Paleoecology of Beringian Lacustrine Deposits As Indicated by Ostracode

Home , Limnocythere, Limnocythere inopinata, Limnocytheridae, Sevier Lake

PALEOECOLOGY OF BERINGIAN LACUSTRINE DEPOSITS AS INDICATED BY NORTHERN HEMISPHERE OSTRACODE BIOGEOGRAPHY

A thesis submitted to Kent State University in partial fulfillment of the requirements for the degree of Master of Science

Kathryn J. Wells

December 2011

Thesis written by Kathryn J. Wells B.A., Kent State University, 2007 M.S., Kent State University, 2011

Approved by

______, Advisor Dr. Alison J. Smith

______, Chair, Department of Geology Dr. Daniel Holm

______, Dean, College of Arts and Sciences Dr. John R.D. Stalvey

TABLE OF CONTENTS

TABLE OF CONTENTS ...... iii

LIST OF FIGURES ...... v

LIST OF TABLES ...... vii

ACKNOWLEDGEMENTS ...... viii

ABSTRACT ...... xi

Introduction ...... 1

Background ...... 5

Location ...... 5

Regional Geology ...... 8

Study Proxies ...... 12

Regional Paleoecology of Beringia during the Late-Glacial ...... 13

Pollen ...... 14

Insects (Beetles and Chironomids) ...... 16

Ostracodes ...... 18

Methods...... 20

Lab Work ...... 21

Statistical Analysis ...... 23

Principal Component Analysis (PCA) – Spectral Reflectance ...... 24 Principal Component Analysis (PCA) - Ostracodes...... 26

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Cluster Analysis ...... 27 Modern Analog Technique ...... 27 Results ...... 29

Ostracode Assemblages ...... 29

Pteroloxa cumuloidea and Candona rectangulata Assemblage ...... 37 Ilyocypris biplicata and Limnocythere inopinata Assemblage ...... 44 Cytherissa lacustris Assemblage ...... 50 Cyclocypris cf. ampla Assemblage ...... 53 Spectral Reflectance (PCA) ...... 56

Ostracodes (PCA) ...... 65

Cluster Analysis ...... 74

Modern Analog Reconstruction ...... 77

Ostracode Zonation ...... 81

Discussion ...... 83

Conclusions ...... 93

References ...... 96

Appendix A: USGS 70-92 Sample Inventory ...... 114

LIST OF FIGURES

Figure 1. Map of Beringia...... 2

Figure 2. Late Pleistocene glaciation in Beringia...... 3

Figure 3. USGS 70-92 Location in northeastern Chukchi Sea...... 7

Figure 4. USGS 70-92 Stratigraphic Column...... 9

Figure 5. Vibracore Locations in the northeastern Chukchi Sea...... 10

Figure 6. Tectonic Setting of the Chukchi Shelf...... 11

Figure 7. Relief map of Beringia region...... 14

Figure 8. Tree macrofossils found on West and East Beringia ...... 16

Figure 9. USGS 70-92 Ostracode Abundance & Zonation...... 33

Figure 10. USGS 70-92 Ostracode Abundance & Zonation, Expanded...... 34

Figure 11. USGS 70-92 Common Ostracode Species ...... 36

Figure 12. Map of Pteroloxa cumuloidea ...... 40

Figure 13. Map of Candona rectangulata ...... 42

Figure 14. Map of Ilyocypris biplicata ...... 46

Figure 15. Map of Limnocythere inopinata...... 48

Figure 16. Map of Cytherissa lacustris...... 52

Figure 17. Map of Cyclocypris cf. ampla ...... 55

Figure 18. Spectral Reflectance Scree Plot from SPSS®...... 57

Figure 19. VPC_1 Spectral Graph...... 59

Figure 20. VPC_2 Spectral Graph...... 60

Figure 21. VPC_3 Spectral Graph...... 61

Figure 22. VPC_4 Spectral Graph...... 62

Figure 23. Downcore Reflectance Scores and Ostracode Abundance...... 63

Figure 24. VPC_4 from USGS 70-92 vs. VPC_1 from Regional Data...... 64

Figure 25. PCA Graph for Ostracodes (Axis 1 vs. 3) ...... 68

Figure 26. PCA Graph for Ostracodes (Axis 1 vs. 2) ...... 70

Figure 27. PCA Graph for Ostracodes and Spectral Reflectance (Axis 1 vs. 2) ...... 72

Figure 28. Cluster Dendrogram...... 76

Figure 29. Modern Analog Map...... 80

Figure 30. Relationship between Cytherissa, Candona, & Limnocythere...... 84

Figure 31. Distribution of Illite...... 88

Figure 32. Clay Provinces of the Arctic...... 88

Figure 33. NGRIP δ18O Record with Downcore Reflectance Scores ...... 91

Figure 34. Warm Arctic – Cold Continent Climate Pattern...... 92

Figure 35. Bering Land Bridge Region...... 95

LIST OF TABLES

Table 1. Non-Ostracode Material in USGS 70-92...... 31

Table 2. USGS 70-92 Species Table with References...... 32

Table 3. Table to Accompany Figure 11 ...... 35

Table 4. Pteroloxa cumuloidea and Candona rectangulata Assemblage ...... 39

Table 5. Ilyocypris biplicata and Limnocythere inopinata Assemblage ...... 45

Table 6. Cytherissa lacustris Assemblage ...... 50

Table 7. Cyclocypris cf. ampla Assemblage ...... 54

Table 8. Eigenvalues and Variance for Spectral Reflectance...... 57

Table 9. Eigenvalues and Variance for Ostracode Species Counts ...... 67

Table 10. Eigenvalues and Variance for Ostracodes and Spectral Reflectance ...... 73

Table 11. Ostracode Clusters by Depth ...... 77

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ACKNOWLEDGEMENTS

I received my bachelor’s degree in Anthropology with a concentration in

Archaeology in 2007 from Kent State University. It was during an internship at the

Cuyahoga Valley National Park that I realized I wanted to pursue post-graduate education in Geology and once again found the appropriate combination of research initiatives at

Kent State University. With the help and encouragement of family and friends, this initiative became a reality.

To my best friend and husband, Kyle Wells, I have you to thank for this experience. Without your encouragement and support, I would not have made it. You are my rock (no pun intended) and my reason for pursuing my passion in life. Thank you for being you.

Many thanks are also due to my fellow geology students, firstly, Emmanuel

(Chuks) Nwaodua, who provided comparison Chukchi Sea mineral spectral distributions from his doctoral research to better demonstrate physical sediment properties in a regional sense. With his regionally significant research I was able to corroborate the findings from the physical data collected from my specific core. Secondly, to Ashley

Tizzano, for her help with preparing sediment samples for VNIR spectroscopy analyses, and lastly, Renee Crane, who helped guide me through the SPSS statistical software package and known mineral database.

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To my committee members, Dr. Ortiz and Dr. Palmer, I have both of you to thank for my being a member of the graduate program to begin with. My first impression of

Kent State’s Geology department was one of welcome and opportunity. From there on, I had the pleasure of being a student in both of your classes, which helped prepare me for this thesis. My thanks go to Dr. Ortiz for helping me fully appreciate the physical properties of sediment and the accompanying statistics and to Dr. Palmer for helping me identify “proud beauties” and place negative signs on longitude coordinates.

To my advisor Dr. Alison Smith, thank you for seeing the potential in me. You gave me the knowledge and support not only to learn a new discipline, but to conduct meaningful research within it. You provided me with valuable experiences that even included travel to Greece and, more recently, Austria, where I was able to work closely with members of the scientific community who I would otherwise never have met. My familiarity and expertise regarding not only geologic and paleoclimatic studies, but also scientific data gathering and analysis, has been fostered and improved upon more quickly and significantly than I could have hoped, and for that I also thank you.

Lastly, I would like to thank the following funding organizations and researchers for their financial and data contributions which made my success at Kent State University possible. For funding, I would like to thank the National Science Foundation and

NEOTOMA project for funding my tuition and assistantship, the Katherine Moulton

Scholarship for supplies, and the Graduate Student Senate and International

Biogeography Society for travel funding to Crete, Greece. In terms of data, I am indebted

to the United States Geological Survey for recovering core 70-92 from the Chukchi Sea in 1985, the Canadian Museum of Nature, Ottawa, Canada, for permission to access the

Delorme ostracode collection, Brandon Curry and Barbara Stiff, Illinois Geological

Survey for assistance with the NANODe maps, and David Horne, University of London,

Queen Mary, for taxon range information regarding ostracode species distributions in

Europe.

ABSTRACT

New analysis of USGS 70-92 taken in the Chukchi Sea at 69.95°, 165.367º during a previous investigation by the United States Geological Survey (USGS) indicates an ostracode record of terrestrial freshwater environments dated from around 13,000 –

11,000 14C years BP (approximately 15,143 – 12,875 calendar years BP). This time frame corresponds to the Bølling/Allerød interstadial. This record is composed of four ostracode zones beginning at 12,640 + 45 14C years BP (14,723 + 93 calendar years BP) with fresh to slightly oligohaline fauna (Zone 1), including Holarctic species Pteroloxa cumuloidea and Candona rectangulata. This assemblage gives way to a freshwater habitat (< 1000 mg/l) ranging from ephemeral (Zone 2) to permanent (Zone 3) systems around ca 12,470

+ 45 14C years BP (14,419 + 127 calendar years BP). Zone 2 includes

Fabaeformiscandona rawsoni and Limnocythere inopinata. Zone 3 is dominated by

Cytherissa lacustris and Candona candida and is relatively short-lived. This freshwater basin is subsequently in-filled and replaced by wetland peats, containing species of

Cyclocypris and Cypria palustera. The final zone culminates in a marine transgression and is barren in terms of ostracodes. Of interest is that only the earliest zone (Zone 1) contains species which are exclusively found in the high Arctic today. Subsequent zones are characterized by freshwater species that occupy a range of temperatures that are commonly present in modern mid-latitude North America and Eurasia. Biogeography of

these species drawn from modern ostracode distributions highlights the absence of high

Arctic and polar fauna in Zones 2-4, suggesting that during the interval following Zone 1, temperature ranges were similar to modern sub-Arctic or mid-latitude temperature ranges. This conclusion is consistent with results from other works on pollen and plant macrofossil records for the region, and helps to narrow the time window in which fauna and humans would have been most likely to cross the Bering land bridge in late glacial time.

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Introduction

Beringia, a term coined by Swedish botanist Eric Hultén (Abbott and Brochmann,

2003), and later expanded on geographically by Alaskan geologist David Hopkins (Elias and Crocker, 2008), has come to represent an area of great importance due to its role as an entry point into North America in Quaternary time for humans as well as many other organisms. It is also believed to have served as refugia for a variety of both temperate and high latitude species (Pruett and Winker, 2008); offering useful information on circumpolar distribution and the paleoclimate conditions during that time. During the late

Pleistocene – early Holocene, the Bering Strait area was a much different environment as a result of the last glaciation, which allowed Beringia to be exposed and relatively free of ice (Figure 1). At its maximum exposure, the Bering Land Bridge is estimated to have spanned 1.5 million km2 from the Lena River west of the Bering Strait to the Mackenzie

River in the east (Elias and Crocker, 2008). This more terrestrial environment spanned from about 13,000 – 11,000 14C years BP (approximately 15,143 – 12,875 calendar years

BP), following the Last Glacial Maximum (LGM) and is well-represented as such in

USGS 70-92 (Figure 2). This relatively short period of time, geologically-speaking, potentially allowed for entry into North America by humans approximately 12,000

14years BP (around 13,810 calendar years BP) (Ager and Phillips, 2008).

Figure 1. The Beringia area as defined by Hultén (1937) with dotted lines representing the margins of exposed continental shelves during the last glacial maximum (modified from Hultén (1937) in Abbott and Brochmann, 2003, Figure 1, p. 300, with permission from Molecular Ecology).

During the late Pleistocene, the northern hemisphere was inundated by the

Laurentide and Cordilleran ice sheets, which provided significant ground coverage and perhaps geographical boundaries that could have influenced dissimilar patterns found in vegetation, freshwater systems, and faunal distribution. Through the use of 13C, 14C, and

15N isotopic data from megafaunal bone collagen, it has been determined that available vegetation on Beringia included grasses, sedges, herbaceous plants, and tundra plants, like lichen, fungi, and mosses (Fox-Dobbs et al., 2008); vegetation common to steppe, tundra, and shrub environments. Interestingly, no modern high-latitude analog is present today (Fox-Dobbs et al., 2008).

Figure 2. Glaciated areas of Beringia (from Elias et al., 2000, Figure 4, p.1359, with permission from the Journal of Biogeography).

The core analyzed during this study, USGS 70-92, came from a previous United

States Geological Survey (USGS) investigation and was obtained in 1985 during the cruise of the National Oceanic and Atmospheric Administration (NOAA) ship,

Discoverer. The purpose of the 1985 field studies was to describe the geologic and geophysical environments of the Chukchi and Beaufort Seas and make recommendations about drilling operations in lease sale areas, as well as supplement knowledge of ice gouging, current scour, and slope stability processes at high latitudes (Barnes et al.,

1986). USGS 70-92, a Vibracore sample, was raised from a water depth of 42 meters and includes deposits to a depth of 270 centimeters. It represents non-marine silty mud with plant material deposited during the late Pleistocene through early Holocene transgressive marine sediments (from approximately 15,000-10,000 calendar years), which overlies an erosional contact with Cretaceous tephras (Elias et al., 1992).

The purpose of this thesis study was to determine the paleoecology of late glacial and early Holocene Beringia as well as to analyze the biogeographical and circumpolar distribution of Late Glacial and modern non-marine ostracodes. During the course of the study, the following questions were addressed:

1. What do the Beringian lacustrine deposits tell us about the paleoecology of this

area during the late glacial – early Holocene time period?

2. What does the assemblage of ostracodes indicate about the paleoclimate and

circumpolar distribution?

3. Does the subsequent distribution of these taxa indicate that Berinigia was a

refugium for certain ostracode species?

4. Is the assemblage consistent with the distribution of common northern

hemisphere high latitude taxa?

5. Are the representative ostracode species known North American taxa? Are

there endemic species?

Through analysis of the biological and physical samples provided by the USGS,

15 ostracode species were extracted indicating the presence of four distinct ostracode zones within the core. This evidence is further supported by the visible near infrared derivative (VNIR) spectroscopy collected from the raw core samples. These data, along with corroboration from known literature allowed the above questions to be answered during the course of this study.

Background

Location

USGS 70-92 was extracted from the northeastern part of the Chukchi Sea in

Alaska, with latitude 69.95° and longitude 165.367º (Figure 3). The Chukchi Sea is located between western Alaska and eastern Chukotka in Siberia (Ager and Phillips,

2008) and is home to the formerly exposed Bering Land Bridge. The continental shelf area was once exposed by low sea levels caused by the late Pleistocene glaciations, the most recent of which was the Wisconsin Glacial Maximum, and extended from northeastern Siberia to the Yukon of Canada (Hetherington et al, 2008). As a high- latitude locality, the Bering region has been an excellent recorder of Quaternary geology including glaciation, high sea levels of the late Cenozoic, and climate change (Brigham-

Grette and Hopkins, 1995).

The Bering Strait, a gateway with a shallow sill depth of approximately 52 meters

(Ortiz et al., 2009), is the only Pacific gateway to the Arctic Ocean (Woodgate et al.,

2006) and thus plays an important part in both regional and global-scale processes

(Goosse et al., 1997). Locally, this through-flow provides nutrient-rich waters to the

Chukchi Sea while also contributing to the global freshwater budget via atmospheric transport of fresh water from the Atlantic Ocean to the Pacific Ocean (Goosse et

al.,1997). The Chukchi Sea is considered a modern analog to epicontinental seas found during the Cretaceous because of its shallow depths (60 meters). In addition it has a low sedimentation rate because of its barrier island system, as well as limited connectivity with rivers (Phillips and Colgan, 1987). During times when sea levels drop below the depth of the Bering Strait and parts of the Chukchi shelf, the Arctic and Pacific oceans become isolated, limiting connectivity between the two oceans (Ortiz et al., 2009) and consequently exposing the area known as Beringia.

Figure 3. Vibracore locations in northeastern Chukchi Sea, with USGS 70-92 identified by a red circle (Phillips and Colgan, 1987, Figure 1, p.158).

During the late glacial, such limited connectivity between the Arctic and Pacific oceans supported the existence of terrestrial systems on the continental shelf, which were later transgressed by early Holocene sea level rise, leaving behind an erosional contact.

USGS 70-92 is an excellent representation of such a record as it captures the transition from terrestrial to marine as a result of inundation of the Bering Land Bridge.

Regional Geology

During the 1985 expedition in which USGS 70-92 was collected, the Chukchi Sea shelf was characterized in terms of its sedimentology and stratigraphy (Figure 4) by means of high-resolution seismic profiling (Barnes et al., 1986) and a 3.5 kHz sub- bottom profiler (Phillips and Colgan, 1987). Interpreted seismic data revealed bedrock outcrops on the seafloor in areas where the overlying sedimentary Quaternary deposits are relatively thin, creating nonconformity. These Quaternary deposits varied with location and were classified based on their proximity (outer shelf, inner shelf, and surficial sediments), texture, mineralogy, and fossils. USGS 70-92, like all other vibracores, was sampled from the Chukchi Sea inner shelf (Figure 5) where it was characterized by well-sorted sands of medium to fine grain with the occurrence of laminated organic-rich peat or pebbly mudstone. The deposition of these sediments was characterized as gradational and has been attributed primarily to the Alaska Coastal

Current (ACC) (Barnes et al., 1986). The Alaska Coastal Current (ACC) is a wind and buoyancy-forced current that follows a northward flow trend (Weingartner et al., 2005).

It operates year-round and has attributes that indicate it is “an important pathway by which climate signals, dissolved and suspended materials, and organisms are advected

Figure 4. USGS 70-92 core stratigraphy based on USGS records. Geological patterns for core stratigraphy adapted from Muhs et al., 2003.

around the gulf and into the Bering Sea” (Weingartner et al., 2005, p. 170). The outer shelf consisted of three sedimentary units: modern mud-sand, marine sand-pebbly mudstone, and volcanic ash. The widespread ash layer, described as fine-grained and vitreous, is attributed to eolian transport (Barnes et al., 1986).

Northwest

Figure 5. Vibracore stratigraphy across northeastern Chukchi Sea (modified from Elias et al., 1992, Figure 2, p. 373, with permission from Quaternary Research). USGS 70-92 located East of USGS 66.

As a potential source for petroleum and natural gas reserves, the Chukchi shelf stratigraphy and tectonic history has been extensively studied. Seismic data from the

1985 expedition revealed that the economic basement underlying the Chukchi shelf is

“gently to steeply dipping folded and faulted bedrock” (Phillips and Colgan, 1987, p.

157) and is Late Devonian in age. These rocks are most closely associated with the

Franklinian sequence, which was deformed by the regionally significant Ellesmerian

orogeny (Grantz et al., 1982). Regionally, the Bering Sea, the Chukotka Peninsula, the

Seward Peninsula and part of western Alaska comprise a section of an independent

tectonic block called the Bering Block which is thought to have first submerged 2.5-4.5

million years prior to glaciation (Brigham-Grette, 2001). This Bering Block, also known

as the Bering Platform, is considered to be relatively tectonically stable despite the

Chukchi shelf rifting (Figure 6) in the Late Devonian and current tectonic activity in the

neighboring Aleutian Arc (Mann and Hamilton, 1995).

Figure 6. Tectonic setting of the Chukchi shelf in the region of USGS 70-92 (Alaska BOEMRE, 2006, Figure 7, p. 26).

Study Proxies

Biological and physical proxies can be used as a means to draw conclusions about the paleoenvironment. Proxies used in this particular study include ostracode assemblage identification and VNIR spectroscopy of sediment, but can also be extended to beetle assemblages, chironomids, pollen distributions, and macrofossils, among others. A number of case studies on Beringia have been conducted, invoking a variety of biological and physical proxies, because it is a unique repository for Arctic and sub-Arctic fossil records (Elias, 2000).

Physical properties of sediment as proxies, similar to biological, can provide insight on paleoclimate and, in particular, provenance of minerals found within the core sediment. The clay minerals, for example, are typically viable tracers used in reflectance studies (Ortiz et al., 2009). In the Arctic and Pacific oceans, the dominant clay types are illite and chlorite, respectively (Ortiz, 2011). Fortunately, these two clay minerals each possess their own distinct spectral signatures, thus providing information on flow through the Bering Strait. Because the processes of absorption and wavelength dependence are indicators of mineral chemistry, they can provide insight based on reflected or emitted light (Clark, 1999).

Regional Paleoecology of Beringia during the Late Glacial

During the latter part of the Last Glacial Maximum (LGM), Beringia was host to a number of terrestrial environments. This time interval has been termed the Late Glacial period (14,000-10,000 calendar years BP) and was a time of “rapid environmental change” (Elias, 2001, p.10). As a result of the glaciation and subsequent decrease in eustatic sea level, approximately 121 + 5 meters below present sea level (Fairbanks,

1989), the continental shelves of the Bering and Chukchi seas were exposed and in the case of core USGS 70-92, supported a number of terrestrial ecosystems prior to the

Holocene marine transgression. The disruption of this biogeographic province, defined as a region in which a particular group of plants and/or animals is distributed (Boggs,

2006), was significant not only to the longitudinal dispersal of flora and fauna, but also to the distribution of our own species. The narrowest portion of Beringia, the Bering Strait, is estimated to have been less than 120 kilometers in width (Elias et al., 1997), making it a distance easily traveled during the late Pleistocene period (Figure 7). Thanks to the existence of biological proxies like pollen, insects (beetles and chironomids), and ostracodes (in this particular case), reconstruction of the paleoecology and

paleoenvironment of Beringia is possible.

Figure 7. Relief map of Beringia region showing limits of exposed land mass following the last glaciation (from Elias and Crocker, 2008, Figure 1, p. 2474, with permission from Quaternary Science Reviews).

Pollen Palynological analysis is a biological proxy that has become very important to

Beringia-related studies interested in anything from paleoclimate reconstructions to the cause(s) of megafaunal extinction. The use of pollen and macrofossils is not limited to studies of Beringia. It has also been instrumental in many Quaternary studies on paleoclimate because of its use in radiocarbon dating and the implications the presence of certain types of vegetation can have on interpretations made in these studies. For example, Elias and Crocker (2008) discuss the occurrence of 8 classes of Beringian tundra based on different species of pollen present within their samples.

In Ager’s and Phillips’s (2008) paper on USGS 76-121, a core collected on a

1976 expedition from the Norton Sound in the northeastern Bering Sea, 26 samples yielded the presence of two distinct pollen zones known as NOR-1 and NOR-2. The older pollen zone, NOR-2, represented an assemblage of graminoid-herb-willow tundra vegetation typically found in climates with cool and arid conditions, whereas the younger pollen zone, NOR-1, contained indicator species characteristic of late glacial dwarf-birch- heath-willow-herb tundra vegetation characteristic of wetter conditions (Ager and

Phillips, 2008). This particular study is fundamental to reconstructing Beringian paleoclimate because it confirms that a transition from herbs to shrubs occurred around

13,000-11,800 14C yr BP (approximately 15,143 – 13,655 calendar years BP) (Ager and

Phillips, 2008), indicating a dramatic shift in the climate represented by the pollen distribution.

Edwards et al. (2005) worked on pollen spectra from a dataset representing

13,500 to 9,500 calendar years BP were compared to modern pollen data from North

America, with little similarity found. In addition to pollen, macrofossils were analyzed, revealing the presence of a transition from shrub-tundra to more forested conditions

(Edwards et al., 2005). These results varied across the bridge and obvious differences in the vegetation were noted (Figure 8). As found by other researchers, Edwards et al.

(2005) confirmed that the “macrofossil data imply that climatic warming at high northern latitudes may favor the development of deciduous forest biomes (Edwards et al., 2005, p.1701). While pollen can be very useful in paleoclimate reconstructions, it is important to note that it has its limitations as a proxy, including difficulty identifying beyond the

family level for many genera and ecological indicators that can be misleading for interpreting moisture requirements (i.e. wet or dry indicators) (Elias and Crocker, 2008).

Figure 8. Graphical representation of tree-sized macrofossils by taxon and number of sites found on West and East Beringia; dated between 13,500-9,500 calendar years BP (from Edwards et al., 2005, Figure 4, p. 1701 with permission from Ecology).

Insects (Beetles and Chironomids)

Like palynology, paleoentomological studies have been instrumental in determining vegetative distributions and thus interpretations of paleoclimate on the former Bering Land Bridge. Beetles, specifically, are generally well-preserved in frozen, organic-rich sediments (Elias et al., 2000), like those found in the Beringia region. In a study by Alfimov and Berman (2001), Stephanocleonus, from the weevil genus, were used as modern analogs to reconstruct the proposed steppe and tundra environments of eastern Beringia. With this study, they concluded that the Bering Land Bridge was analogous to the modern Arctic tundra zone (Alfimov and Berman, 2001). Another study by Elias (2000) also used fossil beetles as a proxy, but did so by using the Mutual

Climate Range (MCR) method. This approach, based on fossil beetle assemblage data,

allowed Elias to yield a maximum temperature of 7°C and a minimum temperature of

5°C above average. These values were then compared to modern values so that a departure from the modern could be determined. This study helped to determine that large-scale warming occurred until the time the Bering Land Bridge was inundated

(approximately 11,000 calendar years BP) (Elias, 2000).

In an additional study by Elias et al. (2000), two fossil beetle assemblages from

Western and Eastern Beringia were studied for their habitat preferences to determine the steppe-tundra extent on Beringia, an on-going point of contention among researchers.

The Western fossil assemblage included 59 species, whereas the Eastern fossil assemblage included 181 species, both including predators and scavengers, but having distinct differences (Elias et al., 2000). In this study they concluded that Beringia as a whole contained “mosaics of habitats” (Elias et al., 2000, p.1349) with a concentration of mesic tundra and riparian ground beetles found in Eastern Beringia and more xeric varieties in Western Beringia. Although there are notable differences in the assemblages, it is important to realize that preservation in the region could also affect the presence or absence of indicator species, thus reinforcing the need for a multi-proxy approach.

Like beetles, chironomids can be used as a biological proxy because their abundance is strongly correlated with summer temperatures (Kurek et al., 2009).

Chironomids are non-biting insects from the order Diptera and their head capsules are typically preserved in lake sediments with a history of warmer temperatures. In Kurek et al. (2009), chironomid assemblages from two lakes in the Beringian region, Zagoskin

Lake and Burial Lake, indicated that summer climates during the Late Glacial had mean

July temperatures that were approximately 3.5 °C below modern temperatures. These chironomid findings along with palynological data, specifically on Populus, suggest that there was relative post-glacial warming (Kurek et al, 2009).

Ostracodes

Ostracodes are members of the Phylum Arthropoda within the class Crustacea

(Haslett, 2002). Historically, the ecology and paleoecology of ostracodes has been studied for about a century, with interdisciplinary focus on systematics, morphology, stratigraphy, and chemistry (Carbonel et al., 1988). As biological and geochemical indicators, the importance of ostracodes to the environmental, genomic, and ecological sub-disciplines is on the rise (Smith and Delorme, 2009). In North America, there are an estimated 56 genera and 420 species of non-marine ostracodes, ranging in size from 0.4-

1.0 millimeters (Smith and Delorme, 2009). Because of their small size and the simple architecture of their carapaces, they are better-preserved than other marine arthropods during burial and throughout the process of diagenesis (Carbonel et al., 1988).

Ostracodes are a diverse group that is typically characterized by their small size and bivalved low-magnesium calcite shell. Morphologically speaking, they have flattened symmetrical bodies that are dorsally hinged and their inner parts consist of soft tissue. In most cases, unfortunately, this tissue is not preserved in fossil specimens and therefore requires differentiation based on the qualities of their carapaces. These crustaceans are useful in paleoclimate research because their “shells provide valuable information on

present and past water salinity, temperature and chemistry, hydrodynamic conditions, substrate characteristics, climate, sea level variations, oxygen and nutrient availability”

(Frenzel and Boomer, 2005, p. 68). Non-marine taxon, like many represented in this study, can be found in lakes, streams, wetlands, springs, and oxygenated aquifers (Smith et al., 2002) and typically reside in the sediment-water interface and live on organic detritus (Bunbury and Gajewski, 2009). The aquatic habitats of these arthropods can range from ephemeral to permanent and many can survive in salinities ranging from 5.5 mg/L to 109,658 mg/L (Smith and Delorme, 2009). Identification of fossil ostracode species can be performed successfully on adult specimens, but is generally not attainable with juvenile specimens because their carapaces do not lend enough features for identification (Smith and Delorme, 2009). In many cases, the autecology (physical and chemical habitat) of living ostracodes can be extrapolated to fossil ostracodes, emphasizing the importance of understanding both the present and the past (Delorme,

1989).

Methods

The materials from USGS 70-92 used to conduct this study were originally acquired by the USGS in 1985 and later provided to Kent State University, where they are now housed, for further research. The core material was sent in the form of raw core sediment (44 samples), sorted core sediment (74 samples), and 71 prepared slides.

Ostracode species identification and counts were obtained from the prepared slides and sorted core sediment was checked for remnant ostracode valves, of which none were found. Physical analysis of the core sediment was performed on the raw core sediment as it was less likely to contain any contaminants from the ostracode picking process.

Accelerator Mass Spectrometry (AMS) radiocarbon dates were derived and provided by Thomas Ager of the USGS by dating fine plant detritus. To prepare the samples for 14C age determination, they were washed in distilled water, air dried in aluminum pans and then weighed. The samples were first examined under a microscope for coal or lignite fragments to ensure they were free of contamination and were then placed in aluminum foil, labeled and then placed into plastic bags. (USGS Open File,

2002; Ager email communication, 2009); the dates provided are listed by depth as follows:

11,130 + 45 14C years BP - core depths of 128-135 cm (12,981 + 47 calendar years BP)

12,470 + 45 14C years BP - core depths of 250-260 cm (14,419 + 127 calendar years BP)

12,640 + 45 14C years BP - core depths of 260-270 cm (14,723 + 93 calendar years BP)

Lab Work

Research on USGS 70-92, including ostracode and sediment analysis, was conducted at Kent State University in the Paleolimnology lab as well as Dr. Ortiz’s lab and did not require any collection at a field site. The ostracode reference collection, ostracode literature collection, NANODe database, microscopes, microscope camera, and a multi-variate statistical package, MVSP (Kovach, 1985-2010), were available resources used to determine the core’s ostracode taxonomy and assemblages. Lab supplies, such as micropaleontology slides (round cavity and 60 grid), aluminum holders, and glass slides were made available in the labs.

Ostracode samples were processed by the USGS Denver lab following standard methods described in Colman et al., (1990), and with washing the samples through a stack of sieves (8-inch diameter standard brass sieves) of 20, 100 and 230 mesh openings

(850, 150 and 63 micrometers, respectively). Most species land on the 100 mesh (150 micrometer) sieve. These were decanted into Whirlpak® bags, frozen, and then freeze- dried.

All 71 slides provided by the USGS were examined for ostracode identification

(genus and species) and then counted using a microscope, a #000 round sable paintbrush, and de-ionized water. During initial slide review, seeds, beetle fragments, charophytes,

chironomids, cladocera, fish bones, gastropods, plant macros, water mites, and inorganic fragments were also noted on a presence (1) or absence (0) basis, in addition to ostracode identification and counts.

Following the ostracode identification and counting process, I pooled data from slide samples by depth as many of them represented the same interval. For example, when the USGS sorted the material by depth, in many cases they conducted two separate investigations; one identified as “Sep 03’ Set” and another as “Lot 2”, which resulted in 2 slides per depth that was resampled. Since the identification and counts represented the same depths, it was logical to combine these data so that the dataset could more easily be statistically manipulated and interpreted. The resultant dataset included 51 samples, categorized into 2 centimeter intervals, with the exception of three depths, 228-235, 250-

260, and 260-270 centimeters. These 3 depths, although not containing a matching depth in both data sets, contained a number of valves and thus were included in statistical analyses. Weights for these 3 samples were approximated based on pooling weight (in grams) data from the individual slides representing the interval. Weights for the remainder of the samples were noted by the USGS in their initial investigation.

For dry sediment analysis, an Analytical Spectral Device (ASD) LabSpec® Pro

FR ultraviolet (UV)/visible (VIS)/near-infrared (nIR) Spectrometer with a spectral range of 350-2500 nanometers was employed (Ortiz et al., 2009). This equipment was used to obtain spectral resolution with a precision of 2 nanometers at 20 millimeter spot size and

2 centimeter intervals, on the samples of raw core sediment from USGS 70-92. Although

the spectrometer can measure a range of 350-2500 nanometers, only 400-2500 nanometers is usable for these analyses, as this range represents the visible and near infrared (VNIR) parts of the electromagnetic spectrum with minimum noise.

The LabSpec® Pro FR UV/VIS/nIR Spectrometer was first run with the spectralone reference panel to calibrate the white value, which registered as a straight line

(value of 1) on the graphical output. Following calibration, the program was set to capture 200 spectra per sample to help minimize noise within the output by homogenizing the resulting data. A total of 44 core sediment samples were analyzed while recalibrating with the spectralone between sample runs to ensure consistency in the data output.

Statistical Analysis

During the course of this study, I used two types of multi-variate statistical analysis to quantitatively analyze the ostracode and spectral data from the sediment: cluster analysis and principal component analysis (PCA). Multi-variate statistics provide powerful methods that allow a number of properties to be analyzed concurrently to evaluate change (Davis, 1986). In the field of Geology, questions are generally focused on what happened and in what order, which can often be explained qualitatively

(Waltham, 2000). However, with the use of multi-variate statistics, we can quantitatively explain the influence of one process upon another or their relationship as a function of environment. Both cluster and principal component analyses are methods of ordination, meaning that they put observations in logical order based on relative similarities (Davis,

1986). Cluster analysis, as defined by Davis (1986, p. 502), is “an assortment of techniques designed to perform classification by assigning observations to groups so each group is more-or-less homogenous and distinct from other groups”. In this study, cluster analysis was used to identify ostracode assemblages as well as to reconstruct the fossil assemblage based on modern species ecology and biogeography (Smith et al., 2002). The distance between samples was measured using the Gower General Similarity Coefficient and constrained by the stratigraphic order. Principal component analysis, “seeks to decompose a data matrix into independent (or orthogonal) components by finding the eigenvalues and eigenvectors of the matrix” (Ortiz, 2011). Like cluster analysis, principal component analysis is designed to extract meaning from a dataset, but instead of doing so by comparing distances among groups using a dissimilarity or similarity coefficient, it extracts orthogonal axes that are independent of one another, each of which accounts for a percentage of the variance within the dataset.

Principal Component Analysis (PCA) – Spectral Reflectance

Once the LabSpec® Pro raw sediment spectral reflectance measurements were obtained, they first needed to be converted from a proprietary output (.asd file format) to a standard ASCII text file (.txt file format), which was then imported into Microsoft

Excel® so that the data could be corrected for two detector transitions. These transitions occurred at the intersections of visible infrared (VIR) and the first short-wave infrared

(SWIR1) at 986 to 987 nanometers and at the first short-wave infrared (SWIR1) and second short-wave infrared (SWIR2) boundary at 1765-1766 nanometers.

Once these data were corrected for the detector, I interpolated to derive a subset of data at 10 nanometer resolution, which was intended to make the dataset more manageable and to increase the signal to noise ratio. Once interpolated, the derivative was calculated for each of the wavelengths down-core, allowing for the rate of change of reflectance versus wavelength to be determined. This transformation removed scattering effects from the spectra. The resultant, derivative data were then imported into SPSS®

14.0 for Windows, where a varimax-rotated R-mode principal component analysis

(variable-by-variable) was conducted. Varimax-rotation is a rigid rotation of the principal axes that does not distort the internal structure of the data, thus allowing the results to be easily interpreted. This analysis produced 4 principal components from the dataset, which were then compared to the known mineral library of Arctic minerals (Ortiz, 2009) as well as the pigment library (Ortiz et al., 2011).

Once the reflectance data were analyzed for USGS 70-92, it was then compared to doctoral research conducted by Emmanuel Nwaodua on regional reflectance data from the Chukchi Sea (Nwaodua and Ortiz, 2011). In order to compare my dry sediment reflectance data to that of regional significance, I first had to rescale my data by a factor of 0.5 for all wavelengths. This was necessary because the dry samples yield a brighter value than the wet samples since water more effectively absorbs in the visible part of the electromagnetic spectrum (Ortiz et al., 2009). Once this adjustment was made, I ran principal component analysis on the revised dataset for USGS 70-92 and then compared the component loading data to that from the regional dataset.

Principal Component Analysis (PCA) - Ostracodes

For this study, I used Multi-Variate Statistical Package (MVSP) 3.2 (Kovach,

1985-2010) to run principal component analysis on ostracode species count data. The analysis was conducted in R-mode (variable-by-variable), which in this case represented species present, and was then standardized. Count data for the juvenile candonids and 3

Eucypris species were excluded as they were not identified to the species level and had minimal contribution at only 1.86% of the overall population, respectively. By not including these data, I was able to minimize noise within the results and filter out the species that were pulling the axes. By approaching the analysis in this manner, I was able to extract eigenvalues and eigenvectors from the matrix and reduce the dimensional space of the dataset. The axes produced were orthogonal, independent of one another, and important in explaining the variance within the dataset. The total variance, in this particular case, was principally explained by 3 axes.

To further explore the relationship between the ostracode species count data and spectral reflectance data from the core sediment, I ran principal component analysis on the collective dataset. Like the ostracode species count run, I excluded the Candona sp. juveniles and the three Eucypris species to eliminate distortion in the dataset. The total variance was explained by 7 axes, which is not particularly telling, but the scatter plot generated an interesting relationship between two noticeable data clusters, when comparing Axis 1 vs. Axis 2.

Cluster Analysis

For this study, I used Multi-Variate Statistical Package (MVSP) 3.2 (Kovach,

1985-2010) to run a constrained cluster analysis on the ostracode distribution in the core.

After trying a number of other distance measures, I chose the Gower General Similarity

Coefficient and the farthest neighbor clustering method as my parameters as they produced a dendrogram with no reversals that identified the underlying structure within my data. This structure was also consistent with the PCA results as well as observations of the fauna. The Gower General Similarity Coefficient, as represented in the following formula, is widely used because it works well with mixed data types and mathematically, the denominator divides the sum of the similarity scores by the number of variables:

The farthest neighbor clustering method measures the distance between the two farthest points within the dataset, as evaluation proceeds between two groups at a time (Kovach,

1985-2010).

Modern Analog Technique

For the modern analog analysis, I also used MVSP 3.2 (Kovach, 1985-2010), but ran an unconstrained cluster analysis with Jaccard’s coefficient and UPGMA as the main parameters. The modern analog technique “is a multivariate statistical technique that makes use of distance measures (dissimilarity coefficients) to compare fossil assemblages with assemblages from a modern data set” (Smith et al., 2002, p. 630). Jaccard’s

similarity coefficient, a binary measure, was sufficient for the modern analog analysis as

I was only concerned with whether the ostracode species were present (1) or absent (0) in

USGS 70-92 and the modern samples:

The modern calibration dataset, to which USGS 70-92 was compared, was compiled from the North American Non-Marine Ostracode Database (NANODe)

(Forester et al., 2005), Canadian Museum of Nature Delorme collection, Matanuska

Alaskan Lakes (Forester et al., 1989), Yukon Territory (Bunbury, 2005), Canadian Arctic

Archipelago (Bunbury, 2009), Yakutia, East Siberia (Wetterich et al., 2008b), and Kara and Laptev Seas (Stepanova, 2007) datasets. The resultant similarity matrix was further analyzed for degree of similarity to other samples by using the filter function in Microsoft

Excel® at a critical value of 0.75, which represents a threshold match of 75% between the fossil and modern assemblages.

Results

Ostracode Assemblages

Of the 71 slides, only 32 (mainly found toward the bottom portion of the 270 centimeter core) had ostracode valves present. Out of these 32 slides confirmed to contain ostracode valves, 14 ostracode species were identified, not including Candona sp. juveniles, which could not be identified to the species level. Of these genera/species, 13 were recognized as freshwater, non-marine and 1 as estuarine. All species identified in this study of a late glacial environment are still extant, although may occupy different geographical ranges today. Table 1 graphically represents the most prevalent of the organic and inorganic fragment observations by depth interval. Plant fragments were observed at all depths and chironomids were noted at most depths throughout the core as well.

The taxon represented in USGS 70-92 were only evaluated for occurrence, not abundance productivity, which presumes that their essential life-cycle needs were met

(Forester, 1991). In terms of habitat, USGS 70-92, although only representing a brief window of time, demonstrates the presence of fluvial/palustrine, ephemeral lacustrine, permanent lacustrine and even estuarine systems indicating a shift in climatic conditions

over time. The ostracode assemblages identified during the course of this study not only represent these systems, but can also be correlated to the presence of specific environmental factors that needed to be present in order to accommodate their existence, like temperature and salinity.

Based on the 14 ostracode species identified in Table 2 and indicator species identified to determine ostracode zonation, 4 assemblages were recognized within USGS

70-92 (Figures 9 and 10). Assemblages were identified with paleoecological and stratigraphic methods further supported by multi-variate statistical analysis like PCA. In the following sections, count data as well as ecological significance is presented in table form in addition to a species map for all of the assemblages, created with ESRI ArcMap

Version 9.3.1. For the species assemblage maps, ostracode presence data for the

Quaternary and modern time periods was compiled from known literature and plotted in circumpolar view to represent biogeographical distribution of the genera / species.

Table 1. Material (non-ostracode) observed in USGS 70-92.

Table 2. USGS 70-92 Species Table with References.

USGS 70-92 Species Table Genera / Species Ecological Significance Reference Candona candida Fluvial / Palustrine O.F. Müller, 1776 Candona rectangulata Fluvial / Palustrine Alm, 1914 Cyclocypris cf. ampla Palustrine Furtos, 1933 Cypria ophthalmica Palustrine Jurine, 1820 Cytherissa lacustris Permanent Lacustrine Sars, 1925 Eucypris sp. Fluvial / Lacustrine Vávra, 1891 Eucypris foveata Fluvial / Lacustrine Delorme, 1968 Eucypris serrata Lacustrine G.W. Müller, 1900 Fabaeformiscandona rawsoni Lacustrine Tressler, 1957 Ilyocypris biplicata Fluvial / Palustrine Koch, 1838 Limnocythere friabilis Fluvial / Lacustrine Benson and Macdonald, 1963 Limnocythere sharpei Fluvial / Lacustrine Staplin, 1963 Limnocythere inopinata Fluvial / Lacustrine Baird, 1843 Pteroloxa cumuloidea Estuarine Swain, 1963

Figure 9. Graph of ostracode species abundance and zonation.

Figure 10. Graph of ostracode species abundance and zonation, expanded to 170-270 cm.

Table 3. Table to accompany Figure 11.

A Candona candida, left valve, female, 265 cm depth in core 70-92

Fabaeformiscandona rawsoni, right valve, female, 265 cm depth in B core 70-92.

C Limnocythere inopinata, right valve, female268 cm depth in core 70-92.

D Ilyocypris biplicata, right valve 255 cm depth in core 70-92.

E Candona rectangulata, left valve, 268 cm depth in core 70-92.

F Cytherissa lacustris, right valve, female, 245 cm depth in core 70-92.

G Pteroloxa cumuloidea, right valve, female, 268 cm depth in core 70-92.

H Pteroloxa cumuloidea, right valve, male, 268 cm depth in core 70-92.

Figure 11. Common ostracode species found in USGS Core 70-92.

Pteroloxa cumuloidea and Candona rectangulata Assemblage

The Pteroloxa cumuloidea and Candona rectangulata assemblage encompasses the basal portion of USGS 70-92, also known as Zone 1, representing depths from 258-

270 centimeters. This assemblage contains 12 ostracode species, all with fairly high valve abundance, especially when compared to the remainder of the core. The mere presence of estuarine species, Pteroloxa cumuloidea (Figure 11), in this zone indicates that the terrestrial system represented is not exclusively a freshwater habitat and has some form of limited contact with a marine input, like sea spray. Presence of non-marine genera like the Candonids, for example, indicates that this is not a marine or exclusively estuarine environment either. Reconstructing the exact paleoenvironment during this time is not necessarily attainable, but with certainty, I can conclude that this environment is terrestrial with limited contact to brackish waters.

Pteroloxa cumuloidea, a brackish indicator species, is identified with an Arctic biogeographical distribution (Figure 12), as is Candona rectangulata (Figure 13). Data used to map Pteroloxa cumuloidea Quaternary sites were obtained from Brouwers et al.

(2000), Stepanova et al. (2007), Swain (1963), and Taldenkova et al. (2008) and modern site data were obtained from the Arctic Ostracode Database, Cronin et al. (1995).

Sampling locations were limited to marginal waters from Alaskan, Canadian, and

Russian datasets.

Like Pteroloxa cumuloidea, Candona rectangulata is also known to have a generally Arctic distribution (Figure 13). It is known to be restricted to areas above 62° latitude (Delorme, 1989) with the exception of a few known Quaternary sites in Germany

and does not typically inhabit brackish water as it is a freshwater, fluvial / palustrine species (Table 4), but is fairly tolerant of changing conditions. Its presence in the assemblage with Pteroloxa cumuloidea indicates that the estuarine influence is prevalent, but not the controlling factor on this paleoecosystem. Although it is not the most abundant ostracode found in Zone 1, it is important when coupled with Pteroloxa cumuloidea since it indicates the presence of colder air masses indicative of an Arctic- like climate. Interestingly, the first zone is the only one to contain Arctic indicator species, Pteroloxa cumuloidea and Candona rectangulata, together. Data used to represent the Quaternary and modern distribution of Candona rectangulata, also known in the literature as Candona harmsworthi and Fabaeformiscandona harmsworthi, were obtained from Kienast et al. (2010), Wetterich et al. (2005), Wetterich et al. (2008b) and

Bunbury and Gajewski (2009), Forester et al. (1989), Namiotko et al. (2009), Stepanova et al. (2007), and Wetterich et al. (2008b), respectively. These datasets represent

Alaskan, Canadian, German, and Russian study sites.

Table 4. Pteroloxa cumuloidea and Candona rectangulata assemblage data.

Ostracode Ecological Significance Count Count Rank Limnocythere inopinata Fluvial / Lacustrine 1573 1 Candona sp. juveniles Fluvial / Palustrine 985 2 Pteroloxa cumuloidea Estuarine 638 3 Limnocythere friabilis Fluvial / Lacustrine 483 4 Ilyocypris biplicata Fluvial / Lacustrine 303 5 Limnocythere sharpei Fluvial / Lacustrine 284 6 Candona rectangulata Fluvial / Palustrine 137 7 Candona candida Fluvial / Palustrine 129 8 Eucypris foveata Fluvial / Lacustrine 76 9 Fabaeformiscandona rawsoni Lacustrine 38 10 Eucypris serrata Lacustrine 29 11 Eucypris sp. Fluvial / Lacustrine 15 12

Figure 12. Circumpolar map of Pteroloxa cumuloidea showing Quaternary and modern distributions created in ESRI ArcMap (Brouwers et al., 2000; Cronin et al., 1995;

Stepanova et al., 2007; Swain, 1963; Taldenkova et al., 2008). Map view magnified to show limited distribution of Pteroloxa cumuloidea in the polar region.

Figure 13. Circumpolar map of Candona rectangulata showing Quaternary and modern distributions created in ESRI ArcMap (Bunbury and Gajewski, 2009; Forester et al.,

1989; Kienast et al., 2010; Namiotko et al., 2009; Stepanova et al., 2007; Wetterich et al., 2005; and Wetterich et al., 2008b). Map view demagnified to show wide distribution of Candona rectangulata Quaternary records.

Ilyocypris biplicata and Limnocythere inopinata Assemblage

The Ilyocypris biplicata and Limnocythere inopinata assemblage (Table 5) represents ostracodes found within the second zone from depths of 250-257 centimeters.

Based on the species found within this interval, the terrestrial system consisted of fresh, but likely ephemeral, water in the form of a fluvial or lacustrine system (Delorme, 1970d,

1971, 1989; Forester, 1991; Forester et al., 1994). There are no indicator species within this assemblage that suggest the presence of a permanent freshwater system, but there is clearly a difference in inputs with the disappearance of estuarine species, Pteroloxa cumuloidea at 250 centimeters. The shift from brackish to freshwater is distinct, but most of the ostracodes that are previously present in Zone 1 (with the exception of Pteroloxa cumuloidea) seem to persist, though in smaller quantities. With this shift we see the first appearance of palustrine species Cyclocypris cf. ampla and significantly smaller numbers of freshwater Arctic species, Candona rectangulata, suggesting a shift in climatic conditions.

The geographic distribution of Ilyocypris biplicata (Figure 14) and Limnocythere inopinata (Figure 15) sites is significantly different from that of Pteroloxa cumuloidea

(Figure 12) and Candona rectangulata (Figure 13) in that they are more widespread and prevalent in the mid-latitudinal ranges of Asia, Europe, and North America. This representation is consistent with the faunal shift seen from the first zone to the second zone and can be seen in both Quaternary and modern sites. Location data for the

Ilyocypris biplicata sites were obtained from the Non-Marine Ostracod Distribution in

Europe (NODE) database – Horne et al. (1998), Canadian Museum of Nature Delorme

Table 5. Ilyocypris biplicata and Limnocythere inopinata assemblage data.

Ostracode Ecological Significance Count Count Rank Candona sp. juveniles Fluvial / Palustrine 81 1 Ilyocypris biplicata Fluvial / Lacustrine 66 2 Limnocythere inopinata Fluvial / Lacustrine 31 3 Limnocythere sharpei Fluvial / Lacustrine 9 4 Candona rectangulata Fluvial / Palustrine 7 5 Cyclocypris cf. ampla Palustrine 6 6 Fabaeformiscandona rawsoni Lacustrine 5 7 Candona candida Fluvial / Palustrine 3 8 Eucypris sp. Fluvial / Lacustrine 1 9 Eucypris foveata Fluvial / Lacustrine 1 9

collection, Külköylüoğlu and Dügel (2004), Lister (1975), Martens (1984), Nazik et al.

(2011), Sun et al. (1999), and Zhu et al. (2007), while, Limnocythere inopinata site data were compiled from the North American Non-Marine Ostracode Database (NANODe) –

Forester et al. (2005), Non-Marine Ostracod Distribution in Europe (NODE) database –

Horne et al. (1998), Bunbury and Gajewski (2005), Curry (1997), Forester et al. (1989),

Frogley et al. (2001), Krzyminska and Przezdziecki (2010), Li et al. (2010), Löffler

(1990), Matyjasik and Smith (1997), Mischke et al. (2003, 2005, 2006, 2010),

Poberezhnaya et al. (2006), Porter et al. (1999), Rossi et al. (2010), Scharf et al. (2005),

Sohar and Kalm (2008), Sohar and Miedla (2010), Van der Meeren et al. (2011),

Wetterich et al.(2008b), Wilkinson et al. (2005), and Zhu, et al. (2007).

Figure 14. Circumpolar map of Ilyocypris biplicata showing Quaternary and modern distributions created in ESRI ArcMap (NODE – Horne et al., 1998; Canadian Museum of Nature Delorme collection; Külköylüoğlu and Dügel, 2004; Lister, 1975; Martens, 1984; Nazik et al., 2011; Sun et al., 1999; and Zhu et al., 2007). Map view demagnified to show wide distribution of Ilyocypris biplicata Quaternary and modern records.

Figure 15. Circumpolar map of Limnocythere inopinata showing Quaternary and modern distributions created in ESRI ArcMap (NANODe – Forester et al., 2005; NODE – Horne et al., 1998; Bunbury and Gajewski, 2005; Curry, 1997; Forester et al., 1989; Frogley et al. 2001; ; Krzyminska and Przezdziecki, 2010; Li et al., 2010; Löffler, 1990; Matyjasik and Smith, 1997; Mischke et al., 2003, 2005, 2006, 2010; Poberezhnaya et al., 2006; Porter et al., 1999; Rossi et al., 2010; Scharf et al., 2005; Sohar and Kalm, 2008; Sohar and Miedla, 2010; Van der Meeren et al., 2011; Wetterich et al., 2008b; Wilkinson et al., 2005; and Zhu, et al., 2007). Map view demagnified to show wide distribution of Limnocythere inopinata Quaternary and modern records.

Cytherissa lacustris Assemblage

The Cytherissa lacustris assemblage, although only a very brief interval within

USGS 70-92 from a depth of 245-247 centimeters, records the presence of a permanent, freshwater lacustrine system. Cytherissa lacustris is known to live in “dilute, cold, stenotopic, boreal forest lakes” and is typically large in size and more ornate than other non-marine ostracodes (Forester, 1991, p.141). This assemblage has limited diversity

(Table 6), especially when compared to the two previous zones, but is clearly a sub-set of species classically associated with permanent limnic environments and associated indicator species, Cytherissa lacustris (Delorme, 1970d, 1989; Forester, 1991; Forester et al., 1994).

Table 6. Cytherissa lacustris assemblage data.

Ostracode Ecological Significance Count Count Rank Candona sp. juveniles Fluvial / Palustrine 32 1 Cyclocypris cf. ampla Palustrine 12 2 Cytherissa lacustris Permanent Lacustrine 12 2 Candona candida Fluvial / Palustrine 1 3

Geographically, Cytherissa lacustris is similar to Limnocythere inopinata in its extensive distribution as well as its presence in the mid-latitudinal range (Figure 16). Its site locations, both Quaternary and modern, suggest that it can occupy habitats with a range of temperatures so long as its requirement for dilute, permanent freshwater is met.

Quaternary and modern site data were obtained from the Non-Marine Ostracod

Distribution in Europe (NODE) database – Horne et al. (1998), Allen and Anderson

(2000), Bunbury and Gajewski (2009), Burke (1987), Curry and Baker (2000), Curry et

al. (2010), Forester (1991), Forester et al. (1994), Gunther and Hunt (1977), Gusskov et al. (2008), Karrow et al. (1997), Kienast et al. (2010), Kramer and Holmes (2009),

Krzyminska and Przezdziecki (2010), Last et al. (1994), Löffler (1990), Majoran and

Nordberg (1997), Matthews (1975), Miller and Palmer (1993), Oviatt (1988),

Poberezhnaya et al. (2006), Rattas et al. (2010), Roe (2001), Rosenbaum and Kaufman

(2009), Smith (1997), Smith et al. (2002), Swain (1990), Thompson et al. (1990),

Wetterich et al. (2009), and Wilkinson et al. (2005).

Figure 16. Circumpolar map of Cytherissa lacustris showing Quaternary and modern distributions created in ESRI ArcMap (Non-Marine Ostracod Distribution in Europe (NODE) – Horne et al., 1998; Allen and Anderson, 2000; Bunbury and Gajewski, 2009; Burke, 1987; Curry and Baker, 2000; Curry et al., 2010; Forester, 1991; Forester et al., 1994; Gunther and Hunt, 1977; Gusskov et al., 2008; Karrow et al., 1997; Kienast et al., 2010; Kramer and Holmes, 2009; Krzyminska and Przezdziecki, 2010; Last et al., 1994; Löffler, 1990; Majoran and Nordberg, 1997; Matthews, 1975; Miller and Palmer, 1993; Oviatt, 1988; Poberezhnaya et al., 2006; Rattas et al., 2010; Roe, 2001; Rosenbaum and Kaufman, 2009; Smith, 1997; Smith et al., 2002; Swain, 1990; Thompson et al., 1990; Wetterich et al., 2009; and Wilkinson et al., 2005). Map view demagnified to show wide distribution of Cytherissa lacustris Quaternary and modern records.

Cyclocypris cf. ampla Assemblage The Cyclocypris cf. ampla assemblage (Table 7) represents the largest portion in

USGS 70-92, known as Zone 4, from a depth of 180-242 centimeters. This environment is best classified as a palustrine system which is dominated by Cyclocypris cf. ampla, but also includes lacustrine species, Fabaeformiscandona rawsoni. This is consistent with the idea that “pond-lake habitats can be viewed as a continuum from shallow to deep water”

(Smith and Delorme, 2009, p. 734). The Cyclocypris cf. ampla valves within USGS 70-

92, although fairly abundant in this zone, were partly decalcified and dissolved and thus were compared to the ampla species of the Cyclocypris genus. Stratigraphically, the

USGS characterized the sediment from this zone as iron-stained sand to sandy mud with pebbly sand located around 240 centimeters. These types of sediments also substantiate the presence of oxygenated terrestrial systems.

Table 7. Cyclocypris cf. ampla assemblage data.

Ostracode Ecological Significance Count Count Rank Cyclocypris cf. ampla Palustrine 44 1 Candona sp. juveniles Fluvial / Palustrine 22 2 Limnocythere inopinata Fluvial / Lacustrine 5 3 Fabaeformicandona rawsoni Lacustrine 4 4 Cypria ophthalmica Palustrine 3 5

Cyclocypris cf. ampla has a modern distribution in North America and Asia that is mid-latitudinal (Figure 17). Similar to the distributions of Limnocythere inopinata and

Cytherissa lacustris, Cyclocypris cf. ampla can tolerate a number of habitats with variable temperatures and precipitation (Delorme, 1970b). Based on the interval represented in USGS 70-92, this final environment persisted for some time prior to the zone devoid of ostracodes and subsequent marine transgression, which likely disrupted the existing sedimentation. Quaternary and modern location data were compiled from known literature by Curry and Baker (2000), Curry and Delorme (2003), Curry et al.

(2010), Forester et al. (1989), Karrow et al. (1995), Lister (1975), Porter et al. (1999),

Smith et al. (2002), Teller (1989), and Vance et al. (1997).

Figure 17. Circumpolar map of Cyclocypris ampla showing Quaternary and modern distributions created in ESRI ArcMap (Curry and Baker, 2000; Curry and Delorme, 2003; Curry et al., 2010; Forester et al., 1989; Karrow et al., 1995; Lister, 1975; Porter et al., 1999; Smith et al., 2002; Teller, 1989; and Vance et al., 1997). Map view demagnified to show North American distribution of Cyclocypris ampla Quaternary records.

Spectral Reflectance (PCA)

In preliminary qualitative analysis of reflectance properties of the core sediment, many of the spectra showed limited graphical variation as expected with the mixed sediment characteristic of USGS 70-92. Based on this initial assessment and further quantitative analysis, I was able to determine that there was an intimate clay mixture because of the heterogeneous nature of the core material. As defined by Clark (1999), an intimate mixture is one that occurs when different materials are in intimate contact in a scattering surface. Despite the heterogeneity of the core sediment, varimax-rotated principal component analysis of the variable-based dataset identified 4 principal components, VPC_1, VPC_2, VPC_3, and VPC_4, which explained 94.15% cumulative variance within the dataset (Table 8). These four principal components can be seen in the scree plot (Figure 18) as leading components (red circles), whereas, the remaining components lack structure and form a “noise floor” (Ortiz et al., 2009, p. 77).

Table 8. Table of eigenvalues and variance explained for USGS 70-92 spectral reflectance principal component analysis.

Eigenvalues VPC Total % of Variance Cumulative % 1 15.06 48.58 48.58 2 10.65 34.36 82.94 3 2.01 6.49 89.43 4 1.46 4.73 94.15

Figure 18. Scree plot of eigenvalues (variance explained) versus component numbers, where red circles represent the four principal components and the open circles represent the “noise floor” in which little additional information is gained (Ortiz et al., 2009 and SPSS® 14.0 for Windows).

The component loadings were statistically compared to center-weighted derivatives of known minerals to identify any correlations, both positive and negative.

Minerals that were positively correlated were then graphed with the principal component spectral signatures. The first principal component (VPC_1) accounted for 48.58% of the total variance (Table 8) and generated a spectral signature that most closely resembled the mixture of minerals Illite + Goethite (Figure 19). Though this mineral combination does not account for every part of the VPC_1 signature, it does fairly represent the overall structure. Illite, a common non-expanding clay mineral in the Arctic, is thought to originate from a locally-enriched terrigenous source (Naidu et al., 1982) possibly delivered in the form of rock flour during glacial times (Ortiz et al., 2009). Goethite, a non-clay iron-bearing oxide, like illite, is also commonly associated with a continental provenance although likely from riverine input and coastal erosion (Ortiz et al., 2009).

The signature noticeably deviates from the Illite + Goethite mixture starting at a wavelength of 600 nanometers up to approximately 680 nanometers. This departure is commonly seen in samples that contain phytoplankton pigments. In this particular case, the peaks most closely represent cyanobacteria pigments which were observed in Ortiz et al. (2011).

The second principal component, VPC_2, accounted for 34.36% of the variance

(Table 8) and, as represented in Figure 20, is most closely associated with a mixture of

Smectite + Chlorite and possibly some illite as well. Smectite and chlorite are both clay minerals, although smectite is typically classified as expandable clay. In related studies of the Arctic, higher concentrations of smectite have been found in Chukchi shelf sediments

located in association with delta and estuarine sectors of rivers (Kalinenko, 2001) as well as in North Pacific sediments derived from the Aleutian arc (Hathon and Underwood,

1991). Conversely, chlorite is largely found in the North Pacific, but serves as a viable tracer for transport northward through the Bering Strait during times of inundation. The spectral signatures for VPC_2 and the Smectite + Chlorite mixtures trend well until a wavelength of approximately 625 nanometers, where a spike in the signature can be seen.

This spike is likely to represent phycocyanin, a light-harvesting pigment that absorbs in the yellow-green portion of the electromagnetic spectrum around 620-630 nanometers

(Ortiz et al., 2011).

Figure 19. Varimax-Rotated Principal Component 1 (VPC_1) compared to the derivatives of known mineral spectra for minerals, Illite + Goethite (Ortiz et al., 2009).

Figure 20. Varimax-Rotated Principal Component 1 (VPC_2) compared to the derivatives of known mineral spectra for minerals, Smectite + Chlorite and Smectite + Chlorite + Illite (Ortiz et al., 2009).

The third principal component, VPC_3, only accounted for 6.49% of the total variance (Table 8), but was strongly correlated with the spectral signature for glauconite

(Figure 21). This mineral is classified as a silicate and is commonly associated with shallow depositional environments on marine shelves, where the conditions are to some extent reducing (Stow, 2005). Yurco et al. (2010) found glauconite in Arctic sediments and compared its spectral signature to manganese (Mn) content as a proxy for glacial- interglacial cycles. They found that the glauconite demonstrated higher frequency variability than the Mn, but peaked primarily during transitions between illite + goethite and smectite + chlorite, indicating that its deposition was associated with late glacial periods (Yurco et al., 2010). Like the previous two components, the spectra for VPC_3 also contains spikes in the signature, the first around 430 nanometers and the second around 625 nanometers. Based on pigment data from Ortiz et al. (2011), these spikes

most closely resemble chlorophyll a and phycocyanin pigments, which typically peak at

440 nanometers and 620-630 nanometers, respectively. The presence of a marine component, like glauconite, is consistent with the location of USGS 70-92 on the

Chukchi continental shelf and the latter part of the core sediment, which represents the early Holocene transgressive event.

Figure 21. Varimax-Rotated Principal Component 1 (VPC_3) compared to the derivatives of known mineral spectra for mineral, Glauconite (Ortiz et al., 2009).

The fourth and final principal component, identified as VPC_4, described 4.73% of the total variance (Table 8) and is closely associated with the mixture of Chlorite +

Amphibole (Figure 22). Although this final component represents the least significant of the principal components, it remains consistent with findings from other Arctic sediment studies. Chlorite, as described previously, is a clay mineral with a North Pacific provenance that is typically transported through the Bering Strait northward in to the

Chukchi Sea. Amphiboles are minerals that can form as a result of late-stage magma crystallization in metamorphic rocks (Gillis, 1996). Presence of this important mineral is likely the result of transport from a gabbroic or andesitic source of metamorphic rocks.

The presence of this particular mixture further corroborates the transport of clay minerals and clastics through the Bering Strait from the Pacific Ocean during times of transgression.

Figure 22. Varimax-Rotated Principal Component 1 (VPC_4) compared to the derivatives of known mineral spectra for minerals, Chlorite + Amphibole (Ortiz et al., 2009).

Because of the assorted nature of the sediment found in USGS 70-92, I did not expect the spectral signatures of the 4 components to be explained by one mineral type

(clay or non-clay), however, given the area of interest, I did anticipate the presence of indicator clay and non-clay minerals as found during the course of this study. When the reflectance data (component scores) were plotted on a down-core graph (Figure 23) with

ostracode abundance data, the heterogeneity of USGS 70-92 became very apparent as did the disparity in the ostracode counts above 205 centimeters of depth. Although there did not seem to be a relationship between the spectral reflectance of the sediment and ostracode abundance, I was able to statistically reveal a trend (See PCA).

Figure 23. Reflectance component scores and ostracode abundance displayed in raw valve count, down-core USGS 70-92. Ostracodes zonation display in vertica gray-scale bars and marine to non-marine transition indicated by vertical dashed line.

In an effort to understand the regional significance of USGS 70-92, the core’s component loadings (VPC_1 – VPC_4) were compared to those from a larger dataset from the Bering and Chukchi Sea shelves that were generated with principal component analysis in the same manner (Nwaodua and Ortiz, 2011). Although the order of the 4 varimax-rotated principal components (VPCs) varied between the local and regional data, they correlated with many of the same known minerals. The variation between the

datasets was to be expected because USGS 70-92 is abbreviated both spatially and temporally, whereas the Bering and Chukchi Sea shelves dataset was compiled from approximately 200 cores. When component loadings from both the local and regional datasets were compared, VPC_3 and VPC_4 from USGS 70-92 matched above a 0.50 critical value with the regional VPC_1, meaning the two datasets were 50% similar.

Interestingly, VPC_3 and VPC_4 from USGS 70-92 represented Glauconite and Chlorite

+ Amphibole mineral assemblages, respectively and the regional VPC_1 represented

Chlorite + Muscovite. When the center-weighted derivatives were graphed for the respective components, it was clear there was a significant relationship between USGS

70-92 VPC_4 and the Bering and Chukchi Sea shelves VPC_1 (Figure 24).

Figure 24. VPC_4 from USGS 70-92 compared to the VPC_1 from Chukchi Sea regional core reflectance data (Nwaodua and Ortiz, 2011 and Ortiz et al., 2009).

Ostracodes (PCA)

The principal component analysis results from the ostracode species count data produced 3 axes that accounted for 80.55% of the dataset’s variance (Table 9). Based on the PCA Variable Loadings (Table 9), it is evident that Axis 1, which is responsible for

48.17% of the total variance, is dominated by Candona candida, Candona rectangulata, three species of Limnocythere, and Pteroloxa cumuloidea. Axis 2, which accounts for

20.19% of the total variance, is dominated by Candona candida, Fabaeformiscandona rawsoni, and Ilyocypris biplicata. The final axis, Axis 3, represents only 12.19% of the total variance in the dataset, but is notably dominated by Cyclocypris cf. ampla and

Cytherissa lacustris.

The independence of ostracode species found on Axes 1 and 3 (Figure 25) provides the most significant insight into the dataset and more specifically its hydrology.

Axis 1 appears to be driven by species limited to the Arctic, Candona rectangulata and

Pteroloxa cumuloidea, perhaps also signifying tolerance of limited saline input.

Conversely, Axis 3 appears to be dominated by species that range through Canada today to the southern limit of the summer position of the Arctic airmass, namely Cyclocypris cf. ampla and Cytherissa lacustris, which are also known for requiring exclusively freshwater habitats. The most notable ostracode extremes, which agree with the axis distributions, are Pteroloxa cumuloidea and Cytherissa lacustris which operate in very different ecological niches, estuarine versus lacustrine, respectively. When comparing

Axis 1 to 2 (Figure 26), the presence of three clusters becomes apparent. Like Figure 25,

this graph reveals the Arctic ostracode assemblage, and it also reveals two non- Arctic freshwater groups, one of which is less stringent in terms of its salinity requirements.

In the principal component analysis of the pooled ostracode species count and spectral reflectance data, 7 axes were generated that accounted for 92.40% of the total variance in the dataset (Table 10). The high amount of axes was expected due to the diversity of the input dataset, which also yielded weak PCA variable loadings. Although the initial statistics were not very informative, I used a scatter plot to graphically depict the results in hope of a trend (Figure 27). When Axes 1 and 2 were compared, such a trend appeared with the PCA cases, which represented depth within the core, measured in centimeters. Two general clusters of cases were apparent in this plot, which revealed a division between the Holocene (mainly marine sediments) and Pleistocene (exclusively non-marine sediments) time periods. In the Pleistocene-aged cluster, the presence of ostracodes is also noted and consistent with my previous findings.

Table 9. Table of eigenvalues, variance, and variable loadings explained for USGS 70-92 ostracode species count principal component analysis.

Eigenvalues Axis 1 Axis 2 Axis 3 Eigenvalues 5.30 2.22 1.34 % of Variance 48.17 20.19 12.19 Cumulative % 48.17 68.36 80.55

PCA Variable Loadings Axis 1 Axis 2 Axis 3 Candona candida 0.32 -0.41 0.04 Candona rectangulata 0.42 0.03 0.02 Cyclocypris cf. ampla -0.07 0.04 0.69 Cypria ophthalmica -0.02 0.02 -0.10 Cytherissa lacustris -0.03 0.03 0.71 Fabaeformiscandona rawsoni 0.17 -0.58 0.05 Ilyocypris biplicata 0.24 -0.53 0.03 Limnocythere friabilis 0.40 0.27 0.01 Limnocythere inopinata 0.40 0.18 0.02 Limnocythere sharpie 0.41 0.15 0.02 Pteroloxa cumuloidea 0.37 0.29 0.01

Figure 25. Principal component analysis scatter plot of Axis 1 versus Axis 3 for ostracode species count data. This graph depicts two separate clusters; non- Arctic species in the top left portion of the plot and more Arctic -like species in the bottom center.

Figure 26. Principal component analysis scatter plot of Axis 1 versus Axis 2 for ostracode species count data. This graph depicts three clusters including the first non- Arctic very freshwater group in the center, the second non- Arctic intermediary freshwater group towards the bottom-right, and the final cluster of Arctic species in the right-center group.

Figure 27. Principal component analysis scatter plot of Axis 1 versus Axis 2 for pooled ostracode and spectral reflectance data. This graph depicts the presence of two groups identified as Pleistocene, Non-Marine sediments (in green) and Holocene, Marine sediments (in red). Ostracode species confirm the division by clustering in the non- marine portion of the graph.

Table 10. Table of eigenvalues and variance for USGS 70-92 pooled ostracode species count and spectral reflectance principal component analysis.

Eigenvalues Axis 1 Axis 2 Axis 3 Axis 4 Axis 5 Axis 6 Axis 7 Eigenvalues 15.47 11.47 5.02 2.15 2.06 1.43 1.21 % of Variance 36.84 27.31 11.94 5.12 4.92 3.39 2.89 Cumulative % 36.84 64.15 76.09 81.21 86.13 89.52 92.40

Cluster Analysis

After running a constrained cluster analysis based on the Gower General

Similarity Coefficient and the farthest neighbor clustering method, 4 distinct groups of ostracodes were apparent (Figure 28, Table 11). The first cluster represents the interval from the base of the 270 centimeter core up to 258 centimeters and, according to the

USGS soil characterization, includes Pleistocene-age non-marine silty mud. This cluster, in terms of the ostracode assemblage, represents an estuarine system which is likely being influenced by minimal marine inputs. The second cluster begins at 257 centimeters and persists up to a depth of 250 centimeters and, like the first cluster, also includes

Pleistocene-age non-marine silty mud. Ostracode data for this section suggests the presence of a lacustrine system, but likely one that was ephemeral. The third cluster is quite brief in terms of the depth interval it represents within the core at 245-247 centimeters, but clearly represents a permanent lacustrine system as indicated by the ostracode indicator species, Cytherissa lacustris. The fourth and final cluster, represented from 180-242 centimeters, is best characterized as a palustrine system meaning it was more likely a wetland. This classification is based on the presence of ostracode species that are typically found in ephemeral wetland systems with peat-dominated soils, which are found as laminations towards the top of this interval. Above the four ostracode clusters at around 177 centimeters, there is no structure to the dendrogram because there are no longer any ostracodes; with the exception of one valve of Cyclocypris cf. ampla.

This valve was excluded from the cluster analysis in an effort to limit distortion on the dendrogram. Based on the core soil characterization from the USGS, the area from 0-125

centimeters represents the Holocene marine transgression sediments through the early occurrence of laminated peats, which persists into the fourth and final cluster.

Figure 28. Cluster analysis dendrogram generated by using the Gower General Similarity Coefficient and Farthest Neighbor cluster method, constrained by depth. The four colored sections represent identified ostracode zones.

Table 11. Ostracode clusters identified through cluster analysis.

Cluster Depth Number Represented Samples Environment 1 258-270 cm 258-259 to 268-270 cm Estuarine 2 250-257 cm 250-252 to 255-257 cm Ephemeral Lacustrine 3 245-247 cm 245 to 247 cm Permanent Lacustrine 4 180-242 cm 180-182 to 240-242 cm Palustrine

Modern Analog Reconstruction The unconstrained cluster analysis used to generate the similarity/distance matrix yielded 147 modern analog sites, 145 located within Canada from the Canadian Museum of Nature Delorme collection, and 2 sites from the Matanuska Alaskan Lakes dataset

(Forester et al., 1989). Matches, filtered at a 0.75 critical value, were generated for 11 depth intervals including: 250-252 cm, 240-242 cm, 235-237 cm, 230-232 cm, 228-235 cm, 215-217 cm, 210-212 cm, 195-197 cm, 190-192 cm, 185-187 cm, and 105-107 cm.

The first analog interval, 250-252 cm, is the only depth associated with Zone 2 and encompasses the upper part of the zone. It is identified as an ephemeral lacustrine environment with indicator species Limnocythere inopinata and Ilyocypris biplicata. The remaining depths, aside from 105-107 cm, are associated with the Zone 4 wetland-like environment, which was identified with palustrine species, Cyclocypris cf. ampla, primarily. The final analog interval, 105-107 cm, was the only depth from the depth range primarily lacking ostracodes and yielded analogs because of the presence of one

Cyclocypris cf. ampla valve, which was not omitted because its presence in this particular case of presence / absence was meaningful.

Site matches drawn from modern analogs are noteworthy; however the no analog situations lend pertinent information as well. The first instance showing no analogs was associated with Zone 3 at 245-247 cm depth, even though the modern dataset included sites with species indicative of a permanent lacustrine system, like Cytherissa lacustris.

This no analog situation can best be explained by the assemblage data used for comparison. In USGS 70-92, there are other species associated with the permanent lacustrine system, including Candona sp. juveniles, Candona candida, and Cyclocypris cf. ampla, but these species only represent a subset of the expected Cytherissa lacustris assemblage, which commonly includes additional species such as, Cypria ophthalmica,

Cypria turneri, Ilyocypris gibba, Candona subtriangulata, Limnocythere liporeticulata, and Tonnacypris glacialis, to name a few (Bunbury and Gajewski, 2005; Bunbury and

Gajewski, 2009).

Once mapped with the use of ESRI ArcMap (Figure 29), it was evident that the modern analog site matches drawn from the Canadian Museum of Nature Delorme collection and the Matanuska Alaskan Lakes dataset (Forester et al., 1989) were well distributed throughout western and south-central Canada including the following provinces: Alberta, British Columbia, Manitoba, the Northwest Territories, Ontario,

Quebec, Saskatchewan, and the Yukon Territory, whereas, the modern analog sites drawn from Matanuska Lakes sites were only located in South-Central Alaska. The lack of

modern analog sites drawn from outside of North America suggests that the faunal assemblages at this time have already been established. Interestingly, the modern analog site locations, for the most part, were located in lower latitudes then the fossil assemblage represented in USGS 70-92. The mean January and July temperatures were averaged from the modern analog sites to determine a temperature range estimate for the fossil assemblage, which yielded the following mean temperatures: January (°C) = -20.9 and

July (°C) = 16.7.

Based on the identified mean temperatures for January and July, I was able to isolate the sites within the modern analog datasets (Canadian Museum of Nature Delorme collection and the Matanuska Alaskan Lakes dataset (Forester et al., 1989), to better determine where these specific conditions are met in the modern world. This analysis yielded 2 sites with a mean January temperature of -20.9 °C and 4 sites with a mean July temperature of 16.7°C, but none of which had both January and July annual temperatures present. Location data for these sites is depicted in Figure 29. As can be seen, these sites are restricted to the south-central portion of Canada and are quite distant from the location of the USGS 70-92 fossil assemblage (Figure 29).

The geographic site distribution coupled with modern temperature data implies that the climatic conditions represented in USGS 70-92, were at one time more temperate and mid-latitudinal. While the modern analog technique allows for reconstruction of past environments, it must be noted that these analogs only represent two of the latter zones (2 and 4) within the core and thus only generally describe the autecology of USGS 70-92.

Figure 29. Map of modern analog sites matched from Zones 2 and 4, as well as sites with mean annual January and July temperatures from Alaska and Canada. Datasets from the Canadian Museum of Nature Delorme collection and (Forester et al. 1989).

Ostracode Zonation

During the course of this study on USGS 70-92, four distinct ostracode zones were identified. In Figure 9, the zonation is best illustrated as a factor of depth (in centimeters) with supplementary data on ostracode species’ abundance in valves / gram.

Although some of the zones are brief, their faunal assemblages represent distinct environmental shifts and record a terrestrial succession on land that is now currently inundated. Zone 1 most clearly represents a freshwater system that is being influenced by some form of saline input, whether in the form of sea spray or connection to an estuarine system. This system is also more Arctic-like in its climate based on the presence of estuarine, Arctic species, Pteroloxa cumuloidea and Arctic species, Candona rectangulata. Zone 2 is marked by the disappearance of Pteroloxa cumuloidea, decrease in Candona rectangulata, and entry of palustrine species, Cyclocypris cf. ampla. At this time, Ilyocypris biplicata and Limnocythere inopinata are very abundant, indicating a more ephemeral lacustrine environment. In Zone 3, the shift from ephemeral lacustrine to permanent lacustrine is indicated by the entry of indicator species, Cytherissa lacustris.

This particular record is fairly brief in the core and does not include the breadth of the average permanent lacustrine assemblage, but is evident in the record. The final transition occurs at Zone 4, where Cytherissa lacustris is no longer present, but palustrine species,

Cyclocypris cf. ampla and Cypria ophthalmica enter the scene. This zone is interpreted as

being more wetland-like and is corroborated by the peat-dominated soils found in the core sediment in the latter part of this zone. The ostracode zonation is further supported by the multi-variate statistics used in this study, namely cluster analysis and principal component analysis.

Discussion

During analysis of the ostracode assemblage of USGS 70-92, four ostracode zones (Figure 9) were identified that represented terrestrial non-marine systems during the late Pleistocene. The first zone is represented by fresh to oligohaline fauna; species

Pteroloxa cumuloidea and Candona rectangulata, and is dated to around 12,640 + 45 14C years BP (14,723 + 93 calendar years BP). This estuarine environment gives way to an ephemeral freshwater habitat at about 12,470 + 45 14C years BP (14,419 + 127 calendar years BP), which includes ostracode assemblages led by Ilyocypris biplicata and

Limnocythere inopinata. This ephemeral system, known as Zone 2, transitions to a permanent lacustrine habitat identified as Zone 3. Its permanence is recognizable by indicator species Cytherissa lacustris. This lacustrine system is short-lived and is eventually in-filled and replaced by a peat-dominated wetland system, recognized as the fourth and final zone. This palustrine system is dominated by indicator species

Cyclocypris cf. ampla and Cypria ophthalmica. The remainder of the core sediment, from approximately 125 centimeters up to the core top, represents early Holocene marine transgression resulting in inundation of the Beringian region.

The transition from an ephemeral lacustrine environment, like that seen in Zone 2, to a permanent lacustrine system (Zone 3), is best represented by Figure 30, which depicts the relationship between common freshwater genera, Cytherissa, Candona, and

Limnocythere (Forester, 1991). In this graphic, it is evident that these 3 genera are

dependent on different levels of annual water-body variability, which includes temperature, chemical, and volume factors (Forester, 1991). As demonstrated in USGS

70-92 and its respective assemblages, Cytherissa requires permanent waters, whereas the limnocytherids are more inclined to ephemeral waters and the candonids fall in-between these two extremes. This scenario is also demonstrated in Table 6, where there are no species from the Limnocythere genus present.

Figure 30. Relationship between genera, Cytherissa, Candona, and Limnocythere in terms of annual water-body variability (from Forester, 1991, Figure 3, p. 135, with permission from Quaternary Science Reviews).

Notably, only the earliest zone contains eurytopic and oligohaline species that are exclusively found in the polar Arctic regions today (Figures 12 and 13). Subsequent ostracode zones are characterized by freshwater species that occupy a range of temperatures and are commonly present in modern mid-latitude North America (Figures

14, 15, 16, and 17). The biogeography of these species highlights the absence of high latitude and polar fauna, suggesting that temperature ranges were consistent with sub-

Arctic and mid-latitude temperature ranges during the interval following the first zone.

Analysis using the modern analog technique supported this hypothesis with reconstruction of Zones 2 and 4 based on corresponding Canadian and Southeastern

Alaskan sites, which were associated with mean annual January and July temperatures of

-20.9 °C and 16.7 °C, respectively. The calibration dataset of 7,036 data points used in this analysis included circumpolar, Holarctic non-marine ostracode distributions for the first time. A significant result of this study is the absence of modern analogs outside of

North American sites. This result suggests that North American assemblages were already established, further strengthening the idea that the sub-Arctic regions were experiencing significant shifts in climatic conditions.

With the transition from Arctic to more mid-latitudinal environmental conditions, this portion of Beringia would have been an effective filter-bridge (Simpson, 1940), allowing the exchange of flora and fauna. Based on the findings from the ostracode and sediment analyses of USGS 70-92, this physical migration route was available and persisted for some time, allowing such an exchange. This study, like all Beringia-related analyses, has implications for narrowing the window in which fauna and humans would have been most likely to cross the Bering land bridge; lending important insight into our prehistoric past.

In case studies conducted by other researchers on Quaternary Arctic ostracodes, the focus has been on not only determining the assemblages present, but also interpreting and reconstructing the environments in which they lived (Stepanova et al., 2010). In

Stepanova, et al.’s 2010 paper, six assemblages (freshwater, brackish-water estuarine, marine of the inner shelf, marine of the middle shelf, marine of the outer shelf, and marine of the upper continental slope) which corresponded to gradual increase in water depth, were identified. The first three assemblages from this study (freshwater, brackish- water estuarine, and marine of the inner shelf) contained indicator species that were also found within the respective zones of USGS 70-92. These species included freshwater taxa, Cytherissa lacustris and Candona sp. and brackish water species, Pteroloxa cumuloidea. In another study specifically of freshwater ostracodes from the Canadian

Arctic Archipelago, Bunbury and Gajewski found seven species of freshwater ostracodes endemic to the arctic, of which two species, Cytherissa lacustris and Candona rectangulata, were also present within USGS 70-92. The correlation of indicator species found within the core of interest and the study areas of other researchers working in the

Beringia area further reinforces the consistency of these findings.

While ostracode assemblages lend insight in to reconstructing the Late Glacial, they must be substantiated with other forms of proxy data that are also effective climate recorders. In Beringia, these data have predominately come from paleoentomological and palynological analyses. In Elias et al. (1992), USGS vibracore sample 69-91 (Barnes et al., 1986), collected during the USGS 70-92 cruise, was investigated. This particular core was located adjacent to USGS 70-92 and represents similar stratigraphy and lithology

(Figure 5). Non-marine strata were sampled for algae, fossil insects, and pollen, primarily within the peat horizons of USGS 69-91. Algae present included Pediastrum and

Botryococcus, indicating the presence of freshwater to brackish waters and fossil beetles were fairly diverse in terms of the species assemblage indicating the presence of a mesic habitat and warmer climatic conditions (Elias et al., 1992). This reconstruction was supported by pollen spectra that were dominated by grasses and sedges and ancillary amounts of birch and herbs (Elias et al., 1992).

Physical property analysis of USGS 70-92 core sediment, namely principal component data from VNIR spectroscopy, agreed well with research conducted by

Kalinenko (2001), Naidu et al. (1982), Naidu and Mowatt (1983), and Ortiz et al. (2009) on clay dispersal in Arctic sediment. The first principal component (VPC_1), and presumably the most abundant from USGS 70-92, was most closely associated with a mixture of Illite + Goethite. When compared with the illite distribution map from Naidu and Mowatt (1983) (Figure 31), the USGS 70-92 location plots within a zone that has 48-

59% illite present, substantiating the principal component data generated for USGS 70-

92. In another map from Kalinenko (2001) (Figure 32) based on X-Ray Diffraction

(XRD) data, clay provinces were determined for the Arctic including the Bering and

Chukchi Sea shelves. Similar to work done by Naidu and Mowatt (1983), the dominant clay province within the area that USGS 70-92 was cored is identified as an illite province (> 50%) (Kalinenko, 2001).

USGS Core 70-92

Figure 31. Distribution of illite in marginal Alaskan seas (modified from Naidua and Mowatt, 1983, Figure 4, p. 845, with permission from GSA Bulletin).

USGS Core 70-92 Figure 32. Clay provinces in the Arctic based on XRD analysis where, (1) Illite > 50%, (2) Smectite (Montmorillonite) 20-50%, (3) Smectite (Montmorillonite) > 50%, (4)

Chlorite > 45%, and (5) Chlorite belt (modified from Kalinenko, 2001, Figure 4, p. 368, with permission from Lithology and Mineral Resources).

When compared to the North Greenland Ice Core Project (NGRIP) record, based on δ18O values, ostracode zones identified within USGS 70-92 appear to coincide with the time frame associated with the Bølling/Allerød (B/A) interstadial (Figure 33). This relatively warm period persisted from approximately 14,700 – 12,900 calendar years BP

(Zheng et al., 2000) and is represented in the oxygen isotope record by lighter values of

δ18O. The transition to heavier values of δ18O signifies the beginning of the Younger

Dryas (YD), a time-transgressive cold period. Although dating of USGS 70-92 is limited, the known chronology corresponds with well-dated ice core data that represents the global signature during this period of time.

In a side-by-side comparison with δ18O values from the NGRIP record, the VNIR spectroscopy data from USGS 70-92, although variable downcore, most notably signals the transition from non-marine to marine depositional environments between approximately 12,800 -12,500 calendar years BP. During this interval, VPC_1 (Illite +

Geothite) and VPC_3 (Glauconite) have the highest component scores and likely represent the onset of inundation and the resultant shallow marine environment. VPC_2

(Smectite + Chlorite) shows little structure, while VPC_4 (Chlorite + Amphibole) has very low component scores at this time indicating that the provenance of minerals at this specific time is probably not from the North Pacific, but more likely from a continental source. Overall, the four principal components appear to show a general trend that when

compared against the NGRIP data record, depicts an inverse relationship between δ18O and temperature.

The onset of a warmer Arctic, like that recorded in USGS 70-92 and other sediment cores from Beringia during the Late Glacial, seems to be reoccurring in today’s climate, although not with the same environmental parameters as before. This general trend is indicated by unprecedented warming of the atmosphere, ocean, and land

(Budikova, 2009). According to the National Oceanic and Atmospheric Administration

(NOAA), this phenomenon, identified as the Warm Arctic-Cold Continent Climate

Pattern (Figure 34), is best explained by weakening of the Polar Vortex which, in turn, allows southerly movement of cold, Arctic air masses. Though seemingly analogous to the events recorded in USGS 70-92, further research is required of additional cores from

Beringia and areas south, representing the same time period, to quantitatively evaluate whether this pattern is cyclical and potentially related to glacial-interglacial phases. More investigation is also needed to determine the departure in conditions present then from now to help further quantify anthropogenic influence on the climate.

Figure 33. NGRIP δ18O record with chronology and ostracode zonation from USGS 70- 92 next to downcore reflectance scores with chronology. Placement of USGS 70-92 zones and transitions estimated from three known 14C dates provided by the USGS. NGRIP data group, 2006 from NOAA/NCDC Paleoclimatology Program, Boulder CO, USA, Data Contribution Series # 2006-118.

Figure 34. Warm Arctic – Cold Continent Climate Pattern from the National Oceanic and Atmospheric Admnistration (NOAA).

Conclusions

Interestingly enough, there are few cores from the now submerged Bering Land

Bridge that extend into the terrestrial sediments beyond the marine surficial sediments which accumulated following the transgression (Ager and Phillips, 2008), making this core even more noteworthy. During the time period represented by USGS 70-92, there is significant paleoclimate change as a result of changes in exposure to sea water and fluctuations in permanence of the systems. These changes are indicated throughout the core by the ostracode species represented along the layers and are further corroborated by other forms of biological proxy data from Beringia as well as reflectance data obtained from the core sediment. As said by Scott Elias (2008, p. 2482),

“All ecosystems, past and present, are made up of patches of varied communities.

Certain community types may dominate, but not to the exclusion of others.”

This is an important concept to keep in mind when studying a formerly vast area like

Beringia (Figure 35) from a variety of proxy data acquired from only a few sites and cores. Consideration must be taken temporally and spatially, especially since the time period is relatively short and the area quite large.

Recommended future analyses of USGS 70-92 include shell chemistry analysis for isotopes (δ18O and δ13C ratios) as the calcite present can offer insight into the water

conditions present during valve formation (Wetterich et al., 2008), continued study of the ostracode assemblages and their ecological significance, as well as, further investigation into the succession of environments as a factor of climate change. By employing a multidisciplinary and multi-proxy approach, a more accurate representation of the Beringian paleoenvironment can be reconstructed.

USGS Core 70-92

Figure 35. Bering Land Bridge (modified from Ager, 2003, Figure 1, p. 20, with permission from Quaternary Research).

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Appendix A: USGS 70-92 Sample Inventory

Chukchi Sea Sample Inventory, Raw Samples, USGS 70-92:

Section/cm Depth Epoch Section 1 (0-125 cm) 0-2 cm Holocene Section 1 (0-125 cm) 8-10 cm Holocene Section 1 (0-125 cm) 15-17 cm Holocene Section 1 (0-125 cm) 25-27 cm Holocene Section 1 (0-125 cm) 33-35 cm Holocene Section 1 (0-125 cm) 43-45 cm Holocene Section 1 (0-125 cm) 53-55 cm Holocene Section 1 (0-125 cm) 61-63 cm Holocene Section 1 (0-125 cm) 72-74 cm Holocene Section 1 (0-125 cm) 87-89 cm Holocene Section 1 (0-125 cm) 94-96 cm Holocene Section 1 (0-125 cm) 105-107 cm Holocene Section 1 (0-125 cm) 115-117 cm Holocene Section 1 (0-125 cm) 121-123 cm Holocene Section 2 (125-270 cm) 125-127 cm Pleistocene Section 2 (125-270 cm) 130-132 cm Pleistocene Section 2 (125-270 cm) 135-137 cm Pleistocene Section 2 (125-270 cm) 140-142 cm Pleistocene Section 2 (125-270 cm) 145-147 cm Pleistocene Section 2 (125-270 cm) 150-152 cm Pleistocene Section 2 (125-270 cm) 155-157 cm Pleistocene Section 2 (125-270 cm) 160-162 cm Pleistocene

114

Section 2 (125-270 cm) 165-167 cm Pleistocene Section 2 (125-270 cm) 170-172 cm Pleistocene Section 2 (125-270 cm) 175-177 cm Pleistocene Section 2 (125-270 cm) 180-182 cm Pleistocene Section 2 (125-270 cm) 185-187 cm Pleistocene Section 2 (125-270 cm) 190-192 cm Pleistocene Section 2 (125-270 cm) 195-197 cm Pleistocene Section 2 (125-270 cm) 200-202 cm Pleistocene Section 2 (125-270 cm) 205-207 cm Pleistocene Section 2 (125-270 cm) 210-212 cm Pleistocene Section 2 (125-270 cm) 215-217 cm Pleistocene Section 2 (125-270 cm) 220-222 cm Pleistocene Section 2 (125-270 cm) 225-227 cm Pleistocene Section 2 (125-270 cm) 230-232 cm Pleistocene Section 2 (125-270 cm) 235-237 cm Pleistocene Section 2 (125-270 cm) 240-242 cm Pleistocene Section 2 (125-270 cm) 245-247 cm Pleistocene Section 2 (125-270 cm) 250-252 cm Pleistocene Section 2 (125-270 cm) 255-257 cm Pleistocene Section 2 (125-270 cm) 260-262 cm Pleistocene Section 2 (125-270 cm) 265-267 cm Pleistocene Section 2 (125-270 cm) 268-270 cm Pleistocene Total Samples: 44

Chukchi Sea Sample Inventory, Sorted Samples, USGS 70-92:

Status by Lot # Depth Epoch Weight Mesh Comments by USGS USGS 2 0-2 cm Holocene 5.2 g 100 Picked 2 8-10 cm Holocene 5.2 g 100 Picked

115

116

2 15-17 cm Holocene - 100 Picked 2 25-27 cm Holocene 5.2 g 100 Picked 2 33-35 cm Holocene 5.5 g 100 Picked 2 43-45 cm Holocene 5.4 g 100 Picked 2 53-55 cm Holocene 5.1 g 100 Picked 2 61-63 cm Holocene 5.2 g 100 Picked 2 72-74 cm Holocene 5.4 g 100 Picked 2 87-89 cm Holocene 5.4 g 100 Picked 2 94-96 cm Holocene 5.8 g 100 Picked 2 105-107 cm Holocene 5.1 g 100 Picked 2 115-117 cm Holocene 5.6 g 100 Picked 2 121-123 cm Holocene 5.4 g 100 Picked 2 125-127 cm Pleistocene 5.2 g 100 Strip Picked 2 130-132 cm Pleistocene 5.6 g 100 Strip Picked 2 135-137 cm Pleistocene 5.1 g 100 Strip Picked 2 140-142 cm Pleistocene 5.5 g 100 Picked 2 145-147 cm Pleistocene 5.1 g 100 Picked, Strip all 2 150-152 cm Pleistocene 5.5 g 100 SeedStrip & Picked Insects 2 155-157 cm Pleistocene 5.5 g 100 Strip Picked 2 160-162 cm Pleistocene 5.2 g 100 Picked 2 165-167 cm Pleistocene 5.6 g 100 Picked 2 170-172 cm Pleistocene 5.2 g 100 - 2 175-177 cm Pleistocene 5.2 g 100 Strip Picked 2 180-182 cm Pleistocene 5.6 g 100 Strip Picked 2 185-187 cm Pleistocene 5.7 g 100 Picked 2 190-192 cm Pleistocene 5.0 g 100 Strip Picked 2 195-197 cm Pleistocene 5.5 g 100 Strip Picked 2 200-203 cm Pleistocene 5.2 g 100 Strip Picked 2 205-207 cm Pleistocene 5.3 g 100 Strip Picked - 210-211 cm Pleistocene 6.4 g 100 Partially Picked

117

- 210-211 cm Pleistocene 6.4 g 230 Partially Picked 2 210-212 cm Pleistocene 5.4 g 100 Strip Picked 2 215-217 cm Pleistocene 5.5 g - Strip Picked - 220-221 cm Pleistocene 11.1 g 100 Picked - 220-221 cm Pleistocene 11.1 g 230 Picked 2 220-222 cm Pleistocene 5.5 g 100 Strip Picked 2 225-227 cm Pleistocene 5.2 g 100 Strip Picked No weight- preprocessed via "float" procedure and reprocessed via code - 228-235 cm Pleistocene - 100 Picked lab procedure using chems but no freeze. No weight- preprocessed via "float" procedure and reprocessed via code - 228-235 cm Pleistocene - 230 Picked lab procedure using chems but no freeze. - 228-235 cm Pleistocene 5.4 g - Picked Second float of organics - 230-231 cm Pleistocene 12.7 g 100 Picked - 230-231 cm Pleistocene 12.7 g 230 Picked 2 230-232 cm Pleistocene 5.2 g 100 Strip Picked 2 235-237 cm Pleistocene 5.4 g 100 Strip Picked - 240-241 cm Pleistocene 30.1 g 100 Picked - 240-241 cm Pleistocene 30.1 g 230 Picked - 240-242 cm Pleistocene 7.5 g 100 Picked Sep '03 Set 2 240-242 cm Pleistocene 5.5 g 100 Strip Picked - 240-242 cm Pleistocene 7.5 g 230 Picked Sep '03 Set - 245-247 cm Pleistocene 15.9 g 100 Strip Picked Sep '03 Set 2 245-247 cm Pleistocene 5.4 g 100 Strip Picked - 245-247 cm Pleistocene 15.9 g 230 Examined Sep '03 Set

118

- 250-252 cm Pleistocene 5.8 g 100 Picked 2 250-252 cm Pleistocene 5.2 g 100 Strip Picked - 250-260 cm Pleistocene - 230 Picked Reprocessed residue from "float - 250-260 cm Pleistocene - 100 + > 20 Picked Reprocessedtechnique" residue from "float - 255-257 cm Pleistocene 11.0 g 100 Picked Septechnique" '03 Set 2 255-257 cm Pleistocene 5.2 g 100 Strip Picked - 255-257 cm Pleistocene 11.0 g 230 Picked Sep '03 Set - 258-259 cm Pleistocene 9.4 g 100 Picked - 258-259 cm Pleistocene 9.4 g 230 Picked - 260-262 cm Pleistocene 7.5 g 100 Picked Sep '03 Set 2 260-262 cm Pleistocene 5.4 g 100 Strip Picked - 260-262 cm Pleistocene 7.5 g 230 Picked Sep '03 Set - 265-267 cm Pleistocene 27.8 g 100 Picked - 265-267 cm Pleistocene 8.3 g 100 Picked Sep '03 Set 2 265-267 cm Pleistocene 5.2 g 100 Strip Picked - 265-267 cm Pleistocene 27.8 g 230 Picked - 265-267 cm Pleistocene 8.3 g 230 Picked Sep '03 Set - 268-270 cm Pleistocene - 100 Picked Sep '03 Set 2 268-270 cm Pleistocene 5.2 g 100 Strip Picked - 268-270 cm Pleistocene - 230 Picked Sep '03 Set Total Samples: 74

Chukchi Sea Sample Inventory, Slides, USGS 70-92:

Slide Tray Lot # Depth Epoch Weight Comments by USGS

1 2 0-2 cm Holocene 5.2 g 1 2 8-10 cm Holocene 5.2 g 1 2 15-17 cm Holocene 5.5 g 1 2 25-27 cm Holocene 5.2 g

119

1 2 33-35 cm Holocene 5.5 g 1 2 43-45 cm Holocene 5.4 g 1 2 53-55 cm Holocene 5.1 g 1 2 61-63 cm Holocene 5.2 g 1 2 72-74 cm Holocene 5.4 g 1 2 87-89 cm Holocene 5.4 g 1 2 94-96 cm Holocene 5.8 g 1 2 105-107 cm Holocene 5.1 g 1 2 115-117 cm Holocene 5.6 g 1 2 121-123 cm Holocene 5.4 g 1 2 125-127 cm Pleistocene 5.2 g 1 2 130-132 cm Pleistocene 5.6 g 1 2 135-137 cm Pleistocene 5.1 g 1 2 140-142 cm Pleistocene 5.5 g 1 2 145-147 cm Pleistocene 5.1 g 1 2 150-152 cm Pleistocene 5.5 g 2 - 129-131 cm Pleistocene 12.4 g 2 - 133.5-134.5 cm Pleistocene 13.6 g 2 - 145-146 cm Pleistocene 26.0 g 2 - 149-150 cm Pleistocene 8.0 g 2 - 160-161 cm Pleistocene 8.1 g 2 - 170-171 cm Pleistocene 6.8 g 2 - 180-181 cm Pleistocene 15.2 g 2 - 190-191 cm Pleistocene 11.0 g 2 - 200-201 cm Pleistocene 22.5 g 2 - 210-211 cm Pleistocene 6.4 g 2 - 220-221 cm Pleistocene 11.1 g 2 - 230-231 cm Pleistocene 12.7 g 2 - 228-235 cm Pleistocene - 2 - 228-235 cm Pleistocene - Second Float of Organics

120

2 - 240-241 cm Pleistocene 30.1 g 2 - 250-251 cm Pleistocene 11.6 g 2 - 250-260 cm Pleistocene - Reprocessed residue from "float technique" 2 - 258-259 cm Pleistocene 9.4 g 2 - 260-270 cm Pleistocene - Preprocessed 2 - 265-267 cm Pleistocene 27.8 g 3 2 155-157 cm Pleistocene 5.5 g 3 2 160-162 cm Pleistocene 5.2 g 3 2 165-167 cm Pleistocene 5.6 g 3 2 170-172 cm Pleistocene 5.2 g 3 2 175-177 cm Pleistocene 5.2 g 3 2 180-182 cm Pleistocene 5.6 g 3 2 185-187 cm Pleistocene 5.7 g 3 2 190-192 cm Pleistocene 5.0 g 3 2 195-197 cm Pleistocene 5.5 g 3 2 200-202 cm Pleistocene 5.2 g 3 2 205-207 cm Pleistocene 5.3 g 3 2 210-212 cm Pleistocene 5.4 g 3 2 215-217 cm Pleistocene 5.5 g 3 2 220-222 cm Pleistocene 5.5 g 3 2 225-227 cm Pleistocene 5.2 g 3 2 230-232 cm Pleistocene 5.2 g 3 2 235-237 cm Pleistocene 5.4 g 3 2 240-242 cm Pleistocene 5.5 g 3 2 245-247 cm Pleistocene 5.4 g 3 2 250-252 cm Pleistocene 5.2 g 4 2 255-257 cm Pleistocene 5.2 g 4 2 260-262 cm Pleistocene 5.4 g 4 2 265-267 cm Pleistocene 5.2 g

121

4 2 268-270 cm Pleistocene 5.2 g 4 - 240-242 cm Pleistocene 7.5 g Sep 03' Set 4 - 245-247 cm Pleistocene 15.9 g Sep 03' Set 4 - 250-252 cm Pleistocene 5.8 g Sep 03' Set 4 - 255-257 cm Pleistocene 11.0 g Sep 03' Set 4 - 260-262 cm Pleistocene 7.5 g Sep 03' Set 4 - 265-267 cm Pleistocene 8.3 g Sep 03' Set 4 - 268-270 cm Pleistocene 12.2 g Sep 03' Set Total Samples: 71