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Green River formation stromatolites as a paleoclimate indicator: an investigation of the early Eocene climatic optimum through mass spectrometry, micro-X-ray fluorescence spectroscopy, and petrography
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Green River formation stromatolites as a paleoclimate indicator: an investigation of the early Eocene climatic optimum through mass spectrometry, micro-X-ray fluorescence spectroscopy, and petrography
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Content
GREEN RIVER FORMATION STROMATOLITES AS A PALEOCLIMATE INDICATOR:
AN INVESTIGATION OF THE EARLY EOCENE CLIMATIC OPTIMUM THROUGH
MASS SPECTROMETRY, MICRO-X-RAY FLUORESCENCE SPECTROSCOPY, AND
PETROGRAPHY
by
Taleen Mahseredjian
A Thesis Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(Geological Sciences)
May 2019
Copyright 2019 Taleen Mahseredjian
1
ACKNOWLEDGMENTS
I would like to begin by expressing my sincere gratitude and appreciation for my advisor,
Dr. Frank Corsetti. It is with his guidance, dedication, and patience, that this project came to life
and continued to expand despite the various false starts and bumps in the road. He has been an
incredible mentor for the past three years, and has generously offered his support and wisdom,
both as an advisor and as a professor. Simply put, Frank is the reason I am the geobiologist-in-
training I am today. Without him, not only would this project be impossible, but I would not be in
the field of Earth Sciences. Thank you for introducing me to geobiology and for saving me from a
sad life of neuroscience.
I would like to thank Aaron Celestian for his guidance and generosity in allowing me to
use his lab equipment over the past year. Thank you for always being willing to experiment and
tinker, and for putting the time and effort into figuring out the head-scratching mechanics of how
to analyze a finicky stromatolite in a mineralogy lab. It has been an inexplicable joy working in
the Natural History Museum Mineral Sciences Laboratory.
I would also like to express my immense gratitude to the USC Earth Sciences department.
Thank you to my undergraduate cohort, Emilie Skoog, Patrick Cho, Yi Hou, Pete Wynn, Amanda
Semler, Kimi Morales, Leslie Insixiengmay, Ariel Borsook, Nathan Kemnitz, Roxanne Lai, and
many others - I am grateful for the friendship they have shown me throughout my time at USC.
Thank you to Dylan Wilmeth and Olivia Paradis for welcoming me and supporting me
during my time in the Corsetti Lab. Thank you to Carie Frantz for not only providing samples and
feedback, but also for being a role model throughout this project. Also, I would like to express my
thanks to Karen Young, Vardui Ter-Simonian, Cindy Waite, and John Yu, without whom I am
convinced the department could not function. Additional thanks to Nick Rollins, Ying Lin, and
Jun Shao for their help in analyzing samples.
I would like to thank my family, including my brother, parents, and grandmother for their
guidance, love, and support throughout my studies, both as an undergraduate and as a Master’s
student.
Finally, I would like to thank my thesis committee, Aaron Celestian, David Bottjer, Will
Berelson, and Frank Corsetti. Funding for this project was provided by the National Science
Foundation Earth-Life Transitions Grant.
2
TABLE OF CONTENTS
ACKNOWLEDGMENTS............................................................................................................ 1
LIST OF FIGURES....................................................................................................................... 3
LIST OF GRAPHS........................................................................................................................ 5
ABSTRACT................................................................................................................................... 6
INTRODUCTION......................................................................................................................... 8
BACKGROUND......................................................................................................................... 10
Early Eocene Climatic Optimum....................................................................................... 10
Geologic Setting: Green River Formation......................................................................... 13
Laney Member: The LaClede Bed...................................................................................... 15
Role of Green River Stromatolites in EECO Paleoclimate Reconstruction....................... 18
MATERIALS AND METHODS................................................................................................ 20
Stromatolite Samples......................................................................................................... 20
Microdrilling..................................................................................................................... 22
Isotope and Gas Concentration Analyzer.......................................................................... 22
Isotope Ratio Mass Spectrometry: Vertical Isotopic Variability........................................ 23
Isotope Ratio Mass Spectrometry: Horizontal Isotopic Variability................................... 25
Micro-XRF Spectroscopy.................................................................................................. 28
Petrographic Analyses: Photomosaics.............................................................................. 38
Petrographic Analyses: Assessment of Lateral Continuity................................................ 45
RESULTS..................................................................................................................................... 46
Isotopic Variability............................................................................................................ 46
Micro-XRF Spectroscopy.................................................................................................. 53
Petrography....................................................................................................................... 66
DISCUSSION...............................................................................................................................72
Assessment of Intra-Lamina Variability............................................................................ 72
Isotopes, Elemental Analyses, and Lake Volume Change.................................................. 74
Lake Level Cycles and Anoxia............................................................................................76
Transition from Closed-Basin to Open-Basin Lake............................................................82
CONCLUSIONS......................................................................................................................... 88
REFERENCES............................................................................................................................ 90
APPENDIX................................................................................................................................ 101
3
LIST OF FIGURES
FIGURE 1: Cenozoic Temperature and Atmospheric CO
2
Trends.............................................. 12
FIGURE 2: Geologic Map of the Green River Formation........................................................... 14
FIGURE 3: Field Image of the LaClede Bed…............................................................................ 16
FIGURE 4: Stratigraphic Section of the Green River Basin........................................................ 17
FIGURE 5: Simple Stromatolite Deposition Model..................................................................... 17
FIGURE 6: Stromatolite Samples ................................................................................................ 21
FIGURE 7: Large Stromatolite Hand Sample with All Microdrill Holes.................................... 24
FIGURE 8: Microdrill Holes Used for Lateral Variability Analysis............................................ 27
FIGURE 9: Six LaClede Billets Used for Micro-XRF Spectroscopy.......................................... 31
FIGURE 10: Aa Line Scans and Area Maps................................................................................ 32
FIGURE 11: Ab Line Scans and Area Maps................................................................................ 33
FIGURE 12: Ac Line Scans and Area Maps................................................................................ 34
FIGURE 13: Ad Line Scans and Area Maps................................................................................ 35
FIGURE 14: Ae Line Scans and Area Maps................................................................................ 36
FIGURE 15: Af Line Scans and Area Maps................................................................................. 37
FIGURE 16: Photomosaic of Aa.................................................................................................. 39
FIGURE 17: Photomosaic of Ab.................................................................................................. 40
FIGURE 18: Photomosaic of Ac.................................................................................................. 41
FIGURE 19: Photomosaic of Ad.................................................................................................. 42
FIGURE 20: Photomosaic of Ae.................................................................................................. 43
FIGURE 21: Photomosaic of Af................................................................................................... 44
FIGURE 22: Qualitative Elemental Heat Map of Billet Aa (Left)............................................... 54
FIGURE 23: Qualitative Elemental Heat Map of Billet Aa (Right)............................................. 55
FIGURE 24: Qualitative Elemental Heat Map of Billet Ab (Left)............................................... 56
FIGURE 25: Qualitative Elemental Heat Map of Billet Ab (Right)............................................ 57
FIGURE 26: Qualitative Elemental Heat Map of Billet Ac (Left)............................................... 58
FIGURE 27: Qualitative Elemental Heat Map of Billet Ac (Right)............................................. 59
FIGURE 28: Qualitative Elemental Heat Map of Billet Ad......................................................... 60
FIGURE 29: Qualitative Elemental Heat Map of Billet Ae (Left)............................................... 61
FIGURE 30: Qualitative Elemental Heat Map of Billet Ae (Right)............................................. 62
4
FIGURE 31: Qualitative Elemental Heat Map of Billet Af (Left)............................................... 63
FIGURE 32: Qualitative Elemental Heat Map of Billet Af (Right)............................................. 64
FIGURE 33: Light Microscopy Image of Lamina 1..................................................................... 68
FIGURE 34: Light Microscopy Image of Lamina 9..................................................................... 69
FIGURE 35: Light Microscopy Image of Lamina 10................................................................... 70
FIGURE 36: Light Microscopy Image of Lamina 14................................................................... 71
FIGURE 37: Lake Level and Anoxia Interpretations................................................................... 81
FIGURE 38: Large LaClede Stromatolite Microfacies................................................................ 84
5
LIST OF GRAPHS
GRAPH 1: d
18
O Variability of Large LaClede Stromatolite........................................................ 48
GRAPH 2: d
13
C Variability of Large LaClede Stromatolite......................................................... 49
GRAPH 3: d
13
C Variability Comparison...................................................................................... 50
GRAPH 4: Large LaClede Stromatolite Carbonate Content........................................................ 51
GRAPH 5: Intra-Lamina Variability of Lamina 1........................................................................ 52
GRAPH 6: Intra-Lamina Variability of Lamina 9........................................................................ 52
GRAPH 7: Intra-Lamina Variability of Lamina 10...................................................................... 52
GRAPH 8: Intra-Lamina Variability of Lamina 14...................................................................... 52
GRAPH 9: Relative Abundance of Magnesium Normalized to Calcium in Aa........................... 65
GRAPH 10: Relative Abundance of Iron Normalized to Calcium in Aa..................................... 65
GRAPH 11: Relative Abundance of Strontium Normalized to Calcium in Aa............................ 65
GRAPH 12: Overall Covariance of d
13
C and d
18
O in Large LaClede Stromatolite...................... 75
GRAPH 13: Relative Abundance of Iron and Magnesium as Lake Level Indicators.................. 78
GRAPH 14: Cross Plot of Sulfur and Iron................................................................................... 79
GRAPH 15: Cross Plot of Sulfur and Magnesium....................................................................... 79
GRAPH 16: Cross Plot of Titanium and Magnesium................................................................... 80
GRAPH 17: Cross Plot of Titanium and Iron............................................................................... 80
GRAPH 18: Covariance of d
13
C and d
18
O in microfacies 1.......................................................... 85
GRAPH 19: Covariance of d
13
C and d
18
O in microfacies 2.......................................................... 85
GRAPH 20: Covariance of d
13
C and d
18
O in microfacies 3.......................................................... 86
GRAPH 21: Covariance of d
13
C and d
18
O in microfacies 4.......................................................... 86
GRAPH 22: Covariance of d
13
C and d
18
O in microfacies 5.......................................................... 87
6
ABSTRACT
The Early Eocene Climatic Optimum (EECO, 52-50 Ma), a global hothouse climate
associated with high temperatures and high CO
2
levels, marked the longest sustained warming
period of the Cenozoic Era. The EECO is well recorded in the Eocene Green River Formation, a
sedimentary formation deposited in a closed-basin lake system. The Green River closed-basin lake
system, especially Lake Gosiute, had a highly dynamic lake volume and dramatically variable
shoreline levels, because of its sensitivity to evaporation and precipitation. This study uses
stromatolites from the LaClede Bed of the Green River Formation to create a fine-scale record of
terrestrial paleoenvironmental and paleoclimate changes during the EECO. The stromatolites of
the LaClede Bed were deposited in Lake Gosiute, and track the fluctuations of lake volume and
shoreline levels through its depositional history.
In a closed-basin lake where water enters solely through ground water, rivers, and
precipitation, periods of lake filling and evaporation are recorded in the chemistry of lake water,
which in turn can be recorded within the carbonate of stromatolites. Changes in d
13
C, d
18
O, and
certain elemental abundances recorded in stromatolites are likely related to periods of precipitation
and evaporation, which can be used to estimate shifting lake shore levels. First, light microscopy
and petrographic methods were used to analyze the carbonate fabrics of the distinct stromatolite
laminae to better characterize the environmental conditions in which they were deposited. Then,
isotopic perturbations and elemental abundances were measured to assess climate change during
the deposition of the stromatolites. In particular, this study introduces a novel application of micro-
XRF spectroscopy to stromatolite-based paleoclimate reconstruction, where elemental abundances
were analyzed via micro-XRF spectroscopy on the micrometer scale, which allows for stromatolite
laminae analyses on a scale previously not presented. Thirteen distinct elemental abundances (Na,
7
Mg, Al, Si, P, S, Cl, K, Ca, Ti, Mn, Fe, and Sr) were measured as vertical transects through the
stromatolite laminae, and magnesium (used as a conservative lake level indicator), iron (used as a
redox-sensitive biologic indicator), and strontium (a redox-insensitive elemental marker) are
highlighted. Using these three lines of evidence, the LaClede stromatolites record a complex
history of lake filling and evaporation during the EECO, rather than a simple transgressive system
as previously hypothesized.
8
INTRODUCTION
Climate change is the most pressing issue impacting the future of the planet and mankind
(Manabe and Wetherald, 1967; Keeling et al., 1976). However, current warming trends of this
century are not the first time the Earth has undergone such significant sustained increases in
temperature and atmospheric CO
2
. Our understanding of previous warming events is imperative
to understanding the implications of rapidly increasing atmospheric carbon dioxide and
temperature levels today. By studying prolonged warming periods in the geologic past and
building a robust understanding of how Earth systems responded, we will be better equipped to
understand the environmental implications on similar settings in the future. The Early Eocene
Climatic Optimum (EECO, ca. 52 – 50 Ma) was one such period of sustained high temperatures
and high atmospheric CO
2
levels. The goal of this study is to understand the variability and climate
trends of the EECO through geochemical analyses of Green River Formation stromatolites, which
were deposited during this hothouse climate. The stromatolitic layers deposited during the EECO
provide a tangible, geologic analog for projected climate scenarios. By understanding the
intricacies of previous warming events such as EECO, perhaps we can apply proxies from previous
paleoclimates to better comprehend future climate projections of a similar high temperature, high
CO
2
environment.
Stromatolites are layered, laminated, sedimentary structures that are formed by the trapping
and cementation of grains (Kalkowsky, 1908). These sedimentary features can form can form
biogenically, as a result of sediment trapping by cyanobacteria and larger microbial mat
communities (Grotzinger and Knoll, 1990), or they can form abiogenically, where banded laminae
form and lithify through processes devoid of biologic input (such as chemical precipitation).
Although the composition of lithified stromatolite laminae may vary in morphology, bulk
9
elemental composition, and isotopic signature, all three characteristics provide integral
information about the stromatolite’s depositional history and environment. Understanding the
chemical and physical makeup of stromatolites allows us to unravel the story of its formation, as
well as the evolution of its surrounding environmental conditions throughout its deposition.
Isotopically, carbon and oxygen (d
13
C and d
18
O) provide information regarding the Earth’s
previous atmosphere and climate, and can be used to reconstruct ancient paleoclimates.
Because stromatolites are laminated features, they have the potential to record a time-series
of lake history during their deposition; thus, Green River Formation stromatolites can potentially
address the state of the climate during the EECO. Here we use petrography, d
18
O, d
13
C, and
elemental analyses to assess the geochemical history of the lake and by extension, the climate
during the EECO. It is well known that, in closed basin lakes, changes in d
18
O reflect cycles of
evaporation and filling (e.g., Talbot, 1990), and if conservative, certain elemental abundances also
scale with lake volume (Berelson et al., 2011; Frantz et al., 2014). For the first time, traditional
isotopic measurements are combined with a novel application of micro-XRF elemental analyses
at very high resolution in a stromatolite to assess changes in lake chemistry and climate.
10
BACKGROUND
The Early Eocene Climatic Optimum
The Eocene was the longest warm climate period of the Cenozoic Era. It reached a thermal
climax during the Early Eocene Climatic Optimum (EECO, ca. 52–50 Ma) and culminated with
the development of Antarctic ice sheets at ca. 34 Ma (Zachos et al., 2001; Zachos et al. 2008;
Beerling and Royer, 2011; Lowenstein and Demicco, 2006, etc.). Evidence for the extreme climate
of the Eocene is derived from various proxies as well as geochemical carbon cycle models, and
support the existence of a warm, arid, stable climate in the early Cenozoic Era. The lowest average
atmospheric CO
2
concentrations during the early Eocene found cited is ca. 280 ppm, and the
highest concentration is ca. 1870 ppm (Royer et al., 2014; Jagniecki et al., 2015). Although
estimates vary, previous proxy studies have agreed on estimated EECO atmospheric CO
2
levels of
greater than 1000ppm (Zachos et al., 2001; Zachos et al., 2008; Yapp, 2004; Beerling and Royer,
2001; Frantz et al., 2014), averaging ca. 1125ppm (Royer, 2014; Lowenstein and Demicco, 2006;
Beerling and Royer, 2011; Jagniecki et al., 2015). Atmospheric CO
2
levels for the early Eocene
(ca. 56–49 Ma, spanning more than the EECO) have been estimated in a variety of ways, including
paleosol proxies (Cerling, 1992; Sinha and Stott, 1994; Ekart et al., 1999; Royer et al., 2001; Yapp,
2004; Breecker et al., 2010; Hyland and Sheldon, 2013; Hyland et al., 2013); leaf stomata index
proxies (McElwain, 1998; Retallack, 2001; Royer, 2003; Greenwood et al., 2003; Beerling et al.,
2009; Smith et al., 2010; Franks et al., 2014); paleoflora fossils (Fletcher et al., 2008); marine
boron isotopic records (Pearson and Palmer, 2000); and sodium carbonate mineral proxies
including trona, nahcolite, and natron (Lowenstein and Demicco, 2006). With the exception of
nahcolite, all of these estimates are indirect proxy measurements that depend on various
calibrations, and are constantly updated. For example, updates of both paleosol proxies (Hyland
11
and Sheldon, 2013; Hyland et al., 2013) and leaf stomata index proxies (Greenwood et al., 2003;
Smith et al., 2010; Franks et al., 2014), have lowered atmospheric CO
2
estimates for this time
period, decreasing the previous upper boundary from ~3500 ppm to ~1800 ppm (Jagniecki et al.,
2015). Temperature of the early Eocene has been estimated through paleofloral proxies and
clumped isotope paleothermometry. Paleofloral examinations of leaf margins and leaf morphology
in the Green River Basin estimate mean annual temperatures to be 23 ± 4˚ C at 51.5 Ma (Wilf,
2000). Clumped isotope paleothermometry data from Green River stromatolites from the Rife Bed
found lake water temperature of Lake Gosiute to fluctuate between 25.6˚C and 38.3˚C (Frantz et
al., 2014) just prior to LaClede deposition. The wide range in clumped isotope paleothermometry
values is based on the type of carbonate fabric deposited (the process of sparry laminae deposition
favored colder lake water temperatures in this case, whereas micritic laminae deposition favored
warmer water temperatures). Lake water temperatures of present-day lakes in the same region
fluctuate between 5˚C and 20˚C seasonally (Utah State Parks Almanac). While the Cenozoic is
characterized by highly variable climate, the EECO is a critical time period due to its similarities
to future environmental projections. Paleoclimatic studies on the EECO act as a benchmark for
research on future climate change, and studying this time period can help inform our understanding
of future global warming trends. Figure 1 presents a schematic for atmospheric carbon dioxide
levels and temperature trends during the EECO.
12
Figure 1: Estimated Cenozoic temperature and atmospheric CO
2
trends from Frantz et al., 2014
modified from Zachos et al., 2008 and Beerling and Royer, 2011. The EECO (ca. 52 – 50 Ma) is
denoted by the bolded black line in the olive Green River Formation box.
13
Geologic Setting: Green River Formation
The Eocene Green River Formation is a succession of lacustrine strata deposited in several
intermontane structural basins spanning the southwestern corner of Wyoming, as well as smaller
portions of northeastern Utah, northwestern Colorado, and southeastern Idaho. The intermontane
basins include the Green River Basin, Washakie Basin, Sand Wash Basin, Bridger Basin, Uinta
Basin, and Piceance Basin (Figure 2). The Green River Formation consists mainly of shales,
mudstones, sandstones, limestones, evaporites, and interbedded tuffs, and can be divided into the
bottommost Tipton Member, middle Wilkins Peak Member, and uppermost Laney Member
(Bradley 1929; Roehler 1973; Roehler 1991a). High resolution dating of the Green River
Formation has been accomplished through
40
Ar/
39
Ar chronostratigraphy of the interbedded tuff
layers in the Green River Formation (Carroll et al., 2001; Smith et al., 2003; Smith et al., 2006;
Pietras et al., 2003). The Green River is recognized as a lagerstätte, due to its exceptional
preservation of vertebrates (such as fish, birds, crocodiles, etc.), which are well preserved in the
varve layers (e.g. Grande, 1985; 1994; 1999). Aside from its unique geology and paleontology,
the Green River Formation is of economic importance due to its large abundance oil shale and
evaporite deposits (e.g. Bradley 1929).
The Green River Formation records the depositional history of an extensive paleolake
system, made up of sporadically interconnected closed-basin lakes (Frantz et al., 2014). These
closed-basin lakes respond dramatically to environmental and atmospheric changes. The high
degree of sensitive to precipitation and evaporation results in extremely dynamic lake shore levels
and lake volumes, making closed-basin lakes optimal systems to study climate change. More than
2000m of sediments accumulated in paleolake basins, and approximately 80% of these sediments
were carbonate (Awramik and Buchheim, 2015). Lake Gosiute of the Green River Basin is one
14
such closed-basin paleolake. Lake Gosiute is unique due to its broad stromatolitic layers that were
initially deposited at its shorelines. Stromatolites have been described in the Tipton Member (Rife
Bed) and Laney Member (LaClede Bed). This study analyzes a stromatolite from the LaClede Bed
of the Laney Member, and records ten thousand years of lacustrine sediment depositional history
overlapping with the EECO.
Figure 2: Geologic map of the greater Green River Basin modified from Murphy Jr. et al., 2014.
15
Laney Member: The LaClede Bed
The LaClede Bed is the lowermost unit of the Laney Member in the Washakie Basin
(Roehler et al., 1991a). Figure 4 depicts the stratigraphic range of the LaClede Bed, with the
Wilkins Peak-Lower LaClede transition occurring in the lower-middle Eocene. The LaClede Bed
is composed primarily of brown to black oil shale with some millimeter to centimeter-scale
sandstones, limestones, shales, siltstones, and tuffs. The LaClede Bed is laterally continuous, and
can be traced throughout the southern portion of the Green River Basin. It was deposited during
the transition between brackish/saline and freshwater lacustrine environments: The Lower
LaClede bed is dominated by brackish-to-saline alkaline lake sediments. Deposition was cyclic,
with stromatolites and other carbonated formed during an initial transgressive phase overlain by
oil shale representing the deepest phase, and culminating with a shallowing upward cycle
increasingly rich in carbonate, especially dolostones (Figure 5). In contrast, the Upper LaClede
bed is dominated by fresh-water lake sediments (Surdam and Stanley, 1979; Awramik and
Buchheim 2015; Roehler, 1973; Roehler 1991a; Roehler 1991b).
The LaClede Bed was deposited in Lake Gosiute, the largest of the Green River paleolakes.
Its deposition coincided with the warmest and wettest period of the Eocene. Lake salinity was
highest in the most basal part of the LaClede, but decreased at higher stratigraphic levels,
exhibiting a general freshening upward trend (Buchheim, 1994). From a paleontological
perspective, the LaClede is teeming with evidence of diverse Eocene life. In addition to the
exceptionally preserved vertebrate fauna, the LaClede also contains various mollusk, hexapod,
fish, and plant fragments (Grande, 1985; 1994; 1999). The LaClede bed is also known for its
stromatolitic layers, which were first described as “algal beds” in 1929 (Bradley, 1929).
16
Stromatolites from the LaClede Bed are well preserved, well laminated, and laterally continuous
on the kilometer scale (Awramik and Buchheim, 2014).
Figure 3: Field image of the LaClede Bed of the Green River Formation, from which our shoreline
stromatolite samples were collected. People in the bottom left/center for scale. Photo courtesy of
Dr. Frank Corsetti.
17
Figure 4: Facies diagram of the Green River Basin from Carroll, 2001. The Lower LaClede
(white) and Upper LaClede beds (dashed lines) exhibit a transition from a saline/brackish-
dominated environment to a freshwater-dominated environment.
Figure 5: Previous interpretations of stromatolite deposition suggest a simple monotonic model.
Deposition was cyclic, with stromatolites forming during an initial transgressive phase overlain by
oil shale representing the deepest phase, and culminating with a shallowing upward phase.
18
Role of Green River Stromatolites in EECO Paleoclimate Reconstruction
The stromatolites used in this study are from the lower LaClede Bed, and were deposited
during a period of filling in Lake Gosiute following extended periods of closure during deposition
of the underlying Wilkins Peak Member (Corsetti et al., 2013). Stromatolites from the LaClede
Bed are typically nearshore deposits, and their fine (millimeter to micrometer-scale) laminae
provide an exceptional opportunity to study environmental changes in the Green River Basin on a
highly-resolved time scale (Buchheim and Surdam, 1977; Roehler 1993; Frantz et al., 2014).
Additionally, the LaClede stromatolites are mainly carbonate, which means they provide a good
record of the geochemistry of the lake in which they were deposited. As a result, the LaClede
stromatolites are ideal for reconstructing the environment of Lake Gosuite during the EECO.
Despite lake volume cyclicity, the LaClede stromatolites were submerged and accreted
continuously, thus their laminae provide a continuous record of lake level change.
Mudcracks are presented beneath the LaClede stromatolites, and are overlain by
kerogenous laminated carbonate and dolomicrite. Due to the presence of mudcracks, it has been
suggested that the LaClede stromatolites were deposited upon a flooding surface at the base of the
deepening limb of the sedimentary cycles (Surdam and Stanley, 1979), as described above.
According to this model, stromatolites were accreted during the beginning of a filling period, and
thus would provide evidence for a lake level transgression. The transgressive nature of the
stromatolites can be tested via geochemical analysis of the stromatolites. Frantz (2013), on the
other hand, reported d18O, d13C, and low-resolution elemental data that suggested a more
complex lake filling scenario. Inspired by the results in Frantz (2013), the transgressive nature of
the stromatolites can be tested via higher resolution geochemical analysis of the same
stromatolites. This study will utilize d
13
C and d
18
O isotopes as well as conservative elemental
19
abundances (e.g. Mg) preserved in the stromatolite to track lake level volumes. In increase in d
13
C
and d
18
O in a closed-basin lake environment is indicative of evaporation, while a decrease in d
13
C
and d
18
O values is indicative of precipitation. Similarly, a smaller conservative elemental
abundance is indicative of lake filling (e.g. dilution) or an increase in lake volume, while a larger
abundance is indicative of evaporation, or a decrease in lake volume. The isotopic and elemental
methods act as complementing tool to track lake level change. Isotopic and elemental analyses
were conducted following microdrilling, and were supplemented with µXRF spectrometry.
Previous interpretations of the isotopic and elemental composition of LaClede stromatolites would
suggest that the d
13
C and d
18
O values and conservative elements would reflect a transgression,
since the stromatolites form at the base of a transgressive cycle, and thus should record
progressively lighter d
18
O values and lower conservative elemental abundances. This study
predicts that the monotonic lake filling model is oversimplified, and acts as the baseline to an
increasingly complex pattern of lake volume change.
20
MATERIALS AND METHODS
Stromatolite Samples
Two adjacent stromatolite samples from the Lower LaClede Bed were used for isotopic
and elemental analyses. The stromatolite samples were provided by Dr. Carie Frantz, and were
first introduced in her thesis (Frantz, 2013). The two samples were cut from the same stromatolite,
and are positioned similarly to two adjacent books on a bookshelf. The same laminae can be traced
throughout both samples, as they are laterally continuous. One sample is a 7cm x 12cm rectangular
block, and was used for isotopic analyses. The other sample was cut into six 2cm x 5cm billets,
thin sectioned, and was used for petrographic and µXRF analyses. The six billets are labelled Aa,
Ab, Ac, Ad, Ae, and Af, as shown in Figure 6. Laminae in all of the samples range from millimeter
scale to sub-micrometer scale. Laminae from the two sample sets can be correlated using the thin
chert band present in both sample sets as a reference frame, as marked with the blue dashed line
in Figure 6.
21
Figure 6: The two stromatolite samples used in this study. Sample 1 is a large 7cm x 12 cm block,
while sample 2 has been cut into six smaller 2cm x 5cm billets. The laminae throughout the two
samples are laterally continuous, and can be easily correlated via the distinct chert band designated
by the dashed blue line.
22
Microdrilling
The LaClede Bed stromatolite used in this study is characterized by micrometer- to
centimeter-scale banding patterns with different sedimentary microfabric compositions that reflect
deposition environment. Light and dark patterns that compose the laminae were drilled using a
1mm diamond dremel bit to produce carbonate powder for isotope ratio mass spectrometry.
Microdrilling was conducted carefully to ensure that only the intended lamina was being drilled,
avoiding any secondary infill or cementation. The depth of microdrilling was limited to a
maximum of 2 mm to prevent penetrating into other underlying fabrics considering the potential
three-dimensional variation beneath the surface of the stromatolite. After microdrilling, powder
was collected and deposited in low-nitrogen weigh paper. Each sample was labeled and stored in
a cool, dry environment out of direct sunlight. Powder samples were collected from 37 distinct
laminae (referred to herein as samples L1, L2,… L36, L37) throughout the stromatolite. Three to
ten holes were microdrilled per lamina, based on how easily drillable a lamina was (i.e. how
resistant a lamina was to microdrilling and powdering).
Isotope and Gas Concentration Analyzer
The original 37 composite microdrilled powder samples were massed and transferred into
glass Standard Labco Exetainer 12ml vials for future isotopic analyses. Each tube carried aliquots
of an average of 4.000 ± .05 mg carbonate powder. Sixteen tubes of standard (OPT calcite) were
also collected in preparation for analysis. A Mettler Toledo Antistatic Deionizer was used to
deionize the metal tools used to transfer carbonate powder between the low-nitrogen weigh paper
and the glass tubes. The de-ionizer played a substantial role in eliminating static attraction that
would otherwise alter recorded mass of the powdered stromatolite and the standard. Powder
23
samples were then evacuated and acidified in 80% phosphoric acid. Aliquots of these samples
were analyzed for bulk carbonate content and d
13
C on a Picarro G2131-i Analyzer.
Isotope Ratio Mass Spectrometry: Vertical Isotopic Variability
In addition to running the stromatolite powder on the Picarro Isotope and Gas
Concentration Analyzer to analyze d
13
C, we also ran the same powder on an isotope ratio mass
spectrometer (IRMS) to obtain d
18
O values for the stromatolite laminae. The original 37 composite
microdrilled powder samples were again massed and transferred into glass test tubes for future
isotopic analyses. Each tube carried aliquots of an average of 0.220 ± .06 mg carbonate powder.
Twenty-two tubes of standard were also massed in preparation for analysis: ten UCD (calcite)
standards, four TYTIRI (dolomite) standards, four NBS18 standards, and four NBS19 standards.
Once evacuated and acidified, all samples and standards were run on a Thermo Fisher Scientific
Delta V Isotope Ratio Mass Spectrometer coupled with a Conflo IV Universal Continuous Flow
Interface and a Thermo Fischer Scientific Gasbench II. Figure 7 depicts the stromatolite that was
microdrilled and prepped for IRMS. With the exception of the two rightmost columns of microdrill
holes (with adjacent faint red or blue ink), all of the powder from the rest of the microdrill holes
were used for Isotope and Gas Concentration Analysis / IRMS.
24
Figure 7: Large LaClede stromatolite hand sample with microdrilled holes. With the exception of
the microdrill holes in the two rightmost columns, each drill hole was used in the Gas
Concentration Analyzer and IRMS analyses. The stromatolite sample is approximately 12cm long;
each microdrill hole is 1mm in diameter.
25
Isotope Ratio Mass Spectrometry: Horizontal Isotopic Variability
Since sample powders used for IRMS and Isotope and Gas Concentration Analysis were a
combination of powders from many microdrilled holes along a lamina, it is important to ensure
that d
18
O and d
13
C values of powders spaced millimeters apart across the same lamina are constant,
and do not affect the integrity of the vertical isotopic transects. It is commonly accepted that
stromatolites are studied as paleoclimate indicators due to the fact that their laminae are
geochemically and petrographically continuous laterally on the scale of up to kilometers. However,
in order to ensure without a doubt that the d
18
O and d
13
C value of the powder from our stromatolite
do not exhibit intra-lamina fluctuation, we assessed the individual isotopic compositions of
individual microdrill holes across four different laminae. This is a necessary step not only to rule
out the influence of intra-lamina isotopic fluctuation in creating EECO paleoclimate models, but
it is also critical to ensure that our reconstructed paleoclimate based on isotopic data from our
specific stromatolite is a concrete indication of EECO sedimentary deposition. In other words, it
is necessary to assess the significance of intra-lamina isotopic fluctuation to ensure our
paleoclimate reconstruction would remain an accurate and dependable representation of the
depositional conditions at the shores of Lake Gosiute regardless of where stromatolites were
sampled along the LaClede Bed.
In order to assess horizontal isotopic variability, multiple holes were microdrilled laterally
within the same lamina along the stromatolite sample. These discrete laminae were chosen based
on thickness, compositional continuity of layer throughout the entire stromatolite, lack of mixing
with secondary sediment, and definition of borders with underlying and overlying layers. Using
these four parameters, four laminae (L1, L9, L10, L11) were deemed most suitable for lateral
variability analysis and were subsequently microdrilled. Figure 8 depicts the location of the
microdrill holes used in this lateral variability examination. Within a single layer, drill holes were
26
spaced 0.5-2 cm apart from each other. A total of 23 powder samples were assessed, with five to
six holes microdrilled per laminae. The 23 powder samples were massed and transferred into glass
vials for IRMS analysis. Each tube carried aliquots of an average of 0.100 ± .01 mg carbonate
powder. Twenty tubes of Ultissima Marble Standard were also massed and stored in glass vials.
Samples were then evacuated, acidified, and analyzed for d
13
C and d
18
O on a VG Prism II Stable
Isotope Ratio Mass Spectrometer.
27
Figure 8: Large LaClede stromatolite hand sample with microdrill holes used for lateral variability
analyses denoted by colored dots. Each color designates a distinct lamina (purple for L1, red for
L9, turquoise for L10, green for L14)
28
Micro-XRF Spectroscopy
Most stromatolite-based paleoclimate reconstruction models in literature have been
conducted through drilling and mass spectroscopy alone. However, the resolution is limited by the
drill bit size, which is typically 10 to 20 times coarser than the lamination in the stromatolite. Using
traditional methods, information present in the stromatolites is lost by low resolution sampling
methods. As a result, the EECO paleoclimate record is missing gaps of elemental and isotopic data
as a large proportion of stromatolite microfacies are too fine to be distinguished by traditional
analysis techniques. While we employ those methods, they are merely one portion of our
paleoclimate analyses, and was supplemented with X-Ray fluorescence spectroscopy and light
microscopy petrographic analyses. X-Ray fluorescence has been used to analyze stromatolites
before, but to our knowledge, not on this scale. Previous studies typically use X-Ray fluorescence
as a tool to determine the presence of one or two elements (Yamamoto et al., 2008; Perri et al.,
2012) or oxides (Lundberg and McFarlane, 2011), or to determine gross morphology via the
qualitative area maps (Flannery et al., 2017). Additionally, while this method has been used to
investigate elemental markers in a few isolated paleoclimate analyses, these studies involve other
carbonate systems such as speleothems (Frisia et al., 2012; Martín-Algarra and Sánchez-Navas,
1995) in completely different environments.
To increase the resolution of data collection, micro-X-Ray fluorescence (µXRF) was
utilized to find elemental abundances in the stromatolite at sub-laminar scales. We utilized a
Horiba XGT-7200 Analytical Microscope with a rhodium X-Ray tube. The backside of the large
stromatolite sample shown in Figure 7 and the six billets shown in Figure 9 were all analyzed
through µXRF. For each sample, we ran vertical quantitative line scans and created corresponding
qualitative area maps via 𝜇XRF for 13 elements (sodium, magnesium, aluminum, silicon,
phosphorus, sulfur, chlorine, potassium, calcium, titanium, manganese, iron, and strontium – as
29
recommended by the µXRF elemental detection software). Sodium and magnesium are of interest
because they are divalent cations serving and conservative lake-level indicators. Calcium and
magnesium represent the primary carbonate fabric. Silicon is indicative of silicification occurring
in the stromatolite, incorporating chert or quartz in the stromatolite laminae. Aluminum, titanium,
and sulfur are proxies for detrital grains trapped secondarily during stromatolite growth. While
aluminum and titanium may indicate clay, siliciclastic grains, and/or volcanic grains, sulfur may
indicate secondary pyritization. Iron is redox-sensitive and may be a potential biologic indicator,
which allows us to distinguish periods of cyanobacteria activity and non-activity during
stromatolite formation. Finally, strontium acts as a non-redox sensitive indicator, and is a good
elemental comparator to iron.
Two line scans were created for the large stromatolite hand sample and each smaller billet,
with the exception of Ad, for which one line scan was created due to its shape and size. These line
scans scanned vertical transects spanning the entirety of the large sample or the billet. For each of
these sections, all line scans were conducted with the highest power voltage X-Ray tube setting
(50 kV), and had a spot size diameter of 50 𝜇m. For the majority of the line scans, the 𝜇XRF would
scan each point in a sample for 10 seconds, scan the designated point three times, increment down
the sample by 250 𝜇m, and repeat the process until it reached the end of the sample. The average
elemental abundance values for each of the three scans were reported for each point. These
parameters remained constant through the study, except for right hand line scan of billet Aa. While
this line scan was still conducted with a 50 kV X-Ray tube and had a spot size diameter of 50 µm,
it scanned each point in the billet for 60 seconds, scanned the designated point four times, and
moved down the sample by 50 𝜇m. While this line scan was by far the most precise, it took over
30
6x the amount of time to complete. Therefore, to maximize efficiency and 𝜇XRF resources while
maintaining high a quality of data, the rest of the line scans were performed as initially described.
A corresponding area scan was created for each line scan for the large hand sample and
each of the six billets. The length of each area corresponding with the height of the hand sample
or billet (ranging between a minimum of 40.96mm and a maximum of 65.392mm), and the width
was set at either 2.048mm or 3.072mm, depending on the length (width and height are fixed by
the Horiba software and cannot be manually overridden). Regardless of the width of the area scan,
each scan was positioned so that the corresponding line scan perfectly bisected the area scan down
to the micrometer. For all but one of the samples, each area scan was conducted with the highest
power voltage X-Ray tube setting (50 kV), and had a spot size diameter of 50 𝜇m. The only
exception was the right-hand area scan of billet Ab, which had the same voltage setting but had a
1.2mm spot size diameter. Like the line scans, each area scan is a compilation of three separate
scans which were overlaid to create the final rendering.
To ensure that we were collecting the highest-resolution possible, each sample was
positioned to be as flat as possible, was mechanically moved as close to the X-Ray detector without
blocking it, and was run in a vacuum sealed chamber. Using these specifications and the
parameters described above, we collected the highest-resolution data for both stromatolite line
scans and area scans. Studying the micro-scale variance in elemental abundance and distribution
throughout stromatolite laminae is critical to our understanding of environmental fluctuations of
the EECO paleoclimate.
31
Figure 9: Six LaClede Bed stromatolite billets used for 𝜇XRF analysis (Aa, Ab, Ac, Ad, Ae, Af). Billets were analyzed for sodium,
magnesium, aluminum, silicon, phosphorus, sulfur, chlorine, potassium, calcium, titanium, manganese, iron, and strontium through
quantitative line scans and qualitative area maps.
32
Figure 10: Billet Aa with quantitative lines scan (red bold lines) and qualitative area map (transparent boxes) placements
denoted.
33
Figure 11: Billet Ab with quantitative lines scan (red bold lines) and qualitative area map
(transparent boxes) placements denoted.
34
Figure 12: Billet Ac with quantitative lines scan (red bold lines) and qualitative area map
(transparent boxes) placements denoted.
35
Figure 13: Billet Ad with quantitative lines scan (red bold lines) and qualitative area map (transparent boxes)
placements denoted. Unlike the other five billets, only one line scan / area map was created for Ad.
36
Figure 14: Billet Ae with quantitative lines scan (red bold lines) and qualitative area map
(transparent boxes) placements denoted.
37
Figure 15: Billet Af with quantitative lines scan (red bold lines) and qualitative area map
(transparent boxes) placements denoted.
38
Petrographic Analyses: Photomosaics
To relate the isotopic and elemental analyses directly to the physical carbonate fabrics of
the stromatolite, we studied the petrography of the LaClede samples through light microscopy.
Stromatolite thin sections corresponding to the billets used in the 𝜇XRF analyses were visualized,
and six detailed photomosaics were created in order to study vertical, inter-laminae variability.
The Zeiss Imager M2m microscope was used to image discrete laminae, and the Zeiss Axiocam
MRc Camera was used to create high-resolution photomosaics of entire thin sections, so that all
laminae could be viewed together. Laminae were evaluated to determine their carbonate textures,
such as sparry, micritic, or mixed microfabrics. Laminae composed predominantly of fine-scale
micrite were designated as micritic, laminae dominated by coarse crystalline spar grains were
designated as sparry, and laminae with both features (ex. coarse spar crystals embedded in
otherwise micritic background) were designated as mixed fabrics. Petrographic analyses were
especially important in supplementing the 𝜇XRF-derived elemental or IRMS-derived isotopic
work done to assess the effect of inter-lamina isotopic variation, in order to determine whether
there are any macro-scale visual markers corresponding to trends.
39
Figure 16: Photomosaic of the thin section corresponding to billet Aa
40
Figure 17: Photomosaic of the thin section corresponding to billet Ab
41
Figure 18: Photomosaic of the thin section corresponding to billet Ac
42
Figure 19: Photomosaic of the thin section corresponding to billet Ad
43
Figure 20: Photomosaic of the thin section corresponding to billet Ae
44
Figure 21: Photomosaic of the thin section corresponding to billet Af
45
Petrographic Analyses: Assessment of Lateral Continuity
To complement the horizontal isotopic analyses used to determine lateral continuity in
stromatolite laminae, we carried out microscale petrographic analyses of distinct laminae. This
was done in order to compare petrography and uniformity (or lack thereof) of carbonate
microfabric to laminar isotopic and elemental variation determined via IRMS and 𝜇-XRF analyses.
To better understand the carbonate microfeatures responsible for lateral isotopic variability, thin
sections of the stromatolite billets were viewed under the Zeiss Imager M2m microscope, and
laminae were imaged individually. These stromatolite laminae were traced throughout their entire
length along which microdrill holes had been carefully made, and were analyzed for micritic versus
sparry makeup. Dominant microfabric (micritic, sparry, mixed), as well as anomalies (ex. unusual
pockets of spar, discontinuous laminae, etc.) were noted for laminae 1, 9, 10, and 14 – the same
laminae microdrilled for the lateral continuity IRMS analyses. Photomicrographs of laminae 1, 9,
10, and 14 were made using the microscope’s Zeiss Axiocam MRc camera. As described earlier
in the methods section, these laminae were chosen deliberately based on their thickness,
compositional continuity, lack of mixing with secondary sediment, and well defined laminar
borders.
46
RESULTS
Isotopic Variability
The graphs below depict the results of the mass spectrometry analysis of stable oxygen
(Graph 1) and carbon (Graph 2) isotope ratios for the powder samples taken along the 37 distinct
laminae of the large LaClede stromatolite. All of the powder samples were run on the same Delta
V Isotope Ratio Mass Spectrometer with Conflo IV Universal Continuous Flow Interface and
Thermo Fischer Scientific Gasbench II with the same standards used throughout, so any systematic
shift caused by the machine and/or standard should be uniform. In Graph 1, d
18
O values fluctuate
by 4.6‰, between a minimum of -6.7‰ and a maximum of -2.1‰. In Graph 2, d
13
C values
fluctuate by 2.7‰, between a minimum of 1.0‰ and a maximum 3.7‰. A larger range in ‰
values for d
18
O is consistent with deposition in a closed basin lake (Talbot, 1990). Additionally,
there is a strong covariance of d
18
O and d
13
C.
For error analysis, standard deviation of d
18
O and d
13
C values was calculated for all data
points and was found to be negligible. Error bars are smaller than the size of the data point each
of the graphs. Another way to check for error involved running the same microdrilled powder on
different machines, using different standards. The Delta V IRMS d
13
C data points (as depicted in
Graph 2) were overlaid with the d
13
C values collected from the Picarro G2131-i Isotope and Gas
Concentration Analyzer and were found to fit quite well with the Picarro values (Graph 3). This
further strengthens our confidence in the reported d
13
C values in Graphs 2 and 3, as the values d
13
C
remained constant regardless of the machine they were run on or the standards to which they were
compared.
Graph 4 depicts the carbonate percentage of each microdrilled powder sample, as
determined by the Picarro G2131-i Isotope and Gas Concentration Analyzer. Graphs 5-8 depict
47
lateral variation of d
13
C and d
18
O within laminae 1, 9, 10, and 14, respectively. Each graph depicts
d
13
C values and d
18
O values from different five to six microdrilled powder samples along the same
lamina. The data points correspond spatially with the position of the microdrilled holes from left
to right, so the leftmost d
13
C and d
18
O data points on the graph correspond to the powder from the
leftmost microdrilled holes in the stromatolite shown in Figure 7.
Graph 7 depicts an example of a lamina with low isotopic variability, in which the total
range of intra-laminar d
13
C and d
18
O values is less than 1‰. Conversely, Graphs 5, 6, and 8 depict
examples of laminae with high isotopic variation, in which d
13
C and d
18
O ranges can vary as much
as nearly 4‰ (Graph 6).
48
Graph 1: d
18
O variability in laminae 1 – 37 of the large LaClede stromatolite sample. d
18
O values
fluctuate between a minimum of -6.7‰ and a maximum of -2.1‰.
0
5
10
15
20
25
30
35
40
-8.0 -7.0 -6.0 -5.0 -4.0 -3.0 -2.0 -1.0 0.0
Lamina
‰
δ
18
O Variability in Laminae 1 -37
49
Graph 2: d
13
C variability in laminae 1 – 37 of the large LaClede stromatolite sample. d
13
C values
fluctuate between a minimum of 1.0‰ and a maximum of 3.7‰.
0
5
10
15
20
25
30
35
40
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
Lamina
‰
δ
13
C Variability in Laminae 1 -37
50
Graph 3: d
13
C variability in laminae 1 – 37 of the large LaClede stromatolite as measured on both
the Delta V Isotope Ratio Mass Spectrometer (blue) and the Picarro G2131-i Isotope and Gas
Concentration Analyzer (red).
0
5
10
15
20
25
30
35
40
0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00
Lamina
‰
δ
13
C Variability in Laminae 1 -37
Picarro
Delta V
51
Graph 4: Carbonate content in laminae 1 – 37 of the large LaClede stromatolite as measured on
the Picarro G2131-i Isotope and Gas Concentration Analyzer.
0
5
10
15
20
25
30
35
40
50.0 55.0 60.0 65.0 70.0 75.0 80.0 85.0 90.0 95.0 100.0
Lamina
Carbonate %
Carbonate Content (%) of Laminae 1 -37
52
Graph 5: Intra-lamina variability of lamina 1.
Moderate d
13
C and d
18
O variability caused by
spar crystals at the layer boundaries.
Graph 6: Intra-lamina variability of lamina 9.
Highest d
13
C and d
18
O variability caused by 125
𝜇m spar crystals (white) found in the middle of
the lamina.
Graph 7: Intra-lamina variability of lamina 10.
Lowest d
13
C and d
18
O variability correlated
with highest percentage of micrite in lamina.
Graph 8: Intra-lamina variability of lamina 14.
High d
13
C and d
18
O caused by spar pockets
dispersed throughout the lamina.
53
Micro-XRF Spectroscopy
To study elemental variability throughout the stromatolite at a fine scale, we utilized µXRF
spectroscopy to assess inter- and intra-laminar bulk elemental composition on the micrometer
scale. Through µXRF, we created quantitative area heat maps for magnesium, calcium, iron,
silicon, and strontium fluctuation through the six stromatolite billets (Aa, Ab, Ac, Ad, Ae, Af).
Figures 22 – 32 depict the area heat maps for each billet in alphabetical order. There are two
transects for billets Aa, Ab, Ac, Ae, and Af, as well as one transect for billet Ad. For each transect,
five area heat maps are presented: calcium in yellow, iron in orange, magnesium in green, silicon
in magenta, and strontium in cyan. For the elemental heat maps, brighter colors indicate higher the
elemental abundances. Element area maps, along with the corresponding billet sections, are
depicted in figures 22 – 32.
In addition to the qualitative area maps, µXRF was used to obtain fine scale quantitative
line scans of the scanned regions corresponding to the area maps. Graphs 9 – 11 depict the relative
abundance of magnesium, iron, and strontium (all normalized to calcium) in a vertical transect of
billet Aa. These three graphs are provided here due to their utility in reconstructing the EECO
paleoenvironment; however, graphs for all 13 elements listed in the methods section were created.
The y-axes of Graphs 9 – 11 correspond with the 800 scan locations spaced 50 µm vertically apart
along the stromatolite billet Aa. Each graph has chart of the maximum value, minimum value,
mean value, and standard deviation superimposed in the corner of each graph. A data table with
complete elemental abundances, as well as the normalized elemental abundances depicted in
Graphs 9 – 11 can be found in the appendix.
54
Figure 22: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium abundance for
billet Aa (left)
55
Figure 23: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium abundance for
billet Aa (right)
56
Figure 24: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium abundance for
billet Ab (left)
57
Figure 25: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium
abundance for billet Ab (right)
58
Figure 26: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium
abundance for billet Ac (left)
59
Figure 27: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium
abundance for billet Ac (right)
60
Figure 28: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium
abundance for billet Ad
61
Figure 29: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium abundance
for billet Ae (left)
62
Figure 30: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium
abundance for billet Ae (right)
63
Figure 31: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium
abundance for billet Af (left)
64
Figure 32: Qualitative heat maps of calcium, iron, magnesium, silicon, and strontium abundance for
billet Af (right)
65
0
100
200
300
400
500
600
700
800
0 0.01 0.02 0.03
Sr/Ca Fluctuation
0
100
200
300
400
500
600
700
800
0 0.1 0.2 0.3
Fe/Ca Fluctuation
0
100
200
300
400
500
600
700
800
0 0.1 0.2 0.3
Mg/Ca Fluctuation
Graph 9: Relative abundance of
magnesium (normalized to
calcium) along a vertical transect
in billet Aa
Graph 11: Relative abundance of
strontium (normalized to
calcium) along a vertical transect
in billet Aa
Graph 10: Relative abundance of
iron (normalized to calcium)
along a vertical transect in billet
Aa
66
Petrography
To understand what was causing the lateral variability, we analyzed the six stromatolite
billets via light microscopy to better understand petrographic anomalies horizontally as well as
vertically. Laminae throughout the stromatolite thin sections ranged from micritc to sparry fabrics,
with some secondary sedimentary infill that occurred after the time of stromatolite accretion and
lithification. Degree of lateral variability is interpreted to vary as a function of the dominant
carbonate crystal type present throughout a lamina: micrite or spar. Figures 33 - 36 are
photomicrographs of laminae 1, 9, 10, and 14, respectively. The petrological makeup reflected in
the photomicrographs is entirely carbonate in composition; however, there is variation in the type
of carbonate grain present throughout the thin section. Fine, dark sediment is micrite, constituting
a micritic fabric. Larger, white rhombohedral crystals are secondary spar crystals, constituting a
diagenetic sparry fabric. Laminae with greater amounts of spar crystals tend to have more lateral
isotopic variability than laminae with fewer spar crystals.
Laminae 1 and 9 had the highest recorded isotopic variability (shown in Graphs 5 and 6),
and their corresponding photomicrographs depict large white crystals stratifying throughout the
laminae. In Figure 33, large spar crystals can be seen flanking the edges of the lamina 1, as well
as some smaller crystals found in throughout. These crystals are spaced closely enough that a 1mm
drill bit would likely hit diagenetic spar when microdrilling lamina 1, which would introduce
variability depending on where along the lamina is microdrilled. In Figure 34, large (~125 µm)
spar crystals are shown creating a distinct layer roughly bisecting lamina 9. Since the spar crystals
are found in the middle of the lamina, a drill bit would most likely hit spar crystals when
microdrilling lamina 9, causing notable isotopic variability between intra-laminar microdrilled
powder samples. Lamina 10 had the lowest recorded isotopic variability (shown in Graph 7).
Lamina 10 is largely devoid of spar crystals, and is mainly micritic in composition, resulting in
67
low intra-lamina isotopic variability (Figure 35). Lamina 14 had intermediate isotopic variability
(shown in Graph 7), resulting from irregular pockets of spar found unevenly through the lamina.
The photomicrograph in Figure 36 shows some small (<100 µm) spar crystals distributed
irregularly in lamina 14, causing some isotopic variability depending on whether the microdrilled
sample randomly included these small spar crystals.
68
Figure 33: Light Microscopy image of lamina 1. Moderate d
13
C and d
18
O variability caused by spar crystals (white) at the layer
boundaries.
69
Figure 34: Light Microscopy image of lamina 9 (L9). Highest d
13
C and d
18
O variability caused by 125 𝜇m spar crystals (white)
found in the middle of the lamina.
70
Figure 35: Light Microscopy image of lamina 10. Lowest d
13
C and d
18
O variability correlated with highest percentage of
micrite in lamina composition.
71
Figure 36: Light Microscopy image of lamina 14. High d
13
C and d
18
O caused by spar pockets dispersed throughout the
lamina.
72
DISCUSSION
Assessment of Intra-Lamina Variability
All studies involving stromatolite-based paleoclimate reconstructions operate on the same
assumption that isotopic variability within the same stromatolite laminae remains relatively
constant throughout the length of the lamina. Based on this assumption, a vertical transect made
at one arbitrary location should yield similar isotopic values as the same laminae at another
location throughout the entirety of a stromatolite, whether they are separated meters or kilometers
apart. Should isotopic signatures within the same laminae vary laterally, transects made at different
points along the stromatolite would yield highly variable and unreliable temperature, atmospheric
CO
2
level, and lake volume data, resulting in vastly different paleoclimate reconstructions for the
same period of time. As a result, it is critical to assess lateral variability within a stromatolite in
order to confirm the validity of stromatolite-based paleoclimate reconstructions. The lateral
variability depicted in graphs 2 – 5 is due to the differing chemical composition of the carbonate
microstructure within laminae. Our results showed that the layers predominantly composed of fine
micrite had lower isotopic variation than the layers containing abundant spar. Micrite deposition
is thought to have occurred during the time of stromatolite growth; therefore, d
13
C and d
18
O
signatures recorded in the micritic grains accurately portray lake water and atmospheric conditions
at time of deposition. Spar deposition is thought to be secondary, forming after the point of initial
deposition due to diagenesis, perhaps due to fluid composition or a similar type of chemical
alteration of the carbonate structure. Because spar crystals formed after initial stromatolite
deposition, their d
13
C and d
18
O signatures do not reflect lake water or atmospheric conditions at
the time of stromatolite growth, and therefore skew the overall d
13
C and d
18
O values detected via
mass spectrometry.
73
For the sake of this thesis, the intra-lamination variability throughout the LaClede Bed
stromatolite is negligible and would have little effect on EECO paleoclimate or paleohydrologic
modeling; in general, few sparry laminae were sampled. However, it is important to be aware of
petrography when conducting isotopic or elemental analyses in stromatolites. This is especially
true when microdrilling, as the drill bit utilized for such analyses is often 1mm or larger in
diameter, and can easily include small pockets of spar without awareness of petrography prior to
microdrilling. As first noted in the results section, Laminae with greater amounts of diagenetic
spar crystals tend to have more lateral isotopic variability than laminae that lack large spar crystals
and are predominantly micritic. For future stromatolite-based isotopic analyses, intra-laminar
isotopic variability can be avoided based on these petrographic insights. For laminae 1 and 14,
isotopic variability can be avoided by examining the laminae through a microscope prior to
drilling. Since spar pockets in lamina 1 are mainly found flanking the lamina, they can be avoided
by the careful placement of the drill bit in the center of the lamina. Lamina 14 has smaller, irregular
spar crystals found intermittently throughout the lamina. As in lamina 1, isotopic variability can
be minimized by careful placement of the drill bit away from spar pockets, which can be visualized
through a microscope. In lamina 9, it is more difficult to avoid spar due to the fact that it constitutes
a fine band near the middle of the lamina. While the best way to avoid intra-lamina isotopic
variability in lamina such as 9 is to avoid drilling altogether, if drilling is required, it should be
noted that sparry laminae are more prone to lateral inconsistencies. Laminae such as lamina 10 –
those that are predominantly micritic throughout – are ideal for microdrilling due to the lack of
spar crystals. In a uniformly micritic lamina, there lesser probability of post-depositional
diagenetic alterations that would cause intra-laminar fabric inconsistencies and subsequent
isotopic variability.
74
Isotopes, Elemental Analyses, and Lake Volume Change
The isotopic signatures d
18
O and d
13
C can inform us of the EECO paleoclimate, and allow
us to identify times of precipitation and evaporation during the EECO. Lake Gosiute likely
underwent periods of evaporation when d
18
O and d
13
C values are relatively high. Enriched d
18
O
and d
13
C values are associated with warmer climate and warmer waters that dominated Lake
Gosiute during periods of amplified evaporation. As temperatures increased, evaporation ensued,
and water vapor with lighter oxygen isotopes preferentially evaporated out of the lake over vapor
with heavier isotopes. This left behind a body of water depleted in light isotopes, in which heavier
d
18
O isotopes recorded in the stromatolite. Periods of evaporation are associated with decreasing
lake volumes, and subsequent dropping of lake shoreline levels. From a petrographic perspective,
these conditions favored the precipitation of micritic stromatolite layers, forming via biogenic
processes such as microbial mat trapping and binding of sediment (Frantz et al., 2014). Conversely,
depleted d
18
O and d
13
C values are associated with periods of amplified precipitation. During these
periods, the lighter isotopes from rainfall were delivered to the lake and recorded in stromatolites.
Alternating enriched, intermediate, and depleted laminae indicate that Lake Gosiute likely
underwent many cycles of evaporation and recharge. Graphs 1 and 2 depict the cyclic nature of
d
18
O and d
13
C, and both graphs depict 4 full oscillations between high and low d
18
O and d
13
C
values.
The classic interpretation of the LaClede stromatolites would suggest that they grew during
transgression at the base of a typical lake cycle (e.g. Surdam and Stanley, 1979.) as the lake filled,
and would carry with it the prediction that the stromatolite should record a monotonic decrease in
d
18
O, reflecting the fact that the lake was filling with relatively d
18
O depleted rainwater. However,
our data suggest the actual situation was much more complex (Figure 37), where the fluctuations
75
in d
18
O within the stromatolite indicate multiple smaller scale filling and evaporation cycles as
suggested in Frantz 2013, rather than one monotonic decrease implied by previous studies (e.g.
Surdam and Stanley, 1979). Thus, it would appear that the hydrologic variability during the EECO
was greater than previously predicted. The covariance of d
18
O and d
13
C (Graph 12), coupled with
the fact that δ
18
O varies over a range of several ‰ suggests the stromatolite was deposited in a
closed basin lake system (Talbot, 1990). The interpretation that this stromatolite was deposited in
a closed basin lake allows for the use of δ
18
O and non-redox-sensitive divalent cations (e.g. Mg)
as lake level indicators to reconstruct periods of evaporation and recharge in Lake Gosiute.
Graph 12: Overall covariance of d
18
O and d
13
C in the large LaClede stromatolite.
y = 0.9886x -6.5046
R² = 0.33423
-8.0
-7.0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
d
18
O (‰ )
d
13
C (‰ )
Overall d
13
C and d
18
O Covariance
76
Lake Level Cycles and Anoxia
The µXRF allows for elemental investigation at the scale of the lamination that can be
directly compared to light microscopy. In addition to raw elemental abundances, measuring
pertinent elemental ratios helps determine if the element is within the carbonate or in some
accessory phase. For example, comparing the element of choice versus Ca (if calcite) or Ca+Mg
(if dolomite) allows for the isolation of the element in question against the bulk carbonate
chemistry of the stromatolite. Ratios with Ti and Al act as proxies for the presence of detrital
siliciclastic grains that commonly become trapped in stromatolites along laminae and are unrelated
to microbial processes involved in stromatolite growth. Ratios with S can account for the possible
presence of trace sulfides (such as pyrite) in the stromatolite. Finally, by mapping out ratios of
redox-sensitive elemental abundance compared to other, non-redox-sensitive elements commonly
incorporated into carbonates (e.g., Sr), we can evaluate whether variance in the element of interest
is related to microbial redox processes associated with the stromatolite or is caused by external
environmental change (such as lake level change).
Magnesium concentration and lake level have an inverse relationship in previously
analyzed older stromatolites from the Green River Formation (Frantz et al., 2014), such that the
relative magnesium abundance in distinct stromatolite laminae are hypothesized to inform us of
paleoenvironments and lake volume during time of stromatolite laminae deposition. Under the
assumption that magnesium behaves conservatively (Frantz et al., 2014), magnesium
concentration fluctuates as a function of lake water volume, where enrichment of magnesium
indicates a relatively shallow lake (potentially indicative of an arid, evaporative event), which a
depletion of magnesium indicates a relatively deep lake (potentially indicative of a wet, recharge
period). Iron is a redox-sensitive element, and can be applied as a proxy for lake water oxygenation
levels. Greater amounts of Fe(II) incorporation in the carbonate lattice of the stromatolite may
77
indicate that lake water was depleted in oxygen. Graph 13 shows a juxtaposition of magnesium
and iron relative abundances in a vertical transect of LaClede billet Aa. Various cycles of
covariance and anti-covariance can be seen. These relative abundance curves reflect iron and
magnesium relative abundance in the carbonate lattice, and are not influenced by detrital grains,
as shown in graphs 14 - 18. There is very weak covariance of iron or magnesium with elemental
sulfur or titanium, which could indicate minor secondary pyritization or a detrital silica grain that
was trapped following stromatolite deposition, though pyrite is not generally abundant in the
stromatolites. As seen in graph 13, there is a large spike in relative iron abundance towards the top
of the stromatolite. The increase in iron abundance implies anoxic conditions, where iron released
from sedimentary iron oxides increases dissolved iron in the (presumed anoxic) water column. The
increase in iron abundance is also consistent with the stratigraphic transition to oil shale above the
LaClede Bed, as well as with magnesium abundance interpretations of a progressively deeper lake.
A first order lake level model of Lake Gosiute can be made based on the relative magnesium
abundance in the stromatolite. There is a clear cyclic pattern visible as lake levels fluctuate between
deep and shallow lake conditions on consistent intervals. With each additional cycle, the
magnitude of the cycle decreases, demonstrating an overarching deepening of Lake Gosiute,
consistent with transgressive shorelines. The Lake Gosiute lake level model is consistent with our
lake water oxygenation interpretations, as determined by the relative iron abundance in the
stromatolite. Greater levels of anoxia (indicated by increased iron abundance) are consistent with
deeper lake levels as predicted by the lake level model (indicated by depleted magnesium
abundance).
78
Graph 13: Vertical transect of iron and magnesium relative abundances in the LaClede billet Aa.
The relative abundance of magnesium in a stromatolite can be used as a conservative lake level
indicator. The relative abundance of iron in a stromatolite can be used as a proxy for lake water
oxygenation.
79
Graph 14: Cross plot of sulfur and magneisum shows little covariance, indicating the relative
abundance of iron is not affected by pyritization.
Graph 15: Cross plot of sulfur and magnesium abundance shows little covariance, indicating the
relative abundance of magnesium is not affected by the trapping of detrital material.
80
Graph 16: Cross plot of titanium and magnesium abundance shows little covariance, indicating
the relative abundance of magnesium is not affected by the trapping of detrital material.
Graph 17: Cross plot of titanium and magnesium abundance shows little covariance, indicating
the relative abundance of magnesium is not affected by the trapping of detrital material.
81
Figure 37: A first order lake level interpretation model based on relative magnesium abundance
in the stromatolite. While Lake Gosiute lake levels cycle between deep and shallow lake
conditions, there is an overarching transgressive pattern that is apparent. The lake level model is
consistent with our understanding of lake water oxygenation levels, as determined by the relative
iron abundance in the stromatolite. Greater levels of anoxia are consistent with deeper lake levels
as predicted by the lake level model.
82
Transition from Closed-Basin to Open-Basin Lake
As Talbot describes in his 1990 paper, carbonate rocks in closed-basin lakes show a strong
covariance in d
13
C and d
18
O. Conversely, this correlation between d
13
C and d
18
O values decouples
in open basin lakes. As a result, d
13
C and d
18
O covariance in lacustrine carbonate rocks (such as
stromatolites) can indicate that the environment in which they formed may have been a closed-
basin lake. These covariant trends can be used to track individual water masses within a closed-
basin lake, and to trace the hydrologic evolution of a basin through time. Lake Gosiute is thought
to have fluctuated between closed-basin and open-basin status as a result of excess precipitation
and evaporation.
While Lake Gosiute is thought to have been a closed-basin lake during the deposition of
the LaClede Bed (Roehler 1991), our d
13
C and d
18
O values suggests that this is an
oversimplification of Lake Gosiute’s paleolimnologic history (see also Frantz, 2013). Isotopic data
presented in this thesis suggest that the majority of LaClede Bed stromatolite deposition occurred
within a closed basin. However, it is unlikely that this closed-basin depositional environment was
stagnant – it is likely that Lake Gosiute underwent cycles of localized filling and spilling periods.
While this may not be immediately evident on the lamina scale, a cyclic pattern becomes apparent
in analyzing the isotopic signatures of groupings of multiple laminae, or microfacies. Based on the
IRMS data, we identified 5 microfacies within the large LaClede stromatolite sample, ranging
from five to ten clustered laminae. Microfacies 1 includes laminae 1 through 7, microfacies 2
includes laminae 8 through 17, microfacies 3 includes laminae 18 through 23, microfacies 4
includes laminae 24 through 28, and microfacies 5 includes laminae 29 through 37. Microfacies 1
– 4 represent four distinct closed-basin cycles, while microfacies 5 includes isotopic data that is
more representative of an open-basin lake. Plots showing d
13
C and d
18
O covariance in each of these
83
microfacies are shown in Graphs 17 -21, each with a linear trend line and a corresponding R
2
value
shown in the upper right hand corner. The R
2
values for microfacies 1 – 4 (Graphs 17 – 20) are
quite high (ranging from a minimum of 0.71 to a maximum of 0.97), indicating a strong trend line
fit. The slopes of the linear trend lines for microfacies 1 – 4 are also quite similar, though the y
axes (d
18
O) of the trend lines differ. A gradual but sustained increase in slope can be seen between
each of the four microfacies best fit trend lines as well. Microfacies also appear to be
distinguishable by color, as each grouping of laminae can be visually distinguished as generally
light or dark.
Microfacies 5, at the top of the stromatolite, does not have the typical isotopic signature of
a closed-basin lake. The covariance plot of microfacies 5 (Graph 22) has an extremely low R
2
value (0.08), indicating a poor fit of the linear trend line caused by a decoupling in d
13
C and d
18
O
correlation, which is a marked changed from the first four microfacies. This loss of d
13
C and d
18
O
covariance near the top of the stromatolite suggests a transition from a closed-basin lake to an
open-basin lake may have occurred during the final stages of LaClede stromatolite growth (i.e. the
deposition laminae 29 and higher in our large stromatolite sample). This hypothesis is bolstered
by the µXRF-derived relative abundances of iron and magnesium supporting a late transition to an
open-basin lake, as depicted in Graph 13. Such a transition may have occurred after a period of
intense precipitation resulting in Lake Gosiute spilling over outside the boundaries of the Green
River Basin.
84
Figure 38: Large LaClede stromatolite microfacies and their boundaries shown in blue
85
Graph 18: Covariance of d
13
C and d
18
O in microfacies 1
Graph 19: Covariance of d
13
C and d
18
O in microfacies 2
y = 1.206x -6.6885
R² = 0.71733
-7.0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
d
18
O (‰ )
d
13
C (‰ )
Microfacies 2 Covariance
y = 1.1043x -7.6351
R² = 0.82466
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
d
18
O (‰ )
d
13
C (‰)
Microfacies 1 Covariance
86
Graph 20: Covariance of d
13
C and d
18
O in microfacies 3
Graph 21: Covariance of d
13
C and d
18
O in microfacies 4
y = 1.7698x -7.7967
R² = 0.97019
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0
d
18
O (‰ )
d
13
C (‰ )
Microfacies 4 Covariance
y = 1.2429x -6.1353
R² = 0.91363
-5.0
-4.5
-4.0
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
d
18
O (‰ )
d
13
C (‰ )
Microfacies 3 Covariance
87
Graph 22: Covariance of d
13
C and d
18
O in microfacies 5
y = 0.8726x -6.6764
R² = 0.08259
-8.0
-7.0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
0.0 0.5 1.0 1.5 2.0 2.5 3.0
d
18
O (‰ )
d
13
C (‰ )
Microfacies 5 Covariance
88
CONCLUSIONS
This study provides updated information about LaClede stromatolite geochemistry and
petrography, introduces a novel application of µXRF spectroscopy, and increases our
understanding of Lake Gosiute’s response to EECO. This is the first time µXRF spectroscopy,
IRMS, and petrography have been used in conjunction to study the fine-scale geochemical and
sedimentological make up of a stromatolite. While IRMS has been used to conduct inter-lamina
studies of stromatolites, µXRF spectroscopy introduces analyses possible at an unprecedented
precision, allowing us to study inter- and intra-lamina perturbation at as low as 50 µm.
Additionally, qualitative area maps made possible by µXRF spectroscopy allow for the creation of
extremely fine-scale elemental heat maps, which complement traditional petrographic methods.
Now in addition to seeing carbonate microfabrics through light microscopy, we are able to see the
elements that make up micro-scale components of stromatolite laminae.
Most notably, this study suggests that there is hydrologic cycling occurring on the scale of
a single, 12cm tall stromatolite. µXRF analyses of magnesium abundance (Graph 13) in a vertical
transect of the stromatolite indicate that lake Gosiute went through regular periods of evaporation
and recharge, resulting in cyclic lake shore level changes. In addition to the cyclicity, we observe
a net transgressive trend in the elemental data, suggesting there is an overarching lake level rise.
This is consistent with the microfacies isotopic analyses, in which the uppermost microfacies is
indicative of open-basin lake conditions (Graph 22) that would occur as a result of Lake Gosiute
filling beyond the confines of a closed-basin lake. µXRF analyses of iron abundance support this
net transgressive behavior, and denote an increasingly anoxic deposition setting nearing the top of
the stromatolite (Graph 13 and Figure 37). These interpretations are also consistent with regional
89
stratigraphy observations, as stromatolites of the LaClede Bed are overlaid by oil shale, which
would likely be deposited in anoxic conditions.
Finally, this study validates the use of finely-laminated stromatolites in reconstructing
paleoclimates such as EECO, as they record isotopic information about the depositional
environment environments. As seen in the multiple lateral drill holes analyzed, isotopic d
13
C and
d
18
O values do not fluctuate significantly enough to suggest drastically different temperature and
atmospheric CO
2
paleoclimate conditions. Additionally, this study describes the necessity of
isolating mainly micritic layers and avoiding drilling spar crystals in order to obtain the most
accurate paleoclimate isotopic d
13
C and d
18
O values. Depending on the scope of a paleoclimate
reconstruction, this paper caution against the use of stromatolite-based paleoclimate reconstruction
in fine-scale paleoclimates in which a 4‰ difference poses a significant amount of modelling
error.
While the EECO was much warmer and was more highly saturated in atmospheric CO
2
that today’s climate, current atmospheric approximations suggests that we are not far off from
another global hothouse climate similar to that of the EECO. Rocks deposited during the EECO
(such as those of the Eocene Green River Formation) serve as an analog for understanding the
impact of long-term high CO
2
/ high temperature climate on hydrologic systems such as closed-
basin lakes. Understanding EECO trends is imperative to our approach in combatting modern
climate change, and for adding to our knowledge of the effects of another global hothouse climate.
90
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101
APPENDIX
Raw Elemental Abundances for Billet Aa:
Spectrum Na Mg Al Si P S Cl K Ca Ti Mn Fe Sr
166 0.77 1.57 2.29 6.66 0.05 0.68 8.78 2.16 66.54 0.35 0.28 8.56 1.31
165 2.72 1.22 2.07 6.6 0 0.61 6.88 2.14 68.23 0.34 0.31 7.63 1.25
164 2.32 1.67 2.01 6.1 0 0.63 5.33 1.99 71.1 0.32 0.31 6.96 1.27
163 2.38 1.52 1.98 5.75 0 0.63 3.87 1.57 75.02 0.29 0.25 5.49 1.26
162 2.23 1.84 1.52 5.06 0.04 0.71 2.48 1.43 78.82 0.29 0.3 4.05 1.23
161 0.86 2.06 1.16 4.31 0 0.82 1.41 0.95 84.5 0.21 0.29 2.3 1.12
160 0.84 2 1.01 3.63 0 0.96 1.2 0.78 86.44 0.23 0.3 1.5 1.1
159 1.36 2.34 1.09 3.57 0 1.12 0.99 0.73 84.6 0.24 0.27 2.64 1.06
158 0.72 2.21 1 3.58 0 1.32 0.79 0.65 85.34 0.28 0.27 2.79 1.05
157 2.47 2.47 0.99 3.9 0 1.42 0.54 0.58 83.5 0.21 0.26 2.65 1.01
156 0.35 1.95 0.96 3.92 0 1.47 0.41 0.69 86.19 0.18 0.28 2.52 1.07
155 0.35 1.91 0.93 3.51 0 1.54 0.34 0.55 87.66 0.2 0.24 1.66 1.11
154 1.6 1.63 0.75 2.74 0 1.69 0.26 0.42 88.79 0.17 0.26 0.62 1.07
153 1.45 1.68 0.62 1.37 0 1.65 0.23 0.27 90.73 0.21 0.25 0.43 1.11
152 1.03 1.48 0.42 1.3 0 1.67 0.22 0.21 91.69 0.24 0.3 0.33 1.12
151 0.39 1.38 0.47 1.08 0 1.93 0.17 0.16 92.43 0.2 0.27 0.32 1.19
150 1.92 1.26 0.32 1.1 0 1.89 0.16 0.14 91.23 0.21 0.27 0.4 1.1
149 2.33 1.94 0.42 1.18 0 1.67 0.12 0.16 89.6 0.08 0.28 1.17 1.05
148 1.34 1.9 0.53 1.87 0 1.55 0.16 0.33 89.02 0.19 0.3 1.79 1.03
147 1.25 1.8 0.91 2.68 0 1.4 0.12 0.47 87.85 0.2 0.27 2.03 1.02
146 0.31 1.83 0.94 2.64 0 1.31 0.14 0.46 88.58 0.24 0.3 2.22 1.04
145 0.94 1.69 0.73 2.69 0 1.18 0.2 0.42 88.56 0.25 0.27 2.04 1.03
144 1.87 1.86 0.87 2.15 0 1.17 0.14 0.37 88.65 0.19 0.26 1.45 1.03
143 0.75 1.3 0.55 1.4 0 1.03 0.18 0.21 92.06 0.2 0.26 1 1.06
142 0 1.74 0.32 1.2 0 0.85 0.13 0.19 93 0.16 0.24 1.11 1.06
141 0.32 3.03 0.45 1.92 0 0.72 0.2 0.24 89.69 0.21 0.28 1.97 0.97
140 0.67 4.94 0.7 3.15 0 0.64 0.25 0.42 84.39 0.24 0.32 3.41 0.87
139 0.06 8.17 1.13 5.03 0 0.76 0.27 0.68 77.77 0.25 0.38 4.64 0.85
138 1.46 10.55 1.34 6.34 0.06 0.71 0.25 0.83 72.16 0.33 0.33 4.79 0.86
137 0.81 10.7 1.44 6.61 0.01 0.69 0.18 0.82 72.76 0.35 0.37 4.41 0.85
136 0.65 8.55 1.41 6.33 0 0.49 0.14 0.81 76.78 0.32 0.35 3.26 0.91
135 0.98 5.1 1.1 5.75 0 0.47 0.16 0.73 81.95 0.3 0.29 2.27 0.91
134 0.41 2.32 1.13 5.5 0 0.43 0.23 0.65 86.11 0.28 0.33 1.65 0.95
133 0.67 1.33 0.95 5.18 0 0.37 0.21 0.74 87.46 0.29 0.29 1.57 0.94
132 1.17 0.97 0.95 4.74 0 0.32 0.16 0.56 88.24 0.3 0.25 1.43 0.93
131 0.26 1.07 0.82 4.03 0 0.3 0.23 0.47 89.82 0.3 0.32 1.4 0.98
130 0.66 1.34 0.91 3.49 0 0.33 0.21 0.46 89.75 0.18 0.29 1.43 0.96
129 1.44 1.64 0.66 3.01 0 0.31 0.18 0.43 89.4 0.22 0.33 1.4 0.98
102
128 1.39 2.38 0.57 2.52 0 0.31 0.22 0.5 89.09 0.19 0.35 1.52 0.97
127 0.34 3.1 0.6 2.54 0 0.31 0.18 0.4 89.28 0.3 0.32 1.64 0.98
126 0.02 3.57 0.75 2.63 0 0.35 0.26 0.39 88.83 0.21 0.34 1.64 1
125 0.41 3.57 0.7 2.4 0 0.29 0.25 0.38 88.8 0.24 0.32 1.66 0.98
124 0 3.84 0.67 2.61 0 0.32 0.22 0.41 88.87 0.17 0.28 1.59 1.03
123 0.22 3.1 0.74 2.68 0 0.33 0.17 0.42 89.32 0.22 0.33 1.41 1.04
122 1.85 2.6 0.6 2.73 0 0.34 0.16 0.4 88.52 0.23 0.36 1.28 0.93
121 1.87 1.9 0.65 3.15 0 0.3 0.18 0.49 88.6 0.33 0.35 1.24 0.95
120 0.27 1.31 0.86 3.54 0 0.31 0.17 0.51 90.31 0.22 0.27 1.26 0.95
119 0 1.21 0.86 3.62 0 0.29 0.21 0.54 90.52 0.31 0.29 1.21 0.95
118 1.97 1.19 0.71 3.53 0 0.25 0.12 0.43 89.21 0.27 0.32 1.05 0.96
117 1.74 1.37 0.63 3.1 0 0.29 0.22 0.51 89.52 0.25 0.33 1.06 0.96
116 0.78 1.8 0.85 2.63 0 0.22 0.26 0.44 90.33 0.25 0.34 1.1 1
115 1.57 1.81 0.6 2.57 0 0.26 0.25 0.41 89.75 0.21 0.35 1.25 0.95
114 0.04 1.89 0.51 2.67 0 0.26 0.25 0.43 91.01 0.26 0.35 1.3 1.03
113 1.43 1.66 0.46 2.58 0 0.24 0.26 0.36 90.04 0.28 0.35 1.35 1
112 1.15 2.07 0.84 2.39 0 0.23 0.22 0.42 89.69 0.23 0.33 1.48 0.97
111 0 1.21 0.71 2.58 0 0.22 0.21 0.43 91.44 0.23 0.4 1.59 0.96
110 0.2 1.53 0.75 2.82 0 0.28 0.24 0.46 90.38 0.24 0.4 1.8 0.92
109 0.6 1.76 0.78 2.97 0 0.29 0.21 0.52 89.24 0.26 0.43 2.06 0.89
108 0.51 1.54 0.84 3.13 0 0.28 0.28 0.69 88.96 0.27 0.45 2.17 0.87
107 1.14 1.36 0.76 3.1 0 0.21 0.27 0.53 89.13 0.2 0.41 2.01 0.88
106 2.1 1.64 0.78 2.84 0 0.22 0.24 0.5 88.13 0.2 0.41 2.11 0.82
105 0.17 1.49 0.85 2.72 0 0.19 0.24 0.44 90.21 0.2 0.44 2.25 0.79
104 2.33 1.82 0.8 2.81 0 0.22 0.32 0.52 87.35 0.18 0.45 2.51 0.69
103 0 2.6 0.75 2.83 0 0.21 0.22 0.52 88.55 0.21 0.46 2.93 0.72
102 0 2.56 0.66 2.66 0 0.21 0.26 0.45 88.78 0.18 0.43 3.1 0.72
101 0.76 3.09 0.8 2.62 0 0.23 0.27 0.55 87.49 0.12 0.41 2.95 0.72
100 0 2.38 0.66 2.64 0 0.24 0.22 0.39 89.17 0.14 0.41 2.97 0.77
99 1.62 4.2 0.79 3.32 0 0.33 0.28 0.46 84.62 0.14 0.37 3.15 0.73
98 0.19 5.12 0.84 3.71 0 0.38 0.26 0.46 84.21 0.26 0.4 3.38 0.79
97 1.13 5.76 0.99 4.1 0 0.45 0.28 0.49 82.21 0.16 0.42 3.2 0.8
96 0.41 6.11 1.08 4.76 0 0.45 0.35 0.61 81.79 0.29 0.39 2.92 0.84
95 1.3 6.65 0.94 4.83 0 0.36 0.34 0.63 80.59 0.25 0.33 2.94 0.84
94 0.83 5.28 0.97 4.44 0 0.32 0.3 0.63 83.05 0.29 0.34 2.68 0.86
93 1.73 5.06 1.07 4.32 0 0.25 0.31 0.6 82.7 0.29 0.38 2.52 0.78
92 0.81 5.52 1.07 5.44 0 0.23 0.32 0.63 81.69 0.26 0.37 2.8 0.86
91 0.41 4.93 1.33 6.06 0 0.2 0.27 0.74 81.68 0.26 0.4 2.9 0.83
90 1.13 5 1.41 6.87 0 0.24 0.27 0.84 80.31 0.26 0.37 2.52 0.78
89 2.31 3.76 1.28 7.76 0 0.34 0.25 1.22 79.63 0.33 0.3 2.19 0.64
88 1.29 1.93 1.31 8.71 0.02 0.37 0.29 1.01 81.13 0.32 0.28 2.65 0.69
87 0.18 1.68 1.48 8.39 0 0.35 0.31 1.1 82 0.31 0.28 3.26 0.65
86 0.02 2.37 1.63 8.59 0 0.4 0.24 0.95 80.48 0.32 0.34 4.02 0.65
103
85 0.16 2.48 1.62 8.27 0 0.37 0.1 0.97 80.45 0.32 0.37 4.26 0.63
84 0 3.94 1.56 7.23 0.04 0.37 0.1 0.85 80.27 0.21 0.41 4.42 0.61
83 0 6.69 1.48 7.54 0 0.35 0.14 0.83 77.56 0.26 0.54 3.99 0.63
82 0 8.34 1.64 8.38 0.06 0.43 0.2 1.11 73.98 0.27 0.55 4.36 0.69
81 1.05 9.96 1.81 9 0.01 0.49 0.23 0.9 70.77 0.31 0.49 4.28 0.68
80 0.78 10.66 1.78 8.18 0 0.5 0.2 0.69 71.71 0.28 0.54 3.91 0.79
79 1.22 9.41 1.13 6.27 0 0.42 0.25 0.75 75.34 0.26 0.45 3.7 0.79
78 0.04 8.68 0.95 4.24 0 0.35 0.25 0.55 80.02 0.31 0.37 3.39 0.85
77 1.02 8.28 0.61 3.26 0 0.28 0.27 0.32 81.36 0.16 0.38 3.25 0.82
76 0 8.24 0.95 4.05 0.02 0.33 0.29 0.43 80.71 0.25 0.33 3.54 0.87
75 0.8 8.54 1.13 5.16 0.01 0.33 0.27 0.66 77.95 0.22 0.37 3.8 0.76
74 0.3 8.78 1.1 6.73 0 0.38 0.26 0.64 76.6 0.24 0.41 3.77 0.78
73 1.45 7.53 1.43 8.7 0 0.34 0.21 0.89 74.43 0.27 0.31 3.71 0.73
72 0 5.72 1.86 13.72 0 0.36 0.35 1.11 71.7 0.33 0.34 3.87 0.65
71 1.1 4.79 2.46 17.17 0 0.29 0.38 1.55 67.18 0.4 0.36 3.74 0.57
70 1.44 3.95 2.22 19.14 0 0.24 0.29 1.65 65.74 0.44 0.33 3.99 0.57
69 0.36 5.53 2.33 19.45 0 0.21 0.33 1.6 64.43 0.38 0.33 4.44 0.61
68 0.64 7.5 2.68 18.09 0 0.24 0.36 1.67 62.42 0.43 0.38 4.97 0.62
67 0.56 9.38 2.01 15.05 0.01 0.25 0.36 1.23 64.1 0.46 0.44 5.48 0.68
66 0.34 12.69 1.82 10.94 0 0.27 0.39 1.04 65.04 0.33 0.37 6.03 0.74
65 0.3 13.26 1.89 8.62 0.05 0.25 0.35 0.93 66.53 0.34 0.48 6.25 0.74
64 0.92 12.1 1.43 7.27 0 0.26 0.41 0.79 69.07 0.25 0.44 6.34 0.71
63 0.36 10.69 1.12 5.66 0.01 0.22 0.41 0.57 73.31 0.23 0.45 6.29 0.69
62 1.1 9.9 0.91 4.49 0 0.19 0.42 0.44 75.47 0.17 0.45 5.74 0.73
61 1.33 8.53 0.83 3.79 0 0.25 0.32 0.32 78.07 0.14 0.48 5.26 0.68
60 0 7.71 0.75 3.33 0 0.19 0.33 0.33 80.95 0.13 0.47 5.09 0.72
59 0.86 8.52 0.87 3.59 0 0.21 0.3 0.48 79.16 0.17 0.45 4.71 0.67
58 1.38 8.16 0.78 3.73 0 0.21 0.3 0.44 79.41 0.17 0.32 4.49 0.62
57 0.25 8.1 0.81 4.17 0.01 0.25 0.31 0.48 79.78 0.13 0.36 4.72 0.65
56 0.46 7.98 1 4.84 0.02 0.24 0.36 0.48 78.13 0.15 0.44 5.22 0.67
55 0 9.78 1.02 6.11 0.08 0.23 0.28 0.9 74.85 0.2 0.46 5.4 0.7
54 1.13 12.07 1.5 7.37 0.01 0.28 0.28 0.69 69.62 0.29 0.44 5.56 0.76
53 0.15 12.27 1.65 8.91 0.03 0.29 0.33 0.9 68.01 0.35 0.48 5.82 0.82
52 0.44 12.77 2.17 10.66 0.01 0.34 0.3 1.26 64.84 0.31 0.4 5.74 0.75
51 0.48 12.88 2.23 11.12 0.02 0.47 0.29 1.73 63.06 0.36 0.39 6.24 0.73
50 2.52 11.98 2.53 12.35 0 0.56 0.33 1.67 60.91 0.3 0.38 5.78 0.68
49 0.75 11.2 2.43 12.56 0.01 0.58 0.19 1.9 63.26 0.29 0.39 5.75 0.71
48 0.2 12.3 2.58 11.63 0.05 0.65 0.23 1.77 64.07 0.26 0.35 5.19 0.72
47 1.72 12.4 1.98 9.74 0 1.41 0.16 1.56 64.81 0.39 0.37 4.72 0.75
46 0.8 12.92 1.79 8.74 0.03 1.58 0.17 1.12 67.15 0.3 0.37 4.27 0.77
45 1.73 12.33 1.53 7.49 0.02 1.39 0.18 0.96 69.03 0.28 0.35 3.93 0.78
44 0.46 12.35 1.51 7.92 0 1.29 0.23 0.99 69.82 0.33 0.36 3.93 0.8
43 1.9 12.38 1.57 8.24 0 0.95 0.14 0.88 68.46 0.29 0.36 4.07 0.76
104
42 1.44 11.82 1.3 8.3 0.05 0.69 0.26 0.91 69.76 0.31 0.36 4.05 0.74
41 1.25 10.3 1.51 8.27 0.11 0.32 0.2 0.83 71.77 0.33 0.34 3.98 0.8
40 0 9.44 1.18 9.24 0 0.22 0.16 0.78 73.62 0.28 0.33 3.95 0.8
39 1.81 7.57 1.28 10.83 0 0.2 0.13 0.92 72.4 0.22 0.27 3.67 0.7
38 0.48 4.94 1.23 12.04 0.02 0.19 0.16 1 75.25 0.28 0.31 3.35 0.75
37 0 3.37 1.67 13.04 0 0.17 0.13 1.02 76.44 0.25 0.26 2.94 0.72
36 0.53 2.12 1.68 13.07 0 0.16 0.15 1.15 77.65 0.24 0.23 2.35 0.68
35 0 1.57 1.29 12.21 0 0.19 0.13 0.9 80.34 0.26 0.23 2.26 0.63
34 0 0.95 1.3 10.44 0 0.21 0.21 0.76 82.81 0.26 0.21 2.19 0.66
33 0.56 1.62 1.22 8.48 0 0.21 0.15 0.63 83.78 0.17 0.24 2.26 0.67
32 0 1.34 0.98 8.61 0 0.24 0.22 0.64 84.47 0.22 0.22 2.33 0.72
31 0 2.01 0.94 7.6 0 0.2 0.18 0.48 85.23 0.23 0.23 2.24 0.65
30 0 1.23 1.01 8.13 0 0.2 0.16 0.56 85.25 0.14 0.29 2.38 0.65
29 1.32 1.87 1.35 9.14 0 0.25 0.13 0.68 82.06 0.15 0.28 2.17 0.6
28 0 1.25 1.34 10.27 0 0.25 0.14 0.67 82.57 0.16 0.3 2.42 0.62
27 2.26 1.85 1.07 10.3 0 0.25 0.12 0.67 80.18 0.14 0.25 2.37 0.54
26 0.43 1.6 1.62 12.42 0 0.21 0.16 1.05 79.26 0.19 0.28 2.2 0.57
25 0 0.96 1.76 16.07 0 0.15 0.2 1.07 76.91 0.29 0.27 1.78 0.54
24 0.57 1.75 2.16 18.55 0 0.21 0.22 1.57 71.81 0.34 0.28 1.99 0.55
23 0.14 2.41 2.37 22.19 0 0.18 0.23 1.68 67.06 0.34 0.26 2.65 0.48
22 0.15 3.5 2.72 24.63 0 0.26 0.23 1.93 61.7 0.43 0.29 3.67 0.5
21 0 3.8 2.45 23.73 0 0.24 0.2 1.9 62.29 0.43 0.31 4.11 0.55
20 1 3.87 1.63 20.17 0 0.25 0.24 1.78 65.64 0.33 0.36 4.14 0.6
19 0.64 4.29 1.92 17.01 0 0.22 0.16 1.13 69.32 0.3 0.32 4.05 0.62
18 1.31 4.82 1.8 14.13 0 0.24 0.28 0.87 71.64 0.29 0.29 3.68 0.65
17 0 5.19 1.45 11.33 0 0.29 0.27 0.75 76.21 0.33 0.3 3.14 0.74
16 1.27 6.83 1.28 9.91 0 0.24 0.29 0.69 75.27 0.25 0.28 2.96 0.73
15 2.56 8.33 1.31 10.09 0 0.31 0.3 0.61 72.34 0.26 0.3 2.84 0.74
14 1.32 8.36 1.39 11.64 0 0.35 0.47 0.91 70.68 0.24 0.3 3.63 0.72
13 0.01 8.05 1.27 12.92 0 0.41 0.4 1.02 70.52 0.31 0.27 4.09 0.72
12 0.87 6.08 1.53 15.95 0 0.51 0.47 0.76 68.35 0.32 0.28 4.17 0.71
11 1.01 5.03 1.54 18.07 0 0.55 0.38 0.77 67.67 0.3 0.25 3.76 0.66
10 1.64 3.07 1.19 21.55 0 0.57 0.54 0.82 66.11 0.2 0.18 3.55 0.58
9 0 1.74 1.49 27.1 0 0.81 0.51 0.89 63.2 0.25 0.18 3.31 0.53
8 1.6 0.88 1.56 30.8 0 0.95 0.61 1.07 58.99 0.24 0.15 2.68 0.48
7 1.38 1.15 1.72 31.64 0 1.1 0.63 1.05 58.15 0.25 0.13 2.36 0.43
6 2.16 1.11 1.55 32.49 0 1.28 0.75 1.1 56.56 0.21 0.12 2.26 0.41
5 0.36 1.04 1.43 33.07 0 1.44 0.77 1.09 57.73 0.2 0.16 2.27 0.44
4 0.45 1.27 1.32 33.99 0 1.46 0.83 1.07 56.71 0.17 0.18 2.1 0.44
3 0.32 1.28 1.42 35.91 0 1.32 1.08 1.09 54.63 0.15 0.16 2.24 0.41
2 0.71 1.25 1.57 37.78 0 1.38 1.25 1.27 51.63 0.15 0.13 2.49 0.4
1 0.27 1.09 1.55 39.98 0 1.26 1.23 1.3 49.95 0.14 0.18 2.6 0.44
105
Normalized Elemental Abundances for Billet Aa (Iron and Sodium):
Fe/Ca Fe/(Ca+Mg) Fe/Ti Fe/Al Fe/S Na/Ca Na/(Ca+Mg) Na/Ti Na/Al Na/S
166 0.1286 0.1257 24.4571 3.7380 12.5882 0.0116 0.0113 2.2000 0.3362 1.1324
165 0.1118 0.1099 22.4412 3.6860 12.5082 0.0399 0.0392 8.0000 1.3140 4.4590
164 0.0979 0.0956 21.7500 3.4627 11.0476 0.0326 0.0319 7.2500 1.1542 3.6825
163 0.0732 0.0717 18.9310 2.7727 8.7143 0.0317 0.0311 8.2069 1.2020 3.7778
162 0.0514 0.0502 13.9655 2.6645 5.7042 0.0283 0.0276 7.6897 1.4671 3.1408
161 0.0272 0.0266 10.9524 1.9828 2.8049 0.0102 0.0099 4.0952 0.7414 1.0488
160 0.0174 0.0170 6.5217 1.4851 1.5625 0.0097 0.0095 3.6522 0.8317 0.8750
159 0.0312 0.0304 11.0000 2.4220 2.3571 0.0161 0.0156 5.6667 1.2477 1.2143
158 0.0327 0.0319 9.9643 2.7900 2.1136 0.0084 0.0082 2.5714 0.7200 0.5455
157 0.0317 0.0308 12.6190 2.6768 1.8662 0.0296 0.0287 11.7619 2.4949 1.7394
156 0.0292 0.0286 14.0000 2.6250 1.7143 0.0041 0.0040 1.9444 0.3646 0.2381
155 0.0189 0.0185 8.3000 1.7849 1.0779 0.0040 0.0039 1.7500 0.3763 0.2273
154 0.0070 0.0069 3.6471 0.8267 0.3669 0.0180 0.0177 9.4118 2.1333 0.9467
153 0.0047 0.0047 2.0476 0.6935 0.2606 0.0160 0.0157 6.9048 2.3387 0.8788
152 0.0036 0.0035 1.3750 0.7857 0.1976 0.0112 0.0111 4.2917 2.4524 0.6168
151 0.0035 0.0034 1.6000 0.6809 0.1658 0.0042 0.0042 1.9500 0.8298 0.2021
150 0.0044 0.0043 1.9048 1.2500 0.2116 0.0210 0.0208 9.1429 6.0000 1.0159
149 0.0131 0.0128 14.6250 2.7857 0.7006 0.0260 0.0255 29.1250 5.5476 1.3952
148 0.0201 0.0197 9.4211 3.3774 1.1548 0.0151 0.0147 7.0526 2.5283 0.8645
147 0.0231 0.0226 10.1500 2.2308 1.4500 0.0142 0.0139 6.2500 1.3736 0.8929
146 0.0251 0.0246 9.2500 2.3617 1.6947 0.0035 0.0034 1.2917 0.3298 0.2366
145 0.0230 0.0226 8.1600 2.7945 1.7288 0.0106 0.0104 3.7600 1.2877 0.7966
144 0.0164 0.0160 7.6316 1.6667 1.2393 0.0211 0.0207 9.8421 2.1494 1.5983
143 0.0109 0.0107 5.0000 1.8182 0.9709 0.0081 0.0080 3.7500 1.3636 0.7282
142 0.0119 0.0117 6.9375 3.4688 1.3059 0.0000 0.0000 0.0000 0.0000 0.0000
141 0.0220 0.0212 9.3810 4.3778 2.7361 0.0036 0.0035 1.5238 0.7111 0.4444
140 0.0404 0.0382 14.2083 4.8714 5.3281 0.0079 0.0075 2.7917 0.9571 1.0469
139 0.0597 0.0540 18.5600 4.1062 6.1053 0.0008 0.0007 0.2400 0.0531 0.0789
138 0.0664 0.0579 14.5152 3.5746 6.7465 0.0202 0.0177 4.4242 1.0896 2.0563
137 0.0606 0.0528 12.6000 3.0625 6.3913 0.0111 0.0097 2.3143 0.5625 1.1739
136 0.0425 0.0382 10.1875 2.3121 6.6531 0.0085 0.0076 2.0313 0.4610 1.3265
135 0.0277 0.0261 7.5667 2.0636 4.8298 0.0120 0.0113 3.2667 0.8909 2.0851
134 0.0192 0.0187 5.8929 1.4602 3.8372 0.0048 0.0046 1.4643 0.3628 0.9535
133 0.0180 0.0177 5.4138 1.6526 4.2432 0.0077 0.0075 2.3103 0.7053 1.8108
132 0.0162 0.0160 4.7667 1.5053 4.4688 0.0133 0.0131 3.9000 1.2316 3.6563
131 0.0156 0.0154 4.6667 1.7073 4.6667 0.0029 0.0029 0.8667 0.3171 0.8667
130 0.0159 0.0157 7.9444 1.5714 4.3333 0.0074 0.0072 3.6667 0.7253 2.0000
129 0.0157 0.0154 6.3636 2.1212 4.5161 0.0161 0.0158 6.5455 2.1818 4.6452
106
128 0.0171 0.0166 8.0000 2.6667 4.9032 0.0156 0.0152 7.3158 2.4386 4.4839
127 0.0184 0.0178 5.4667 2.7333 5.2903 0.0038 0.0037 1.1333 0.5667 1.0968
126 0.0185 0.0177 7.8095 2.1867 4.6857 0.0002 0.0002 0.0952 0.0267 0.0571
125 0.0187 0.0180 6.9167 2.3714 5.7241 0.0046 0.0044 1.7083 0.5857 1.4138
124 0.0179 0.0172 9.3529 2.3731 4.9688 0.0000 0.0000 0.0000 0.0000 0.0000
123 0.0158 0.0153 6.4091 1.9054 4.2727 0.0025 0.0024 1.0000 0.2973 0.6667
122 0.0145 0.0140 5.5652 2.1333 3.7647 0.0209 0.0203 8.0435 3.0833 5.4412
121 0.0140 0.0137 3.7576 1.9077 4.1333 0.0211 0.0207 5.6667 2.8769 6.2333
120 0.0140 0.0138 5.7273 1.4651 4.0645 0.0030 0.0029 1.2273 0.3140 0.8710
119 0.0134 0.0132 3.9032 1.4070 4.1724 0.0000 0.0000 0.0000 0.0000 0.0000
118 0.0118 0.0116 3.8889 1.4789 4.2000 0.0221 0.0218 7.2963 2.7746 7.8800
117 0.0118 0.0117 4.2400 1.6825 3.6552 0.0194 0.0191 6.9600 2.7619 6.0000
116 0.0122 0.0119 4.4000 1.2941 5.0000 0.0086 0.0085 3.1200 0.9176 3.5455
115 0.0139 0.0137 5.9524 2.0833 4.8077 0.0175 0.0171 7.4762 2.6167 6.0385
114 0.0143 0.0140 5.0000 2.5490 5.0000 0.0004 0.0004 0.1538 0.0784 0.1538
113 0.0150 0.0147 4.8214 2.9348 5.6250 0.0159 0.0156 5.1071 3.1087 5.9583
112 0.0165 0.0161 6.4348 1.7619 6.4348 0.0128 0.0125 5.0000 1.3690 5.0000
111 0.0174 0.0172 6.9130 2.2394 7.2273 0.0000 0.0000 0.0000 0.0000 0.0000
110 0.0199 0.0196 7.5000 2.4000 6.4286 0.0022 0.0022 0.8333 0.2667 0.7143
109 0.0231 0.0226 7.9231 2.6410 7.1034 0.0067 0.0066 2.3077 0.7692 2.0690
108 0.0244 0.0240 8.0370 2.5833 7.7500 0.0057 0.0056 1.8889 0.6071 1.8214
107 0.0226 0.0222 10.0500 2.6447 9.5714 0.0128 0.0126 5.7000 1.5000 5.4286
106 0.0239 0.0235 10.5500 2.7051 9.5909 0.0238 0.0234 10.5000 2.6923 9.5455
105 0.0249 0.0245 11.2500 2.6471 11.8421 0.0019 0.0019 0.8500 0.2000 0.8947
104 0.0287 0.0281 13.9444 3.1375 11.4091 0.0267 0.0261 12.9444 2.9125 10.5909
103 0.0331 0.0321 13.9524 3.9067 13.9524 0.0000 0.0000 0.0000 0.0000 0.0000
102 0.0349 0.0339 17.2222 4.6970 14.7619 0.0000 0.0000 0.0000 0.0000 0.0000
101 0.0337 0.0326 24.5833 3.6875 12.8261 0.0087 0.0084 6.3333 0.9500 3.3043
100 0.0333 0.0324 21.2143 4.5000 12.3750 0.0000 0.0000 0.0000 0.0000 0.0000
99 0.0372 0.0355 22.5000 3.9873 9.5455 0.0191 0.0182 11.5714 2.0506 4.9091
98 0.0401 0.0378 13.0000 4.0238 8.8947 0.0023 0.0021 0.7308 0.2262 0.5000
97 0.0389 0.0364 20.0000 3.2323 7.1111 0.0137 0.0128 7.0625 1.1414 2.5111
96 0.0357 0.0332 10.0690 2.7037 6.4889 0.0050 0.0047 1.4138 0.3796 0.9111
95 0.0365 0.0337 11.7600 3.1277 8.1667 0.0161 0.0149 5.2000 1.3830 3.6111
94 0.0323 0.0303 9.2414 2.7629 8.3750 0.0100 0.0094 2.8621 0.8557 2.5938
93 0.0305 0.0287 8.6897 2.3551 10.0800 0.0209 0.0197 5.9655 1.6168 6.9200
92 0.0343 0.0321 10.7692 2.6168 12.1739 0.0099 0.0093 3.1154 0.7570 3.5217
91 0.0355 0.0335 11.1538 2.1805 14.5000 0.0050 0.0047 1.5769 0.3083 2.0500
90 0.0314 0.0295 9.6923 1.7872 10.5000 0.0141 0.0132 4.3462 0.8014 4.7083
89 0.0275 0.0263 6.6364 1.7109 6.4412 0.0290 0.0277 7.0000 1.8047 6.7941
88 0.0327 0.0319 8.2813 2.0229 7.1622 0.0159 0.0155 4.0313 0.9847 3.4865
87 0.0398 0.0390 10.5161 2.2027 9.3143 0.0022 0.0022 0.5806 0.1216 0.5143
86 0.0500 0.0485 12.5625 2.4663 10.0500 0.0002 0.0002 0.0625 0.0123 0.0500
107
85 0.0530 0.0514 13.3125 2.6296 11.5135 0.0020 0.0019 0.5000 0.0988 0.4324
84 0.0551 0.0525 21.0476 2.8333 11.9459 0.0000 0.0000 0.0000 0.0000 0.0000
83 0.0514 0.0474 15.3462 2.6959 11.4000 0.0000 0.0000 0.0000 0.0000 0.0000
82 0.0589 0.0530 16.1481 2.6585 10.1395 0.0000 0.0000 0.0000 0.0000 0.0000
81 0.0605 0.0530 13.8065 2.3646 8.7347 0.0148 0.0130 3.3871 0.5801 2.1429
80 0.0545 0.0475 13.9643 2.1966 7.8200 0.0109 0.0095 2.7857 0.4382 1.5600
79 0.0491 0.0437 14.2308 3.2743 8.8095 0.0162 0.0144 4.6923 1.0796 2.9048
78 0.0424 0.0382 10.9355 3.5684 9.6857 0.0005 0.0005 0.1290 0.0421 0.1143
77 0.0399 0.0363 20.3125 5.3279 11.6071 0.0125 0.0114 6.3750 1.6721 3.6429
76 0.0439 0.0398 14.1600 3.7263 10.7273 0.0000 0.0000 0.0000 0.0000 0.0000
75 0.0487 0.0439 17.2727 3.3628 11.5152 0.0103 0.0092 3.6364 0.7080 2.4242
74 0.0492 0.0442 15.7083 3.4273 9.9211 0.0039 0.0035 1.2500 0.2727 0.7895
73 0.0498 0.0453 13.7407 2.5944 10.9118 0.0195 0.0177 5.3704 1.0140 4.2647
72 0.0540 0.0500 11.7273 2.0806 10.7500 0.0000 0.0000 0.0000 0.0000 0.0000
71 0.0557 0.0520 9.3500 1.5203 12.8966 0.0164 0.0153 2.7500 0.4472 3.7931
70 0.0607 0.0573 9.0682 1.7973 16.6250 0.0219 0.0207 3.2727 0.6486 6.0000
69 0.0689 0.0635 11.6842 1.9056 21.1429 0.0056 0.0051 0.9474 0.1545 1.7143
68 0.0796 0.0711 11.5581 1.8545 20.7083 0.0103 0.0092 1.4884 0.2388 2.6667
67 0.0855 0.0746 11.9130 2.7264 21.9200 0.0087 0.0076 1.2174 0.2786 2.2400
66 0.0927 0.0776 18.2727 3.3132 22.3333 0.0052 0.0044 1.0303 0.1868 1.2593
65 0.0939 0.0783 18.3824 3.3069 25.0000 0.0045 0.0038 0.8824 0.1587 1.2000
64 0.0918 0.0781 25.3600 4.4336 24.3846 0.0133 0.0113 3.6800 0.6434 3.5385
63 0.0858 0.0749 27.3478 5.6161 28.5909 0.0049 0.0043 1.5652 0.3214 1.6364
62 0.0761 0.0672 33.7647 6.3077 30.2105 0.0146 0.0129 6.4706 1.2088 5.7895
61 0.0674 0.0607 37.5714 6.3373 21.0400 0.0170 0.0154 9.5000 1.6024 5.3200
60 0.0629 0.0574 39.1538 6.7867 26.7895 0.0000 0.0000 0.0000 0.0000 0.0000
59 0.0595 0.0537 27.7059 5.4138 22.4286 0.0109 0.0098 5.0588 0.9885 4.0952
58 0.0565 0.0513 26.4118 5.7564 21.3810 0.0174 0.0158 8.1176 1.7692 6.5714
57 0.0592 0.0537 36.3077 5.8272 18.8800 0.0031 0.0028 1.9231 0.3086 1.0000
56 0.0668 0.0606 34.8000 5.2200 21.7500 0.0059 0.0053 3.0667 0.4600 1.9167
55 0.0721 0.0638 27.0000 5.2941 23.4783 0.0000 0.0000 0.0000 0.0000 0.0000
54 0.0799 0.0681 19.1724 3.7067 19.8571 0.0162 0.0138 3.8966 0.7533 4.0357
53 0.0856 0.0725 16.6286 3.5273 20.0690 0.0022 0.0019 0.4286 0.0909 0.5172
52 0.0885 0.0740 18.5161 2.6452 16.8824 0.0068 0.0057 1.4194 0.2028 1.2941
51 0.0990 0.0822 17.3333 2.7982 13.2766 0.0076 0.0063 1.3333 0.2152 1.0213
50 0.0949 0.0793 19.2667 2.2846 10.3214 0.0414 0.0346 8.4000 0.9960 4.5000
49 0.0909 0.0772 19.8276 2.3663 9.9138 0.0119 0.0101 2.5862 0.3086 1.2931
48 0.0810 0.0680 19.9615 2.0116 7.9846 0.0031 0.0026 0.7692 0.0775 0.3077
47 0.0728 0.0611 12.1026 2.3838 3.3475 0.0265 0.0223 4.4103 0.8687 1.2199
46 0.0636 0.0533 14.2333 2.3855 2.7025 0.0119 0.0100 2.6667 0.4469 0.5063
45 0.0569 0.0483 14.0357 2.5686 2.8273 0.0251 0.0213 6.1786 1.1307 1.2446
44 0.0563 0.0478 11.9091 2.6026 3.0465 0.0066 0.0056 1.3939 0.3046 0.3566
43 0.0595 0.0503 14.0345 2.5924 4.2842 0.0278 0.0235 6.5517 1.2102 2.0000
108
42 0.0581 0.0496 13.0645 3.1154 5.8696 0.0206 0.0177 4.6452 1.1077 2.0870
41 0.0555 0.0485 12.0606 2.6358 12.4375 0.0174 0.0152 3.7879 0.8278 3.9063
40 0.0537 0.0476 14.1071 3.3475 17.9545 0.0000 0.0000 0.0000 0.0000 0.0000
39 0.0507 0.0459 16.6818 2.8672 18.3500 0.0250 0.0226 8.2273 1.4141 9.0500
38 0.0445 0.0418 11.9643 2.7236 17.6316 0.0064 0.0060 1.7143 0.3902 2.5263
37 0.0385 0.0368 11.7600 1.7605 17.2941 0.0000 0.0000 0.0000 0.0000 0.0000
36 0.0303 0.0295 9.7917 1.3988 14.6875 0.0068 0.0066 2.2083 0.3155 3.3125
35 0.0281 0.0276 8.6923 1.7519 11.8947 0.0000 0.0000 0.0000 0.0000 0.0000
34 0.0264 0.0261 8.4231 1.6846 10.4286 0.0000 0.0000 0.0000 0.0000 0.0000
33 0.0270 0.0265 13.2941 1.8525 10.7619 0.0067 0.0066 3.2941 0.4590 2.6667
32 0.0276 0.0272 10.5909 2.3776 9.7083 0.0000 0.0000 0.0000 0.0000 0.0000
31 0.0263 0.0257 9.7391 2.3830 11.2000 0.0000 0.0000 0.0000 0.0000 0.0000
30 0.0279 0.0275 17.0000 2.3564 11.9000 0.0000 0.0000 0.0000 0.0000 0.0000
29 0.0264 0.0259 14.4667 1.6074 8.6800 0.0161 0.0157 8.8000 0.9778 5.2800
28 0.0293 0.0289 15.1250 1.8060 9.6800 0.0000 0.0000 0.0000 0.0000 0.0000
27 0.0296 0.0289 16.9286 2.2150 9.4800 0.0282 0.0276 16.1429 2.1121 9.0400
26 0.0278 0.0272 11.5789 1.3580 10.4762 0.0054 0.0053 2.2632 0.2654 2.0476
25 0.0231 0.0229 6.1379 1.0114 11.8667 0.0000 0.0000 0.0000 0.0000 0.0000
24 0.0277 0.0271 5.8529 0.9213 9.4762 0.0079 0.0077 1.6765 0.2639 2.7143
23 0.0395 0.0381 7.7941 1.1181 14.7222 0.0021 0.0020 0.4118 0.0591 0.7778
22 0.0595 0.0563 8.5349 1.3493 14.1154 0.0024 0.0023 0.3488 0.0551 0.5769
21 0.0660 0.0622 9.5581 1.6776 17.1250 0.0000 0.0000 0.0000 0.0000 0.0000
20 0.0631 0.0596 12.5455 2.5399 16.5600 0.0152 0.0144 3.0303 0.6135 4.0000
19 0.0584 0.0550 13.5000 2.1094 18.4091 0.0092 0.0087 2.1333 0.3333 2.9091
18 0.0514 0.0481 12.6897 2.0444 15.3333 0.0183 0.0171 4.5172 0.7278 5.4583
17 0.0412 0.0386 9.5152 2.1655 10.8276 0.0000 0.0000 0.0000 0.0000 0.0000
16 0.0393 0.0361 11.8400 2.3125 12.3333 0.0169 0.0155 5.0800 0.9922 5.2917
15 0.0393 0.0352 10.9231 2.1679 9.1613 0.0354 0.0317 9.8462 1.9542 8.2581
14 0.0514 0.0459 15.1250 2.6115 10.3714 0.0187 0.0167 5.5000 0.9496 3.7714
13 0.0580 0.0521 13.1935 3.2205 9.9756 0.0001 0.0001 0.0323 0.0079 0.0244
12 0.0610 0.0560 13.0313 2.7255 8.1765 0.0127 0.0117 2.7188 0.5686 1.7059
11 0.0556 0.0517 12.5333 2.4416 6.8364 0.0149 0.0139 3.3667 0.6558 1.8364
10 0.0537 0.0513 17.7500 2.9832 6.2281 0.0248 0.0237 8.2000 1.3782 2.8772
9 0.0524 0.0510 13.2400 2.2215 4.0864 0.0000 0.0000 0.0000 0.0000 0.0000
8 0.0454 0.0448 11.1667 1.7179 2.8211 0.0271 0.0267 6.6667 1.0256 1.6842
7 0.0406 0.0398 9.4400 1.3721 2.1455 0.0237 0.0233 5.5200 0.8023 1.2545
6 0.0400 0.0392 10.7619 1.4581 1.7656 0.0382 0.0375 10.2857 1.3935 1.6875
5 0.0393 0.0386 11.3500 1.5874 1.5764 0.0062 0.0061 1.8000 0.2517 0.2500
4 0.0370 0.0362 12.3529 1.5909 1.4384 0.0079 0.0078 2.6471 0.3409 0.3082
3 0.0410 0.0401 14.9333 1.5775 1.6970 0.0059 0.0057 2.1333 0.2254 0.2424
2 0.0482 0.0471 16.6000 1.5860 1.8043 0.0138 0.0134 4.7333 0.4522 0.5145
1 0.0521 0.0509 18.5714 1.6774 2.0635 0.0054 0.0053 1.9286 0.1742 0.2143
109
Normalized Elemental Abundances for Billet Aa (Magnesium and Strontium):
Mg/Ca Mg/(Ca+Mg) Mg/Ti Mg/Al Mg/S Sr/Ca Sr/(Ca+Mg) Sr/Ti Sr/Al Sr/S
166 0.0236 0.0231 4.4857 0.6856 2.3088 0.0197 0.0192 3.7429 0.5721 1.9265
165 0.0179 0.0176 3.5882 0.5894 2.0000 0.0183 0.0180 3.6765 0.6039 2.0492
164 0.0235 0.0229 5.2188 0.8308 2.6508 0.0179 0.0175 3.9688 0.6318 2.0159
163 0.0203 0.0199 5.2414 0.7677 2.4127 0.0168 0.0165 4.3448 0.6364 2.0000
162 0.0233 0.0228 6.3448 1.2105 2.5915 0.0156 0.0152 4.2414 0.8092 1.7324
161 0.0244 0.0238 9.8095 1.7759 2.5122 0.0133 0.0129 5.3333 0.9655 1.3659
160 0.0231 0.0226 8.6957 1.9802 2.0833 0.0127 0.0124 4.7826 1.0891 1.1458
159 0.0277 0.0269 9.7500 2.1468 2.0893 0.0125 0.0122 4.4167 0.9725 0.9464
158 0.0259 0.0252 7.8929 2.2100 1.6742 0.0123 0.0120 3.7500 1.0500 0.7955
157 0.0296 0.0287 11.7619 2.4949 1.7394 0.0121 0.0117 4.8095 1.0202 0.7113
156 0.0226 0.0221 10.8333 2.0313 1.3265 0.0124 0.0121 5.9444 1.1146 0.7279
155 0.0218 0.0213 9.5500 2.0538 1.2403 0.0127 0.0124 5.5500 1.1935 0.7208
154 0.0184 0.0180 9.5882 2.1733 0.9645 0.0121 0.0118 6.2941 1.4267 0.6331
153 0.0185 0.0182 8.0000 2.7097 1.0182 0.0122 0.0120 5.2857 1.7903 0.6727
152 0.0161 0.0159 6.1667 3.5238 0.8862 0.0122 0.0120 4.6667 2.6667 0.6707
151 0.0149 0.0147 6.9000 2.9362 0.7150 0.0129 0.0127 5.9500 2.5319 0.6166
150 0.0138 0.0136 6.0000 3.9375 0.6667 0.0121 0.0119 5.2381 3.4375 0.5820
149 0.0217 0.0212 24.2500 4.6190 1.1617 0.0117 0.0115 13.1250 2.5000 0.6287
148 0.0213 0.0209 10.0000 3.5849 1.2258 0.0116 0.0113 5.4211 1.9434 0.6645
147 0.0205 0.0201 9.0000 1.9780 1.2857 0.0116 0.0114 5.1000 1.1209 0.7286
146 0.0207 0.0202 7.6250 1.9468 1.3969 0.0117 0.0115 4.3333 1.1064 0.7939
145 0.0191 0.0187 6.7600 2.3151 1.4322 0.0116 0.0114 4.1200 1.4110 0.8729
144 0.0210 0.0206 9.7895 2.1379 1.5897 0.0116 0.0114 5.4211 1.1839 0.8803
143 0.0141 0.0139 6.5000 2.3636 1.2621 0.0115 0.0114 5.3000 1.9273 1.0291
142 0.0187 0.0184 10.8750 5.4375 2.0471 0.0114 0.0112 6.6250 3.3125 1.2471
141 0.0338 0.0327 14.4286 6.7333 4.2083 0.0108 0.0105 4.6190 2.1556 1.3472
140 0.0585 0.0553 20.5833 7.0571 7.7188 0.0103 0.0097 3.6250 1.2429 1.3594
139 0.1051 0.0951 32.6800 7.2301 10.7500 0.0109 0.0099 3.4000 0.7522 1.1184
138 0.1462 0.1276 31.9697 7.8731 14.8592 0.0119 0.0104 2.6061 0.6418 1.2113
137 0.1471 0.1282 30.5714 7.4306 15.5072 0.0117 0.0102 2.4286 0.5903 1.2319
136 0.1114 0.1002 26.7188 6.0638 17.4490 0.0119 0.0107 2.8438 0.6454 1.8571
135 0.0622 0.0586 17.0000 4.6364 10.8511 0.0111 0.0105 3.0333 0.8273 1.9362
134 0.0269 0.0262 8.2857 2.0531 5.3953 0.0110 0.0107 3.3929 0.8407 2.2093
133 0.0152 0.0150 4.5862 1.4000 3.5946 0.0107 0.0106 3.2414 0.9895 2.5405
132 0.0110 0.0109 3.2333 1.0211 3.0313 0.0105 0.0104 3.1000 0.9789 2.9063
131 0.0119 0.0118 3.5667 1.3049 3.5667 0.0109 0.0108 3.2667 1.1951 3.2667
130 0.0149 0.0147 7.4444 1.4725 4.0606 0.0107 0.0105 5.3333 1.0549 2.9091
129 0.0183 0.0180 7.4545 2.4848 5.2903 0.0110 0.0108 4.4545 1.4848 3.1613
110
128 0.0267 0.0260 12.5263 4.1754 7.6774 0.0109 0.0106 5.1053 1.7018 3.1290
127 0.0347 0.0336 10.3333 5.1667 10.0000 0.0110 0.0106 3.2667 1.6333 3.1613
126 0.0402 0.0386 17.0000 4.7600 10.2000 0.0113 0.0108 4.7619 1.3333 2.8571
125 0.0402 0.0386 14.8750 5.1000 12.3103 0.0110 0.0106 4.0833 1.4000 3.3793
124 0.0432 0.0414 22.5882 5.7313 12.0000 0.0116 0.0111 6.0588 1.5373 3.2188
123 0.0347 0.0335 14.0909 4.1892 9.3939 0.0116 0.0113 4.7273 1.4054 3.1515
122 0.0294 0.0285 11.3043 4.3333 7.6471 0.0105 0.0102 4.0435 1.5500 2.7353
121 0.0214 0.0210 5.7576 2.9231 6.3333 0.0107 0.0105 2.8788 1.4615 3.1667
120 0.0145 0.0143 5.9545 1.5233 4.2258 0.0105 0.0104 4.3182 1.1047 3.0645
119 0.0134 0.0132 3.9032 1.4070 4.1724 0.0105 0.0104 3.0645 1.1047 3.2759
118 0.0133 0.0132 4.4074 1.6761 4.7600 0.0108 0.0106 3.5556 1.3521 3.8400
117 0.0153 0.0151 5.4800 2.1746 4.7241 0.0107 0.0106 3.8400 1.5238 3.3103
116 0.0199 0.0195 7.2000 2.1176 8.1818 0.0111 0.0109 4.0000 1.1765 4.5455
115 0.0202 0.0198 8.6190 3.0167 6.9615 0.0106 0.0104 4.5238 1.5833 3.6538
114 0.0208 0.0203 7.2692 3.7059 7.2692 0.0113 0.0111 3.9615 2.0196 3.9615
113 0.0184 0.0181 5.9286 3.6087 6.9167 0.0111 0.0109 3.5714 2.1739 4.1667
112 0.0231 0.0226 9.0000 2.4643 9.0000 0.0108 0.0106 4.2174 1.1548 4.2174
111 0.0132 0.0131 5.2609 1.7042 5.5000 0.0105 0.0104 4.1739 1.3521 4.3636
110 0.0169 0.0166 6.3750 2.0400 5.4643 0.0102 0.0100 3.8333 1.2267 3.2857
109 0.0197 0.0193 6.7692 2.2564 6.0690 0.0100 0.0098 3.4231 1.1410 3.0690
108 0.0173 0.0170 5.7037 1.8333 5.5000 0.0098 0.0096 3.2222 1.0357 3.1071
107 0.0153 0.0150 6.8000 1.7895 6.4762 0.0099 0.0097 4.4000 1.1579 4.1905
106 0.0186 0.0183 8.2000 2.1026 7.4545 0.0093 0.0091 4.1000 1.0513 3.7273
105 0.0165 0.0162 7.4500 1.7529 7.8421 0.0088 0.0086 3.9500 0.9294 4.1579
104 0.0208 0.0204 10.1111 2.2750 8.2727 0.0079 0.0077 3.8333 0.8625 3.1364
103 0.0294 0.0285 12.3810 3.4667 12.3810 0.0081 0.0079 3.4286 0.9600 3.4286
102 0.0288 0.0280 14.2222 3.8788 12.1905 0.0081 0.0079 4.0000 1.0909 3.4286
101 0.0353 0.0341 25.7500 3.8625 13.4348 0.0082 0.0079 6.0000 0.9000 3.1304
100 0.0267 0.0260 17.0000 3.6061 9.9167 0.0086 0.0084 5.5000 1.1667 3.2083
99 0.0496 0.0473 30.0000 5.3165 12.7273 0.0086 0.0082 5.2143 0.9241 2.2121
98 0.0608 0.0573 19.6923 6.0952 13.4737 0.0094 0.0088 3.0385 0.9405 2.0789
97 0.0701 0.0655 36.0000 5.8182 12.8000 0.0097 0.0091 5.0000 0.8081 1.7778
96 0.0747 0.0695 21.0690 5.6574 13.5778 0.0103 0.0096 2.8966 0.7778 1.8667
95 0.0825 0.0762 26.6000 7.0745 18.4722 0.0104 0.0096 3.3600 0.8936 2.3333
94 0.0636 0.0598 18.2069 5.4433 16.5000 0.0104 0.0097 2.9655 0.8866 2.6875
93 0.0612 0.0577 17.4483 4.7290 20.2400 0.0094 0.0089 2.6897 0.7290 3.1200
92 0.0676 0.0633 21.2308 5.1589 24.0000 0.0105 0.0099 3.3077 0.8037 3.7391
91 0.0604 0.0569 18.9615 3.7068 24.6500 0.0102 0.0096 3.1923 0.6241 4.1500
90 0.0623 0.0586 19.2308 3.5461 20.8333 0.0097 0.0091 3.0000 0.5532 3.2500
89 0.0472 0.0451 11.3939 2.9375 11.0588 0.0080 0.0077 1.9394 0.5000 1.8824
88 0.0238 0.0232 6.0313 1.4733 5.2162 0.0085 0.0083 2.1563 0.5267 1.8649
87 0.0205 0.0201 5.4194 1.1351 4.8000 0.0079 0.0078 2.0968 0.4392 1.8571
86 0.0294 0.0286 7.4063 1.4540 5.9250 0.0081 0.0078 2.0313 0.3988 1.6250
111
85 0.0308 0.0299 7.7500 1.5309 6.7027 0.0078 0.0076 1.9688 0.3889 1.7027
84 0.0491 0.0468 18.7619 2.5256 10.6486 0.0076 0.0072 2.9048 0.3910 1.6486
83 0.0863 0.0794 25.7308 4.5203 19.1143 0.0081 0.0075 2.4231 0.4257 1.8000
82 0.1127 0.1013 30.8889 5.0854 19.3953 0.0093 0.0084 2.5556 0.4207 1.6047
81 0.1407 0.1234 32.1290 5.5028 20.3265 0.0096 0.0084 2.1935 0.3757 1.3878
80 0.1487 0.1294 38.0714 5.9888 21.3200 0.0110 0.0096 2.8214 0.4438 1.5800
79 0.1249 0.1110 36.1923 8.3274 22.4048 0.0105 0.0093 3.0385 0.6991 1.8810
78 0.1085 0.0979 28.0000 9.1368 24.8000 0.0106 0.0096 2.7419 0.8947 2.4286
77 0.1018 0.0924 51.7500 13.5738 29.5714 0.0101 0.0091 5.1250 1.3443 2.9286
76 0.1021 0.0926 32.9600 8.6737 24.9697 0.0108 0.0098 3.4800 0.9158 2.6364
75 0.1096 0.0987 38.8182 7.5575 25.8788 0.0097 0.0088 3.4545 0.6726 2.3030
74 0.1146 0.1028 36.5833 7.9818 23.1053 0.0102 0.0091 3.2500 0.7091 2.0526
73 0.1012 0.0919 27.8889 5.2657 22.1471 0.0098 0.0089 2.7037 0.5105 2.1471
72 0.0798 0.0739 17.3333 3.0753 15.8889 0.0091 0.0084 1.9697 0.3495 1.8056
71 0.0713 0.0666 11.9750 1.9472 16.5172 0.0085 0.0079 1.4250 0.2317 1.9655
70 0.0601 0.0567 8.9773 1.7793 16.4583 0.0087 0.0082 1.2955 0.2568 2.3750
69 0.0858 0.0790 14.5526 2.3734 26.3333 0.0095 0.0087 1.6053 0.2618 2.9048
68 0.1202 0.1073 17.4419 2.7985 31.2500 0.0099 0.0089 1.4419 0.2313 2.5833
67 0.1463 0.1277 20.3913 4.6667 37.5200 0.0106 0.0093 1.4783 0.3383 2.7200
66 0.1951 0.1633 38.4545 6.9725 47.0000 0.0114 0.0095 2.2424 0.4066 2.7407
65 0.1993 0.1662 39.0000 7.0159 53.0400 0.0111 0.0093 2.1765 0.3915 2.9600
64 0.1752 0.1491 48.4000 8.4615 46.5385 0.0103 0.0087 2.8400 0.4965 2.7308
63 0.1458 0.1273 46.4783 9.5446 48.5909 0.0094 0.0082 3.0000 0.6161 3.1364
62 0.1312 0.1160 58.2353 10.8791 52.1053 0.0097 0.0086 4.2941 0.8022 3.8421
61 0.1093 0.0985 60.9286 10.2771 34.1200 0.0087 0.0079 4.8571 0.8193 2.7200
60 0.0952 0.0870 59.3077 10.2800 40.5789 0.0089 0.0081 5.5385 0.9600 3.7895
59 0.1076 0.0972 50.1176 9.7931 40.5714 0.0085 0.0076 3.9412 0.7701 3.1905
58 0.1028 0.0932 48.0000 10.4615 38.8571 0.0078 0.0071 3.6471 0.7949 2.9524
57 0.1015 0.0922 62.3077 10.0000 32.4000 0.0081 0.0074 5.0000 0.8025 2.6000
56 0.1021 0.0927 53.2000 7.9800 33.2500 0.0086 0.0078 4.4667 0.6700 2.7917
55 0.1307 0.1156 48.9000 9.5882 42.5217 0.0094 0.0083 3.5000 0.6863 3.0435
54 0.1734 0.1478 41.6207 8.0467 43.1071 0.0109 0.0093 2.6207 0.5067 2.7143
53 0.1804 0.1528 35.0571 7.4364 42.3103 0.0121 0.0102 2.3429 0.4970 2.8276
52 0.1969 0.1645 41.1935 5.8848 37.5588 0.0116 0.0097 2.4194 0.3456 2.2059
51 0.2042 0.1696 35.7778 5.7758 27.4043 0.0116 0.0096 2.0278 0.3274 1.5532
50 0.1967 0.1644 39.9333 4.7352 21.3929 0.0112 0.0093 2.2667 0.2688 1.2143
49 0.1770 0.1504 38.6207 4.6091 19.3103 0.0112 0.0095 2.4483 0.2922 1.2241
48 0.1920 0.1611 47.3077 4.7674 18.9231 0.0112 0.0094 2.7692 0.2791 1.1077
47 0.1913 0.1606 31.7949 6.2626 8.7943 0.0116 0.0097 1.9231 0.3788 0.5319
46 0.1924 0.1614 43.0667 7.2179 8.1772 0.0115 0.0096 2.5667 0.4302 0.4873
45 0.1786 0.1515 44.0357 8.0588 8.8705 0.0113 0.0096 2.7857 0.5098 0.5612
44 0.1769 0.1503 37.4242 8.1788 9.5736 0.0115 0.0097 2.4242 0.5298 0.6202
43 0.1808 0.1531 42.6897 7.8854 13.0316 0.0111 0.0094 2.6207 0.4841 0.8000
112
42 0.1694 0.1449 38.1290 9.0923 17.1304 0.0106 0.0091 2.3871 0.5692 1.0725
41 0.1435 0.1255 31.2121 6.8212 32.1875 0.0111 0.0097 2.4242 0.5298 2.5000
40 0.1282 0.1137 33.7143 8.0000 42.9091 0.0109 0.0096 2.8571 0.6780 3.6364
39 0.1046 0.0947 34.4091 5.9141 37.8500 0.0097 0.0088 3.1818 0.5469 3.5000
38 0.0656 0.0616 17.6429 4.0163 26.0000 0.0100 0.0094 2.6786 0.6098 3.9474
37 0.0441 0.0422 13.4800 2.0180 19.8235 0.0094 0.0090 2.8800 0.4311 4.2353
36 0.0273 0.0266 8.8333 1.2619 13.2500 0.0088 0.0085 2.8333 0.4048 4.2500
35 0.0195 0.0192 6.0385 1.2171 8.2632 0.0078 0.0077 2.4231 0.4884 3.3158
34 0.0115 0.0113 3.6538 0.7308 4.5238 0.0080 0.0079 2.5385 0.5077 3.1429
33 0.0193 0.0190 9.5294 1.3279 7.7143 0.0080 0.0078 3.9412 0.5492 3.1905
32 0.0159 0.0156 6.0909 1.3673 5.5833 0.0085 0.0084 3.2727 0.7347 3.0000
31 0.0236 0.0230 8.7391 2.1383 10.0500 0.0076 0.0075 2.8261 0.6915 3.2500
30 0.0144 0.0142 8.7857 1.2178 6.1500 0.0076 0.0075 4.6429 0.6436 3.2500
29 0.0228 0.0223 12.4667 1.3852 7.4800 0.0073 0.0071 4.0000 0.4444 2.4000
28 0.0151 0.0149 7.8125 0.9328 5.0000 0.0075 0.0074 3.8750 0.4627 2.4800
27 0.0231 0.0226 13.2143 1.7290 7.4000 0.0067 0.0066 3.8571 0.5047 2.1600
26 0.0202 0.0198 8.4211 0.9877 7.6190 0.0072 0.0070 3.0000 0.3519 2.7143
25 0.0125 0.0123 3.3103 0.5455 6.4000 0.0070 0.0069 1.8621 0.3068 3.6000
24 0.0244 0.0238 5.1471 0.8102 8.3333 0.0077 0.0075 1.6176 0.2546 2.6190
23 0.0359 0.0347 7.0882 1.0169 13.3889 0.0072 0.0069 1.4118 0.2025 2.6667
22 0.0567 0.0537 8.1395 1.2868 13.4615 0.0081 0.0077 1.1628 0.1838 1.9231
21 0.0610 0.0575 8.8372 1.5510 15.8333 0.0088 0.0083 1.2791 0.2245 2.2917
20 0.0590 0.0557 11.7273 2.3742 15.4800 0.0091 0.0086 1.8182 0.3681 2.4000
19 0.0619 0.0583 14.3000 2.2344 19.5000 0.0089 0.0084 2.0667 0.3229 2.8182
18 0.0673 0.0630 16.6207 2.6778 20.0833 0.0091 0.0085 2.2414 0.3611 2.7083
17 0.0681 0.0638 15.7273 3.5793 17.8966 0.0097 0.0091 2.2424 0.5103 2.5517
16 0.0907 0.0832 27.3200 5.3359 28.4583 0.0097 0.0089 2.9200 0.5703 3.0417
15 0.1152 0.1033 32.0385 6.3588 26.8710 0.0102 0.0092 2.8462 0.5649 2.3871
14 0.1183 0.1058 34.8333 6.0144 23.8857 0.0102 0.0091 3.0000 0.5180 2.0571
13 0.1142 0.1025 25.9677 6.3386 19.6341 0.0102 0.0092 2.3226 0.5669 1.7561
12 0.0890 0.0817 19.0000 3.9739 11.9216 0.0104 0.0095 2.2188 0.4641 1.3922
11 0.0743 0.0692 16.7667 3.2662 9.1455 0.0098 0.0091 2.2000 0.4286 1.2000
10 0.0464 0.0444 15.3500 2.5798 5.3860 0.0088 0.0084 2.9000 0.4874 1.0175
9 0.0275 0.0268 6.9600 1.1678 2.1481 0.0084 0.0082 2.1200 0.3557 0.6543
8 0.0149 0.0147 3.6667 0.5641 0.9263 0.0081 0.0080 2.0000 0.3077 0.5053
7 0.0198 0.0194 4.6000 0.6686 1.0455 0.0074 0.0073 1.7200 0.2500 0.3909
6 0.0196 0.0192 5.2857 0.7161 0.8672 0.0072 0.0071 1.9524 0.2645 0.3203
5 0.0180 0.0177 5.2000 0.7273 0.7222 0.0076 0.0075 2.2000 0.3077 0.3056
4 0.0224 0.0219 7.4706 0.9621 0.8699 0.0078 0.0076 2.5882 0.3333 0.3014
3 0.0234 0.0229 8.5333 0.9014 0.9697 0.0075 0.0073 2.7333 0.2887 0.3106
2 0.0242 0.0236 8.3333 0.7962 0.9058 0.0077 0.0076 2.6667 0.2548 0.2899
1 0.0218 0.0214 7.7857 0.7032 0.8651 0.0088 0.0086 3.1429 0.2839 0.3492
Abstract (if available)
Abstract
The Early Eocene Climatic Optimum (EECO, 52-50 Ma), a global hothouse climate associated with high temperatures and high CO₂ levels, marked the longest sustained warming period of the Cenozoic Era. The EECO is well recorded in the Eocene Green River Formation, a sedimentary formation deposited in a closed-basin lake system. The Green River closed-basin lake system, especially Lake Gosiute, had a highly dynamic lake volume and dramatically variable shoreline levels, because of its sensitivity to evaporation and precipitation. This study uses stromatolites from the LaClede Bed of the Green River Formation to create a fine-scale record of terrestrial paleoenvironmental and paleoclimate changes during the EECO. The stromatolites of the LaClede Bed were deposited in Lake Gosiute, and track the fluctuations of lake volume and shoreline levels through its depositional history. ❧ In a closed-basin lake where water enters solely through ground water, rivers, and precipitation, periods of lake filling and evaporation are recorded in the chemistry of lake water, which in turn can be recorded within the carbonate of stromatolites. Changes in δ¹³C, δ¹⁸O, and certain elemental abundances recorded in stromatolites are likely related to periods of precipitation and evaporation, which can be used to estimate shifting lake shore levels. First, light microscopy and petrographic methods were used to analyze the carbonate fabrics of the distinct stromatolite laminae to better characterize the environmental conditions in which they were deposited. Then, isotopic perturbations and elemental abundances were measured to assess climate change during the deposition of the stromatolites. In particular, this study introduces a novel application of micro-XRF spectroscopy to stromatolite-based paleoclimate reconstruction, where elemental abundances were analyzed via micro-XRF spectroscopy on the micrometer scale, which allows for stromatolite laminae analyses on a scale previously not presented. Thirteen distinct elemental abundances (Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, Mn, Fe, and Sr) were measured as vertical transects through the stromatolite laminae, and magnesium (used as a conservative lake level indicator), iron (used as a redox-sensitive biologic indicator), and strontium (a redox-insensitive elemental marker) are highlighted. Using these three lines of evidence, the LaClede stromatolites record a complex history of lake filling and evaporation during the EECO, rather than a simple transgressive system as previously hypothesized.
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University of Southern California Dissertations and Theses
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Asset Metadata
Creator
Mahseredjian, Taleen
(author)
Core Title
Green River formation stromatolites as a paleoclimate indicator: an investigation of the early Eocene climatic optimum through mass spectrometry, micro-X-ray fluorescence spectroscopy, and petrography
School
College of Letters, Arts and Sciences
Degree
Master of Science
Degree Program
Geological Sciences
Publication Date
05/06/2019
Defense Date
04/01/2019
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
Early Eocene Climatic Optimum,Green River Formation,OAI-PMH Harvest,paleoclimate,stromatolite,XRF
Format
application/pdf
(imt)
Language
English
Contributor
Electronically uploaded by the author
(provenance)
Advisor
Corsetti, Frank (
committee chair
), Berelson, William (
committee member
), Bottjer, David (
committee member
), Celestian, Aaron (
committee member
)
Creator Email
mahsered@usc.edu,tmahseredjian@gmail.com
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c89-167686
Unique identifier
UC11660724
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etd-Mahseredji-7413.pdf (filename),usctheses-c89-167686 (legacy record id)
Legacy Identifier
etd-Mahseredji-7413.pdf
Dmrecord
167686
Document Type
Thesis
Format
application/pdf (imt)
Rights
Mahseredjian, Taleen
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA
Tags
Early Eocene Climatic Optimum
Green River Formation
paleoclimate
stromatolite
XRF