1% for bleached; 13.0% for unbleached) than in the Holocene samples (5.7% for bleached; 6.0% for unbleached).

I also notice species differences in the subsample rejection rates when the species are considered individually in the Holocene and down-core sites. For both Holocene and down-core sites as a whole, bleached P. obliquiloculata show an increase in subsample rejection relative to unbleached P. obliquiloculata while bleached G. truncatulinoides show a decrease in the subsample rejection relative to unbleached G. truncatulinoides

(Table 4). In the Holocene samples, G. tumida shows an increase in subsample rejection with the bleach pretreatment method. Since I do not have down-core samples of G. tumida, I do not know whether this is a reoccurring trend within the species.

38 Table 4. Percent of subsamples rejected. The species in red show higher rejection rates in the bleached samples than unbleached samples. Data used to determine the subsample rejection rate are shown in Table A2.

Foraminifera Species na Unbleached Bleached All Samples All Species 382 7.6% 7.0%

Holocene All Species 291 6.0% 5.7% P. obliquiloculata 89 8.5% 9.5% G. truncatulinoides 144 6.6% 2.9% G. tumida 58 0.0% 6.7%

Down Core All Species 91 13.0% 11.1% P. obliquiloculata 36 10.5% 23.5% G. truncatulinoides 55 14.8% 3.6% a Number of subsamples analyzed.

39 5.2 Effect of Bleaching on the Concentration of Amino Acids Amino acid concentrations of the total hydrolysable fraction (THAA) of amino acids are summarized by species and site in Table A3. Differences in amino acid concentrations between bleached and unbleached samples were assessed for statistical significance using Welch’s t-tests with significance evaluated at the 95% confidence level (α = 0.05). On average, the total amino acid concentration is 165 pmol/test and 52 pmol/test for unbleached and bleached Holocene samples, respectively (Figure 7). Here the amino acid concentrations for the pretreatments are significantly different (P = 1.8*10-8) with bleach reducing the concentration by 113 pmol/test on average or 68%. For down-core samples, the average total amino acid concentration is 135 pmol/test and 53 pmol/test for unbleached and bleached samples, respectively, which also shows a significant reduction (61%) in amino acid concentration with bleaching (P = 2.3*10-3) (Figure 7). When treated with NaOCl, the total concentration of THAA in all species decreased (Figure 8). Generally, unbleached G. tumida within Holocene samples has the highest average total concentration (> 200 pmol/test) (Figure 8A). Of the unbleached samples, P. obliquiloculata has the lowest average total recovery (128 pmol/test and 116 pmol/test for Holocene and down-core samples, respectively). These findings are not surprising because the tests of G. tumida and P. obliquiloculata are typically the largest and smallest among the species, respectively. The total concentration of amino acids shows slightly different trends between the species of Holocene and down-core samples (Figure 8). While there seems to be more variation between the total hydrolysates of the species within bleached and unbleached Holocene samples, the species within both pretreatments in down-core samples seem to be more uniform. Yet, the relative proportions of amino acids in the THAA of all species remain relatively similar upon the

40 addition of bleach (Figure 9). Within down-core samples, bleach causes a slight increase in the proportion Ala and decrease in the proportion of Asp.

Figure 8. Average recovery of total amino acid (Asp, Glu, Ser, Ala, Val, Phe, Ile, and Leu) concentrations (pmol/test) for each foraminiferal species from Holocene (A) and down-core (B) samples. Data are listed in A3.

43 5.3 Effect of Bleaching on the D/L Ratios by Species Box and whisker plots of the aspartic acid (Asp) and glutamic acid (Glu) D/L ratios were used to visualize the effect of bleaching on the mean D/L ratio (average D/L of the subsamples) of a sample and standard deviation of the subsamples. Holocene plots of Asp (Figure 10) and Glu (Figure 11) focus on P. obliquiloculata, G. truncatulinoides (sinistral), and G. tumida at Holocene Sites 1056D, 1059A, and 1062B. Down-core plots of Asp (Figure 12) and Glu (Figure 13) focus on P. obliquiloculata and G. truncatulinoides (sinistral and dextral) at Sites JPC-37 and 1056B. The coiling directions (sinistral and dextral) of G. truncatulinoides are treated separately here in case there are any potential differences in the D/L ratios between the coiling directions (see Section 5.4). Therefore, Holocene intervals that have both varieties of G. truncatulinoides (Site 1059A 44 cm and 54 cm) are plotted based on the sinistral variety because they are more abundant (Figure 10E, Figure 11E). For Holocene samples, bleaching generally reduces the standard deviation in the subsamples for Asp and Glu (Figure 10 and Figure 11, respectively), as opposed to down-core samples where the standard deviation for Asp and

Glu remains relatively constant upon bleaching (Figure 12 and Figure 13, respectively). Welch’s independent t-tests were used to determine whether there is a significant difference between the mean D/L ratios for bleached and unbleached samples from the same interval and species (Table 5). t-test results for the Holocene sites show that 10/16 and 5/16 samples had significant differences (P < 0.05) in the mean D/L values between the two pretreatments for Asp and Glu, respectively (Table 5). When the Holocene results are broken down by species, G. tumida has the largest proportion of samples indicating considerable differences between the pretreatments for both amino acids (Figure 10C and 10F, Figure 11C and 11F). P. obliquiloculata and G. truncatulinoides (sinistral) show the greatest resistance to Asp (Figure 10A and 10D) and Glu (Figure 11B, 11E, and 11G)

44 D/L differences respectively, between the pretreatments with only 2/5 and 0/6 samples resulting in significant P-values. For Asp and Glu samples that showed significant differences, bleach increased the D/L of all P. obliquiloculata samples (n=4) and decreased the D/L of all G. truncatulinoides (sinistral) samples (n=4). The effect of bleach on G. tumida is much more complicated where 3/5 significant differences showed that bleach decreases the D/L values. G. truncatulinoides (dextral) has only two samples that show significance (Site 1059A 54 cm interval Asp and Glu); therefore, it is difficult to determine a trend with only two comparison points. Unlike the Holocene sites, down-core sites show negligible significance in the mean values between samples from the differing treatment methods (Table 5). t-test results for the down-core sites show that 0/5 (Asp) and 1/5 (Glu) samples had significant differences in the mean D/L ratios between the bleaching and non-bleaching methods (Figures 12 and 13, respectively).Only one P. obliquiloculata Glu sample indicated a difference in the mean D/L between pretreatments (Figure 13C).

Within a sample, I looked at three of the variables that can contribute to differences in the D/L ratios of a single site: pretreatment (fixed factor), foraminifera species (fixed factor), and sample interval (random factor). By looking at only one species and one site at a time, two-way replicated analyses of variance (ANOVA) were used to test for the significance of the pretreatment on the subsample mean D/L values for Holocene samples (Table 6). More specifically, these ANOVAs were arranged for each Holocene site to determine whether there was an effect of the treatment (fixed factor) within the site intervals (random factor) on the D/L ratio (response variable). ANOVA is the most powerful approach known for simultaneously testing whether the means of different groups are equal. It works by assessing whether individuals chosen from different groups (i.e. D/L ratios from bleached subsamples, unbleached subsamples,

45 and subsamples from different intervals) are, on average, more different than individuals chosen from the same group. Largely, the ANOVA results indicate that the D/L values between intervals of the Holocene sites do not differ significantly. This makes sense because the intervals of a site are closely spaced and show approximately the same age, thus the D/L ratios should closely resemble each other. The ANOVA results align with those from the t-tests, indicating that the D/L ratios of some Holocene samples are impacted by the bleaching pretreatment. For Site 1056D, there are significant differences in the D/L ratios between the treatments for two of the three species (P. obliquiloculata and G. truncatulinoides sinistral) for Asp and all three species for Glu. For Site 1059A, only one of the species (G. truncatulinoides sinistral and dextral) displays significant differences between the treatments. In sum, t-tests determined that there were some differences in the mean D/L values between the two pretreatments for Holocene samples. Most notably, for Asp and Glu samples that indicated significant differences, bleach caused an increase the D/L of all P. obliquiloculata and decrease in the D/L of all G. truncatulinoides (sinistral) and most G. tumida. However, down-core samples reveal negligible differences between the pretreatments. From this information, it is evident that the temperatures determined for down-core samples would be similar reguardless of the pretreatment method utilized.

Figure 11. Same as Figure 10 but for glutamic acid (Glu) D/L ratios.

Figure 12. Down-core plots of the aspartic acid (Asp) D/L ratios from Sites JPC-37 (A- B) and 1056B (C-D) to compare the effect of bleaching on sample mean and standard deviation within P. obliquiloculata and G. truncatulinoides (dextral and sinistral). Mean Asp D/L values are shown as dashed lines for each treatment. The box is plotted from the first quartile to the third quartile. The whiskers extend from each quartile to the minimum or maximum values. Subsample values outside of the quartiles by more than 1.5 times the interquartile range are plotted as small circular data points. The numbers are the P-values from Welch’s independent t-tests (5) of each interval individually that evaluate the significance of the treatment on the subsample mean D/L values. P-values < 0.05 are significant.

Figure 13. Same as Figure 12 but for glutamic acid (Glu) D/L ratios.

50 Table 5. Mean D/L values for the unbleached (unbl) and bleached (bl) treatments with the statistical results of Welch’s independent t-tests.

Interval Asp D/L Glu D/L Site Speciesa (cm) Unbl Bl Pc Unbl Bl Pc Holocene Sites 1056D 62 P. obliq 0.111 0.129 0.0038 0.053 0.064 0.0434 1056D 64 P. obliq 0.122 0.134 0.0002 0.056 0.063 0.0068 1056D 70 P. obliq 0.126 0.123b 0.6881 0.059 0.057b 0.5627 1056D 64 G. trun (s) 0.143 0.123 0.0004 0.060 0.054 0.0715 1056D 70 G. trun (s) 0.144 0.129 0.0004 0.061 0.058 0.2054 1056D 64 G. tum 0.125 0.143b 0.0007 0.053 0.100b 0.0002 1056D 68 G. tum 0.139 0.125 0.0234 0.061 0.054 0.2291 1059A 44 P. obliq 0.125 0.126 0.8821 0.060 0.062 0.5751 1059A 54 P. obliq 0.129 0.125 0.3692 0.060 0.062 0.5850 1059A 44 G. trun (s) 0.134 0.130 0.2548 0.059 0.060 0.4539 1059A 44 G. trun (d) 0.131 0.134 0.1998 0.056 0.056 0.9436 1059A 50 G. trun (s) 0.135 0.133 0.7726 0.058 0.064 0.0684 1059A 54 G. trun (s) 0.147 0.130b 0.0002 0.061 0.063b 0.3748 1059A 54 G. trun (d) 0.129b 0.149 0.0003 0.052b 0.060 0.0062 1059A 44 G. tum 0.152 0.131 0.0009 0.069 0.054 0.0184 1062B 62 G. trun (s) 0.155 0.133 0.0097 0.060 0.057 0.3900

Down-Core Sites JPC-37 150 P. obliq 0.178 0.181 0.6772 0.072 0.080 0.1998 JPC-37 150 G. trun (s) 0.206 0.196 0.0702 0.080 0.081 0.7880 JPC-37 1112 G. trun (d) 0.286 0.284 0.7495 0.098 0.098 0.9361 1056B 44 P. obliq 0.432 0.437 0.6963 0.225 0.239 0.0386 1056B 44 G. trun (d) 0.463 0.464 0.8752 0.249 0.244 0.4924 a P. obliq = Pulleniatina obliquiloculata; G. trun (s) = Globorotalia truncatulinoides (sinistral); G. trun (d) = Globorotalia truncatulinoides (dextral); G. tum = Globorotalia tumida b These D/L values are either higher or lower than expected values based on adjacent D/L ratios within a core interval (see Table A5). c P-values from independent t-tests of the subsamples where the null hypothesis was that the true difference in means is equal to 0. Samples in red refute the null hypothesis and show a significant (P<0.05) difference in the means of the treatments.

51 Table 6. Results of two-way replicated ANOVA models to determine the effects of the different pretreatments on the D/L ratios.

Asp D/L P-valuesa Glu D/L P-valuesa Site Species Treatment Interval Treatment Interval 1056D P. obliquiloculata 0.0002 0.3400 0.0065 0.4753 1056D G. truncatulinoides (s) 1.495*10-6 0.2935 0.0324 0.3224 1056D G. tumida 0.4393 0.4221 0.0003 0.0003 1059A P. obliquiloculata 0.4781 0.4180 0.4826 0.8903 1059A G. truncatulinoides (s) 0.0074 0.1285 0.0258 0.1493 1059A G. truncatulinoides (d) 2.163*10-5 0.0059 0.0242 0.6848 a Samples in red refute the null hypothesis and show a significant (P < 0.05) difference in the means of the treatments.

52 5.4 Effect of Bleaching on the Variability of D/L Ratios of Subsamples within a Sample Reducing the variability (i.e. increasing the precision) of the D/L ratios of the subsamples of a particular sample is needed to improve AAR as a paleothermometer. The variability was determined using a coefficient of variation (CV) for both pretreatments. The CV describes the variation in D/L ratios among approximately 5-10 subsamples per sample (i.e. one species from a single core interval). The CV, represented as a percent, is calculated as the ratio of the standard deviation of the D/L values of the subsamples to the mean D/L value multiplied by 100 (Table A6). D/L values vary by approximately 5-14% depending on the pretreatment and amino acid analyzed (Table 7). The average CVs for Holocene (5-14%) and down-core sites (5-10%) are very similar when all species are grouped together. However, when the species are analyzed separately, I notice slight differences in the average CVs for each species in Holocene and down-core sites, in line with the observation of Kaufman et al. (2013) (Table 7). To quantify the average change in the sample variability between the pretreatments for Asp and Glu, I subtracted the average unbleached CV from the average bleached CV for each sample. Thus, a decrease in the sample variability is described by a decrease in the CV and indicates an improvement due to the bleaching pretreatment. Considering all samples (n=21), bleaching reduces the variability in D/L values within a sample by an average of 1.1% and 3.0% for Asp and Glu, respectively (Table 7). I notice that the amino acid Glu allows for a slightly greater improvement in the variability with the bleaching pretreatment. Results from Glu show that the CV in 13/16 and 4/5 samples were improved for Holocene and down-core sites, respectively, as opposed to only 10/16 and 2/5 samples improved for Asp. Within Holocene samples, bleaching slightly reduces the variability in D/L values within a sample by an average of 1.8% (Asp) and 3.5% (Glu) (Table 7). Down-core samples are affected differently. In

53 these samples, bleaching causes a slight increase in the average D/L variability of Asp by 1.2% and decrease in the variability of Glu by 1.5% (Table 7). Results also highlight that sample variability differs between species. Among the three species, P. obliquiloculata shows the largest and most consistent improvement in the CV with bleaching. On average, the CVs for P. obliquiloculata decrease by 1.6% (Asp) and 6.4% (Glu) within Holocene sites and by 0.2% (Asp) and 2.5% (Glu) within down-core sites (Table 7). In contrast, the sample variability from G. truncatulinoides is the least consistent. On average, the CVs from this species decrease 2.0% (Asp) and 4.1% (Glu) for Holocene sites. Down core, the CVs increase 2.1% (Asp) and decrease by 0.9% (Glu). In sum, bleaching reduces the variability in D/L values among subsamples from the same interval for Asp and Glu by a small amount (1.1% for Asp and 3.0% for Glu). Within down-core samples, I even noticed that bleaching increases the sample variability in Asp. Based on these results, it may not be necessary to add the bleaching step for down-core samples.

54 Table 7. Average sample variability (coefficient of variation, CV) in Holocene and down-core sites for both pretreatments (unbleached = unbl and bleached = bl). Data used to calculate the average variability are shown in Table A6.

CV (%) Asp ΔCV Asp CV (%) Glu ΔCV Glu

Unbl Bl (%)a Unbl Bl (%)a All Samples All Species 6.5 5.4 -1.1 12.7 9.7 -3.0 P. obliquiloculata 6.4 5.2 -1.2 14.4 9.1 -5.3 G. truncatulinoides 6.1 5.2 -0.9 10.3 7.1 -3.2 G. tumida 8.1 6.4 -1.7 17.3 20.2 2.9

Holocene All Species 7.1 5.3 -1.8 13.5 10.0 -3.5 P. obliquiloculata 6.6 4.9 -1.7 15.6 9.2 -6.4 G. truncatulinoides 7.0 5.0 -2.0 10.8 6.7 -4.1 G. tumida 8.1 6.4 -1.7 17.3 20.2 2.9

Down Core All Species 4.5 5.7 1.2 9.9 8.4 -1.5 P. obliquiloculata 5.9 5.7 -0.2 11.4 8.9 -2.5 G. truncatulinoides 3.6 5.7 2.1 9.0 8.1 -0.9 a The values in red show an increase in variance with the bleaching pretreatment where ΔCV = Bleached CV – Unbleached CV.

55 5.5 Effect of Bleaching on Species Differences in D/L For all samples (Figure 14 and Figure 15), unbleached samples of P. obliquiloculata tend to have lower Asp and Glu D/L values than G. tumida and G. truncatulinoides from the same sample interval. Most often, when Holocene samples are bleached, P. obliquiloculata D/L values (Figure 14 C-D) and G. truncatulinoides Glu D/L values (Figure 14 B,D,F,H) remain unchanged, while G. tumida D/L values (Figure 14 A-B, E-F) and G. truncatulinoides Asp D/L values (Figure 14 A,C,G) change (5). For the older species down core, there is no statistical difference in the unbleached and bleached D/L values (Figure 15, Table 5). Welch’s independent t-tests were used to determine whether there is a significant difference (P < 0.05) between the mean D/L ratios for different species from the same interval (Table 8). From these analyses, it is evident that there are species effects on the D/L ratios. Within Holocene intervals, a majority of the species comparisons for Asp (10/13 unbleached and 6/13 bleached) and less than half of the species comparisons for Glu (4/13 unbleached and 5/13 bleached) show significant differences in the means of coexisting species (Table 8). I also gather that the D/L values from unbleached samples have a slightly higher rate of significance due to species effects than bleached samples. The most common species involved in the significant differences of unbleached and bleached samples are G. tumida and P. obliquiloculata, respectively. For down-core intervals, I see the same trend where the majority of species comparisons for Asp (3/4 for both unbleached and bleached) and less than half of the species comparisons for Glu (2/4 unbleached and 1/4 bleached) show significant differences in the mean D/L ratios of the different foraminiferal species (Table 8). Within the down-core analyses, the significance levels (e.g., the number of significant differences with respect to the number of intervals compared) for bleached and

56 unbleached species comparisons are the same. Unlike the Holocene samples, the most common species involved in the differences of unbleached and bleached down-core samples are P. obliquiloculata and G. truncatulinoides (sinistral), respectively. t-tests were also used to determine whether the D/L ratios of the sinistral and dextral coiling directions of G. truncatulinoides were similar enough to be combined for larger sample sizes down core. The results show no definitive answer on whether the coiling direction has an effect on the D/L ratios because 3/4 of the sample comparisons for Site 1059 54 cm (unbleached Asp, bleached Asp, and unbleached Glu samples) give significant P-values while 3/4 of the sample comparisons for Site 1059 44 cm (unbleached Asp, bleached Asp, and unbleached Glu samples) give non-significant P- values (Table 8). Sinistral and dextral G. truncatulinoides also give the same statistical result for the pretreatments within the same sample interval, meaning that if the sinistral variety show a significant difference in the unbleached mean Asp D/L ratios, then the dextral variety will also show a significant difference in the unbleached mean Asp D/L ratios (Table 8). With no clear significance on the D/L ratios due to the coiling direction and insufficient samples sizes for G. truncatulinoides sinistral and dextral individually down core, I will combine the sinistral and dextral samples for subsequent analyses. The rate of racemization is known to differ among taxa. Species were compared based on coeval intervals in order to determine the differences in the rate of racemization among taxa. Due to a lack of samples containing, G. tumida, D/L values of P. obliquiloculata and G. truncatulinoides (sinistral and dextral averaged) were compared in six Holocene and down-core intervals (Figure 16). Using the slope of the regression fit to the D/L versus D/L data as an index of the difference in the rate of racemization indicates that Asp racemizes ~5% faster in G. truncatulinoides for unbleached and 7% faster for bleached samples. Glu racemizes ~14% faster in unbleached G. truncatulinoides and

57 ~4% faster in bleached G. truncatulinoides Kaufman et al. (2013) compared the racemization of P. obliquiloculata to Neogloboquadrina pachyderma, Globigerinoides obliquus, and Globigerinoides sacculifer. He saw that Asp racemizes 12-16% faster in P. obliquiloculata compared with the two other species, while Glu racemizes ~23% faster in P. obliquiloculata compared with N. pachyderma (Kaufman et al. 2013). In sum, we do see species differences in the mean D/L ratios of samples for Holocene and down-core sites. However, the species differences down core are the same regardless of the pretreatment used. Within coeval intervals, G. truncatulinoides show faster racemization rates than P. obliquiloculata.

Figure 14. Aspartic acid (Asp) and glutamic acid (Glu) D/L ratios from Sites 1056D (A-D) and 1059A (E-H) showing the species effects of P. obliquiloculata, G. truncatulinoides (sinistral and dextral), and G. tumida on sample mean and standard deviation. In these box and whisker plots, mean D/L values are shown as dashed lines for each treatment. The box is plotted from the first quartile to the third quartile. The whiskers extend from each quartile to the minimum or maximum values. Subsample values outside of the quartiles by more than 1.5 times the interquartile range are plotted as small circular data points.

60 Table 8. Results of Welch’s independent t-tests to determine the species effects on the D/L ratios.

c c Interval Asp P-values Glu P-values Site Species Comparisona (cm) Unbl Bl Unbl Bl Holocene Sites 1056D 64 P. obliq vs G. trun (s) 0.0010 0.0068 0.1290 0.0058 1056D 64 P. obliq vs G. tum 0.2549 0.0348b 0.3776 0.0014b 1056D 64 G. trun (s) vs G. tum 0.0007 0.0004b 0.0244 0.0002b 1056D 70 P. obliq vs G. trun (s) 0.0009 0.1672b 0.5000 0.6776b 1059A 44 P. obliq vs G. trun (s) 0.0075 0.1473 0.7869 0.5774 1059A 44 P. obliq vs G. trun (d) 0.0207 0.0027 0.2955 0.0064 1059A 44 P. obliq vs G. tum 0.0001 0.0748 0.0647 0.1332 1059A 44 G. trun (s) vs G. trun (d) 0.2603 0.2439 0.3175 0.0105 1059A 44 G. trun (s) vs G. tum 0.0039 0.9602 0.0263 0.1890 1059A 44 G. trun (d) vs G. tum 0.0013 0.1737 0.0066 0.6925 1059A 54 P. obliq vs G. trun (s) 0.0004 0.2236b 0.7339 0.7872b 1059A 54 P. obliq vs G. trun (d) 0.9947b 0.0001 0.0883b 0.4979 1059A 54 G. trun (s) vs G. trun (d) 0.0003b 0.0003b 0.0056b 0.0985b

Down-Core Sites JPC-37 150 P. obliq vs G. trun (s) 0.0005 0.0180 0.1125 0.8290 1056B 44 P. obliq vs G. trun (s) 0.0017 0.0462 0.0050 0.4217 1056B 44 P. obliq vs G. tum 0.0003 0.0995 0.0013 0.0507 1056B 44 G. trun (s) vs G. tumida 0.1352 0.0156 0.2221 0.0334 a P. obliq = Pulleniatina obliquiloculata; G. trun (s) = Globorotalia truncatulinoides (sinistral); G. trun (d) = Globorotalia truncatulinoides (dextral); G. tum = Globorotalia tumida b Mean D/L value of one of the species in the comparison has either a higher or lower than expected values based on adjacent D/L ratios within a core interval (see Figure A2). c Samples in red refute the null hypothesis and show a significant (P<0.05) difference in the mean of the species.

Figure 16. Extent of racemization (D/L) for aspartic acid (A) and glutamic acid (B) measured in six coeval intervals of P. obliquiloculata and G. truncatulinoides. Data are listed in Table A5.

62 5.6 Down-Core Trend As a first order look into the effect of the pretreatments on the down-core trends of D/L ratios, I compare the extent of racemization (D/L ratios) in P. obliquiloculata and G. truncatulinoides, two foraminiferal species abundant down core, as a function of age (Figure 17). The rate of racemization is a function of the integrated post-depositional bottom water temperature experienced at the site following foraminiferal deposition (Kaufman et al. 2013). To extend the down-core trend to 410 ka, I combine Holocene

Site 1059A and down-core Site JPC-37 (both at ~3000 m water depth) with down-core Site 1056B (~2000 m water depth). Combining these cores assumes a similar water mass temperature history and is sufficient for the first order look (will be discussed further in Section 6.1). As expected from AAR geochronology, the D/L ratios increase with age in all samples, reflecting the increased proportion of D-Asp and D-Glu as the samples age due to the extent of racemization (Figure 17). The similar racemization rates for P. obliquiloculata and G. truncatulinoides are again evident in Figure 17 where the slopes of the lines are close to parallel and the D/L ratios are similar. Overall, the rates between the pretreatments for both amino acids from P. obliquiloculata and G. truncatulinoides down core (10.5-410 ka) show no differences. The similar rates between the two pretreatments also confirm the result in Section 5.4 that differences in the mean D/L ratios of down-core species would be essentially the same regardless of which pretreatment was used.Therefore, temperatures determined from down-core samples would be similar regardless of the pretreatments.

64 5.7 Discussion of Pretreatment Analyses In order to infer long-term changes in bottom water temperature, the high error associated with paleotemperature calculations from amino acid racemization must be constrained. Current calculated post-depositional temperatures for this method have uncertainties ranging from ±2 to 4°C with the dominant source of error in the D/L ratios (Kaufman 2003). Kaufman et al. (2013) concluded that one of the biggest limitations to the AAR method was the variability in D/L values among subsamples from a single stratigraphic level. A review of a large collection of AAR data from foraminifer (Kaufman et al. 2013) showed that D/L values typically vary by 10-20%, depending on the species and amino acid analyzed. Here, I see similar variability where D/L values differ by approximately 5-14% depending on the pretreatment and amino acid analyzed (Table 7). Ideally, the bleaching pretreatment should reduce the sample variability in D/L values. Penkman et al. (2008) showed that bleach reduced the CV of gastropods by 51%. However, within this study, bleach only reduces the variability in foraminiferal D/L values within a sample by an average of 1.1% and 3.0% for Asp and Glu, respectively.

Such a small reduction is not worth adding the extra sample preparation time for the bleaching method. Since the down-core trend shows no difference with bleaching, the rest of the down-core samples for temperature reconstruction will not undergo the time consuming bleach pretreatment. In theory, bleaching a foraminiferal test should isolate the intra-crystalline fraction of amino acids, which is less prone to post-depositional environmental influences (i.e. contamination by exogenous amino acids, microbial decomposition, and leaching), thus improving the analytical variability (Penkman et al. 2008). In line with Penkman et al. (2008), bleach significantly reduced but did not completely remove amino acids within the foraminiferal tests. This decrease in amino acid concentration reflects the

65 removal of easily accessed matrix proteins, thereby isolating the intra-crystalline fraction. The results from this study provide further evidence for a residual fraction of amino acids within foraminifera, similar to data published from the molluscs Corbicula, Margaritifera, and Bithynia (Penkman et al. 2008), the bivalve Mercenaria (Crenshaw 1972), and the gastropod Cepaea (Sykes et al. 1995). Here, approximately 32% and 39% of the THAA for Holocene and down-core samples, respectively, were unaffected by the bleach, and is defined as the intra-crystalline fraction. This is a much larger residual fraction than found in mollusk shells (10%, Penkman et al. 2008). Results indicate that the Holocene and down-core sites react differently to the bleach pretreatment. In Holocene samples, bleach causes significant differences in the mean D/L values between 10/16 and 5/16 samples of Asp and Glu, respectively. However, bleach does not significantly affect the D/L ratios in down-core samples. The most likely explanation for why down-core results do not show D/L differences between the pretreatments is that some easily accessed free amino acids and matrix proteins from the inter-crystalline fraction of down-core samples have already been removed over time, possibly due to leaching and/or microbial influences (Penkman et al. 2008; Demarchi and Collins 2015). Therefore, the amino acids remaining would be more reflective of the intra-crystalline fraction, which is resistant to exposure to strong chemical oxidation (Stathoplos and Hare 1993; Penkman et al. 2008). For unbleached Holocene samples, a larger proportion of inter-crystalline proteins would remain due to the shorter burial time experienced by these younger samples.

Our results agree with findings using gastropods (Penkman et al. 2008), where the greatest difference in amino acid concentration between the unbleached and bleached shells tends to be in the younger samples (low D/L values). Within Holocene and down- core samples, bleach reduces the concentration of amino acids by 68% and 61%,

66 respectively. This 7% difference in the reduction of THAA concentrations seems to have a big difference on D/L differences between bleached and unbleached samples. The difference in the concentrations between the Holocene and down-core samples could be larger or smaller than what is presented due to the inherent inaccuracies in calculating the concentration of amino acids within a sample, which is dependent on the accuracy of the measurements of the small masses (mg) of samples and volumes (μL) of spiked reagents (Penkman et al. 2008).

Collins and Riley (2000) suggested that isolating the intra-crystalline fraction might eliminate the species differences observed in mollusc shells. Although the amino acid compositions were very similar between the species (Figure 9), I still observe significant species differences in the mean D/L of bleached as well as unbleached samples (Table 8). The compositional differences between bleached (intra-crystalline) and unbleached (inter- and intra-crystalline) samples observed in all species indicate that the intra-crystalline fraction is comprised of a similar protein fraction as the whole shell

(Figure 9). The only compositional shift observed following bleaching is in down-core species where there is an increase in the relative abundance of Ala in the intra-crystalline fraction with a corresponding decrease in Asp (Figure 9).

5.8 Summary In conclusion, the primary objective of the pretreatment procedures was to reduce the variability in D/L by removing exogenous organic material and isolating the intra- crystalline fraction of amino acids. Our results show that bleach is not essential to remove leachable matrix proteins down core because it appears that these components have already been removed over time. Bleaching samples also does not reduce the subsample rejection rate or CV significantly within Holocene and down-core samples to warrant

67 adding extra time to sample preparation. Because the D/L ratios of down-core samples show no significance between the pretreatments, paleotemperatures derived from bleached or unbleached samples down core would be very similar. Since the down-core D/L ratios increase with age for both P. obliquiloculata and G. truncatulinoides regardless of which pretreatment was used, down-core samples for paleotemperature reconstruction will not undergo the relatively time consuming bleach pretreatment.

68 Chapter 6

APPLICATION TO PALEOTHERMOMETRY

6.1 Determination of the Effective Diagenetic Temperatures By applying the kinetic variables of racemization (previously obtained by

Kaufman 2006 for P. obliquiloculata) and ages of the samples, the post-depositional temperatures (i.e. the effective diagenetic temperatures) for down-core samples can be calculated. The effective diagenetic temperature (EDT) is the weighted post-depositional temperature that integrates the thermal history of a shell (Kaufman 2003). Since the rate of racemization is dependent exponentially on temperature, the EDT is weighted toward the higher temperatures that is experienced and will be somewhat higher than the arithmetic mean annual temperature (MAT) (Kaufman 2003). Two different paleotemperature calculations can be made using the D/L ratios of fossils: (1) the EDT of the entire time interval under study based on a single sample whose age is known (Eq. 9) and (2) the EDT of an interval of time bracketed by two samples of different (known) ages (Eq. 10). The temperature equations are derived from the combination of a simple power law to model the rate of amino acid racemization (Eq. 7) and the Arrhenius equation (Eq. 8). Figure 18 shows a conceptual representation of the individual EDTs calculated from a bracketed interval of time. T1 and T2 are represented as the entire post depositional history of two samples extending to modern time (t1 – 0 ka and t2 – 0 ka) and are calculated from Eq. 9. T1 represents the temperature history of a younger sample, while

T2 is for an older sample. T(t2-t1) is the temperature history between the ages of the

69 younger and older sample (t1 and t2, respectively). Due to the duplicated depositional history of 0-t1 ka within both T1 and T2, the change in EDT between the younger interval

(T1) and older interval (Tt2-t1) is:

∆푇 = 푇(푡2−푡1) − 푇1 Eq. 12 The kinetic variables of racemization for P. obliquiloculata do not directly apply to derive EDTs for other species; therefore, to calculate paleotemperatures using G. truncatulinoides (which is abundant at JPC-37), I must make a species correction for the

D/L. By comparing the D/L for both species in coeval samples, I am able to create the species correction for Asp and Glu using a linear regression (Figure 19). As a result, the correction is based on 6 intervals from Holocene and down-core sites for unbleached samples:

퐴푠푝 푐표푟푟푒푐푡푖표푛 = 0.9458(퐺. 푡푟푢푛푐푎푡푢푙푖푛표푖푑푒푠 퐷/퐿) − 0.0080 퐺푙푢 푐표푟푟푒푐푡푖표푛 = 0.8758(퐺. 푡푟푢푛푐푎푡푢푙푖푛표푖푑푒푠 퐷/퐿) + 0.0063 The coefficient of correlation values (R2) show excellent fit between the linear equation and the data points for both Asp (R2 = 0.997) and Glu (R2 = 0.998) (Figure 19). The slopes of the linear equations are close to 1, indicating that the species differences are close to a 1:1 relationship offset by some constant value. I examined plots of the D/L ratios of G. truncatulinoides, which are abundant down core, corrected to P. obliquiloculata with respect to sample age in order to fully explore the down-core trend in D/L ratios (Figure 20). The BBOR D/L ratios can thus be compared to P. obliquiloculata data from the depth transect on the Queensland Margin in the western subtropical Pacific (Hearty et al. 2004). This comparison shows that for a given age, the down-core ratios at BBOR are higher than those at the Queensland margin, with the exception of the oldest data point at 410 ka. This could be either due to 1) the BBOR ages are significantly older than those based on the published δ18O stratigraphy

70 (Hagen and Keigwin 2002), or 2) the BBOR temperatures are higher than those from the Queensland margin. I do not think that underestimating the BBOR ages is the reason for the high D/L as the ages of the δ18O record are based on tuning the Site’s δ18O record to the nearby 14C dated Site 1059 δ18O record. Although Figure 20 illustrates that overall the D/L ratios increase with age, at the finer scale there are discrepancies. EDTs for a bracketed interval cannot be determined when the D/L value of an older sample is smaller than that of the younger sample because the K(t2-t1) (Eq. 11) is negative, causing T(t2-t1) to be unidentifiable. EDTs for a bracketed interval also cannot be determined accurately when the D/L value of two samples is the same. Therefore, visualizing the trend in D/L are important. Within our initial analyses, the Asp D/L values of the 15.4 ka and 30.8 ka samples were reversed and the Glu D/L values of the 10.5 ka and 15.4 ka samples were the same (Figure 20). This led me to believe that either the 15.4 ka sample or the 30.8 ka sample was potentially an outlier because I should be able to determine a temperature difference between time intervals spanning 5 kyr. When the 15.4 ka and 30.8 ka samples were reanalyzed, the D/L values for the 15.4 ka sample remained approximately the same, while the D/L values for the 30.8 ka sample increased dramatically. Such a large increase led me to believe that the initial values of the 30.8 ka sample were artifacts of air in the capillaries causing a high baseline in the chromatogram (Whitacre personal communication 2019) and therefore, the initial value for the 30.8 ka sample will not be used in paleotemperature calculations. Since the values for the 15.4 ka sample remained the same, I averaged the D/L’s for the temperature calculations. Upon reanalyzing the two samples, I noticed that the D/L values of the 51.5 ka sample no longer aligned with the trend of glutamic acid. Because the Glu D/L at 51.5 ka is less than the value at 30.8 ka (Table A5), I cannot use the 51.5 ka sample in succession with the 30.8 ka sample in the integration of the temperature

71 history at the Blake-Bahama Outer Ridge. Thus, I have chosen to exclude the 51.5 ka sample in the EDT calculations. The thermal history of Sites JPC-37 (~3000 m water depth) and 1056B (~2000 m water depth) may not have the same temperature history, thus I have evaluated them separately. For the starting point of the ~3000 m EDT history, I used Site 1059A sample 5.04 ka because this site is at the same depth as JPC-37. For the starting point of the ~2000 m EDT history, I used Site 1056D sample 4.82 ka because this site is at the same depth as Site 105B. Although there is no measurable difference in the D/L ratios from age equivalent intervals from Sites 1056D and 1059A in the Holocene, this approach rules out any potential water depth related temperature effects in the initial intervals at least conceptually. EDT calculations were made with successive intervals from samples dated at 5.04 ka to 86.4 ka for Site 1059/JPC-37 and samples dated at 4.82 ka to 410 ka for Site 1056 (Table 9). EDTs were calculated for the period since the beginning of each sample

(T1 or T2; Eq. 9), for the interval itself (T(t2-t1); Eq. 10), and for the change in temperatures between the younger and older intervals (ΔT; Eq. 12) (Table 9). The temperature equations (Eq. 9, Eq. 10, and Eq. 12) were evaluated with a bootstrap propagation and the ±1σ was used to estimate the uncertainty (more about this in Section 6.2).

Figure 19. Comparison between the extent of racemization (D/L) in coeval samples (n=6) of P. obliquiloculata and G. truncatulinoides for aspartic acid (A) and glutamic acid (B).

Figure 20. Comparison of the down-core trends of aspartic acid (A) and glutamic acid (B) D/L ratios of G. truncatulinoides corrected to P. obliquiloculata from the BBOR (this study) and P. obliquiloculata from the Queensland margin (Hearty et al. 2004). The lines show the data fit with a power curve. Samples shown in red are the initial analyses for samples 15.4 ka and 30.8 ka. The sample at 51.5 ka is shown as an open circle because it no longer aligns with the BBOR trend of the new 30.8 ka Glu D/L value.

Table 9. Effective diagenetic temperatures (EDTs) and uncertainties in °C derived from amino acid paleothermometry of P. obliquiloculata and G. truncatulinoides for 2000 m (Site 1056) and 3000 m (Site 1059A/JPC-37) water depths. Sample ages and D/L values for the bracketed time intervals used to calculate the EDTs are included.

Depth t1 t2 Tt1 Tt2 T(t2-t1) ΔT D/Lt1 D/Lt2 (m) (ka) (ka) (°C) ±1σ (°C) ±1σ (°C) ±1σ (°C) ±1σ Aspartic Acid 2000 4.82 410 0.122 0.432 5.2 0.6 2.3 0.6 2.2 0.6 -3.0 0.9 3000 5.04 10.5 0.125 0.178 5.4 0.6 7.1 0.7 8.3 1.3 2.9 1.5 3000 5.04 15.4 0.125 0.242a 5.4 0.6 9.8 0.6 11.1 0.9 5.7 1.1 3000 10.5 15.4 0.178 0.242a 7.1 0.7 9.8 0.6 13.1 2.7 6.0 2.8 3000 15.4 30.8 0.242a 0.254a 9.8 0.6 7.1 0.6 0.8 2.9 -9.1 2.9 3000 30.8 86.4 0.254a 0.327a 7.1 0.6 5.8 0.7 4.8 1.1 -2.3 1.3

Glutamic Acid 2000 4.82 410 0.056 0.225 8.6 0.8 3.5 0.7 3.4 0.7 -5.2 1.1 3000 5.04 10.5 0.060 0.072 9.3 1.0 7.9 1.0 6.2 3.2 -3.0 3.3 3000 5.04 15.4 0.060 0.077a 9.3 1.0 6.8 0.7 5.0 1.4 -4.2 1.7 3000 10.5 15.4 0.072 0.077a 7.9 1.0 6.8 0.7 3.3 4.9 -4.6 5.0 3000 15.4 30.8 0.077a 0.093a 6.8 0.7 5.7 0.7 4.3 1.5 -2.6 1.7 3000 30.8 86.4 0.093a 0.130a 5.7 0.7 5.7 0.7 4.0 1.1 -1.8 1.3

Weighted mean and σ of aspartic and glutamic acid results (based on Taylor 1982) 2000 4.82 410 ------6.4 0.5 2.8 0.5 2.7 0.5 -3.7 0.7

Table 9 Continued

Depth t1 t2 Tt1 Tt2 T(t2-t1) ΔT D/Lt1 D/Lt2 (m) (ka) (ka) (°C) ±1σ (°C) ±1σ (°C) ±1σ (°C) ±1σ 3000 5.04 10.5 ------6.5 0.5 7.4 0.6 8.0 1.2 1.5 1.3 3000 5.04 15.4 ------6.5 0.5 8.6 0.5 9.3 0.8 2.9 0.9 3000 10.5 15.4 ------7.4 0.6 8.6 0.5 10.9 2.3 3.5 2.4 3000 15.4 30.8 ------8.6 0.5 6.5 0.5 3.5 1.3 -5.1 1.4 3000 30.8 86.4 ------6.5 0.5 5.2 0.5 4.4 0.8 -2.1 0.9

Mean and σ of aspartic and glutamic acid results 2000 4.82 410 ------6.9 0.5 2.9 0.5 2.8 0.5 -4.1 0.7 3000 5.04 10.5 ------7.3 0.6 7.5 0.6 7.3 1.7 -0.1 1.8 3000 5.04 15.4 ------7.3 0.6 8.3 0.5 8.1 0.9 0.8 1.0

3000 10.5 15.4 ------7.5 0.6 8.3 0.5 8.2 2.8 0.7 2.9 3000 15.4 30.8 ------8.3 0.5 6.4 0.5 2.5 1.6 -5.8 1.7 3000 30.8 86.4 ------6.4 0.5 5.2 0.5 4.4 0.8 -2.0 0.9

a D/L of G. truncatulinoides corrected to P. obliquiloculata values.

6.2 Paleotemperature Uncertainties and Trend Selection A bootstrap method coded in R was used to propagate the uncertainty (±1σ) of paleotemperatures for the period since the beginning of each interval (Eq. 9), for the interval itself (Eq. 10), and for the change in EDT between the younger and older intervals (Eq. 12).This procedure models the interdependency between Ea and ln(A) by simulating the compensating effect in the temperature equation that the uncertainty in one variable has on the other. Ten thousand random draws were made from normally distributed populations of the initial D/L (0.040 ± 20% for Asp and 0.020 ± 20% for

Glu), the mean D/L of the sample (± standard error (1σx) of the inter-shell variation within a sample), and the age (±10%). Uncertainties in the ages and initial D/L values were modeled after Kaufman (2006). Since the slope and intercept of the Arrhenius regression are strongly correlated, Ea values within 31.5 ± 0.2 kcal/mol for Asp and 31.2 ± 0.3 kcal/mol for Glu were also chosen randomly and propagated through the linear Arrhenius equation with 7 pairs of k and 1/T values determined from experimental heating of P. obliquiloculata from Kaufman (2006). The resulting ln(A) was the average of the 7 Arrhenius regression propagations. The validity of this method for determining ln(A) from Ea was checked with Asp values by inputting a constant Ea = 31.5 kcal/mol and observing whether ln(A) = 42.12 yr-1 was the output. When random draws of k and 1/T pairs were used, the ln(A) varied from 32.3-51.7 yr-1 due to the varying positions of the intercept even with a constant slope. However, by averaging the ln(A) values from each k and 1/T pair, ln(A) = 42.2 yr-1 was calculated, which is very close to the expected value of 42.12 yr-1. The same method was used for Glu, and the average ln(A) value from each k and 1/T pair was 40.2 yr-1, which is very close to the expected value of 40.25 yr-1.

Uncertainties for the EDTs were evaluated not just to show the uncertainty in paleotemperature reconstructions but to also determine a temperature history with the lowest uncertainty. I calculated EDTs for the 5.04-10.5 ka, 10.5-15.4 ka, and 5.04-15.4 ka intervals to see whether intervals spanning 5 kyr in the Holocene could be resolved with minimal uncertainty. For both Asp and Glu, the uncertainties in T(t2-t1) and ΔT for the 5.04-10.5 ka and 10.5-15.4 ka intervals are much greater than the uncertainties for 5.04- 15.4 ka (Table 9). Therefore, using the 5.04-15.4 ka should enhance the temperature history of the Holocene (Table 9), and the 5.04-10.5 ka and 10.5-15.4 ka intervals will not be discussed further. The bootstrap propagation yielded uncertainties in the EDTs since the beginning of each interval (Tt1 and Tt2; Eq. 9) for 4.82 ka, 5.04 ka, 15.4 ka, 30.8 ka, 86.4 ka, and 410 ka ranging from ±0.6°C to 0.7°C for Asp and ±0.7°C to 1.0°C for Glu (Table 9). The average is ±0.6°C and ±0.8°C for Asp and Glu, respectively, which is smaller than the values determined from the Monte Carlo simulation in Kaufman (2006) (±0.8°C for Asp and ±1.0°C for Glu) due to smaller σx in mean D/L values. In this study, the average ±σx for Asp is 1.6% and 2.9% for Asp and Glu, respectively, whereas the average values in Kaufman (2003) were 1.7% for Asp and 5.5% for Glu. The average uncertainties in T for foraminifera here are much less than those determined for ostracods (±1.8-2.1°C; Kaufman 2003) and gastropods (±2.0°C; McCoy 1987a). A sensitivity test showed that doubling the error in the age (from ±10% to ±20%) had the largest effect on σT as shown in Kaufman (2006). With a ±20% uncertainty in age, σT increased by an average of ±0.5°C for Asp and ±0.4°C for Glu. Doubling the error in the Arrhenius parameters and mean D/L had similar effects on σT. With an uncertainty of ±0.4 kcal/mol and ±0.6 kcal/mol in Ea for Asp and Glu, respectively, σT increased by an average of ±0.2°C for

Asp and ±0.3°C for Glu. Doubling the standard error of D/L values increased σT by an average of ±0.1°C and ±0.2°C for Asp and Glu, respectively.

Uncertainties associated with T(t2-t1) (Eq. 10) for the intervals of interest (5.04- 15.4 ka, 15.4-30.8 ka, 30.8-86.4 ka, and 4.82-410 ka) are higher, ranging from ±0.6°C to 2.9°C for Asp and ±0.7°C to 1.5°C for Glu (Table 9). These uncertainties are smaller than those determined for ostracodes by Kaufman (2003) (±1.9-3.7°C) and for snails by McCoy (1987) (±2-4°C). The average of the intervals is ±1.4°C and ± 1.2°C for Asp and

Glu, respectively, which represents a more useful uncertainty towards determining bottom water temperatures. A sensitivity test showed that doubling the error in the ages of both samples had the largest effect on σT(t2-t1) while doubling the error in the Arrhenius parameters had the smallest effect on σT(t2-t1). A 100% increase in the uncertainty of both ages led σT(t2-t1) to increase by an average of ±0.9°C for Asp and ±1.0°C for Glu. A 100% increase in σEa for Asp and Glu causes σT(t2-t1) to increase by an average of ±0.1°C for

Asp and ±0.2°C for Glu. A 100% increase in σxD/L causes σT(t2-t1) to increase by an average of ±0.6°C and ±0.7°C for Asp and Glu, respectively, which is significantly larger than in the effect of σT. The propagation yielded uncertainties in ΔT (Eq. 12) ranging from ±0.9°C to 2.9°C for Asp and ±1.1°C to 1.7°C for Glu (Table 9). The average for the intervals of interest is ±1.6°C and ±1.5°C for Asp and Glu, respectively. Unlike Kaufman’s (2003) analysis, the uncertainty in the relative EDT between the two time intervals (ΔT) is slightly higher than the uncertainty associated with the absolute EDT of the older time interval (T(t2-t1)). As with σT(t2-t1), doubling the error in the ages of the samples results in the largest effect on σΔT, while doubling the error in the Arrhenius parameters have the smallest effect on σΔT.

The associated uncertainties (σT1, σT2, σT(t2-t1), and ΔT) between the average and weighted average EDTs are approximately the same (Table 9), and the trend between the two temperature histories is similar in shape (Figure 20), but the change in temperature between the two intervals of the Holocene vary. For the standard average and weighted average, respectively, there is a 0.8°C and 2.8°C difference between the 0-5.04 ka and 5.04-15.4 ka intervals. The post-depositional temperature change represented by the weighted average is essentially too high for what is to be expected during the Holocene at this water depth. Weighted averages are sensitive to which amino acid gives the smaller

σ; therefore, the T(t2-t1) value from the 5.04-15.4 ka interval is larger because it is weighted towards 11.1°C ± 0.9°C from Asp rather than 5.0°C ± 1.4°C from Glu (Table 9). For now, I see no reason to use the weighted average that biases the temperature towards Asp because 11.1°C is anomalously high for deep water temperatures in the ocean and the weight assumes that a value with a smaller uncertainty is inherently closer to the actual temperature, which may not be true in this case. Because of this, I believe that the simple average EDT history is a better representation of bottom water temperature changes here. Therefore, uncertainties for T, T(t2-t1), ΔT within the EDT history range from ±0.5-0.6°C, ±0.5-1.6°C, and ±0.7-1.7°C, respectively (Table 9).

Figure 21. Global benthic δ18O records (Lisiecki and Raymo 2005) spanning 410 kyr (A) and 150 kyr (B) provide a corresponding view of interglacial-glacial climate background. EDTs for ~2000 m and ~3000 m water depth at the Blake-Bahama Outer Ridge based on the average (C and D) and weighted average (E and F) of the extent of racemization in aspartic acid and glutamic acid of P. obliquiloculata and G. truncatulinoides (corrected to P. obliquiloculata using the species correction from Figure 19). Since EDTs are an average post-depositional temperature between intervals of time, they are represented as lines between the data points for the beginning and end of the intervals of interest. For the ~2000 m water depth trend, samples at 4.82 ka and 410 ka are from Sites 1056D and 1056B, respectively. For the ~3000 m water depth trend, the sample at 5.04 ka is from Site 1059A, and the samples at 15.4 ka, 30.8 ka, and 86.4 ka are from JPC-37. Data are in Table 9.

6.3 Temperature Histories P. obliquiloculata D/L ratios from both Asp and Glu provide estimates for the EDT history at 2000 m water depth on Blake-Bahama Outer Ridge since 410 ka (Table 9; Figure 21C). The EDT calculated for the last 4.82 ka at Site 1056D averages 6.9 ± 0.5°C for the two amino acids, which is 3.3°C warmer than modern mean annual bottom water temperature of 3.6°C (Levitus and Boyer 1994). The average EDT for the interval between 4.82 ka and 410 ka is 2.8 ± 0.5°C. This EDT is 4.1 ± 0.7°C lower than the EDT calculated for just the past 4.82 ka; therefore, the cooler EDT for the bracketed time interval is consistent with a cooler depositional environment and hence, a decrease in racemization rates presumably during the four glacial intervals of the past 410 kyr. P. obliquiloculata D/L provides an estimate for the EDT temperature history at the Blake-Bahama Outer Ridge in the Atlantic Ocean (Site 1059/JPC-37; ~3000 m) since 5.04 ka (Table 9; Figure 21D). At JPC-37 I can extend the temperature history back to 86.4 ka and thus incorporate the depositional history during the Last Glacial Maximum (~20 ka) by using D/L ratios from G. truncatulinoides corrected to P. obliquiloculata

(Table 9; Figure 21D).The average EDT calculated for the last 5.04 kyr at Site 1059A is 7.3 ± 0.6°C, which is 4.6°C higher than the modern bottom water temperature of 2.7°C (Levitus and Boyer 1994). This temperature is expected to be higher than the mean temperature due to the exponential dependence of the rate constant on the post- depositional temperature but not in the order that I have observed. The overall EDT for the entire Holocene (since 15.4 ka) is 8.3 ± 0.5°C. This EDT is higher than the previous interval, potentially due to the effects of the early Holocene maximum (period of high temperatures during ~5-7 ka).The overall EDT for the interval between 5.04 ka and 15.4 ka is 8.1 ± 0.9°C. This EDT is only 0.8°C and 0.3°C higher than the EDTs calculated for the past 5.04 ka and 15.4 ka, respectively; thereby, indicating that the Holocene

depositional temperature history remained relatively constant at the site. The derived overall EDT for the interval encompassing the LGM (15.4 ka to 30.8 ka) is 2.5 ± 1.6°C. The EDT of the LGM is 5.8 °C and 4.8°C lower than the EDTs calculated for just the past 15.4 ka and 5.04 ka, respectively, which is consistent with lower racemization rates due to a cooler depositional environment during this interval due to the LGM. T(t2-t1) from 30.8 ka to 86.4 ka is 4.4 ± 0.8°C and highlights the warmer period before the LGM. The EDT for the entire 86.4 kyr period is 5.2 ± 0.5°C, which is ~3.1°C lower than the EDT encompassing the period before the LGM (15.4 ka T2 = 8.3 ± 0.5°C), signifying the cooling of bottom water temperatures during the LGM. The absolute temperatures derived from AAR here are unrealistically high (by ~3- 4°C) for bottom water temperatures at ~2000 to 3000 m water depth. It appears these high temperatures result from the relatively high D/L ratios at the BBOR (e.g. Figure 20). At this point, I do not have an explanation for this phenomenon. Perhaps it is possible that at BBOR, the simple power law kinetics is not the best model for this particular dataset. Yet, this explanation is highly speculative because all other published D/L ratios fit this model well (Kaufman et al. 2013). As discussed below, the magnitude of the temperature changes are on the order of ~1-5°C between the discrete intervals, which are more realistic given changes in water mass history in this region.

6.4 Paleoceanographic Implications

6.4.1 Comparison with Other Records of Bottom Water Temperature The most established proxy to reconstruct global climate (i.e. glacial-interglacial variations in sea level, continental ice volume, etc.) and general temperature trends is oxygen isotope ratios (δ18O) of benthic foraminifera (Lear et al. 2002). However, δ18O is a function of both temperature and seawater isotopic composition, and separating these

two effects has been a long-standing problem in paleoceanography. Within the past few decades, scientists have used Mg/Ca ratios (Elderfield et al. 2010) to attempt to isolate the temperature effect in order to reconstruct bottom water temperatures. To assess the applicability of AAR paleothermometry, I compare temperature changes from this study to results from Labeyrie et al. (1987) and Martin et al. (2002). Labeyrie et al. (1987) used benthic foraminiferal δ18O from Core M12392 (25°10’S, 16°50’W; 2573 m) to determine changes in interglacial and glacial deep water temperatures in the Atlantic. They determined that there were two cooling phases associated with the Atlantic Ocean over the past 125 kyr: 1) temperatures decreased ~2.5°C at 115 ka during the MIS 5e/5d transition and 2) temperatures decreased another ~1°C at 70 ka during the MIS 5a/4 transition (Labeyrie et al. 1987). The global deepwater temperatures then remained in the 0°C to -1°C range until the end of glaciation at MIS 2 (Labeyrie et al. 1987). There is similarity between the temperature changes within the trend of the Labeyrie et al. (1987) δ18O derived tropical Atlantic deep water temperature reconstruction and the EDT reconstruction presented here (Figure 21B). Most notably, the temperature difference between the LGM and early Holocene maximum was ~4-5°C, from Labeyrie et al. (1987) and between 4.8°C and 5.8°C within this study depending on the interval of consideration because both 0-5.04 ka and 5.04- 15.4 ka include a time within the early Holocene maximum.

Martin et al. (2002) used Mg/Ca ratios from the benthic foraminifer species Cibicidoides wuellerstorfi to reconstruct glacial-interglacial temperatures from Eastern

Atlantic Core M16772 (1°21’S, 11°58’W; 2912 m). Core M16772 is bathed predominantly in lower-NADW with a modern bottom water temperature of ~2.2°C (Martin et al. 2002), which is analogous to my study sites in the Western Atlantic (ODP Site 1059 and KNR140 JPC-37; ~3000 m; modern temperature of ~2.7°C). The Mg/Ca

data implied shifts in tropical Atlantic deep water temperatures of ~4°C between the LGM and early Holocene maximum (Martin et al. 2002). With AAR paleothermometry, I determined approximately the same shift in temperature (~4.8-5.8°C) between the LGM and the past 5.04 kyr and the 5.04-15.4 ka interval. There is also good agreement between the shape of the temperature changes of the Martin et al. (2002) Mg-derived temperature estimates of the eastern tropical Atlantic and EDTs of the western tropical Atlantic determined here (Figure 21D).

In comparison to the studies presented here, AAR paleothermometry gives similar bottom water temperature changes and paleotemperature uncertainties based on independent evidence and without the limitations of δ18O and Mg/Ca paleothermometry. As mentioned before, δ18O is limited by the entwined effects of temperature and seawater isotopic composition. Mg/Ca paleothermometry is limited by uncertainties in the effect of dissolution and carbonate ion saturation on shell Mg/Ca that can lead to calculated temperatures that overestimate glacial cooling (Martin et al. 2002; Elderfield et al. 2010).

The estimated errors in δ18O and Mg/Ca paleothermometry are ±0.7°C (Labeyrie et al. 1987) and ±1.4°C (Martin et al. 2002), respectively, which are very close to the ±0.5-

1.6°C uncertainties in AAR EDTs (σT(t2-t1)) from Site 1059/JPC-37 (Table 9). It is important to note that the absolute LGM temperature derived here is ~3-4°C higher than those of previous studies. Taking the modern and LGM offset into consideration, there seems to be a constant ~3-4°C offset between the AAR data presented here and published temperature reconstructions.

6.4.2 Deep Water Circulation Effective diagenetic temperature changes at my deep Atlantic sites (1056 and 1059/JPC-37) most likely reflect a combination of changes in deep water circulation and

the temperatures of water masses bathing the deep Atlantic (Figure 4; Figure 22). Warm, salty NADW is formed in the Nordic seas (most dense component = lower-NADW), the Labrador Sea, and the Mediterranean (lighter component = upper-NADW) (Hagen and Keigwin 2002). Cold, fresh AABW is formed on continental shelves in the Antarctic Ocean and penetrates the deep Atlantic with a temperature near -1°C (Adkins et al. 2002; Martin et al. 2002). Due to AABW’s greater density, it underlies NADW in the Atlantic at all latitudes south of ~40°N (Adkins et al. 2002). Sites at the Blake-Bahama Outer

Ridge (BBOR) used in this study are south of ~40°N, thus during interglacial periods, AABW will lie below NADW at ~4000 m. Currently, Sites 1056 (~2000 m) and 1059/JPC-37 (~3000 m) are bathed by relatively warm upper-NADW and lower-NADW, respectively. During the Holocene (4-5 ka) at ~2000 and 3000 m water depth, these sites have approximately the same EDT (7.3 ± 0.6°C and 6.9 ± 0.5°C, respectively). Although the absolute value of the EDT is too high for bottom water temperatures, the similarity suggests that these sites were bathed in the same water mass (NADW).

Numerous studies document considerable decreases in the contribution of NADW with subsequent increases in the contribution of AABW during the LGM (Boyle and Keigwin 1985/86; Labeyrie et al. 1987; Duplessy et al. 1988; Boyle 1995). Nutrient proxy records such as δ13C (Hagen and Keigwin 2002; Poirier and Billups 2014) have suggested that deep water masses at the BBOR ~3000 m water depth alternated between a northern and southern source where AABW penetration at JPC-37 during the LGM replaced NADW contribution. If glacial AABW was at least as cold as modern AABW (

-1°C), then JPC-37 should have experienced at least a 2°C glacial-interglacial temperature change from the inferred circulation changes alone (Martin et al. 2002). The EDT encompassing the LGM at ~3000 m water depth is 5.8°C lower than the past 15.4 kyr and 1.9°C lower than the period from 30.8 ka to 86.4 ka. These temperature

differences suggest that AABW shoaled to at least ~3000 m water depth at the BBOR during this time period. Since Site 1056 is within the core of NADW, it should be insensitive to all but the largest changes in benthic fronts between the AABW and NADW (Hagen and Keigwin 2002). During peak cooling, a shallower, nutrient void water mass forms south of Iceland (Glacial North Atlantic Intermediate Water = GNAIW) (Hagen and Keigwin 2002). When GNAIW forms, nutrient enriched deep water from the south could have replaced

NADW below ~2000 m while GNAIW occupied shallower depths (Hagen and Keigwin 2002). The 4.82-410 ka interval at ~2000 m (EDT = 2.8 ± 0.5°C) is 4.1°C colder than the past 4.82 kyr of the Holocene (EDT = 6.9 ± 0.5°C). Assuming that the temperature of the Holocene was relatively constant, this difference in water temperature could be due to a larger proportion of colder water from the south.

6.5 Summary

Uncertainties in EDTs (T(t2-t1)) predicted from a single amino acid (± 0.6-2.9°C for Asp and ± 0.7-1.5°C for Glu) are lower than previously reported for ostracodes (±

1.9-3.6°C for Asp and ± 2.0-3.7°C for Glu; Kaufman 2003) due to smaller σx in the D/L ratios of foraminifera (average ±σx is 1.6% for Asp and 2.9% for Glu). Currently, uncertainties of EDTs averaged for the amino acids are ≤ ±0.6°C for T and ≤ ±1.6°C for

T(t2-t1), which are useful uncertainties for determining bottom water temperatures in the ocean. This shows the significant contribution that minimizing the variability in D/L ratios (standard deviation and therefore standard error) could have on reducing the uncertainty of AAR temperature estimates even though the uncertainty in sample ages has the largest effect on σT, σT(t2-t1), and σΔT. If the independent ages of samples were better constrained, uncertainties in AAR temperature estimates of foraminifera would

decrease further. AAR paleothermometry is not hampered by the same limitations of other proxies (δ18O and Mg/Ca) with similar temperature uncertainties. Bottom water temperature changes presented here with the species correction are in general agreement with studies from Labeyrie et al. (1987) and Martin et al. (2002). Therefore, effective diagenetic temperature changes at the deep Atlantic sites (1056 and 1059/JPC-37) can be used to infer changes in deep water circulation of water masses bathing the deep Atlantic. Most notably, large temperature differences (greater than ~4°C) between the EDT encompassing the LGM (15.4-30.8 ka) and the early Holocene maximum (0-5.04 ka and 5.04-15.4) indicate that AABW shoaled to at least ~3000 m water depth sometime between 30 ka and 86.4 ka at the BBOR in line with conclusions from Hagen and Keigwin (2002) and Poirier and Billups (2014).

Chapter 7

CONCLUSION

The purpose of this study was to assess amino acid racemization within foraminifera for paleotemperature reconstructions at the Blake-Bahama Outer Ridge in the Western Atlantic. I hypothesized that bleach (NaOCl) pretreatments on Holocene (~4- 5 ka) and down-core (10.5 ka and 410 ka) samples could be used to reduce the variability in foraminiferal D/L ratios and improve down-core trends in D/L, which would reduce current uncertainties and improve the precision of environmental temperature estimates using AAR. The bleaching procedures attempted to remove contaminants and isolate intra-crystalline matrix amino acids in order to reduce the variability in D/L ratios calculated as the coefficient of variation (CV). Utilizing the bleach pretreatment only reduced the variability within a sample by an average of 1.1% and 3.0% for Asp and Glu, respectively. Treating Holocene and down-core sites as separate entities shows that bleaching reduces the CV by an average of 1.8% for Asp and 3.5% for Glu within Holocene samples, while the CV increases 1.2% for Asp and decreases 1.5% for Glu within down-core samples. Such small reductions in the CVs as compared to other bleaching studies (i.e. Penkman et al. 2008) do not warrant adding the extra time to pick more foraminiferal tests and prepare them for the bleaching procedure for our purposes here. Results indicate that bleach is not essential for the removal of organic contamination or leachable matrix amino acids down core because it appears that some of these components have already been removed over time, possibly due to increased leaching of free amino acids as they are hydrolyzed over long periods of time and microbial influences in the sediment that remove surface contamination. The reduced effect of bleach in the D/L ratios and amino acid concentrations of down-core samples

align with results from Penkman et al (2008) where she determined that the greatest difference in amino acid concentration between unbleached and bleached gastropod shells was in the younger samples. The down-core D/L values increase with age for both P. obliquiloculata and G. truncatulinoides regardless of the pretreatment used, therefore, the down-core samples for paleotemperature reconstruction did not undergo the time consuming bleach pretreatment. Effective temperature gradients calculated from unbleached D/L measurements of aspartic and glutamic acids in the foraminiferal species P. obliquiloculata and species corrected G. truncatulinoides independently dated by radiocarbon and δ18O stratigraphy give an account of the thermal history at ~2000 m and ~3000 m water depth at the Blake- Bahama Outer Ridge in the Western Atlantic. Although the derived EDTs are much too warm for bottom water temperatures, the temperature changes within the EDT history are on order of ~1-5°C, which are much more realistic. Amino acid paleotemperature estimates of >4°C cooling during the last glacial maximum at ~3000 m is consistent with previous studies (Labeyrie et al. 1987; Martin et al. 2002; Hagen and Keigwin 2002; Poirier and Billups 2014). Within this study, uncertainties of EDTs averaged for the amino acids are ≤ ±0.6°C for T and ≤ ±1.6°C for T(t2-t1) due to an average of ±1.6% and

±2.9% σx in D/L for Asp and Glu, respectively. These values, are an improvement upon the ±2°C uncertainty of T and ±2-4°C uncertainty of T(t2-t1) on snails (McCoy 1987a) and highlight the necessity of minimized variability in D/L ratios in order to determine realistic bottom water temperatures.

In order to compare the entire 410 kyr thermal history at ~2000 m and ~3000 m water depth, it would be ideal to obtain D/L measurements on a 410 ka sample (G. truncatulinoides) from JPC-37 (~3000 m). This would allow me to compare the temperatures between the two water depths over the course of glacial-interglacial periods

during the past 410 kyr in the Quaternary. To more fully compare the water mass changes at ~2000 m and ~3000 m water depth, the resolution of the time periods at the shallower site should be increased. This way, changes in temperature for the LGM and other glacial periods can be directly compared. To understand the movement of AABW during glacial periods, it would be beneficial to add other sites (at ~3000 m and ~4000 m water depth) from the Southern Ocean and South Atlantic Ocean between 0°W and 45°W and Central Atlantic Ocean between 60°W and 30°W for AAR temperature reconstruction. Future studies should also involve laboratory heating of G. truncatulinoides in line with the methods of Kaufman (2006) in order to determine the racemization kinetics of this species, which is abundant within the Atlantic Ocean. It is crucial to know how the kinetics of different foraminiferal species differs in order to make more accurate temperature estimates without species corrections.

REFERENCES

Adkins, J.F., McIntyre, K., & Schrag, D.P. (2002). The salinity, temperature, and δ18O of the glacial deep ocean. Science, 298, 1769-1773.

Aguirre, M.L., Bowen, D.Q., Sykes, S.A., & Whatley, R.C. (1995). A provisional aminostratigraphical framework for late Quaternary marine deposits in Buenos Aries province, Argentina. Marine Geology, 128, 85-104.

Allen, A.P., Kosnik, M.A., Kaufman, D.S. (2013). Characterizing the dynamics of amino acid racemization using time-dependent reaction kinetics: A Bayesian approach to fitting age-calibration models. Quaternary Geochronology, 18, 63-77.

Andrews, J.T., Bowen, D.Q., & Kidson, C. (1979). Amino acid ratios and the correlation of raised beach deposits in southwest England and Wales. Nature, 281, 566-568.

Atwater, B.F., Ross, B.E., & Wehmiller, J.F. (1981). Stratigraphy of late Quaternary estuarine deposits and amino acid stereochemistry of oyster shells beneath San Francisco Bay, California. Quaternary Research, 16, 181-200.

Ausín, B., Haghipour, N., Wacker, L., Voelker, A.H.L., Hodell, D., Magill, C., Looser N., Bernasconi, S.M., & Eglinton, T.I. (2019). Radiocarbon age offsets between two surface dwelling planktonic foraminifera species during abrupt climate events in the SW Iberian margin. Paleoceanography and Paleoclimatology, 34, 63-78.

Bada, J.L., & Schroeder, R.A. (1972). Racemization of isoleucine in calcareous marine sediments: kinetics and mechanism. Earth and Planetary Science Letters, 15, 1- 11.

Bada, J.L., & Schroeder, R.A. (1975). Amino acid racemization reactions and their geochemical implications. Naturwissenchaften, 62, 71-79.

Barbour-Wood, S.L., Krause, R.A., Jr., Kowalewski, M., Wehmiller, J.F., & Simoes, M.G. (2006). Aspartic acid racemization dating of Holocene brachiopods and bivalves from the southern Brazilian shelf, South Atlantic. Quaternary Research , 66, 323-331.

Bates, M.R. (1993). Quaternary aminostratigraphy in Northwestern France. Quaternary Science Reviews, 12(9), 793-809.

Belknap, D.F. (1979). Application of amino acid geochronology to stratigraphy of late Cenozoic marine units of the Atlantic coastal plain, (Doctoral Dissertation). Department of Geology, University of Delaware, Newark, DE.

Belknap, D.F., & Wehmiller, J.F. (1980). Amino acid racemization in Quaternary mollusks: examples from Delaware, Maryland, and Virginia. In: Hare, P.E., Hoering, T.C., & King, K. Jr. (Eds.), Biogeochemistry of amino acids (pp. 401- 414). New York, NY: Wiley.

Billups, K., Chaisson, W., Worsnopp, M., & Thunell, R. (2004). Millennial-scale fluctuations in subtropical northwestern Atlantic surface ocean hydrography during the mid-Pleistocene. Paleoceanography, 19, PA2017.

Bowen, D.W., & Sykes, G.A. (1988). Correlation of marine events and glaciations on northeast Atlantic margin. Philosophical Transactions of the Royal Society of London. Series B, 318, 619-635.

Bowen, D.W., Sykes, G.A., Reeves, A., Miller, G.H., Andrews, J.T., Brew, J.W., & Hare, P.E. (1985). Amino acid geochronology of raised beaches in southwest Britain. Quaternary Science Reviews, 4, 279-318.

Boyle, E.A. (1995). Last glacial maximum North Atlantic Deep Water: On, off, or somewhere in between. Philosophical Transactions of the Royal Society of London. Series B, 348, 243-253.

Boyle, E.A., & Keigwin, L.D. (1985/86). Comparison of Atlantic and Pacific paleochemical records for the last 215,000 years: changes in deep ocean circulation and chemical inventories. Earth and Planetary Science Letters, 76, 135-150.

Brigham-Grette, J., & Carter, L.D. (1992). Pliocene marine transgressions of Northern Alaska: circumarctic correlations and paloeclimatic interpretations. Arctic, 45(1), 74-89.

Broecker, W., Barker, S., Clark, E., Hajdas, I., & Bonani, G. (2006). Anomalous radiocarbon ages for foraminifera shells. Paleoceanography, 21, PA2008.

Brooks, A.S., Hare, P.E., Kokis, J.E., Miller, G.H., Ernst, R.D., & Wendorf, F. (1990). Dating Pleistocene archeological sites by protein diagenesis in ostrich eggshell. Science, 248, 60-64.

Bush, S.L., Santos, G.M., Xu, X., Southon, J.R., Thiagarajan, N., Hines, S.K., & Adkins, J.F. (2013). Simple, rapid, and cost effective: a screening method for 14C analysis of small carbonate samples. Radiocarbon, 55, 631-640.

Carroll, M., Kowalewski, M., Simões, M.G., & Goodfriend, G.A. (2003). Quantitative estimates of time averaging in terebratulid brachiopod shell accumulations from a modern tropical shelf. Paleobiology, 29, 381-402.

Collins, M.J., & Riley, M.S. (2000). Amino acid racemization in biominerals, the impact of protein degradation and loss. In: Goodfriend, G.A., Collins, M.J., Fogel, M.L., Macko, S.A., & Wehmiller, J.F. (Eds.), Perspective in amino acid and protein geochemistry (pp. 120-142). Oxford University Press.

Crenshaw, M.A. (1972). The soluble matrix from Mercenaria mercenaria shell. Biomineralisation, 6, 6-11.

Demarchi, B., & Collins, M. (2015). Amino acid racemization dating. In: Rink, J.W., & Thompson, J.W. (Eds.), Encyclopedia of scientific dating methods (pp. 13-26). Dordrecht: Springer.

Demarchi, B., Collins, M.J., Bergstom, E., Dowle, A., Penkman, K.E.H., Thomas-Oates, J., & Wilson, J. (2013). New experimental evidence for in-chain amino acid racemization of serine in a model peptide. Analytical Chemistry, 85(12), 5835- 5842.

Duplessy, J.C., Shackleton, N.J., Fairbanks, R.G., Labeyrie, L., Oppo, D., & Kallel, N. (1988). Deepwater source variations during the last climatic cycle and their impact on the global deepwater circulation. Paleoceanography, 3, 343-360.

Elderfield, H., Greaves, M., Barker, S., Hall, I.R., Tripati, A., Ferretti, P., Crowhurst, S., Booth, L., & Daunt, C. (2010). Quaternary Science Reviews, 29, 160-169.

Engel, M.H., & Macko, S.A. (Eds.). 1993. Organic Geochemistry: Principles and Applications. New York, NY: Plenum Press.

Franz, S.O., & Tiedemann, R. (2002). Depositional changes along the Blake-Bahama Outer Ridge deep water transect during marine isotope stages 8 to 10 – links to the Deep Western Boundary Current. Marine Geology, 189, 102-122.

Geiger, T., & Clarke, S. (1987). Deamidation, isomerization, and racemization at asparaginyl and aspartyl residues in peptides – succinimide-linked reactions that contributed to protein degradation. Journal of Biological Chemistry, 262, 785- 794.

Goodfriend, G.A. (1987a). Evaluation of amino acid racemization/epimerization dating using radiocarbon-dated fossil land snails. Geology, 15, 698-700.

Goodfriend, G.A. (1987b). Chronostratigraphic studies of sediments in the Negev Desert, using amino acid epimerization analysis of land snail shells, Quaternary Research, 28, 374-392.

Goodfriend, G.A. (1989). Complementary use of amino-acid epimerization and radiocarbon analysis for dating of mixed-age fossil assemblages. Radiocarbon, 31(3), 1041-1047.

Goodfriend, G.A. (1997). Aspartic acid racemization and amino acid composition of the organic endoskeleton of the deep-water colonial anemone Gerardia: Determination of the longevity from kinetic experiments. Geochimica et Cosmochimica Acta, 61(9), 1931-1939.

Goodfriend, G.A., Brigham-Grette, J., & Miller, G.H. (1996). Enhanced age resolution of the marine Quaternary record in the Arctic using aspartic acid racemization dating of bivalve shells. Quaternary Research, 45, 176-187.

Goodfriend, G.A., Hare, P.E., & Druffel, E.R.M. (1992). Aspartic acid racemization and protein diagenesis in corals over the last 350 years. Geochimica et Cosmochimica Acta, 56, 3847-3850.

Grützner , J., Giosan, L., Franz, S.O., Tiedmann, R., Cortijo, E., Chaisson, W.P., Flood, R.D., Hagen, S., Keigwin, L.D., Poli, S., Rio, D., & Williams, T. (2002). Astronomical age models for the Pleistocene drift sediments from the western North Atlantic (ODP Sites 1056 to 1063). Marine Geology, 189, 5-23.

Hagen, S., & Keigwin, L.D. (2002). Sea-surface temperature variability and deep water reorganization in the subtropical North Atlantic during isotope stage 2-4. Marine Geology, 189, 145-162.

Harada, N., & Handa, N. (1995). Amino acid chronology in the fossil planktonic foraminifers, Pulleniatina obliquiloculata from Pacific Ocean. Geophysical Research Letters, 22, 2353-2356.

Hearty, P.J., & Kaufman, D.S. (2000). Whole-rock aminostratigraphy and Quaternary sea-level history of the Bahamas. Quaternary Research, 54, 163-173.

Hearty, P.J., Miller, G.H., Sterns, C.E., & Szabo, B.J. (1986). Aminostratigraphy of Quaternary shorelines in the Mediterranean Basin. Geological Society of America Bulletin, 97, 850-858.

Hearty, P.J., O’Leary, M.J., Kaufman, D.S., Page, M.C., & Bright, J. (2004). Amino acid geochronology of individual foraminifer (Pulleniatina obliquiloculata) tests, north Queensland margin, Australia: a new approach to correlating and dating Quaternary tropical marine sediment cores. Paleoceanography, 19, PA4022.

Jenkins, W.J., & Rhines, P.B. (1980). Tritium in the deep North Atlantic Ocean. Nature, 286, 877-880.

Johnson, B.J. (1990). The Pleistocene planktonic foraminiferal aminostratigraphy of Ocean Drilling Program Hole 625B in the Northeast Gulf of Mexico (Unpublished Master’s Thesis). University of Delaware, Newark, DE.

Kaufman, D.S. (1992). Aminostratigraphy of Pliocene-Pleistocene high-sea-level deposits, Nome coastal plain and adjacent nearshore area, Alaska. Geological Society of America Bulletin, 104, 40-52.

Kaufman, D.S. (2000). Amino acid racemization in ostracodes. In: Goodfriend, G., Collins, M., Fogel, M., Macko, S., & Wehmiller, J. (Eds.), Perspectives in amino acid and protein geochemistry (pp. 145-160). New York, NY: Oxford University Press.

Kaufman, D.S. (2003). Amino acid paleothermometry of Quaternary ostracodes from the Bonneville Basin, Utah. Quaternary Science Reviews, 22, 899-914.

Kaufman, D.S. (2006). Temperature sensitivity of aspartic and glutamic acid racemization in the foraminifera Pulleniatina. Quaternary Geochronology, 1, 188-207.

Kaufman, D.S. (2015). Amino acid racemization, marine sediments. In: Rink, J.W. & Thompson, J.W. (Eds.), Encyclopedia of scientific dating methods (pp. 44-46). Dordrecht: Springer.

Kaufman, D.S., & Brigham-Grette, J. (1993). Aminostratigraphic correlations and paleotemperature implications, Pliocene-Pleistocene high-sea-level deposits, Northwestern Alaska. Quaternary Science Reviews, 12, 21-33.

Kaufman, D.S., Cooper, K., Behl, R., Billups, K., Bright, J., Gardner, K., Hearty, P., Jakobsson, M., Mendes, I., O’Leary, M., Polvak, L., Rasmussen T., Rosa, F., & Schmidt, M. (2013). Amino acid racemization in mono-specific foraminifera from Quaternary deep-sea sediments. Quaternary Geochronology, 16, 50-61.

Kaufman, D.S. & Manley, W.F. (1998). A new procedure for determining enantiomeric (D/L) amino acid ratios in fossils using reverse phase liquid chromatography. Quaternary Science Reviews, 17, 987-1000.

Kaufman, D.S., & Miller, G.H. (1992). Overview of amino acid geochronology. Comparative Biochemistry and Physiology. Part B, 102 (2), 199-204.

Kaufman, D.S., Polyak, L., Adler, R., Channell, J.E.T., & Xuan, C. (2008). Dating late Quaternary planktonic foraminifer Neogloboquadrina pachyderma from the Arctic Ocean using amino acid racemization. Paleoceanography, 23, PA3224.

Kaufman, D.S., & Sejrup, H. (1995). Isoleucine epimerization in the high-molecular- weight-fraction of Pleistocene Arctica. Quaternary Science Reviews, 14, 337-350.

Keigwin, L.D., Rio, D., & Acton, G.D. (1998). Proceedings of the Ocean Drilling Program. Initial Reports, 172, 77-156.

Kennedy, G.L. (1978). Pleistocene paleoecology, zoogeography, and geochronology of marine invertebrate faunas of Pacific Northwest coast (San Francisco Bay to Puget Sound) (Doctoral dissertation). University of California at Davis, Davis, CA.

Kennedy, G.L., Lajoie, K.R., & Wehmiller, J.F. (1982). Aminostratigraphy and faunal correlations of late Quaternary marine terraces, Pacific coast USA. Nature, 299, 545-547.

Kennett, J.P., & Srinivasan, M.S. (1983). Neogene planktonic foraminiferal: a phylogenetic atlas. University of California: Hutchinson Ross Publishing Company.

Kidwell, S.M., Best, M.M.R., & Kaufman, D.S. (2005). Taphonomic trade-offs in tropical marine death assemblages: differential time averaging, shell loss, and probable bias in siliciclastic vs. carbonate facies. Geology, 33, 729-732.

King, K. Jr. (1977). Amino acid survey of recent calcareous and siliceous deep-sea microfossils. Micropaleontology, 23, 180-193.

Kosnik, M.A., Hua, Q., Jacobsen, G.E., Kaufman, D.S., & Wüst, R.A. (2007). Sediment mixing and stratigraphic disorder revealed by the age-structure of Tellina shells in Great Barrier Reef sediment. Geology, 35, 811-814.

Kosnik, M.A., Hua, Q., Kaufman, D.S., & Wüst, R.A. (2009). Taphonomic bias and time-averaging in tropical molluscan death assemblages: differential shell half- lives in Great Barrier Reef sediment. Paleobiology, 35, 565-586.

Kosnik, M.A., & Kaufman, D.S. (2008). Identifying outliers and assessing the accuracy of amino acid racemization measurements for geochronology: II. Data screening. Quaternary Geochronology, 3, 328-241.

Kosnik, M.A., Kaufman, D.S., & Hua, Q. (2008). Identifying outliers and assessing the accuracy of amino acid racemization measurements for geochronology: I. Age calibration curves. Quaternary Geochronology, 3, 308-327.

Kosnik, M.A., Kaufman, D.S., & Hua, Q. (2013). Radiocarbon-calibrated multipleamino acid geochronology of Holocene molluscs from Bramble and Rib Reefs (Great Barrier Reef, Australia). Quaternary Geochronology, 16, 73-86.

Kowalewski, M., Goodfriend, G.A., & Flessa, K.W. (1998). The high-resolution estimates of temporal mixing in shell beds: the evils and virtues of time averaging. Paleobiology, 24, 287-304.

Kowalewski, M., Serrano, G.E.A., Flessa, K.W., & Goodfriend, G.A. (2000). Dead delta’s former productivity: two trillion shells at the mouth of the Colorado River. Geology, 28, 1059-1062.

Krause, R.A., Barbour, S.L., Kowalewski, M., Kaufman, D.S., Romanek, C.S., Simões, M.G., & Wehmiller, J.F. (2010). Quantitative comparisons and models of time- averaging in bivalve and brachiopod shell accumulations. Paleobiology, 36(3), 428-452.

Kvenvolden, K.A., Peterson, E., Wehmiller, J., & Hare, P.E. (1973). Racemization of amino acids in marine sediments determined by gas chromatography. Geochimica et Cosmochimica Acta, 37, 2215-2225.

Laabs, B.J.C., & Kaufman, D.S. (2003). Quaternary highstands in Bear Lake Valley, Utah and Idaho. Geological Society of America Bulletin, 115(4), 463-478.

Labeyrie, L.D., Duplessy, J.C., & Blanc, P.L. (1987). Variations in mode of formation and temperature of oceanic deep waters over the past 125,000 years. Nature, 327, 477-482.

Lajoie, K.R., Kern, J.P., Wehmiller, J.F., Kennedy, G.L., Mathieson, S.A., Sarna- Wojcicki, A.M., Yerkes, R.F., & McCrory, P.A. (1979). Quaternary shorelines and crustal deformations, San Diego to Santa Barbara, California. In: Abbott, P.L. (Ed.), Geological excursions in the Southern California area (pp. 3-15), San Diego, CA: San Diego State University Department of Geology.

Lear, C.H., Rosenthal, Y., & Slowey, N. (2002). Benthic foraminiferal Mg/Ca- paleothermometry: a revised core-top calibration. Geochimica et Cosmochimica Acta, 66(19), 3375-3387.

Levitus, S., & Boyer, T.P. (1994). World Ocean Atlas 1994, Vo. 4: Temperature. NOAA Atlas NESDIS 4, National Oceanic and Atmospheric Administration, Silver Springs, MD, pp. 129.

Libes, S.M. (2009). Introduction to marine biogeochemistry. Amsterdam: Elsevier, pp. 80.

100

Lisiecki, L.E., & Raymo, M.E. (2005). A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography, 20, PA1003.

Macko, S.A., & Aksu, A.E. (1986). Amino acid epimerization in planktonic foraminifera suggests slow sedimentation rates for Alpha Ridge, Arctic Ocean. Nature, 322, 730-732.

Martin, P.A., Lea, D.W., Rosenthal, Y., Shackleton, N.J., Sarnthein, M., & Papenfuss, T. (2002). Quaternary deep sea temperature histories derived from benthic foraminiferal Mg/Ca. Earth and Planetary Science Letters, 198, 193-209.

McCoy, W.D. (1987a). The precision of amino acid geochronology and paleothermometry. Quaternary Science Reviews, 6, 43-54.

McCoy, W.D. (1987b). Quaternary aminostratigraphy of the Bonneville Basin, western United States. Geological Society of America Bulletin, 98, 99-112.

McCoy, W.D., & Miller, B.B. (1990). Relative ages of late Cenozoic fossil assemblages from SW Kansas and NW Oklahoma interpreted from isoleucine epimerization in mollusk shells. Geological Society of America, 22(7), 146.

Meijer, T., & Cleveringa, P. (2009). Aminostratigraphy of middle and late Pleistocene deposits in the Netherlands and the southern part of the North Sea Basin. Global and Planetary Change, 68, 326-345.

Mekik, F. (2014). Radiocarbon dating of planktonic foraminifer shells: a cautionary tale. Paleoceanography, 29, 13-19.

Meldahl, K.H., Flessa, K.W., & Cutler, A.H. (1997). Time averaging and postmortem skeletal survival in benthic fossil assemblages: quantitative comparisons among Holocene environment. Paleobiology, 23, 207-229.

Miller, G.H. (1985). Aminostratigraphy of Baffin Island shell-bearing deposits. In: Andrews, J.T. (Ed.), Quaternary environments – Baffin Island, Baffin Bay and West Greenland (pp. 392-427). London: Allen and Unwin.

Miller, G.H., & Brigham-Grette, J. (1989). Amino acid geochronology: resolution and precision in carbonate fossils. Quaternary International, 1, 111-128.

Miller, G.H., & Hare, P.E. (1980). Amino acid geochronology: integrity of the carbonate matrix and potential of molluscan fossils. In: Hare, P.E., Hoering, T.C., & King, K. Jr., (Eds.), Biogeochemistry of amino acids (pp. 415-443). New York, NY: Wiley.

101

Miller, G.H., Hollin, J.T., & Andrews, J.T. (1979). Aminostratigraphy of U.K. Pleistocene deposits. Nature, 281, 539-543.

Miller, G.H., Jull, A.J.T., Linick, T., Sutherland, D., Sejrup, H.P., Brigham, J.K., Bowen, D.Q., & Mangerud, J. (1987). Racemization-derived late Devensian temperature reduction in Scotland. Nature, 326, 593-595.

Miller, G.H., Kaufman, D.S., & Clarke, S.J. (2013). Amino acid dating. In: Elias, S.A., & Mock, C.J. (Eds.), Encyclopedia of Quaternary Science: Second Edition (pp. 37- 48). Waltham, MA: Elsevier.

Miller, G.H., Magee, J.W., & Jull, A.J.T. (1997). Low-latitude glacial cooling in the Southern Hemisphere from amino-acid racemization in emu eggshells. Nature, 385, 241-244.

Miller, G.H., & Mangerud, J. (1985). Aminostratigraphy of European marine interglacial deposits. Quaternary Science Reviews, 4, 215-278.

Miller, G.H., Sejrup, H.P., Mangerud, J., & Anderson, B.G. (1983). Amino acid ratios in Quaternary mollusks and foraminifera from western Norway: Correlation, geochronology, and paleotemperature estimates. Boreas, 12, 107-124.

Miller, G.H., Wendorf, F., Ernst, R., Schild, R., Close, A.E., Friedman, I., & Schwarcz, H.P. (1991). Dating lacustrine episodes in the eastern Sahara by the epimerization of isoleucine in ostrich eggshells. Paleogeography, Palaeoclimatology, Palaeocology, 84, 175-189.

Mitterer, R.M. (1974). Pleistocene stratigraphy in southern Florida based upon amino acid diagenesis in fossil Mercenaria. Geology, 2, 425-428.

Mitterer, R.M. (1975). Ages and diagenetic temperatures of Pleistocene deposits of Florida based upon isoleucine epimerization in Mercenaria. Earth and Planetary Science Letters, 28, 275-282.

Mitterer, R.M., & Kriausakul, N. (1984). Comparison of rates and degrees of isoleucine epimerization in dipeptides and tripeptides. Organic Geochemistry, 7, 91-98.

Mitterer, R.M., & Kriausakul, N. (1989). Calculation of amino acid racemization ages based on apparent parabolic kinetics. Quaternary Science Reviews, 8, 353-358.

Müller, P.J. (1984). Isoleucine epimerization in Quaternary planktonic foraminfera: effects of diagenetic hydrolysis and leaching, and Atlantic-Pacific intercore correlations. Meteor Forsch.-Ergenbruisse, Reiche Co., No. 38, pp. 25-37.

102

Murray-Wallace, C.V. (2000). Quaternary coastal aminostratigraphy: Australian data in a global context. In: Goodfriend, G.A., Collins, M.J., Fogel, M.L., Macko, S.A., & Wehmiller, J.F. (Eds.), Perspectives in amino acid and protein geochemistry (pp. 279-300). Oxford/New York: Oxford University Press.

Murray-Wallace, C.V., Belperio, A.P., Picker, K., & Kimber, R.W.L. (1991). Coastal aminostratigraphy of the last interglaciation in Southern Australia. Quaternary Research, 35(1), 63-71.

Murray-Wallace, C.V., Ferland, M.A., & Roy, P.S. (2005). Further amino acid racemisation evidence for glacial age, multiple lowstand deposition on the New South Wales outer continental shelf, southeastern Australia. Marine Geology, 214, 235-250.

Murray-Wallace, C.V., Kimber, R.W.L., & Belperio, A.P. (1988). Holocene palaeotemperature studies using amino acid racemization reactions. Australian Journal of Earth Sciences, 35, 575-577.

Nelson, A.R. (1981). Quaternary glacial and marine stratigraphy of the Qivitu Peninsula, northern Cumberland Peninsula, Baffin Island, Canada: summary. Geological Society of America Bulletin, 92, 512-518.

Oches, E.A., & McCoy, W.D. (1990). Aminostratigraphic evaluation of central European loess deposits: new data from the Pleistocene of Hungary. Geological Society of America, 21(6), 210.

Oches, E.A., McCoy, W.D., & Clark, P.U. (1996). Amino acid estimates of latitudinal temperature gradients and geochronology of loess deposition during the last glaciation, Mississippi Valley, United States. Geological Society of America Bulletin, 108, 892-903.

Peng, T., & Broecker, W.S. (1984). The impacts of bioturbation on the age difference between benthic and planktonic foraminifera in deep sea sediments. Nuclear Instruments and Methods in Physics Research Section B: Bean Interactions with Materials and Atoms, 5(2), 346-352.

Penkman, K.E.H., Kaufman, D.S., Maddy, D., & Collins, M.J. (2008). Closed-system behaviour of the intra-crystalline fraction of amino acids in mollusk shells. Quaternary Geochronology, 3, 2-25.

Poirier, R.K., & Billups, K. (2014). The intensification of northern component deepwater formation during the mid-Pleistocene climate transition. Paleoceanography, 29, PA002661.

103

Refsnider, K.A., Miller, G.H., Frechette, B., & Rood, D.H. (2013). A chronological framework for the Clyde Foreland Formation, Eastern Canadian Arctic, derived from amino acid racemization and cosmogenic radionuclides. Quaternary Geochronology, 16, 21-34.

Reichert, K.L., Licciardi, J.M., Kaufman, D.S. (2011). Amino acid racemization in lacustrine ostracodes, part II: Paleothermometry in Pleistocene sediments at Summer Lake, Oregon, 6, 174-185.

Rockwell, T.K., Nolan, J.M., Johnson, D.L., & Patterson, R.H. (1992). Ages and deformation of amrine terraces between Point Conception and Gaviota, western transverse ranges, California. In: Fletcher, C.H., III, & Wehmiller, J.F. (Eds.), Quaternary coasts of the United States: marine and lacustrine systems (pp. 333- 341). Tulsa, OK: SEPM (Society for Sedimentary Geology).

Scott, W.E., McCoy, W.D., Shroba, R.R., & Rubin, M. (1983). Reinterpretation of the exposed record of the last two cycles of Lake Bonneville, Western United States. Quaternary Research, 20, 261-285.

Sejrup, H.P., Aarseth, I., Ellingsen, K.L., Reither, E., Jansen, E., Lovlie, R., Bent, A., Brigham-Grette, J., Larsen, E., & Stoker, M. (1987). Quaternary stratigraphy of the Fladen area, central North Sea: a multidisciplinary study. Journal of Quaternary Science, 2(1), 35-58.

Sejrup, H.P., Miller, G.H., Brigham-Grette, J., Lovlie, R., & Hopkins, D. (1984a). Amino acid epimerization implies rapid sedimentation rates in Arctic cores. Nature, 310, 772-775.

Sejrup, H.P., Rokoengen, K., & Miller, G.H. (1984b). Isoleucine epimerization in Quaternary benthonic foraminifera from the Norwegian continental shelf: a pilot study. Marine Geology, 56, 227-239.

Simonson, A.E., Lockwood, R., & Wehmiller, J.F. (2013). Three approaches to radiocarbon calibration of amino acid racemization in Mulina lateralis from the Holocene of the Chesapeake Bay, USA. Quaternary Geochronology, 16, 62-72.

Sloss, C.R., Murray-Wallace, C.V., Jones, B.G., & Wallin, T. (2004). Aspartic acid racemization dating of mid-Holocene to recent estuarine sedimentation in New South Wales, Australia: a pilot study. Marine Geology, 212, 45-59.

Stathoplos, L., & Hare, P.E. (1993). Bleach removes labile amino acids from deep sea planktonic foraminiferal shells. Journal of Foraminiferal Research, 23(2), 102- 107.

104

Stuiver, M., & Polach, H.A. (1977). Discussion reporting 14C data. Radiocarbon, 19(3), 355-363.

Sykes, G.A., Collins, M.J., Walton, D.I. (1995). The significance of a geochemically isolated intracrystalline fraction within biominerals. Organic Geochemistry, 23, 1059-1065.

Taylor, J.R. (1982). An introduction to error analysis: the study of uncertainties in physical measurements. Sausalito, CA: University Science Books, pp.174-176.

Teal, L.R., Bulling, M.T., Parker, E.R., & Solan, M. (2008). Global patterns of bioturbation intensity and mixed depth of marine soft sediments. Aquatic Biology, 2, 207-218.

Walker, M. (2005). Quaternary dating methods. West Sussex, England: Wiley & Sons Ltd., pp. 184-195.

Weaver, P.P, Wynn, R.B., Kenyon, N.H., & Evans, J. (2000). Continental margin sedimentation, with special reference to the north-east Atlantic margin. Sedimentology, 47, 239-256.

Wehmiller, J.F. (1977). Amino acid studies of the Del Mar, California, midden site – apparent rate constants, ground temperature models, and chronological implications. Earth and Planetary Science Letters, 37, 184-196.

Wehmiller, J.F. (1980). Intergeneric differences in apparent racemization kinetics in mollusks and foraminifera: implications for models of diagenetic racemization. In: Hare, P.E., Hoering, T., & King, K. (Eds.), Biogeochemistry of amino acids (pp. 341-345). New York: Wiley.

Wehmiller, J.F. (1982). A review of amino acid racemization studies in Quaternary mollusks: stratigraphic and chronologic applications in coastal and interglacial sites, Pacific and Atlantic coasts, United States, United Kingdom, Baffin Island, and tropical islands. Quaternary Science Reviews, 1, 83-120.

Wehmiller, J.F. (1984). Interlaboratory comparison of amino acid enantiomeric ratios in fossil Pleistocene mollusks. Quaternary Research, 22, 109-120.

Wehmiller, J.F. (2013). United States Quaternary coastal sequences and molluscan racemization geochronology – what have they meant for each other over the past 45 years?. Quaternary Geochronology, 16, 3-20.

105

Wehmiller, J.F., Belknap, D.F., Boutin, B.S., Mirecki, J.E., Rahamin, S.D., & York, L.L. (1988). A review of the aminostratigraphy of Quaternary mollusks from United States Atlantic Coastal Plain sites. In: Easterbrook, D.J. (Ed.), Dating Quaternary sediments (pp. 69-110). Geological Society of America.

Wehmiller, J.F., & Hall, F.R. (1997). Data report: amino acid racemization geochronological studies of selected Leg 155 samples. In: Flood, R.D., Piper, D.J.W., Klaus, A., & Peterson, L.C. (Eds.), Proceedings of the Ocean Drilling Program, scientific results (Vol. 155, pp. 375-378). College Station, Texas.

Wehmiller, J.F., & Hare, P.E. (1971). Racemization of amino acids in marine sediments. Science, 173, 907-911.

Wehmiller, J.F., Lajoie, K.R., Kvenvolden, K.A., Peterson, E., Belknap, D.F., Kennedy, G.L., Addicott, W.O., Vedder, J.G., & Wright, R.W. (1977). Correlation and chronology of Pacific coast marine terraces of continental United States by amino acid stereochemistry – technique evaluation, relative ages, kinetic model ages, and geologic implications. U.S. Geological Survey Open-File Report, 77-680, pp. 1-196.

Wehmiller, J.F., Thieler, E.R., Miller, D., Pellerito, V., Keeney, V.B., Riggs, S.R., Culver, S., Mallinson, D., Farrell, K.M., York, L.L., Pierson, J., Parham, P.R. (2010). Amino stratigraphy of surface and subsurface Quaternary sediments, North Carolina coastal plain, USA. Quaternary Geochronology, 5, 459-492.

Wehmiller, J.F., York, L.L, & Bart, M.L. (1995). Amino acid racemization geochronology of reworked Quaternary mollusks on U.S. Atlantic coast beaches; implications for chronostratigraphy, taphonomy, and coastal sediment transport. Marine Geology, 124, 303-337.

Whitacre, K.E., Kaufman, D.S., Kosnik, M.A., & Hearty, P.J. (2017). Converting A/I values (ion exchange) to D/L values (reverse phase) for amino acid geochronology. Quaternary Geochronology, 37, 1-6.

York, L.L, Wehmiller, J.F., Cronin, T.M., & Ager, T.A. (1989). Stetson Pit, Dar Country, North Carolina: An integrated chronologic, faunal and floral record of subsurface coastal sediments. Palaeogeography, Palaeoclimatology, Palaeoecology, 72, 115- 132.

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Appendix

SUPPLEMENTARY TABLES AND FIGURES

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108

Table A1. Subsample D/L values used for bleached and unbleached comparison.

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 1056D, 1H-1, 62 cm 16347A P. obliq unbleached 5 0.100 0.049 0.150 0.5 16347B P. obliq unbleached 5 0.072 0.031 0.063 1.0 1 16347C P. obliq unbleached 5 0.099 0.044 0.125 0.5 16347D P. obliq unbleached 5 0.094 0.033 0.081 1.0 1 16347E P. obliq unbleached 5 0.098 0.038 0.075 1.1 1 16347F P. obliq unbleached 5 0.129 0.073 0.236 0.3 16347G P. obliq unbleached 5 0.103 0.047 0.189 0.4 16347H P. obliq unbleached 5 0.110 0.050 0.224 0.3 16347I P. obliq unbleached 5 0.118 0.055 0.197 0.4 16347J P. obliq unbleached 6 0.116 ------16347K P. obliq bleached 10 0.128 0.064 0.361 0.6 16347L P. obliq bleached 10 0.122 0.061 0.332 0.5 16347M P. obliq bleached 10 0.125 0.059 0.337 0.3 16347N P. obliq bleached 10 0.131 0.061 0.298 0.4 16347O P. obliq bleached 10 0.133 0.071 0.348 0.3 16347P P. obliq bleached 10 0.127 0.061 0.325 0.3 16347Q P. obliq bleached 10 ------16347R P. obliq bleached 10 0.134 0.061 0.361 0.3 16347S P. obliq bleached 10 0.129 0.071 0.338 0.3 16347T P. obliq bleached 12 0.132 0.071 0.358 0.3

1056D, 1H-1, 64 cm 16348A P. obliq unbleached 5 0.119 0.049 0.182 0.4 16348B P. obliq unbleached 5 0.125 0.066 0.203 0.5 16348C P. obliq unbleached 5 0.115 0.055 0.221 0.4 16348D P. obliq unbleached 5 0.123 0.058 0.238 0.4 16348E P. obliq unbleached 5 0.123 0.106 0.194 0.4 2 16348F P. obliq unbleached 5 0.128 0.055 0.249 0.3 16348G P. obliq unbleached 5 0.119 0.051 0.199 0.4 16348H P. obliq unbleached 5 0.126 0.057 0.233 0.4 16348I P. obliq unbleached 4 ------16348J P. obliq unbleached 4 0.120 0.055 0.201 0.4 16348K P. obliq bleached 10 0.135 0.062 0.356 0.3 16348L P. obliq bleached 10 0.136 0.062 0.348 0.3

109

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16348M P. obliq bleached 10 0.125 0.058 0.317 0.3 16348N P. obliq bleached 10 0.131 0.061 0.357 0.3 16348O P. obliq bleached 10 0.141 0.068 0.367 0.3 16348P P. obliq bleached 10 0.134 0.063 0.228 0.5 16348Q P. obliq bleached 10 0.127 0.058 0.354 0.3 16348R P. obliq bleached 12 0.134 0.065 0.359 0.3 16348S P. obliq bleached 14 0.114 0.045 0.169 0.6 3 16348T P. obliq bleached 15 0.140 0.073 0.365 0.3

16352A G. truncat (s) unbleached 5 0.155 0.069 0.278 0.3 16352B G. truncat (s) unbleached 4 0.138 0.056 0.262 0.4 16352C G. truncat (s) unbleached 5 0.125 0.052 0.204 0.5 16352D G. truncat (s) unbleached 4 0.141 0.057 0.266 0.3 16352E G. truncat (s) unbleached 5 0.138 0.056 0.244 0.4 16352F G. truncat (s) unbleached 5 0.152 0.062 0.286 0.4 16352G G. truncat (s) unbleached 5 0.155 0.066 0.289 0.3 16352H G. truncat (s) unbleached 5 0.148 0.057 0.217 0.4 16352I G. truncat (s) unbleached 5 0.153 0.072 0.273 0.3 16352J G. truncat (s) unbleached 4 0.126 0.055 0.233 0.4 16352K G. truncat (s) bleached 10 0.126 0.053 0.206 0.4 16352L G. truncat (s) bleached ------16352M G. truncat (s) bleached 10 0.109 0.043 0.116 0.6 16352N G. truncat (s) bleached 10 0.130 0.058 0.291 0.3 16352O G. truncat (s) bleached 9 0.121 0.054 0.208 0.4 16352P G. truncat (s) bleached 9 0.113 0.044 0.140 0.6 16352Q G. truncat (s) bleached 10 0.130 0.055 0.262 0.4 16352R G. truncat (s) bleached 8 0.128 0.065 0.247 0.6 16352S G. truncat (s) bleached 9 0.119 0.055 0.243 0.4 16352T G. truncat (s) bleached 9 0.133 0.060 0.287 0.3

16346A G. tumida unbleached 3 0.134 0.065 0.181 0.5 16346B G. tumida unbleached 3 0.129 0.059 0.194 0.5 16346C G. tumida unbleached 2 0.116 0.046 0.218 0.4 16346D G. tumida unbleached 3 0.124 0.051 0.204 0.4 16346E G. tumida unbleached 3 0.120 0.056 0.208 0.5 16346F G. tumida unbleached 2 0.124 0.052 0.175 0.5

110

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16346G G. tumida unbleached 3 0.119 0.054 0.220 0.4 16346H G. tumida unbleached 2 0.138 0.052 0.178 0.5 16346I G. tumida unbleached 3 0.128 0.050 0.218 0.4 16346J G. tumida unbleached 2 0.119 0.050 0.176 0.4 16346K G. tumida bleached 4 0.143 0.149 0.255 0.3 16346L G. tumida bleached 4 0.129 0.106 0.098 0.5 16346M G. tumida bleached 4 0.140 0.100 0.227 0.1 16346N G. tumida bleached 4 0.158 0.123 0.307 0.3 16346O G. tumida bleached 4 0.145 0.076 0.295 0.4 16346P G. tumida bleached 4 0.155 0.127 0.269 0.2 16346Q G. tumida bleached 4 0.121 0.087 0.060 0.5 16346R G. tumida bleached 4 0.151 0.079 0.288 0.4 16346S G. tumida bleached 4 0.145 0.077 0.222 0.5 16346T G. tumida bleached 4 0.143 0.077 0.272 0.4

1056D, 1H-1, 68 cm 16576A G. tumida unbleached 3 0.126 0.048 0.177 0.4 16576B G. tumida unbleached 2 0.146 0.053 0.207 0.4 16576C G. tumida unbleached 2 0.156 0.098 0.237 0.4 16576D G. tumida unbleached 3 0.139 0.056 0.242 0.3 16576E G. tumida unbleached 3 ------16576F G. tumida unbleached 3 0.124 0.044 0.205 0.4 16576G G. tumida unbleached 3 0.146 0.068 0.246 0.4 16576H G. tumida unbleached 3 0.154 0.072 0.265 0.3 16576I G. tumida unbleached 3 0.139 0.055 0.239 0.3 16576J G. tumida unbleached 3 0.117 0.056 0.198 0.3 16576K G. tumida bleached 4 0.134 0.054 0.281 0.4 16576L G. tumida bleached 4 0.125 0.054 0.238 0.5 16576M G. tumida bleached 4 0.113 0.050 0.144 0.6 16576N G. tumida bleached 4 0.114 0.050 0.173 0.4 16576O G. tumida bleached 4 0.119 0.047 0.159 0.6 16576P G. tumida bleached 4 0.132 0.060 0.312 0.3 16576Q G. tumida bleached 4 0.131 0.053 0.270 0.4 16576R G. tumida bleached 4 0.117 0.047 0.166 0.4 16576S G. tumida bleached 4 0.137 0.070 0.305 0.4 16576T G. tumida bleached 4 0.128 0.051 0.251 0.4

111

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 1056D, 1H-1, 70 cm 16581A P. obliq unbleached 5 ------16581B P. obliq unbleached 5 ------16581C P. obliq unbleached 5 0.119 0.053 0.206 0.4 16581D P. obliq unbleached 5 0.124 0.062 0.212 0.6 16581E P. obliq unbleached 5 0.148 0.074 0.283 0.4 16581F P. obliq unbleached 5 0.123 0.053 0.223 0.4 16581G P. obliq unbleached 5 0.118 0.051 0.225 0.4 16581H P. obliq unbleached 5 0.123 0.066 0.197 0.6 16581I P. obliq unbleached 6 0.121 0.054 0.223 0.5 16581J P. obliq unbleached 6 0.128 0.057 0.194 0.5 16581K P. obliq bleached 10 0.117 0.048 0.209 0.5 16581L P. obliq bleached 10 0.128 0.061 0.152 0.8 16581M P. obliq bleached 10 0.116 0.050 0.174 0.6 16581N P. obliq bleached 10 ------16581O P. obliq bleached 10 0.144 0.058 0.201 0.5 16581P P. obliq bleached 10 0.120 0.056 0.268 0.4 16581Q P. obliq bleached 10 ------16581R P. obliq bleached 10 0.119 0.053 0.257 0.3 16581S P. obliq bleached 12 ------16581T P. obliq bleached 12 0.120 0.069 0.266 0.6

16583A G. truncat (s) unbleached 5 0.147 0.064 0.227 0.4 16583B G. truncat (s) unbleached 5 0.136 0.063 0.258 0.4 16583C G. truncat (s) unbleached 5 0.151 0.062 0.254 0.5 16583D G. truncat (s) unbleached 5 0.129 0.053 0.237 0.4 16583E G. truncat (s) unbleached 5 0.131 0.051 0.228 0.4 16583F G. truncat (s) unbleached 5 0.151 0.058 0.235 0.4 16583G G. truncat (s) unbleached 5 0.146 0.063 0.228 0.5 16583H G. truncat (s) unbleached 5 0.153 0.078 0.296 0.3 16583I G. truncat (s) unbleached 5 0.150 0.064 0.249 0.4 16583J G. truncat (s) unbleached 5 0.144 0.057 0.248 0.4 16583K G. truncat (s) bleached 10 0.130 0.059 0.334 0.3 16583L G. truncat (s) bleached 10 0.132 0.055 0.261 0.4 16583M G. truncat (s) bleached 10 0.125 0.055 0.269 0.4 16583N G. truncat (s) bleached 10 0.127 0.054 0.284 0.3

112

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16583O G. truncat (s) bleached 10 ------16583P G. truncat (s) bleached 10 0.128 0.057 0.300 0.4 16583Q G. truncat (s) bleached 10 0.134 0.061 0.311 0.4 16583R G. truncat (s) bleached 10 0.116 0.049 0.163 0.4 3 16583S G. truncat (s) bleached 10 0.130 0.063 0.289 0.5 16583T G. truncat (s) bleached 10 ------16583U G. truncat (s) bleached 9 ------

1059A 1H-1, 44 cm 16589A P. obliq unbleached 5 0.129 0.059 0.217 0.4 16589B P. obliq unbleached 5 0.122 0.053 0.200 0.4 16589C P. obliq unbleached 5.5 0.122 0.059 0.208 0.5 16589D P. obliq unbleached 5 0.127 0.054 0.227 0.4 16589E P. obliq unbleached 5 0.122 0.061 0.215 0.4 16589F P. obliq unbleached 5 0.134 0.065 0.228 0.5 16589G P. obliq unbleached 5 0.127 0.069 0.207 0.4 16589H P. obliq unbleached 5 0.135 0.079 0.187 0.6 16589I P. obliq unbleached 5 0.118 0.049 0.205 0.4 16589J P. obliq unbleached 5 0.115 0.048 0.218 0.4 16589K P. obliq bleached 10 0.122 0.059 0.304 0.4 16589L P. obliq bleached 10 ------16589M P. obliq bleached 10 0.126 0.058 0.327 0.4 16589N P. obliq bleached 10 0.128 0.063 0.323 0.4 16589O P. obliq bleached 10 0.124 0.064 0.338 0.4 16589P P. obliq bleached 10 0.084 0.031 0.073 1.0 1 16589Q P. obliq bleached 7 0.132 0.066 0.354 0.3 16589R P. obliq bleached 9 0.121 0.059 0.279 0.4

16591A G. truncat (s) unbleached 5 ------16591B G. truncat (s) unbleached 5 0.121 0.046 0.139 0.6 16591C G. truncat (s) unbleached 5 0.133 0.054 0.206 0.5 16591D G. truncat (s) unbleached 5 0.147 0.067 0.210 0.6 16591E G. truncat (s) unbleached 5 0.143 0.066 0.230 0.5 16591F G. truncat (s) unbleached 5 0.132 0.063 0.252 0.7 16591G G. truncat (s) unbleached 5 0.138 0.061 0.235 0.4 16591H G. truncat (s) unbleached 5 0.133 0.057 0.222 0.6

113

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16591I G. truncat (s) unbleached 5 0.136 0.056 0.202 0.5 16591J G. truncat (s) unbleached 5 0.127 0.054 0.222 0.5 16591K G. truncat (s) unbleached 5 0.135 0.062 0.226 0.5 16591L G. truncat (s) bleached 10 0.118 0.058 0.283 0.3 16591M G. truncat (s) bleached 10 0.125 0.059 0.292 0.3 16591N G. truncat (s) bleached 10 ------16591O G. truncat (s) bleached 10 0.131 0.059 0.251 0.1 16591P G. truncat (s) bleached 10 0.127 0.064 0.293 0.2 16591Q G. truncat (s) bleached 10 0.146 0.065 0.343 0.4 16591R G. truncat (s) bleached 10 0.132 0.057 0.252 0.3 16591S G. truncat (s) bleached 10 0.125 0.055 0.232 0.5 16591T G. truncat (s) bleached 12 0.134 0.066 0.348 0.4 16591U G. truncat (s) bleached 11 0.135 0.061 0.255 0.4

16590A G. truncat (d) unbleached 5 0.147 0.055 0.213 0.5 3 16590B G. truncat (d) unbleached 5 0.135 0.051 0.194 0.4 16590C G. truncat (d) unbleached 5 0.137 0.050 0.196 0.4 16590D G. truncat (d) unbleached 5 0.133 0.059 0.203 0.4 16590E G. truncat (d) unbleached 5 0.128 0.056 0.190 0.4 16590F G. truncat (d) unbleached 5 0.128 0.064 0.196 0.4 16590G G. truncat (d) unbleached 5 0.128 0.055 0.199 0.4 16590H G. truncat (d) unbleached 5 0.133 0.061 0.205 0.4 16590I G. truncat (d) unbleached 5 0.129 0.050 0.210 0.4 16590K G. truncat (d) bleached 10 0.127 0.052 0.229 0.6 16590L G. truncat (d) bleached 10 0.139 0.059 0.332 0.3 16590M G. truncat (d) bleached 10 0.134 0.057 0.292 0.4 16590N G. truncat (d) bleached 10 0.144 0.061 0.344 0.4 16590O G. truncat (d) bleached 10 0.129 0.053 0.312 0.4 16590P G. truncat (d) bleached 10 0.133 0.056 0.232 0.2 16590Q G. truncat (d) bleached 10 0.131 0.056 0.329 0.4 16590R G. truncat (d) bleached 10 0.138 0.055 0.318 0.4 16590S G. truncat (d) bleached 10 0.134 0.057 0.305 0.4 16590T G. truncat (d) bleached 6.5 0.132 0.053 0.253 0.4

16588A G. tumida unbleached 2 0.150 0.077 0.242 0.7 16588B G. tumida unbleached 2 ------

114

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16588C G. tumida unbleached 3 0.155 0.074 0.260 0.4 16588D G. tumida unbleached 2 0.177 0.089 0.294 0.4 16588E G. tumida unbleached 3 0.140 0.054 0.257 0.3 16588F G. tumida unbleached 2 0.144 0.062 0.237 0.4 16588G G. tumida unbleached 3 0.154 0.072 0.266 0.4 16588H G. tumida unbleached 2 0.136 0.060 0.254 0.4 16588I G. tumida unbleached 2 0.166 0.063 0.254 0.3 16588J G. tumida unbleached 2 0.145 0.068 0.236 0.3 16588K G. tumida bleached 4 0.141 0.181 0.304 0.6 3 16588L G. tumida bleached 4 0.124 0.050 0.255 0.4 16588M G. tumida bleached 4 0.132 0.080 0.303 0.5 16588N G. tumida bleached 4 0.078 0.025 0.045 1.2 1 16588O G. tumida bleached 4 0.121 0.045 0.164 0.4 16588P G. tumida bleached 4 0.134 0.039 0.193 0.5 16588Q G. tumida bleached 4 0.133 0.055 0.259 0.3 16588R G. tumida bleached 4 0.130 0.054 0.298 0.3 16588S G. tumida bleached 4 0.138 0.055 0.315 0.4 16588T G. tumida bleached 4 0.132 0.055 0.258 0.3

1059A 1H-1, 50 cm 16595A G. truncat (s) unbleached 5 ------16595B G. truncat (s) unbleached 5 0.170 0.064 0.227 0.5 16595C G. truncat (s) unbleached 5 0.114 0.049 0.166 0.6 16595D G. truncat (s) unbleached 5 0.135 0.055 0.195 0.6 16595E G. truncat (s) unbleached 5 0.134 0.053 0.225 0.5 16595F G. truncat (s) unbleached 5 ------16595G G. truncat (s) unbleached 5 ------16595H G. truncat (s) unbleached 5 0.130 0.060 0.207 0.5 16595I G. truncat (s) unbleached 5 0.154 0.069 0.240 0.5 16595J G. truncat (s) unbleached 5 0.105 0.049 0.148 0.5 16595K G. truncat (s) unbleached 5 0.140 0.064 0.194 0.5 16595L G. truncat (s) bleached 10 0.139 0.069 0.295 0.4 16595M G. truncat (s) bleached 11 0.135 0.064 0.316 0.4 16595N G. truncat (s) bleached 10 0.128 0.064 0.288 0.3 16595O G. truncat (s) bleached 10 0.146 0.070 0.380 0.4 16595P G. truncat (s) bleached 10 0.133 0.059 0.317 0.3

115

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16595Q G. truncat (s) bleached 10 0.128 0.064 0.328 0.3 16595R G. truncat (s) bleached 10 0.131 0.064 0.331 0.3 16595S G. truncat (s) bleached 10 0.133 0.059 0.203 0.5 16595T G. truncat (s) bleached 10 0.130 0.061 0.314 0.3 16595U G. truncat (s) bleached 11 0.127 0.064 0.322 0.3

1059A 1H-1, 54 cm 16597A P. obliq unbleached 5 0.134 0.064 0.222 0.5 16597B P. obliq unbleached 5 0.120 0.051 0.208 0.4 16597C P. obliq unbleached 5 0.127 0.056 0.213 0.5 16597D P. obliq unbleached 5 0.127 0.065 0.223 0.4 16597E P. obliq unbleached 5 0.141 0.071 0.221 0.5 16597F P. obliq unbleached 5 0.117 0.045 0.231 0.4 16597G P. obliq unbleached 5 0.126 0.054 0.202 0.5 16597H P. obliq unbleached 5 0.143 0.081 0.230 0.5 16597I P. obliq unbleached 5 0.121 0.051 0.211 0.5 16597J P. obliq unbleached 5 0.133 0.060 0.232 0.4 16597K P. obliq bleached 10 0.121 0.058 0.264 0.3 16597L P. obliq bleached 10 0.124 0.060 0.296 0.4 16597M P. obliq bleached 10 0.098 0.047 0.096 0.9 1 16597N P. obliq bleached 10 0.130 0.064 0.340 0.3 16597O P. obliq bleached 10 0.123 0.062 0.296 0.3 16597P P. obliq bleached 10 0.117 0.056 0.235 0.3 16597Q P. obliq bleached 10 0.132 0.063 0.299 0.4 16597R P. obliq bleached 7 0.114 0.055 0.264 0.3 16597S P. obliq bleached 7 0.140 0.080 0.355 0.6

16599A G. truncat (s) unbleached 5 0.147 0.063 0.266 0.3 16599B G. truncat (s) unbleached 5 0.150 0.056 0.237 0.4 16599C G. truncat (s) unbleached 5 0.142 0.053 0.235 0.4 16599D G. truncat (s) unbleached 5 0.135 0.060 0.246 0.5 16599E G. truncat (s) unbleached 5 0.113 0.045 0.207 0.5 3 16599F G. truncat (s) unbleached 5 0.146 0.062 0.225 0.4 16599G G. truncat (s) unbleached 5 0.110 0.042 0.202 0.5 3 16599H G. truncat (s) unbleached 5 0.140 0.063 0.207 0.5 16599I G. truncat (s) unbleached 5 0.153 0.069 0.257 0.5

116

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16599J G. truncat (s) unbleached 6 0.160 0.063 0.242 0.5 16599K G. truncat (s) bleached 10 0.121 0.061 0.385 0.8 16599L G. truncat (s) bleached 10 0.126 0.062 0.397 0.8 16599M G. truncat (s) bleached 10 0.135 0.063 0.376 0.5 16599N G. truncat (s) bleached 10 0.140 0.073 0.397 0.5 16599O G. truncat (s) bleached 10 0.126 0.060 0.381 0.6 16599P G. truncat (s) bleached 10 0.129 0.060 0.327 0.4 16599Q G. truncat (s) bleached 10 0.125 0.063 0.366 0.6 16599R G. truncat (s) bleached 10 0.130 0.060 0.398 0.7 16599S G. truncat (s) bleached 10 0.138 0.067 0.407 0.4 16599T G. truncat (s) bleached 10 0.127 0.062 0.387 0.7

16598A G. truncat (d) unbleached 5 0.130 0.059 0.204 0.5 16598B G. truncat (d) unbleached 5 0.118 0.048 0.163 0.4 16598C G. truncat (d) unbleached 5 0.138 0.049 0.187 0.4 16598D G. truncat (d) unbleached 5 0.131 0.063 0.166 0.4 16598E G. truncat (d) unbleached 5 0.150 0.059 0.242 0.3 3 16598F G. truncat (d) unbleached 5 0.122 0.051 0.207 0.6 16598G G. truncat (d) unbleached 4 0.137 0.051 0.189 0.4 16598H G. truncat (d) unbleached 4 0.126 0.048 0.195 0.4 16598I G. truncat (d) unbleached 4 0.129 0.052 0.176 0.5 16598J G. truncat (d) bleached 8 0.149 0.055 0.317 0.4 16598K G. truncat (d) bleached 10 0.148 0.061 0.318 0.4 16598L G. truncat (d) bleached 10 ------16598M G. truncat (d) bleached 10 0.145 0.061 0.357 0.3 16598N G. truncat (d) bleached 8 0.147 0.064 0.351 0.3 16598O G. truncat (d) bleached 8 0.147 0.061 0.340 0.4 16598P G. truncat (d) bleached 8 0.140 0.058 0.313 0.3 16598Q G. truncat (d) bleached 8 0.166 0.061 0.312 0.3

1062B, 1H-1, 62 cm 16611A G. truncat (s) unbleached 5 0.138 0.054 0.272 0.4 16611B G. truncat (s) unbleached 5 0.160 0.075 0.297 0.5 16611C G. truncat (s) unbleached 5 0.152 0.059 0.276 0.4 16611D G. truncat (s) unbleached 5 0.166 0.057 0.317 0.3 16611E G. truncat (s) unbleached 5 0.118 0.036 0.117 0.7 3

117

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16611F G. truncat (s) unbleached 5 0.167 0.061 0.303 0.4 16611G G. truncat (s) unbleached 5 0.174 0.061 0.314 0.5 16611H G. truncat (s) unbleached 5 0.146 0.059 0.256 0.4 16611I G. truncat (s) unbleached 4 0.151 0.060 0.272 0.4 16611J G. truncat (s) unbleached 5 0.139 0.053 0.212 0.4 16611K G. truncat (s) bleached 10 0.124 0.053 0.226 0.5 16611L G. truncat (s) bleached 10 0.129 0.055 0.116 0.5 16611M G. truncat (s) bleached 10 0.134 0.059 0.223 0.4 16611N G. truncat (s) bleached 10 ------16611O G. truncat (s) bleached 10 ------16611P G. truncat (s) bleached 10 ------16611Q G. truncat (s) bleached 10 ------16611R G. truncat (s) bleached 10 ------16611S G. truncat (s) bleached 10 0.120 0.063 0.231 1.1 1 16611T G. truncat (s) bleached 11 0.146 0.062 0.241 0.3

KNR140 JPC-37, 150 cm 16631A P. obliq unbleached 5 0.153 0.055 0.152 0.7 16631B P. obliq unbleached 5 0.173 0.067 0.238 0.6 16631C P. obliq unbleached 5 0.193 0.087 0.315 0.4 16631D P. obliq unbleached 5 0.170 0.063 0.205 0.6 16631E P. obliq unbleached 5 ------16631F P. obliq unbleached 5 0.163 0.056 0.099 1.2 1 16631G P. obliq unbleached 5 0.194 0.090 0.295 0.5 16631H P. obliq unbleached 5 0.185 0.074 0.317 0.4 16631I P. obliq unbleached 6 0.184 0.075 0.292 0.5 16631J P. obliq unbleached 5 0.175 0.066 0.294 0.4 16631K P. obliq bleached 10 0.205 0.092 0.454 0.3 16631L P. obliq bleached 10 0.231 0.149 0.674 0.3 2 16631M P. obliq bleached 10 0.179 0.099 0.418 0.3 16631N P. obliq bleached 10 ------16631O P. obliq bleached 10 0.183 0.079 0.428 0.3 16631P P. obliq bleached 10 0.190 0.084 0.472 0.3 16631Q P. obliq bleached 10 0.179 0.077 0.372 0.3 16631R P. obliq bleached 11 0.182 0.080 0.416 0.3 16631S P. obliq bleached 10 0.183 0.077 0.427 0.3

118

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16631T P. obliq bleached 10 0.172 0.071 0.374 0.4 16631U P. obliq bleached 14 0.157 0.059 0.111 0.9

16632A G. truncat (s) unbleached 5 0.206 0.080 0.301 0.5 16632B G. truncat (s) unbleached 5 0.195 0.077 0.291 0.4 16632C G. truncat (s) unbleached 5 0.202 0.085 0.326 0.5 16632D G. truncat (s) unbleached 5 0.219 0.086 0.346 0.4 16632E G. truncat (s) unbleached 6 0.227 0.082 0.320 0.5 16632F G. truncat (s) unbleached 5 0.205 0.075 0.340 0.5 16632G G. truncat (s) unbleached 5 0.199 0.079 0.328 0.4 16632H G. truncat (s) unbleached 5 0.191 0.069 0.252 0.5 16632I G. truncat (s) unbleached 5 0.213 0.081 0.327 0.5 16632J G. truncat (s) unbleached 5 0.200 0.087 0.316 0.4 16632K G. truncat (s) bleached 10 0.220 0.088 0.479 0.3 16632L G. truncat (s) bleached 10 0.202 0.081 0.446 0.4 16632M G. truncat (s) bleached 10 0.181 0.078 0.419 0.7 16632N G. truncat (s) bleached 10 0.197 0.083 0.469 0.4 16632O G. truncat (s) bleached 10 0.197 0.080 0.475 0.5 16632P G. truncat (s) bleached 10 0.188 0.079 0.358 0.8 16632Q G. truncat (s) bleached 10 ------16632R G. truncat (s) bleached 10 0.197 0.082 0.454 0.5 16632S G. truncat (s) bleached 12 0.191 0.078 0.432 0.6 16632T G. truncat (s) bleached 11 0.191 0.077 0.438 0.4

KNR140 JPC-37, 1112 cm 16636A G. truncat (d) unbleached 5 0.357 0.107 0.296 0.5 3 16636B G. truncat (d) unbleached 5 0.288 0.094 0.319 0.4 16636C G. truncat (d) unbleached 5 0.289 0.116 0.405 0.3 16636D G. truncat (d) unbleached 5 ------16636E G. truncat (d) unbleached 4 0.292 0.104 0.368 0.4 16636F G. truncat (d) unbleached 4 0.287 0.098 0.356 0.4 16636G G. truncat (d) unbleached 4 0.276 0.079 0.180 0.5 16636H G. truncat (d) unbleached 4 0.533 0.060 0.177 0.9 1 16636I G. truncat (d) bleached 9 0.272 0.099 0.395 0.4 16636J G. truncat (d) bleached 10 0.286 0.108 0.433 0.3 16636K G. truncat (d) bleached 10 0.275 0.101 0.375 0.4

119

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16636L G. truncat (d) bleached 10 0.294 0.113 0.454 0.3 16636M G. truncat (d) bleached 9 0.239 0.088 0.364 0.4 16636N G. truncat (d) bleached 8 0.314 0.115 0.514 0.3 16636O G. truncat (d) bleached 8 0.266 0.087 0.351 0.4 16636P G. truncat (d) bleached 8 0.311 0.068 0.257 0.7 16636Q G. truncat (d) bleached 6.5 0.296 0.099 0.381 0.4

1056B, 5H-7, 44 cm 16640A P. obliq unbleached 5 0.299 0.099 0.092 0.9 1 16640B P. obliq unbleached 5 0.435 0.227 0.419 0.2 16640C P. obliq unbleached 5 0.416 0.210 0.404 0.2 16640D P. obliq unbleached 5 0.427 0.213 0.365 0.3 16640E P. obliq unbleached 5 0.402 0.213 0.412 0.2 16640F P. obliq unbleached 5 0.417 0.211 0.349 0.3 16640G P. obliq unbleached 5 0.446 0.237 0.487 0.2 16640H P. obliq unbleached 5 0.449 0.239 0.433 0.2 16640I P. obliq unbleached 5 0.459 0.247 0.470 0.2 16640J P. obliq unbleached 5 0.439 0.225 0.406 0.3 16640K P. obliq bleached 10 0.411 0.228 0.576 0.2 16640L P. obliq bleached 10 0.100 0.038 0.014 1.9 1 16640M P. obliq bleached 10 0.450 0.240 0.544 0.2 16640N P. obliq bleached 10 0.436 0.242 0.564 0.1 16640O P. obliq bleached 10 0.326 0.120 0.300 0.1 3 16640P P. obliq bleached 10 ------16640Q P. obliq bleached 10 0.450 0.245 0.552 0.2 16640R P. obliq bleached 10 0.264 0.095 0.121 0.2 2 16640S P. obliq bleached 10 ------16640T P. obliq bleached 11 ------

16641A G. truncat (d) unbleached 5 0.482 0.262 0.480 0.3 16641B G. truncat (d) unbleached 5 0.474 0.270 0.505 0.2 16641C G. truncat (d) unbleached 5 0.213 0.076 0.036 1.4 1 16641D G. truncat (d) unbleached 5 0.460 0.247 0.454 0.2 16641E G. truncat (d) unbleached 5 0.383 0.172 0.167 0.5 3 16641F G. truncat (d) unbleached 5 0.451 0.242 0.369 0.2 16641G G. truncat (d) unbleached 5 0.457 0.241 0.407 0.2

120

Table A1 Continued

Asp Glu Ser L-Ser/ Rejection UAL Speciesa Pretreatment nb D/L D/L D/L L-Asp Criteriac 16641H G. truncat (d) unbleached 5 0.469 0.250 0.422 0.2 16641I G. truncat (d) unbleached 5 0.436 0.219 0.380 0.4 16641J G. truncat (d) unbleached 5 0.478 0.257 0.407 0.2 16641K G. truncat (d) bleached 10 0.458 0.236 0.357 0.2 16641L G. truncat (d) bleached 10 0.478 0.246 0.444 0.3 16641M G. truncat (d) bleached 10 0.457 0.237 0.346 0.3 16641N G. truncat (d) bleached 10 0.477 0.256 0.415 0.2 16641O G. truncat (d) bleached 10 0.460 0.250 0.452 0.2 16641P G. truncat (d) bleached 10 0.467 0.253 0.520 0.2 16641Q G. truncat (d) bleached 10 0.474 0.247 0.458 0.3 16641R G. truncat (d) bleached 10 0.478 0.253 0.451 0.2 16641S G. truncat (d) bleached 10 0.432 0.214 0.309 0.3 16641T G. truncat (d) bleached 10 0.243 0.088 0.051 1.3 1 a P. obliq = Pulleniatina obliquiloculata; G. trun (s) = Globorotalia truncatulinoides (sinsitral); G. trun (d) = Globorotalia truncatulinoides (dextral); G. tumida = Globorotalia tumida b Number of foraminiferal tests per subsample. c The rejection criteria are (1) L-Ser/L-Asp ≥ 0.9, (2) D/L values off the Glu vs. Asp trend, and (3) subsamples with D/L Asp or Glu values that fell beyond ±2σ of the mean of the rest of the group.

121

1056D 62 cm

1056D 64 cm

1056D 68 cm

1056D 70 cm

1059A 44 cm

1059A 50 cm

1059A 54 cm 1062B 62 cm

JPC-37 150 cm

JPCJPC--37370 1112 1112 cm cm

1056B 44 cm

Figure A2. Cross plots of unbleached D/L values for aspartic acid (Asp) and glutamic acid (Glu) in subsamples of the foraminiferal species G. truncatulinoides dextral (A) and sinistral (B), G. tumida (C), and P. obliquiloculata (D). Data are shown in Table A1.

122

1056D 62 cm

1056D 64 cm 1056D 68 cm

1056D 70 cm

1059A 44 cm

1059A 50 cm

1059A 54 cm

1062B 62 cm

JPC-37 150 cm

JPC--37370 1112 1112 cm cm

1056B 44 cm

123

Table A2. Data used to determine the effect of the bleaching pretreatment on the subsample rejection rate.

Interval na rejb Site Species (cm) Unbleached Bleached Unbleached Bleached 1056D 62 P. obliq 7 9 3 0 1056D 64 P. obliq 8 9 1 1 1056D 70 P. obliq 8 6 0 1 1056D 64 G. trun (s) 10 9 0 0 1056D 70 G. trun (s) 10 7 0 1 1056D 64 G. tum 10 10 0 0 1056D 68 G. tum 9 10 0 0 1059A 44 P. obliq 10 6 0 1 1059A 54 P. obliq 10 8 0 1 1059A 44 G. trun (s) 10 9 0 0 1059A 44 G. trun (d) 8 10 1 0 1059A 50 G. trun (s) 8 10 0 0 1059A 54 G. trun (s) 8 10 2 0 1059A 54 G. trun (d) 8 7 1 0 1059A 44 G. tum 9 8 0 2 1062B 62 G. trun (s) 9 4 1 1

Holocene Sites Total: 142 132 9 8

JPC-37 150 P. obliq 8 9 1 1 JPC-37 150 G. trun (s) 10 9 0 0 JPC-37 1112 G. trun (d) 5 9 2 0 1056B 44 P. obliq 9 4 1 3 1056B 44 G. trun (d) 8 9 2 1

Down-Core Sites Total: 40 40 6 5

a Number of subsamples used to calculate the mean D/L ratio and standard deviation. b Number of subsamples rejected.

124

Table A3. Average concentration of amino acids in pmol/test. Data are from Table A4.

Interval Unbleached Concentrations (pmol/test) Bleached Concentrations (pmol/test) Site Species (cm) [Asp] [Glu] [Ser] [Ala] [Val] [Other]a [Asp] [Glu] [Ser] [Ala] [Val] [Other]a Holocene Sites

1056D 62 P. obliq 35 20 16 23 11 22 12 6 5 9 5 7 1056D 64 P. obliq 28 15 12 19 9 18 14 7 5 10 5 7 1056D 70 P. obliq 33 19 17 28 13 24 3 3 2 7 3 4 1056D 64 G. trun (s) 27 16 11 23 10 19 8 6 4 8 4 7 1056D 70 G. trun (s) 42 25 19 36 14 30 7 8 3 14 6 7 1056D 64 G. tum 67 41 31 51 20 40 3 3 2 7 3 4 1056D 68 G. tum 58 32 23 44 19 34 22 15 10 20 10 18

125 1059A 44 P. obliq 38 22 18 29 14 26 10 7 4 9 4 8

1059A 54 P. obliq 34 20 16 27 12 24 9 6 3 9 4 7 1059A 44 G. trun (s) 43 28 24 43 17 35 12 9 4 12 6 10 1059A 44 G. trun (d) 49 28 21 42 17 33 14 9 6 16 6 11 1059A 50 G. trun (s) 53 35 30 51 19 45 14 10 6 16 6 10 1059A 54 G. trun (s) 47 27 22 39 16 33 10 8 7 18 7 8 1059A 54 G. trun (d) 45 25 21 38 17 31 21 13 9 20 8 16 1059A 44 G. tum 49 26 22 43 19 33 17 15 7 22 10 16 1062B 62 G. trun (s) 23 14 11 22 8 16 3 3 1 5 2 3

Down-Core Sites

JPC-37 150 P. obliq 27 18 15 23 11 21 10 7 4 9 5 7 JPC-37 150 G. trun (s) 34 21 16 32 12 25 8 5 5 11 5 6 JPC-37 1112 G. trun (d) 43 27 18 41 18 38 16 11 6 17 7 11

Table A3 Continued

Interval Unbleached Concentrations (pmol/test) Bleached Concentrations (pmol/test) Site Species (cm) [Asp] [Glu] [Ser] [Ala] [Val] [Other]a [Asp] [Glu] [Ser] [Ala] [Val] [Other]a 1056B 44 P. obliq 33 20 8 28 12 23 15 10 3 13 7 9 1056B 44 G. trun (d) 26 17 6 28 13 23 15 10 3 16 7 12

a The combined concentrations of Phe, Ile, and Leu make up the “other” category due to their small concentrations.

126

Table A4. Subsample amino acid abundances in pmol/test, excluding rejected subsamples and those with missing data.

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Species Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 1056D, 1H-1, 62 cm 16347A P. obliq unbleached 29 19 16 23 11 8 7 9 16347C P. obliq unbleached 41 26 23 27 11 8 7 11 16347F P. obliq unbleached 30 14 10 17 8 5 5 5 16347G P. obliq unbleached 45 24 19 30 15 9 10 10 16347H P. obliq unbleached 36 18 13 21 9 6 5 6 16347I P. obliq unbleached 30 16 13 20 10 7 6 7

127 16347J P. obliq unbleached 7 3 4 9 5 3 3 2

16347K P. obliq bleached 12 6 7 12 6 3 3 3 16347L P. obliq bleached 12 6 5 9 5 1 3 3 16347M P. obliq bleached 7 4 3 5 3 1 1 1 16347N P. obliq bleached 5 3 2 4 2 1 1 1 16347O P. obliq bleached 11 7 5 11 6 1 3 3 16347P P. obliq bleached 21 11 8 14 7 4 4 4 16347Q P. obliq bleached 15 8 6 11 6 3 3 3 16347R P. obliq bleached 14 7 6 10 5 3 3 3 16347S P. obliq bleached 29 19 16 23 11 8 7 9 16347T P. obliq bleached 41 26 23 27 11 8 7 11

1056D, 1H-1, 64 cm 16348A P. obliq unbleached 5 3 2 4 2 2 1 1

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16348B P. obliq unbleached 42 23 17 33 14 10 8 8 16348C P. obliq unbleached 24 16 12 22 10 7 6 6 16348D P. obliq unbleached 34 18 13 27 12 8 7 7 16348F P. obliq unbleached 34 18 13 27 12 8 7 7 16348G P. obliq unbleached 23 13 9 20 8 5 4 4 16348H P. obliq unbleached 29 17 13 23 10 7 6 7 16348I P. obliq unbleached 24 13 9 18 8 6 4 5 16348J P. obliq unbleached 39 24 17 37 17 8 10 11 16348K P. obliq bleached 13 9 6 11 6 2 4 4 16348L P. obliq bleached 5 4 3 4 2 1 2 2 16348M P. obliq bleached 8 5 3 7 4 1 2 2

128 16348N P. obliq bleached 10 7 5 9 4 2 3 3

16348O P. obliq bleached 2 2 1 2 1 1 1 1 16348P P. obliq bleached 14 9 5 12 6 2 4 4 16348Q P. obliq bleached 4 3 3 6 3 2 2 2 16348R P. obliq bleached 10 7 4 9 4 2 3 3 16348T P. obliq bleached 8 5 3 8 4 1 2 2

16352A G. trun (s) unbleached 5 3 2 4 2 2 1 1 16352B G. trun (s) unbleached 42 23 17 33 14 10 8 8 16352C G. trun (s) unbleached 24 16 12 22 10 7 6 6 16352D G. trun (s) unbleached 34 18 13 27 12 8 7 7 16352E G. trun (s) unbleached 21 12 9 16 7 5 4 5 16352F G. trun (s) unbleached 34 18 13 27 12 8 7 7

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16352G G. trun (s) unbleached 23 13 9 20 8 5 4 4 16352H G. trun (s) unbleached 29 17 13 23 10 7 6 7 16352I G. trun (s) unbleached 24 13 9 18 8 6 4 5 16352J G. trun (s) unbleached 39 24 17 37 17 8 10 11 16352K G. trun (s) bleached 13 9 6 11 6 2 4 4 16352M G. trun (s) bleached 5 4 3 4 2 1 2 2 16352N G. trun (s) bleached 8 5 3 7 4 1 2 2 16352O G. trun (s) bleached 10 7 5 9 4 2 3 3 16352P G. trun (s) bleached 2 2 1 2 1 1 1 1 16352Q G. trun (s) bleached 14 9 5 12 6 2 4 4 16352R G. trun (s) bleached 4 3 3 6 3 2 2 2

129 16352S G. trun (s) bleached 10 7 4 9 4 2 3 3

16352T G. trun (s) bleached 8 5 3 8 4 1 2 2

16346A G. tumida unbleached 4 2 2 3 2 1 1 1 16346B G. tumida unbleached 55 35 27 43 20 14 13 15 16346C G. tumida unbleached 97 58 43 74 36 23 22 25 16346D G. tumida unbleached 65 39 29 48 24 15 14 16 16346E G. tumida unbleached 47 30 23 26 17 13 10 13 16346F G. tumida unbleached 60 40 31 49 23 16 14 18 16346G G. tumida unbleached 71 43 31 54 22 15 12 17 16346H G. tumida unbleached 80 52 44 66 27 22 16 23 16346I G. tumida unbleached 76 46 32 55 27 17 16 19 16346J G. tumida unbleached 119 68 48 86 0 0 0 0

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16346K G. tumida bleached 3 2 1 4 2 1 1 1 16346L G. tumida bleached 2 2 1 3 2 1 1 1 16346M G. tumida bleached 4 3 1 6 3 1 2 2 16346N G. tumida bleached 6 4 2 5 2 2 1 1 16346O G. tumida bleached 13 9 5 12 6 2 3 4 16346P G. tumida bleached 7 5 2 8 4 1 2 2 16346Q G. tumida bleached 4 4 2 4 2 2 2 2 16346R G. tumida bleached 13 9 5 14 5 2 3 4 16346S G. tumida bleached 8 6 4 7 3 2 2 2 16346T G. tumida bleached 13 9 5 14 5 2 3 4

130 1056D, 1H-1, 68 cm

16576A G. tumida unbleached 56 33 26 43 21 13 11 14 16576B G. tumida unbleached 67 40 31 54 25 17 12 14 16576C G. tumida unbleached 95 54 37 77 31 22 16 20 16576D G. tumida unbleached 55 29 20 39 17 11 9 10 16576F G. tumida unbleached 57 34 25 45 22 13 11 12 16576G G. tumida unbleached 46 27 18 38 16 10 8 10 16576H G. tumida unbleached 45 23 16 31 13 8 7 8 16576I G. tumida unbleached 47 24 18 33 14 9 7 8 16576J G. tumida unbleached 52 26 19 36 16 10 8 10 16576K G. tumida bleached 25 17 12 24 10 8 6 7 16576L G. tumida bleached 20 16 10 24 10 5 7 8 16576M G. tumida bleached 9 7 5 9 4 2 3 4

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16576N G. tumida bleached 24 19 11 22 11 4 7 9 16576O G. tumida bleached 9 7 5 8 4 3 3 3 16576P G. tumida bleached 21 13 7 19 9 3 5 5 16576Q G. tumida bleached 42 26 19 33 17 9 9 11 16576R G. tumida bleached 7 7 3 8 5 2 3 4 16576S G. tumida bleached 31 19 13 26 11 5 6 7 16576T G. tumida bleached 32 24 12 33 16 6 10 12

1056D, 1H-1, 70 cm 16581C P. obliq unbleached 46 24 20 33 16 10 9 10 16581D P. obliq unbleached 33 20 21 36 17 11 10 11

131 16581E P. obliq unbleached 23 12 10 18 8 5 4 5

16581F P. obliq unbleached 42 24 20 34 16 11 9 10 16581G P. obliq unbleached 35 20 15 26 12 8 7 8 16581H P. obliq unbleached 22 13 15 24 12 8 7 8 16581I P. obliq unbleached 31 18 17 27 12 8 7 8 16581J P. obliq unbleached 31 19 16 24 11 7 7 8 16581K P. obliq bleached 2 4 1 8 4 0 2 2 16581L P. obliq bleached 1 2 0 5 3 0 1 1 16581M P. obliq bleached 5 4 3 6 3 1 1 2 16581O P. obliq bleached 0 1 0 4 2 0 1 1 16581P P. obliq bleached 1 3 1 7 3 0 2 2 16581R P. obliq bleached 12 9 4 11 5 0 4 4 16581T P. obliq bleached 4 2 3 10 2 0 1 2

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16583A G. trun (s) unbleached 46 28 22 40 16 12 10 12 16583B G. trun (s) unbleached 47 26 18 36 12 9 7 8 16583C G. trun (s) unbleached 37 24 19 35 12 12 8 10 16583D G. trun (s) unbleached 48 28 21 39 16 12 11 11 16583E G. trun (s) unbleached 49 30 22 42 18 14 11 13 16583F G. trun (s) unbleached 45 27 21 38 14 13 10 11 16583G G. trun (s) unbleached 41 26 20 37 15 13 9 11 16583H G. trun (s) unbleached 26 14 9 20 8 6 5 5 16583I G. trun (s) unbleached 35 21 16 31 13 10 8 9 16583J G. trun (s) unbleached 48 28 21 39 17 12 10 11 16583K G. trun (s) bleached 6 7 2 13 6 0 3 2

132 16583L G. trun (s) bleached 2 3 1 8 3 0 2 1

16583M G. trun (s) bleached 3 5 1 9 4 0 2 1 16583N G. trun (s) bleached 11 10 4 15 6 0 4 4 16583P G. trun (s) bleached 8 8 4 14 7 0 4 3 16583Q G. trun (s) bleached 9 9 4 16 7 0 4 3 16583S G. trun (s) bleached 10 12 5 20 8 0 6 5

1059A 1H-1, 44 cm 16589A P. obliq unbleached 35 21 17 28 12 7 7 9 16589B P. obliq unbleached 38 22 17 27 14 8 9 9 16589C P. obliq unbleached 38 23 18 30 13 9 8 10 16589D P. obliq unbleached 38 22 16 28 14 9 8 9 16589E P. obliq unbleached 30 16 13 22 10 7 6 6

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16589F P. obliq unbleached 31 20 17 30 14 10 8 10 16589G P. obliq unbleached 44 26 20 33 15 9 9 10 16589H P. obliq unbleached 35 23 21 31 13 11 8 10 16589I P. obliq unbleached 49 28 21 35 15 11 9 11 16589J P. obliq unbleached 42 23 17 29 15 9 8 9 16589K P. obliq bleached 20 13 8 16 8 4 5 5 16589M P. obliq bleached 11 9 5 12 6 1 4 4 16589N P. obliq bleached 11 6 5 8 4 2 2 2 16589O P. obliq bleached 5 3 2 5 2 1 1 1 16589Q P. obliq bleached 8 5 3 7 4 1 2 2 16589R P. obliq bleached 7 5 3 7 3 2 2 2

133

16591B G. trun (s) unbleached 46 33 29 45 18 13 12 16 16591C G. trun (s) unbleached 54 34 26 44 18 15 12 13 16591D G. trun (s) unbleached 31 27 21 48 17 4 10 13 16591E G. trun (s) unbleached 40 25 21 37 15 12 8 11 16591F G. trun (s) unbleached 26 17 19 35 14 11 8 9 16591G G. trun (s) unbleached 54 30 24 44 18 13 10 11 16591H G. trun (s) unbleached 40 28 25 42 16 14 9 12 16591I G. trun (s) unbleached 48 30 26 44 17 14 11 13 16591J G. trun (s) unbleached 51 33 27 47 18 16 11 14 16591K G. trun (s) unbleached 36 24 21 37 15 12 9 11 16591L G. trun (s) bleached 16 10 6 14 7 3 4 4 16591M G. trun (s) bleached 8 6 2 8 4 1 3 2

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16591O G. trun (s) bleached 8 7 1 11 6 0 4 3 16591P G. trun (s) bleached 13 10 4 14 7 1 5 5 16591Q G. trun (s) bleached 16 11 7 16 7 4 5 5 16591R G. trun (s) bleached 13 11 5 14 6 2 5 5 16591S G. trun (s) bleached 11 8 6 11 5 2 4 4 16591T G. trun (s) bleached 18 12 8 17 7 3 5 5 16591U G. trun (s) bleached 3 2 1 3 2 0 1 1

16590B G. trun (d) unbleached 42 23 17 34 15 10 9 9 16590C G. trun (d) unbleached 61 32 25 48 20 14 11 12 16590D G. trun (d) unbleached 48 28 21 45 17 13 10 12

134 16590E G. trun (d) unbleached 49 30 23 44 16 12 10 13

16590F G. trun (d) unbleached 51 32 24 49 18 14 11 13 16590G G. trun (d) unbleached 53 30 22 46 19 13 11 12 16590H G. trun (d) unbleached 45 26 18 39 16 11 9 10 16590I G. trun (d) unbleached 37 21 16 30 12 9 7 8 16590K G. trun (d) bleached 8 6 5 12 5 2 3 3 16590L G. trun (d) bleached 16 10 6 17 6 2 4 4 16590M G. trun (d) bleached 14 9 6 14 6 3 4 4 16590N G. trun (d) bleached 15 9 6 17 6 4 4 3 16590O G. trun (d) bleached 27 17 12 27 9 7 6 6 16590P G. trun (d) bleached 1 2 0 5 2 1 2 1 16590Q G. trun (d) bleached 26 17 11 27 10 4 6 7 16590R G. trun (d) bleached 14 10 6 18 6 1 4 4

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16590S G. trun (d) bleached 9 6 4 10 4 1 3 2 16590T G. trun (d) bleached 14 9 6 15 6 3 4 4

16588A G. tumida unbleached 56 31 41 81 35 26 19 23 16588C G. tumida unbleached 33 18 13 27 13 8 6 7 16588D G. tumida unbleached 44 25 18 37 16 12 9 11 16588E G. tumida unbleached 38 19 14 26 12 7 6 7 16588F G. tumida unbleached 69 37 26 50 23 15 11 13 16588G G. tumida unbleached 41 23 18 37 14 10 7 9 16588H G. tumida unbleached 48 27 22 43 19 11 8 9 16588I G. tumida unbleached 58 29 20 39 17 11 9 10

135 16588J G. tumida unbleached 56 29 21 43 19 13 9 10

16588L G. tumida bleached 24 17 10 22 11 4 7 8 16588M G. tumida bleached 25 20 13 31 12 6 7 9 16588O G. tumida bleached 11 13 5 18 10 2 7 8 16588P G. tumida bleached 20 19 10 16 8 3 5 6 16588Q G. tumida bleached 11 13 4 28 12 2 8 8 16588R G. tumida bleached 24 17 9 26 12 3 7 8 16588S G. tumida bleached 9 12 4 28 11 2 7 7 16588T G. tumida bleached 8 6 3 9 5 2 3 3

1059A 1H-1, 50 cm 16595B G. trun (s) unbleached 39 23 20 36 13 11 8 10 16595C G. trun (s) unbleached 52 36 32 50 19 18 12 16

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16595D G. trun (s) unbleached 55 36 32 52 19 19 12 15 16595E G. trun (s) unbleached 54 34 29 51 21 17 13 15 16595H G. trun (s) unbleached 69 44 37 64 26 22 16 20 16595I G. trun (s) unbleached 40 25 23 41 15 15 10 12 16595J G. trun (s) unbleached 68 44 36 63 24 21 16 22 16595K G. trun (s) unbleached 52 34 29 47 17 16 10 14 16595L G. trun (s) bleached 17 11 7 15 6 3 4 5 16595M G. trun (s) bleached 17 11 8 16 6 1 4 5 16595N G. trun (s) bleached 9 7 3 11 5 0 3 3 16595O G. trun (s) bleached 15 11 7 17 6 1 4 5 16595P G. trun (s) bleached 3 4 1 10 5 0 3 3

136 16595Q G. trun (s) bleached 11 10 4 16 6 0 4 4

16595R G. trun (s) bleached 16 12 6 17 8 0 5 5 16595S G. trun (s) bleached 16 13 9 18 7 2 4 6 16595T G. trun (s) bleached 14 12 5 19 8 0 5 5 16595U G. trun (s) bleached 17 12 7 18 7 1 4 5

1059A 1H-1, 54 cm 16597A P. obliq unbleached 33 23 18 30 14 11 8 10 16597B P. obliq unbleached 34 19 15 24 11 7 6 8 16597C P. obliq unbleached 47 28 24 39 17 13 10 13 16597D P. obliq unbleached 36 21 17 29 10 8 6 9 16597E P. obliq unbleached 28 17 14 25 11 8 6 7 16597F P. obliq unbleached 41 23 19 31 12 10 8 10

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16597G P. obliq unbleached 33 20 16 26 11 8 6 8 16597H P. obliq unbleached 26 16 13 22 10 8 6 7 16597I P. obliq unbleached 33 20 17 26 12 7 8 8 16597J P. obliq unbleached 26 16 13 21 9 5 5 7 16597K P. obliq bleached 10 7 3 9 5 1 3 3 16597L P. obliq bleached 11 7 5 9 5 2 3 3 16597N P. obliq bleached 7 7 3 12 6 0 4 4 16597O P. obliq bleached 9 6 3 9 5 1 3 3 16597P P. obliq bleached 10 7 4 7 4 2 3 3 16597Q P. obliq bleached 13 9 6 11 6 1 4 4 16597R P. obliq bleached 10 7 3 9 5 2 3 3

137 16597S P. obliq bleached 0 0 0 3 1 0 1 1

16599A G. trun (s) unbleached 32 18 12 25 10 8 6 7 16599B G. trun (s) unbleached 60 31 25 44 19 14 11 12 16599C G. trun (s) unbleached 51 28 21 38 16 12 10 11 16599D G. trun (s) unbleached 54 33 27 48 19 16 11 14 16599F G. trun (s) unbleached 56 32 25 45 20 14 11 14 16599H G. trun (s) unbleached 41 28 22 36 15 12 10 12 16599I G. trun (s) unbleached 38 25 21 38 14 12 8 11 16599J G. trun (s) unbleached 41 25 20 36 14 11 8 10 16599K G. trun (s) bleached 10 8 10 24 9 0 5 4 16599L G. trun (s) bleached 5 5 5 19 7 0 4 4 16599M G. trun (s) bleached 11 8 6 15 6 0 3 3

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16599N G. trun (s) bleached 18 12 12 25 9 3 6 7 16599O G. trun (s) bleached 11 8 7 18 7 0 4 3 16599P G. trun (s) bleached 7 7 3 12 5 0 3 2 16599Q G. trun (s) bleached 13 9 8 20 7 0 3 3 16599R G. trun (s) bleached 8 6 7 18 7 0 3 3 16599S G. trun (s) bleached 8 8 4 16 5 0 3 3 16599T G. trun (s) bleached 8 6 7 18 7 0 4 3

16598A G. trun (d) unbleached 32 20 18 34 15 9 9 10 16598B G. trun (d) unbleached 44 25 20 36 16 10 10 11 16598C G. trun (d) unbleached 55 27 22 39 17 10 10 11

138 16598D G. trun (d) unbleached 40 20 16 29 13 8 8 8

16598F G. trun (d) unbleached 39 25 23 45 20 12 12 13 16598G G. trun (d) unbleached 64 34 28 48 21 13 12 13 16598H G. trun (d) unbleached 41 22 20 35 13 8 7 9 16598I G. trun (d) unbleached 46 29 24 40 17 11 11 13 16598J G. trun (d) bleached 30 19 13 28 11 8 7 8 16598K G. trun (d) bleached 17 12 8 19 7 1 4 4 16598M G. trun (d) bleached 28 16 11 26 10 6 7 7 16598N G. trun (d) bleached 25 15 10 22 10 7 6 6 16598O G. trun (d) bleached 26 16 11 24 10 7 6 7 16598P G. trun (d) bleached 17 10 7 15 7 3 4 4 16598Q G. trun (d) bleached 8 4 3 7 3 1 2 2

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 1062B, 1H-1, 62 cm 16611A G. trun (s) unbleached 22 12 10 19 6 5 3 4 16611B G. trun (s) unbleached 20 14 12 25 7 7 4 6 16611C G. trun (s) unbleached 17 10 7 15 6 3 4 4 16611D G. trun (s) unbleached 22 12 8 18 7 5 4 4 16611F G. trun (s) unbleached 20 12 9 18 7 5 4 5 16611G G. trun (s) unbleached 24 16 13 27 10 6 6 7 16611H G. trun (s) unbleached 25 16 12 24 10 7 6 6 16611I G. trun (s) unbleached 37 22 17 34 13 9 8 9 16611J G. trun (s) unbleached 17 10 8 17 7 3 4 4 16611K G. trun (s) bleached 2 2 1 4 2 0 1 1

139 16611L G. trun (s) bleached 3 2 1 3 1 0 1 1

16611M G. trun (s) bleached 3 3 1 4 2 0 1 1 16611T G. trun (s) bleached 6 6 2 8 4 0 2 2

KNR140 JPC-37, 150 cm 16631A P. obliq unbleached 37 28 24 29 14 10 9 12 16631B P. obliq unbleached 21 15 12 20 9 6 5 6 16631C P. obliq unbleached 21 13 10 18 8 5 5 5 16631D P. obliq unbleached 28 19 16 23 11 8 7 8 16631G P. obliq unbleached 30 20 15 26 11 8 6 7 16631H P. obliq unbleached 28 17 13 24 11 7 6 7 16631I P. obliq unbleached 21 15 12 20 9 7 6 6 16631J P. obliq unbleached 32 19 15 26 12 8 7 7

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16631K P. obliq bleached 14 8 5 11 5 3 3 3 16631M P. obliq bleached 14 9 5 11 5 0 3 3 16631O P. obliq bleached 11 6 4 8 4 2 2 2 16631P P. obliq bleached 10 7 4 10 5 0 3 3 16631Q P. obliq bleached 9 6 3 8 4 1 3 2 16631R P. obliq bleached 3 3 1 6 3 0 2 2 16631S P. obliq bleached 14 9 5 12 6 1 4 4 16631T P. obliq bleached 2 2 1 4 2 0 1 1 16631U P. obliq bleached 11 11 9 10 6 4 4 6

16632A G. trun (s) unbleached 36 23 19 37 15 12 9 10

140 16632B G. trun (s) unbleached 27 16 11 23 10 7 6 6

16632C G. trun (s) unbleached 38 24 19 36 13 11 8 9 16632D G. trun (s) unbleached 26 17 13 25 9 7 5 6 16632E G. trun (s) unbleached 38 24 20 38 14 12 8 10 16632F G. trun (s) unbleached 34 23 17 34 12 10 7 9 16632G G. trun (s) unbleached 35 20 14 30 13 9 8 8 16632H G. trun (s) unbleached 35 23 20 32 12 10 8 10 16632I G. trun (s) unbleached 33 21 16 32 13 10 8 9 16632J G. trun (s) unbleached 33 20 14 29 12 9 7 8 16632K G. trun (s) bleached 9 5 4 9 4 1 3 3 16632L G. trun (s) bleached 11 6 5 11 5 1 3 3 16632M G. trun (s) bleached 5 3 4 10 4 0 3 3 16632N G. trun (s) bleached 10 7 5 14 6 0 3 3

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16632O G. trun (s) bleached 13 8 8 18 7 1 4 5 16632P G. trun (s) bleached 7 5 6 14 6 0 3 3 16632R G. trun (s) bleached 7 4 5 13 6 0 4 3 16632S G. trun (s) bleached 5 3 3 9 4 0 3 2 16632T G. trun (s) bleached 5 3 2 6 3 0 2 1

KNR140 JPC-37, 1112 cm 16636B G. trun (d) unbleached 39 24 17 44 14 10 9 10 16636C G. trun (d) unbleached 36 21 13 31 13 9 8 9 16636E G. trun (d) unbleached 38 23 15 40 14 10 9 10 16636F G. trun (d) unbleached 47 30 19 34 21 14 14 14

141 16636G G. trun (d) unbleached 56 39 27 56 28 21 19 24

16636I G. trun (d) bleached 14 9 6 14 6 4 4 4 16636J G. trun (d) bleached 13 8 5 12 5 2 3 3 16636K G. trun (d) bleached 13 9 5 12 5 2 3 4 16636L G. trun (d) bleached 20 13 8 20 7 1 5 5 16636M G. trun (d) bleached 6 7 2 15 6 1 4 4 16636N G. trun (d) bleached 30 17 10 26 9 3 6 7 16636O G. trun (d) bleached 23 18 10 24 10 1 6 7 16636P G. trun (d) bleached 4 6 2 10 4 1 3 2 16636Q G. trun (d) bleached 18 14 8 21 7 1 5 6

1056B, 5H-7, 44 cm 16640B P. obliq unbleached 32 19 8 27 12 8 7 8

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16640C P. obliq unbleached 45 27 10 36 17 11 10 11 16640D P. obliq unbleached 35 23 11 32 14 10 8 10 16640E P. obliq unbleached 9 7 2 12 4 2 3 2 16640F P. obliq unbleached 36 23 11 33 10 10 7 9 16640G P. obliq unbleached 38 22 8 32 14 9 8 8 16640H P. obliq unbleached 36 23 8 30 14 9 8 9 16640I P. obliq unbleached 32 19 6 25 12 7 7 7 16640J P. obliq unbleached 30 19 8 28 13 9 8 8 16640K P. obliq bleached 9 8 2 13 7 0 4 3 16640M P. obliq bleached 15 9 3 11 6 0 3 3 16640N P. obliq bleached 19 11 3 15 8 0 5 4

142 16640Q P. obliq bleached 18 10 3 13 7 2 4 4

16641A G. trun (d) unbleached 24 18 6 36 15 9 9 8 16641B G. trun (d) unbleached 22 14 5 26 12 7 7 7 16641D G. trun (d) unbleached 34 20 6 34 15 8 9 8 16641F G. trun (d) unbleached 34 21 7 31 15 8 9 8 16641G G. trun (d) unbleached 38 22 7 33 17 9 10 9 16641H G. trun (d) unbleached 28 18 6 28 14 7 8 7 16641I G. trun (d) unbleached 11 9 4 17 8 6 5 5 16641J G. trun (d) unbleached 21 13 5 21 11 6 7 6 16641K G. trun (d) bleached 11 7 2 11 5 2 3 3 16641L G. trun (d) bleached 16 12 4 18 7 6 5 5 16641M G. trun (d) bleached 17 11 4 15 7 4 5 4

Table A4 Continued

[Asp] [Glu] [Ser] [Ala] [Val] [Phe] [Ile] [Leu] UAL Speciesa Pretreatment pmol pmol pmol pmol pmol pmol pmol pmol 16641N G. trun (d) bleached 16 11 3 16 7 4 4 4 16641O G. trun (d) bleached 18 11 3 18 8 4 5 5 16641P G. trun (d) bleached 15 10 3 16 6 5 4 4 16641Q G. trun (d) bleached 16 12 4 19 8 5 5 5 16641R G. trun (d) bleached 17 11 4 18 8 2 5 5 16641S G. trun (d) bleached 6 5 2 8 4 1 3 2

a P. obliq = Pulleniatina obliquiloculata; G. trun (s) = Globorotalia truncatulinoides (sinsitral); G. trun (d) = Globorotalia truncatulinoides (dextral); G. tumida = Globorotalia tumida

143

Table A5. Average aspartic acid (Asp) and glutamic acid (Glu) D/L values for both pretreatments, including the standard deviation of the subsamples. Subsample values are in Table A1.

Mean Asp D/L Mean Glu D/L Interval Age b UAL Site a Species (cm) (ka) Unbleached Bleached Unbleached Bleached

Holocene Sites 16347 1056D 62 4.82 ± 0.140 P. obliq 0.111 ± 0.011 0.129 ± 0.004 0.053 ± 0.011 0.064 ± 0.005 16348 1056D 64 4.82 ± 0.120 P. obliq 0.122 ± 0.004 0.134 ± 0.005 0.056 ± 0.005 0.063 ±0.005 16581 1056D 70 ---- P. obliq 0.126 ± 0.010 0.123 ± 0.010 0.059 ± 0.008 0.057 ± 0.007

144 16352 1056D 64 4.82 ± 0.120 G. trun (s) 0.143 ± 0.011 0.123 ± 0.008 0.060 ± 0.007 0.054 ± 0.007

16583 1056D 70 5.00 ± 0.130 G. trun (s) 0.144 ± 0.009 0.129 ± 0.003 0.061 ± 0.008 0.058 ± 0.003 16346 1056D 64 4.82 ± 0.120 G. tum 0.125 ± 0.007 0.143 ± 0.011 0.053 ± 0.005 0.100 ± 0.026 16576 1056D 68 ---- G. tum 0.139 ± 0.014 0.125 ± 0.009 0.061 ± 0.016 0.054 ± 0.007 16589 1059A 44 5.04 ± 0.090 P. obliq 0.125 ± 0.006 0.126 ± 0.004 0.060 ± 0.010 0.062 ± 0.003 16597 1059A 54 5.42 ± 0.100 P. obliq 0.129 ± 0.009 0.125 ± 0.008 0.060 ± 0.011 0.062 ± 0.008 16591 1059A 44 5.04 ± 0.090 G. trun (s) 0.134 ± 0.008 0.130 ± 0.008 0.059 ± 0.006 0.060 ± 0.004 16590 1059A 44 5.04 ± 0.090 G. trun (d) 0.131 ± 0.004 0.134 ± 0.005 0.056 ± 0.005 0.056 ± 0.003 16595 1059A 50 ---- G. trun (s) 0.135 ± 0.020 0.133 ± 0.006 0.058 ± 0.007 0.064 ± 0.004

Table A5 Continued

Mean Asp D/L Mean Glu D/L Interval Age b UAL Site a Species (cm) (ka) Unbleached Bleached Unbleached Bleached 16599 1059A 54 5.42 ± 0.100 G. trun (s) 0.147 ± 0.008 0.130 ± 0.006 0.061 ± 0.005 0.063 ± 0.004 16598 1059A 54 5.42 ± 0.100 G. trun (d) 0.129 ± 0.007 0.149 ± 0.008 0.052 ± 0.005 0.060 ± 0.003 16588 1059A 44 5.04 ± 0.090 G. tum 0.152 ± 0.013 0.131 ± 0.006 0.069 ± 0.011 0.054 ± 0.012 6.68 ± 0.150 16611 1062B 62 G. trun (s) 0.155 ± 0.013 0.133 ± 0.009 0.060 ± 0.006 0.057 ± 0.004 7.23 ± 0.120

Down-core Sites 16631 JPC-37 150 10.5 P. obliq 0.178 ± 0.014 0.181 ± 0.013 0.072 ± 0.012 0.080 ± 0.012

145 16632 JPC-37 150 10.5 G. trun (s) 0.206 ± 0.011 0.196 ± 0.011 0.080 ± 0.006 0.081 ± 0.003

0.266 ± 0.014 0.080 ± 0.006 17577 JPC-37 238 15.4 G. trun (s+d) ------0.261 ± 0.007 0.082 ± 0.008

0.251 ± 0.020 0.086 ± 0.006 17576 JPC-37 666 30.8 G. trun (s+d) ------0.277 ± 0.014 0.099 ± 0.005 16636 JPC-37 1112 51.5 G. trun (d) 0.286 ± 0.006 0.284 ± 0.024 0.098 ± 0.014 0.098 ± 0.015 16637 JPC-37 1615 86.4 G. trun (s+d) 0.354 ± 0.027 ---- 0.141 ± 0.013 ---- 16640 1056B 44 410 P. obliq 0.432 ± 0.018 0.437 ± 0.018 0.225 ± 0.014 0.239 ± 0.008 16639 1056B 44 410 G. tum 0.479 ± 0.026 ---- 0.261 ± 0.025 ---- 16641 1056B 44 410 G. trun (d) 0.463 ± 0.016 0.464 ± 0.015 0.249 ± 0.015 0.244 ± 0.013

a Ages for Sites 1056D, 1059A, and 1062B were determined from low precision 14C analyses. Ages for Sites JPC-37 (Hagen and Keigwin 2002) and 1056 (Billups et al. 2004) were determined from δ18O stratigraphy. b P. obliq = Pulleniatina obliquiloculata; G. trun (s) = Globorotalia truncatulinoides (sinsitral); G. trun (d) = Globorotalia truncatulinoides (dextral); G. tum = Globorotalia tumida

146

Table A6. Sample variability in Holocene and down-core sites represented as the coefficient of variation (CV).

Improvement Interval CV (%) Asp CV (%) Glu a Site Species w/ Bleaching? (cm) Unbl Bl Unbl Bl Asp Glu Holocene Sites 1056D 62 P. obliq 9.9 3.0 20.0 8.0 yes yes 1056D 64 P. obliq 3.6 3.9 8.7 7.7 no yes 1056D 70 P. obliq 7.6 8.0 13.5 12.6 no yes 1056D 64 G. trun (s) 7.9 6.7 11.0 13.1 yes no 1056D 70 G. trun (s) 6.2 2.3 12.2 5.9 yes yes 1056D 64 G. tum 5.8 7.8 9.9 25.7 no no 1056D 68 G. tum 9.9 7.1 26.7 12.9 yes yes 1059A 44 P. obliq 5.1 3.2 16.0 5.1 yes yes 1059A 54 P. obliq 6.7 6.6 17.9 12.8 yes yes 1059A 44 G. trun (s) 5.6 6.1 10.9 6.3 no yes 1059A 44 G. trun (d) 2.7 3.7 9.3 4.9 no yes 1059A 50 G. trun (s) 15.1 4.3 13.0 5.6 yes yes 1059A 54 G. trun (s) 5.2 4.7 8.0 6.2 yes yes 1059A 54 G. trun (d) 5.3 5.4 10.4 4.5 no yes 1059A 44 G. tum 8.5 4.3 15.3 22.1 yes no 1062B 62 G. trun (s) 8.3 6.9 11.7 7.2 yes yes

Down-Core Sites JPC-37 150 P. obliq 7.6 7.2 16.6 14.5 yes yes JPC-37 150 G. trun (s) 5.4 5.5 7.0 4.1 no yes JPC-37 1112 G. trun (d) 2.1 8.4 13.8 14.9 no no 1056B 44 P. obliq 4.2 4.2 6.1 3.3 no yes 1056B 44 G. trun (d) 3.4 3.2 6.2 5.4 yes yes a An improvement with bleaching would be apparent in a lower CV for the bleached samples.

147