Climate and Vegetation Change in Late Pleistocene Central Appalachia: Evidence From

Home , Greenbrier River, Mylohyus, Older Dryas

Climate and Vegetation Change in Late Pleistocene Central Appalachia: Evidence from

Stalagmites and Lake Cores

A thesis presented to

the faculty of

the College of Arts and Sciences of Ohio University

In partial fulfillment

of the requirements for the degree

Master of Science

Kelli W. Baxstrom

May 2019

This thesis titled

Climate and Vegetation Change in Late Pleistocene Central Appalachia: Evidence from

Stalagmites and Lake Cores

KELLI W. BAXSTROM

has been approved for

the Department of Geological Sciences

and the College of Arts and Sciences by

Gregory S. Springer

Associate Professor of Geological Sciences

Joseph Shields

Interim Dean, College of Arts and Sciences 3

ABSTRACT

BAXSTROM, KELLI W., M.S., May 2019, Geological Sciences

Climate and Vegetation Change in Late Pleistocene Central Appalachia: Evidence from

Stalagmites and Lake Cores

Director of Thesis: Gregory S. Springer

This thesis uses a multi-proxy approach involving pollen and speleothem isotopes, to determine how climate events and vegetation changes influenced biomes in the Appalachian Mountains of East Central North America (ECNA) during the Last

Glacial Maximum and glacial retreat leading into the Holocene. To do this, a stalagmite from Culverson Creek Cave in West Virginia was collected and analyzed for carbon and oxygen isotopes, and two pollen and macrofossil records were collected and analyzed from Browns Pond and Pancake Field in Virginia. The Browns Pond pollen record was previously published, but the Pancake Field pollen record is novel in partnership with the

U. S. Geological Survey in Reston, VA. The records helped reconstruct the history of prairie development and transition into woodland from 27-10 thousand years before present. These two types of records were compared to construct a palaeoecological account of ECNA. Results show that ECNA vegetation closely tracked climate events, including precipitation and temperature changes, that affected North America and the

Northern Hemisphere in general, but the Appalachian Mountains provided refugia for some species. 4

DEDICATION

For Bryce, Emily, Leo, and Archie.

Success excerpt from “The Ladder of Saint Augustine”: The heights by great men reached and kept Were not attained by sudden flight, But they, while their companions slept, Were toiling upward in the night. – Henry Wadsworth Longfellow (1807-1882)

ACKNOWLEDGMENTS

Thank you to my advisor Gregory S. Springer for introducing me to the wonderful world of caving, and for patiently guiding me through endless drafts. Thank you to Drew

Hall for being a sounding board, caving partner, and sanity checker for two years. Thank you to the Cave Conservancy of the Virginias, Ohio University’s Geological Sciences

Alumni Grant, and Ohio University’s Student Enhancement Award for the funding of this project.

TABLE OF CONTENTS

Page

Abstract ...... 3 Dedication ...... 4 Acknowledgments...... 5 List of Tables ...... 8 List of Figures ...... 9 Chapter 1: Introduction ...... 10 Stalagmites ...... 11 Relating Modern Climate to the Past ...... 12 Plant Associations ...... 14 Implications...... 19 Research Objectives ...... 21 Chapter 2: Geologic Setting ...... 23 Greenbrier Geology ...... 23 Karst and Speleothem Stable Isotopes ...... 24 Chapter 3: Methods ...... 31 Stalagmite Collection and Processing ...... 31 230Th Age Dating...... 31 Stable Isotopic Analysis ...... 32 Chronology ...... 32 Pollen ...... 33 Browns Pond ...... 33 Pancake Field ...... 34 Statistical Analyses ...... 36 Chapter 4: Results ...... 38 Stalagmite ...... 38 230Th Age Dates ...... 39 Stable Isotope Analysis ...... 42 Browns Pond ...... 45 Pancake Field ...... 48 Statistics ...... 48 7

Chapter 5: Discussion ...... 55 Stalagmite Interpretations ...... 55 The Last Glacial Maximum ...... 55 Glacial Retreat ...... 59 Correlations Between CCC-003 and Pollen ...... 63 The Last Glacial Maximum ...... 63 Glacial Retreat ...... 66 Implications for Megafauna and Humans ...... 72 Conclusions ...... 75 References ...... 78 Appendix A: U/TH Data Table and 230Th Ages for CCC-003 ...... 102 Appendix B: Pancake Field Percent Abundance ...... 105 Appendix C: Neotoma Data ...... 108

LIST OF TABLES

Page

Table 1. Timeline of climate events and dominant vegetation ...... 71 9

LIST OF FIGURES

Page

Figure 1. Holocene mean seasonal summer and wintertime ensembles ...... 13 Figure 2. Map of sampling locations ...... 23 Figure 3. Subsurface karst system ...... 25 Figure 4. Stalagmite creation ...... 27 Figure 5. Climate controls that affect δ18O variations ...... 29 Figure 6. Pancake Field...... 35 Figure 7. Halved CCC-003 and 230Th sample locations ...... 38 Figure 8a. StalAge original age data ...... 40 Figure 8b. StalAge final age model with original errors ...... 41 Figure 8c. StalAge final age model with screened errors ...... 42 18 13 Figure 9. δ O and δ C with corresponding linear correlation coefficient values ...... 43 Figure 10. Time series of carbon and oxygen stable isotopes ...... 44 Figure 11. Pollen accumulation rate in core BR92 ...... 46 Figure 12. Browns Pond pollen zones ...... 47 Figure 13. Constrained Hierarchical Cluster Analysis ...... 49 Figure 14. Percent abundance of major taxa (>2%) in Pancake Field core 10-8-41-2 ..... 50 Figure 15. Pancake Field pollen zone ...... 52 Figure 16. Pancake Field vibracore ...... 53 Figure 17. Detrended Correspondance Analysis ...... 54 Figure 18. Climate events transpiring over the course of the stalagmite record ...... 56 Figure 19. 18O percent-temperature graph ...... 57 Figure 20. Composite figure of stable isotope data and pollen zones with depths and calendar age dates aligned to scale ...... 64 10

CHAPTER 1: INTRODUCTION

Global climate varies in periodic, quasi-periodic, and non-periodic ways, as a result of a number of factors ranging from changing insolation to volcanic eruptions

(Bradley, 1999). Ecosystems do not respond linearly to these climate variations and similar climates sometimes yield different ecologies (Burkett et al., 2005). In addition, sometimes species distribution is in disequilibrium with climate (Davis, 1981). The spatial and temporal movements of biota are affected by their individual tolerances and preferences, but records of these movements are sparse, making historic plant and animal migration difficult to map (Gajewski, 1988, Kneller and Peteet, 1999). Palaeoclimatology provides a framework for understanding, predicting, and/or back-estimating the spatial and temporal variations of flora and fauna and can give context to their movements

(Sahney and Benton, 2008). Evidence of past climates can be found in some geologic records and, with proper age controls, may provide high-quality archives of climate change through time (Sorooshian and Martinson, 1995). Ice cores and marine biogenic and inorganic sediments hold long and contiguous records, but lack information that may be gained by terrestrial or lower-latitude continental records (Rack et al., 2011).

Continental geological and biological archives include lacustrine sediments, charcoal, fossil pollen, speleothems, and tree cores (Bradley, 1999). Of these climate proxies, speleothems preserve site-specific information about hydrology and climatology in the form of carbon and oxygen stable isotopes (McDermott, 2004). These speleothem isotopes are an archive of local mean atmospheric temperature and precipitation and 11 epikarst processes (McDermott, 2004), and are used in palaeoclimatology for their exceptional detail and high dating precision (Springer et al., 2014).

Stalagmites

Speleothems are singular in their ability to provide climatic and environmental information, and the implications that may be garnered from the interpretation of such information are numerous (e.g., Cheng et al., 2016). Climatic and ecological information gained from speleothems can provide new insights on the Pleistocene-Holocene transition

(e.g., Springer et al., 2010). Stalagmites have been used for continental palaeoclimate reconstruction all over the world (ex. Austrian Alps, Lobatse II Cave in southeastern

Botswana, Grotte de Clamouse and Villars Cave in southern France, etc.) because they preserve comparatively untainted calcite precipitate from sequestered precipitation in a setting where it is shielded from erosion for millennia in relatively constant temperature and humidity conditions (McDermott, 2004). Speleothem stable isotopic composition outline conditions under which their mode of formation may be used to give palaeoclimatic data (Hendy, 1971).

The strengths of a speleothem archive can include continuous growth over thousands of years in duration over time scales from days to a million years; unparalleled chronologies that can be accurately dated by U-Th series dating; proxy parameters that can be used singly or together; and their presence over several continental areas, with records directly relevant to regional climates and environments (Fairchild and Baker,

2012). In fact, stalagmitic stable isotope records have become a common tool for evaluating local ecosystem responses to climate change and impactful climate events due 12 to their containing information on temperature, precipitation, biomass, and vegetation changes, which means that data gained from stalagmites can differ greatly from one location to another nearby (Bradley, 1999). Such records can be compared to other types of archives and previous studies have indicated that vegetation changes can closely track millennial-scale climate variability with only short time lags (Clark et al., 2012). A sufficiently detailed climatic record can be compared to pollen, much the same as was done by Harrison and Anderson (1993). Harrison and Anderson (1993) used sub-fossil pollen to reconstruct late Holocene climate changes in north-eastern and -central North

America, with results that gave general annual precipitation trends and summer temperature variation in broad, long-term scales.

Relating Modern Climate to the Past

East-central North America (ECNA) is subject to seasonal climate variations in regard to the position of the low-level jet stream which is affected by the Northern

Hemisphere westerlies (NHW) and humid air masses from the Gulf of Mexico (GOM)

(Figure 1) (Springer et al., 2008). The jet stream’s location is dependent on evaporation and moisture input from both these meteoric influences, which means they have a non- static junction (Springer et al., 2014). As a consequence, local climate can be greatly affected by contrasts in north-south pressure gradients (Springer et al., 2008), and seasonally varying circulation characteristics are closely linked to longitudinal temperature gradients. This is due to obliquity and how the tropics are heated more evenly throughout the year while mid- and high latitudes undergo considerable variation in heating from summer to winter (Marengo and Rogers, 2001). Weak N-S pressure 13

Figure 1. Holocene mean seasonal summer and wintertime ensembles for December- February (above), and June-August (below) depending on circulation pressures over the Americas. Likely Northern Hemisphere midlatitude jet stream location represented by red line (modified from Marengo and Rogers, 2001, and an original G. S. Springer figure).

gradients as well as the polar jet stream subdue northeastward moisture passage across

ECNA (Enfield et al., 2001), in addition to controlling the routes and northward dissemination of moist, subtropical air through the course of the year (Springer et al.,

2008). In the Western Hemisphere in general, zonal (east-west) asymmetries occur in atmospheric circulation due to differing thermal capacities between land and water, 14 sometimes resulting in blockages of the westerlies which create cold weather over North

America for weeks (Marengo and Rogers, 2001).

Though the Pleistocene glaciers would have altered air flow over North America

(Kirby et al., 2002), it is very likely that seasonal variations that affect ECNA today, such as those of the jet stream, NHW, and Gulf Stream did so during glacial intervals as well

(Russell et al., 2008). Therefore, a stalagmitic proxy record can be used for palaeoclimate reconstruction with an understanding of modern climate effects on ECNA as well as events in the glacial cycle in the Late Pleistocene and Holocene (c.f. Springer et al.,

2008).

Plant Associations

Climate change may encourage species to respond geographically depending on their adaptive capabilities (Jackson et al., 1997, Peteet et al., 2000, Joyce and Refeldt,

2013). Many ecological factors influence biotic response to environmental change, ranging from responses in thresholds to resilience (Birks et al., 2010). The rate at which flora migrate varies depending on seed dispersal methods, ability to colonize substrates, and time between growth initiation and sexual maturity rates (Webb et al., 2003; Jackson and Williams, 2004; Williams et al., 2004), but it has been proposed that trees moved at rates of 150-500 m per year post-Last Glacial Maximum (LGM) (Clark et al., 1998), and even 1-km per year for Fagus trees of ECNA (Pitelka and the Plant Migration Working

Group, 1997). Rates of biome changes have been determined to be greatest between 13-

11 ka (13,000-11,000 yr BP), which coincides with the Younger Dryas (YD) climate episode and rapid retreat of continental ice sheets (Williams et al., 2004). Though many 15 plants were forced to follow shifting climate zones, some persisted in refugia without movement.

Refugia are safe havens in which populations can survive and even thrive through a period of unfavorable conditions, and they are often discussed in studies focused on the

Late Pleistocene and Holocene (e.g. Provan and Bennett, 2008, Keppel et al., 2012)

(Gavin et al., 2014). These refugia are often associated with complex landscape topography within mountain ranges and deep valleys, which host microclimates distinct from those in the surrounding region (Keppel et al., 2011). After glaciation, the biota would subsequently expand into the surrounding landscape from refugia (Bennett and

Provan, 2008). Ecological responses of migration and retreat into refugia in reaction to climate change can be recorded in the geologic record as distinctive pollen accumulations. It is important to address refugia in this research because the foothills of

Appalachia are known to have provided refugia for Pinus strobus (eastern white pine) and Tsuga canadensis (eastern hemlock) in Virginia (Davis, 1981). The Appalachian

Mountains having provided refugia for these two species could also explain why other species’ pollen exists in the study area during a time when climate may not be expected to support their existence.

Pollen has been widely used as a source of palaeoecological and palaeoclimatic information in both continental- and local-scale reconstructions (Delcourt and Delcourt,

1984). Pollen-based climate reconstructions over the latest Pleistocene-early Holocene boundary indicate that pollen is broadly distributed, well-dispersed, and, when buried in annually laminated lakes, stratigraphically exhibit a no-time lag temporal correlation with 16 vegetation changes (Seppä, 2003), making correlation with speleothem isotope time series a promising source of synthesis. Additional supporting pollen studies include paleosols, such as the study completed by Driese et al. (2005) completed in Pocohontas

County, southeastern West Virginia, which documents analysis and radiocarbon dating of pollen grains contained within paleosols from a floodplain of Douthard Creek and the alluvial fans of the floodplain valley.

Early pollen-based studies of tree migration rates during the termination of the most recent glacial phase (i.e., the Wisconsin) determined that migration rates of many tree species were not in equilibrium with climate, meaning some moved east and west, not just north and south. This may reflect that the Appalachian Mountains were a significant geographic barrier to northward migration (Davis, 1981). Kneller and Peteet

(1993, 1999) obtained a late-glacial to early Holocene record of pollen, plant macrofossils, and charcoal in two cores from Browns Pond in Williamsville, Virginia

(38.15507, -79.61609, 525 m). Radiocarbon dates and pollen assemblages from these cores allowed for climate interpretations based on vegetation transitions over time.

Comparing independent stalagmitic climate records to nearby pollen and charcoal assemblages such as those at Browns Pond would produce detailed information about the relationship between climate and vegetation through time in the Appalachians of ECNA.

Communities in the pollen assemblages include those with no modern analog (no-analog or novel), which are a well-documented and recognized feature of late-glacial palaeoecological records for central Appalachia (Russell et al., 2009; Gill et al., 2012). 17

Palaeoclimatic and palaeoecological information garnered from these pollen assemblages can have great implications for interpreting faunal and even human activities in the area.

Among the major questions left unanswered by previous studies on biotic change during the Pleistocene-Holocene boundary in central Appalachia are (1) whether vegetation change was solely climate induced; (2) whether it was climate change, overhunting, or both that drove megafauna extinctions; and (3) the possible cause and effect relationships between climate, defaunation, fire, and vegetation change (Gill et al.,

2009). These questions are left unanswered due to a variety of reasons: eastern North

America experiences high weathering rates making fossil preservation rare, megafaunal decline closely preceded enhanced fire regimes and development of no-analog plant communities, and rapid climate fluctuations took place regularly alongside these events

(Gill et al., 2009, Faith et al., 2011, Gil and Keigwin, 2018). Interpreting the fossil record is limited by the Signor-Lipps Effect: although the last fossil occurrence is the observed extinction point, it is unlikely to be the true extinction point (Signor and Lipps, 1982).

Overall, the major unanswered questions are problematic because climate change, biotic migration, extinction, and human immigration occurred rapidly, intensely and concurrently over the course of only a few thousand years (Jackson et al., 2000, Faith et al., 2011, Blois et al., 2013). Due to this fact, proxy evidence from ice, deep ocean, lake, or tree cores, speleothems, fossil pollen and charcoal are the best remaining opportunity for recreating climate histories (McDermott, 2004, Birks et al., 2010, Griggs et al., 2017).

More and better proxies for climate and vegetation changes are needed to answer the questions above. Ideally, these proxies will be from independent source types so that 18 one may support or refute the other. Multiple proxies are not only valuable, but are best for climate reconstructions (Mann, 2002). However, each proxy has its own limitations.

For example, tree-rings are subpolar records, reflect warm-season conditions, and are temporally limited (Esper et al., 2006). Multi-proxy records harness each proxy’s strengths to multidimensionally reconstruct climate change and thereby lessen the chances of a biased reconstruction (Mann, 2002). Essentially, using multiple proxies entertains multiple viewpoints of the same geographic location over the same time period, and creates a system of checks and balances for data interpretation.

One proxy record, such as a tree core, and its interpretation may vary from another tree core proxy record at a nearby location due to ECNA’s variable meridional

(latitudinal) relationship with the glacial front during the Pleistocene, affecting air flow and precipitation patterns (Kirby et al., 2002), but also due to a host of other physical and environmental factors affecting the ability of each proxy to make a record, such as calcite deposition (stalagmite), pollen deposition (lake core), or drought (tree rings). Due to this discrepancy, it becomes important to use a broad suite of climate proxies for high resolution palaeoclimate reconstructions because, as a detailed record of past climatic fluctuations accumulates, the mechanisms and results of climatic variation become more understandable (Bradley, 1999).

The proxy data available for eastern North America range from fossils, to charcoal, lake core pollen counts, and stalagmites. Many of these records are from the

Late Pleistocene. The research described herein uses two lacustrine pollen records which are approximately 120 km away from a cave that contained the stalagmite used in this 19 study. These proxies have been individually used for palaeoclimate reconstructions, and synthesizing those works is an integral part of the research presented below. The stalagmite data used in this study is original and unpublished, but the primary pollen record was taken from lacustrine sediments and published by Kneller and Peteet (1999).

The second pollen record is the product of a U.S. Geological Survey collaborator,

Christopher Bernhardt, whose data is unpublished and being analyzed for the first time.

This investigation uses these existing records because the comprehensive studies of pollen overlap with the stalagmite data produced by Dr. Springer, my advisor, and his research collaborators. Put together, this project uses these proxies to tell a comprehensive story of the relationship between climate and vegetation change in central

Appalachia at the end of the Late Pleistocene.

Implications

Late Pleistocene-Holocene deglaciation of North America produced enormous biotic disruption, resulting in the extinction of at least 97 megafauna (animals weighing

>44kg) genera (Gill et al., 2009; Barnosky et al., 2016). Of the 97 extinct megafauna, 16 species went extinct between 12 and 10 ka (Grayson, 2007, Faith and Surrovell, 2009).

These extinctions coincided with no-analog vegetation and altered fire regimes throughout east-central North America (Gill et al., 2012). Fire and megaherbivore browsing usually promotes grasslands and suppresses forests (Whyte et al., 2003, Bond,

2005, Gill et al., 2012). Today, we can observe megaherbivores reduce fuel loads and suppress wildfires via grazing and browsing (Gill et al., 2009), which was also observed in pollen and Sporomiella spore studies at Appleman Lake in Ohio by Gill (2009). 20

Sporomiella is a fungus evolved to thrive in the dung of wild herbivores. The extinction of herbivores and elimination of their browsing effects throughout the Holocene has been understood as a contributor to floral changes (Webb et al., 2004; Webb and Simons,

2006). However, it is still debated whether bottom-up (plant and soil resources) or top- down (fauna and fire) forces control grassy biomes (Kujiper, 2015). Nonetheless, climate change is a known contributor to vegetation, fire, and fauna changes, though it is argued that vegetation and fire respond less drastically to climate change alone than to combined climate and faunal changes (Barnosky et al., 2016).

Human immigration into ECNA would have greatly affected vegetation as well.

Archaeological sites as far northeast as Meadowcroft Rockshelter in Pennsylvania contain ~14 ka projectile points and may be considered the marker for the first human immigrants to the area, although the dating is questionable (Goebel et al., 2008).

Pleistocene climate was dry and low in atmospheric CO2, making plant domestication difficult, and encouraged a continuance of the hunter-gatherer lifestyle (Snow, 2010).

However, once the Holocene began, the Clovis period is considered to have officially ended (Snow, 2010) and, soon afterwards, plant domestication became a part of

Paleoindian life (Smith, 2006). Preceding plant domestication and continuing throughout it, humans would have used fire to control their landscape and to promote vegetation that would have provided food, shelter, or medicine, and enhancing fire regimes remains a topic of active discussion (e.g., Gill et al., 2009; Springer et al., 2010). Homo sapiens began igniting their own fires to clear vegetation, facilitate transportation, promote edible plant growth, and attract animals to hunting grounds (Bond and Keane, 2017). 21

Archaeological deposits provide strong evidence for frequent controlled burns by humans beginning in the Late Pleistocene by increasing the number of ignitions and changing their timing, thereby altering fuel abundance and structure (Bowman et al., 2011). In

North America, significant charcoal deposition in Appleman Lake, Indiana begin as early as 10.5 ka, and continued at an uninterrupted and increasing level through the Holocene

(Gill et al., 2009), which is a strong and likely indication of Paleoindian burning in the area, increased fire regimes due megafauna loss and fuel increase, or a combination of these factors.

Research Objectives

This study analyzes climate trends and variability in the central Appalachian

Mountains along the border between West Virginia and Virginia in the Late Pleistocene and Holocene. The project will focus on comparisons of climate records from stalagmitic carbon and oxygen stable isotopes with two pollen assemblage studies completed ~120 and 80 kilometers away to determine if the stalagmite record and vegetation assemblages correlate well. Next, a detailed climate and ecosystem history will be constructed for the region.

Further research on Late Quaternary climate is necessary because only generalized ECNA climate trends have been reported, such as those by Webb III et al.

(1991), Harrison and Anderson (1993), and Clark et al. (2011). These studies are extensive in their coverage of climate trends covering large regions of ECNA, but none absolutely puts regional pollen studies into a proper perspective. Hypothetically, 22 understanding vegetation movement over the course of the same time period as the stalagmite record assists in understanding climate changes at the end of the LGM.

As noted earlier, ECNA precipitation patterns are sensitive to the transitory nature of the junction of the Gulf Stream and NHW (Springer et al., 2014). Understanding climate controls on the resulting isotopic ratios found in stalagmites allows insight from an alternative perspective on pollen assemblages from studies in nearby areas covering the same time period. This work can be further used to understand fire histories during this time of abrupt climate and ecosystem change.

The specific objectives of this research are to:

1) Interpret the relationship of regional or global climate events to local variations in

climate as recorded by stable carbon and oxygen isotope ratios in speleothems.

2) Create a composite record of stalagmitic stable carbon and oxygen isotope data

from Culverson Creek Cave, West Virginia and pollen abundance community

composition data from Browns Pond and Pancake Field, Virginia.

3) Give context to the amalgamated pollen data by adding climate constraints.

The impacts of this study include an understanding of precipitation levels and temperature variations in ECNA coming out of the LGM, the relationship between those variations and floral communities during deglaciation. 23

CHAPTER 2: GEOLOGIC SETTING

Greenbrier Geology

Greenbrier County straddles the border between the Valley and Ridge and

Appalachian Plateau Physiographic Provinces (Figure 2) (Gwinn, 1964). The region has over 1100 mm of annual rainfall that rapidly enters local karst systems (Hardt et al.,

2010). This area includes the Greenbrier River watershed, which drains over 4000 km2

(Hocutt et al., 1978) and contains 3000 caves within the 366-meter-thick, flat-lying middle Mississippian Greenbrier Group limestones (Dasher, 2012). This karst region is

Figure 2: Location of Greenbrier County (outlined in red) Culverson Creek Cave, WV, Pancake Field and Browns Pond, VA. From Google Earth. 24 an ideal location for a speleothem-based palaeoclimate study because of its position in the mid-latitudes. Here, at 37oN, there is seasonal precipitation likely to be sensitive to climate changes, which is in contrast to the region’s tropical counterparts which have less dramatic climate shifts (Hardt et al., 2010). The countryside is generally woodland with a humid, temperate climate, and midlatitude seasonality (Springer et al., 2014). Average annual temperature and precipitation are 10.2oC and 1130 mm, respectively (Hardt et al.,

2010). Additionally, the region is ideal because it is sensitive to climate changes due to its location near the jet stream, while remaining unexposed to the Laurentide Ice Sheet

(LIS) during the Last Glacial Maximum (LGM) (McDermott, 2004). The central and southern Appalachian Mountains are located roughly 300 km southeast of the LGM glacial front, the closest terminal moraine of which can be found to the northwest in Ohio

(Dyke et al., 2002).

Karst and Speleothem Stable Isotopes

Calcareous speleothems are common in karst and grow from dripwaters that degas excess CO2 (Fairchild and Treble, 2009). The progression of water from Earth’s surface to karst and speleothems comprises several chemical reactions that transpire over space and time (Figure 3). These reactions occur in a process in which soil, regolith, and epikarst zones facilitate dissolution reactions, followed by precipitation reactions in the lower epikarst zone and cave itself. As precipitation migrates through the soil, it is exposed to carbon dioxide derived from atmospheric, plant, and microbial respiration, and forms carbonic acid (Fairchild and Baker, 2012). Because of this, carbon isotopes, 25

Figure 3. Subsurface karst system illustrating chemical reactions from dissolution to precipitation. Modified from Tooth (2000).

δ13C specifically, can be a record of soil, plant type, and moisture above a cave. The ratio for δ13C is

13 C (12 )sample 13 C 훿 C (‰) = ( 13 − 1) 푥 1000 C (12 )standard C

(Fairchild and Baker, 2012). Subsequently, the sample value is divided by the reference standard which is determined from the isotopic composition of a Cretaceous Pee Dee

Belemnite (Brand et al., 2014), the result is subtracted by 1 and then multiplied by 1000 to get the parts per thousand or per mil (‰). δ13C is controlled in the long-term by 26 location and altitude, but on the millennial, decadal and annual scale by total biomass

(inverse relationship), δ13C composition of biomass, epikarst processes, atmospheric circulation, and precipitation (Fairchild and Baker, 2012).

Plant photosynthesis is characterized by preferred uptake of the 12C isotope relative to 13C, so times of high bioproductivity and biocarbon burial result in an enrichment of 12C and depletion of 13C in soils (more negative δ13C values) (Saltzman,

13 2002). Low (depleted) δ C values are considered a marker of C3 plants – plants that utilize a three-carbon compound photosynthetic process. Higher (less negative) δ13C values generally record comparatively more abundant C4 plants, which utilize a four- carbon process that is more efficient at lower CO2 values than the C3 process (Saltzman,

2002). These carbon values are considered markers for C3 and C4 plants because of their different tolerances. C3 plants are more responsive to elevated CO2 than C4 plants

(Bazzaz, 1990), and C3 plants are also more reactive to water deficiency than C4 plants

(Lisar et al., 2012). After the plants take up carbon, exhalation and infiltration move the carbon enriched water into the epikarst. The CO2 interacts with calcareous bedrock and groundwater, and subsequently can precipitate calcite (CaCO3) to form stalagmites

(Fairchild et al., 2006).

Stalagmite growth rates depend on temperature and calcium ion concentration of drip water, and vary over a range of 0.01-1.0 mm/year (McDermott, 2004). If drip is continuous, stalagmites can provide ideal climate records that can be used to describe the climate directly from the source water (Figure 4). It is important to note, however, that depending on precipitation and moisture availability, complete isotopic equilibration may 27

Figure 4. Stalagmite creation. From University of Waikato.

not occur between soil CO2 and the percolating H2O (McDermott, 2004). This can be due to short water residence times in the soil, which can result in the water retaining a component of isotopically heavier (less negative) atmospheric CO2 in solution

(McDermott, 2004). Therefore, this isotopically heavier atmospheric CO2 might not be incorporated into speleothem calcite during growth.

Although stable isotopes can be highly informative and detailed regarding the type of precipitation and carbon sequestration that was occurring from vegetation overlying a cave, in the case of precipitation there is source discrepancy. Because of the universality of oxygen in Earth’s cycles, the δ18O value of local systems is controlled by 28 a multitude of regional and global processes. Long-term controlling variables include location and altitude, while short-term include atmospheric moisture dynamics as well as seasonal weather system variation (Fairchild and Baker, 2012). The ratio δ18O is

18 O (16 )sample 18 O 훿 O (‰) = ( 18 − 1) 푥 1000 O (16 )standard O where the standard is a known isotopic composition, commonly the typical composition of seawater or the Vienna Standard Mean Ocean Water (VSMOW) (Fairchild and Baker,

2012). In short, water that evaporates to form water vapor tends to be richer in 16O than

18O relative to seawater, and additional fractionation occurs in the atmosphere (Saltzman,

2002) to make water vapor even isotopically lighter. The stable isotopic composition of seawater varied extensively during the Quaternary, due to it being intimately linked with fractionation processes within the hydrologic cycle, storage in aquifers and ice sheets, as well as advection and mixing of water masses from different source regions that have their own distinct isotopic signatures (Rohling, 2013).

Variations in seawater δ18O are mainly attributed to ice cap size (Saltzman, 2002), due to preferential accumulation of 16O in ice sheets. This process of fractionation and storage results in large amounts of 16O being sequestered in the ice sheets, and comparatively more 18O being available for continued oxygen cycling through precipitation. Rainwater, already lighter in 18O than the vapor from which it condenses, will preferentially lose 18O in proportion to many factors including the relative warmth of the atmosphere and acceleration of an already accelerated fractionation process during

Ice Ages (Saltzman, 2002). Altogether, this makes the controls of δ18O cave dripwater countless and obscure (Figure 5) (Lachniet, 2009). This obscurity is what makes source 29 discrepancy a problem when interpreting where the speleothem oxygen atoms originated.

Therefore, a control for ice volume is needed to get a clear signal using the Vienna

Standard Mean Ocean Water (VSMOW). Overall, 18O is a useful proxy for moisture seasonality, as δ18O would reach its minimum in the winter (most negative), and origin when interpreted carefully and conservatively (Hardt et al., 2010).

Figure 5. Climate controls that affect δ18O variations. Illustration of processes related to oxygen isotope ratio change based on variations in temperature and relative humidity as oxygen moves through oceanic, atmospheric, hydrospheric, soil, and epikarst zones, before finally being sequestered in a stalagmite. From Lachniet (2009).

Just like today, the Gulf Stream functioned as an oceanic heat conveyer during the late Pleistocene (Russell et al., 2009). There are a series of melting episodes known as meltwater pulses that could potentially be attributed to increased Gulf Stream activity during the Pleistocene-Holocene transition. The LGM ended with a melting epoch that 30 began with a meltwater pulse generated by the partial collapse of Northern Hemisphere ice sheets ~19 ka and 14 ka during which sea level rose rapidly for several centuries

(Russell et al., 2009). Melting was reduced for more than a millennium during the

Younger Dryas (12.9-11.7 ka) (Alley, 2000; Lohne et al., 2004), but continued after initiation of the Holocene Thermal Maximum (11 to 9 ka) (PARCS Group 2004) until eustatic sea level stabilized by 7 ka (Russell et al., 2009). These climatic events may be represented in North American speleothem and pollen records.

Oxygen isotope values in ECNA speleothems may record changes in precipitation sources associated with the above climate changes. If precipitation was transported from the GOM, then the isotope ratio from the stalagmite will be different than that of precipitation from the Pacific Ocean via NHW, because precipitation from the GOM has less distance to cover in traveling to the Appalachian Mountains than precipitation from the NHW. Therefore, there would be less fractionation and a higher 18O concentration in the stalagmite, which is why understanding climate events that would determine precipitation source is so important. Fortunately, due to the centrality of oxygen to every

Earth system, carbon and oxygen in stalagmites constitute components of a useful tool for reconstructing rainfall, temperature, and vegetation/soil conditions among other conditions (Fairchild and Treble, 2009), if the source can be determined. Therefore, an understanding of regional hydrology and climatology is required to interpret the palaeoclimatic signal (Lachniet, 2009).

CHAPTER 3: METHODS

Stalagmite Collection and Processing

A stalagmite measuring 425 mm was collected from Culverson Creek Cave

(CCC), Greenbrier County, West Virginia (Figure 2)., 37o50’N, 80o24’W at 600 m elevation and labeled CCC-003 by G.S. Springer. The sample was collected in-situ from a low passage 600 m from the entrance. The speleothem was inactive (not growing) at the time of collection. After collection, CCC-003 was cut in half perpendicular to its growth axis using a wet-saw with a continuous-rimmed diamond blade attachment and polished smooth with a hand-held water-spray polisher. The interior of CCC-003 is composed of dense columnar calcite with no readily visible evidence of hiatuses in laminae deposition.

230Th Age Dating

The most commonly used method for radiometric dating of speleothems is the uranium-thorium disequilibrium method, used because speleothems incorporate some uranium from aqueous solutions but no thorium as they grow. The method is used to date samples up to 500,000 years in age (Fairchild and Baker, 2012). 230Th age dating was completed by Dr. Y. Gao and assistants at the University of Minnesota Isotope

Laboratory using a Finnigan-MAT Neptune Multicollector Inductively Coupled Plasma

Mass Spectrometer (Springer et al., 2014) with a single MasCom multiplier using the decay constants reported by Cheng et al. (2000). Thirty-seven samples (8% of them being duplicates, locations for which were determined by Dr. Y. Gao) for 230Th Age dating were drilled using 0.9 mm diameter tungsten carbide dental burrs (Buckles, 2014).

Sample powders were dissolved in nitric acid, then mixed with a 229Th/233U/236U tracer 32 and set aside to dry. An iron chloride solution was added and followed incrementally by ammonium hydroxide until the iron precipitated completely. The supernatant was then decanted and columns of anion resin were used to separate the thorium and uranium.

Hydrochloric acid was added to elute the Th and water to elute the U. Each sample was then dried and dilute nitric acid was added (Buckles, 2014).

Stable Isotopic Analysis

Stable isotopic analyses were conducted at the University of Texas at Arlington by Jessica Buckles using a GasBench-II coupled to a ThermoFinnigan DeltaPlusXP

IRMS and standardized V-PDB through NBS-19. CCC-003 was sampled using a hand- held milling tool Foredom model SR-2272 furnished with a Bresseler USA #1/4 dental burr at 0.5 mm increments along the growth axis. Samples were taken contiguously in order to decrease any aliasing effects that may be produced from taking samples at distinct intervals. After collection, the sample powders were stored in micro-centrifuge tubes. Next, powders were weighed using a Sartorius CP microbalance and placed in individual vials (LabCo Exetainer 12 ml borosilicate vials). The sealed vials were cleansed with helium and acidified using pure orthophosphoric acid then equilibrated at

50oC for 12 hours (Buckles, 2014). Oxygen results were corrected for glacial ice using the VSMOW.

Chronology

Proxy age values were constructed using the StalAge algorithm which was designed specifically for speleothem age models with a 95% confidence interval (Scholz and Hoffmann, 2011). StalAge is written in R programming open-source statistical 33 software (Scholz and Hoffman, 2011). The most straightforward method for age model construction is via linear interpolation between data points. Though often used and easily constructed, this method has distinctive disadvantages: 1) each section between age dates is treated as its own age model, with all values between age dates given an inferred linear relationship, reducing the definition of each line to only two data points, 2) age inversion may occur via analytical error or overlapping error bars, producing negative slopes and results in discarded data, and 3) uncertainty in these models is often omitted (Mudelsee,

2013).

Pollen

Browns Pond

Browns Pond (Figure 2) is found at 38o09’17”N, 79o36’59”W in the central

Appalachians of Virginia, at an elevation of 620 m in an area with moderate to hilly relief. The pond basin is 60 by 20 m in diameter and water ranges from 17 to 21 cm in depth (Kneller and Peteet, 1993). Underlying bedrock is Upper Silurian and Lower

Devonian limestone, sandstone, and shale (Swezey, 2015). Sandstone colluvium and acidic soils locally overlay karst topography (Kneller and Peteet, 1993). The closest weather station (Lewisburg, WV, 37o85’66”N, -80o40’42”W at 500 m in elevation) has an annual average temperature of 10.8oC and 1213 mm of precipitation (NOAA, 2010).

The pond is in the Ridge and Valley section of the Oak-Chestnut Forest region described by Abrams (2003), and the predominate trees are Quercus alba and Q. rubra with Pinus strobus, Sassafras albidum, Acer rubrum, Nyssa sylvatica, Carya, Liriodendron tulipifera, Betula lenta, and Castanea dentata is also nearby (Kneller and Peteet, 1993). 34

Neighboring brushes includes Vaccinium corymbosum, V. angustifolium, Rhododendron,

Kalmia latifolia, Cornus, and Rosaceae (Kneller and Peteet, 1993). The pond itself is covered with Dulichium arandinaceum, and Cephalanthus occidentalis, Osmunda, Crex vesicaria, and Sphagnum surrounds the perimeter (Kneller and Peteet, 1999).

The data set from Kneller and Peteet (1999) is re-analyzed in this study. Kneller and Peteet (1999) used the pollen classification schemes of McAndrews et al. (1988) and

Faegri et al. (1989).The CONISS program for hierarchical cluster analysis (discussed in subsequent statistical analysis section) was applied to the upland pollen taxa to define assemblage zones, and the age model for Browns Pond is a straight-line interpolation between radiocarbon dates conducted by the Center for Accelerator Mass Spectrometry,

Lawrence Livermore National Laboratory, California, and the National Science

Foundation Arizona AMS Facility (Kneller and Peteet, 1999). Though calendar year conversions were calculated in the original publication by Kneller and Peteet, these ages were recalculated here due to changes in global radiocarbon models and their radiocarbon dates are reported as calendar years before present. The Northern hemisphere curve from

INTCAL13 was used in this study.

Pancake Field

Pancake Field (Figure 6) is part of the Water Sinks Depression at the northeastern end of Burnsville Cove, VA (Figure 2). Burnsville Cove is a synclinal valley underlain by

Silurian-Devonian limestones and is located in the Valley and Ridge Province of the

Appalachian Highlands (White, 2015). Pancake Field is a series of depressions in a mile- long valley on the southeast side of Route 609 bounded by Jack Mountain to the west and 35 divided by Chestnut Ridge. The field is thought to have once been a lake bed due to the

>35-foot-thick clay beds that make up the valley bottom. Sinking Creek enters Pancake

Field from the southwest and runs into a swallet at the foot of a sheer walled sink at the head of the valley. The levees of the swallet consist of a meandering channel of grass

(White, 2015).

Surrounding vegetation has not been described, though the area has a history of maple sugaring, and has place names such as Chestnut Ridge, indicating tree species of those types being common for the last few centuries at a minimum.

Figure 6. View to the northeast over Pancake Field. From White (2015, Fig 11.1). 36

Statistical Analyses

Statistical analyses were conducted using PAST version 3.21. PAST was designed as a follow-up to PALSTAT specifically for palaeontological statistics (Hammer et al.,

2001). A constrained hierarchical cluster analysis (CCA) was run in PAST to find hierarchical grouping in a multivariate data set and produce a dendrogram (Hammer et al., 2001). CCA is a multivariate method for quantitative definition of stratigraphic zones

(Grimm, 1987). The advantage to running a CCA as opposed to an unconstrained cluster analysis (UCA) in this research is to limit comparison between data sets to only stratigraphically adjacent clusters when PAST creates the dendrogram. This method has been widely used for pollen frequency data (Grimm, 1987).

Detrended correspondence analysis (DCA) is a multivariate reciprocal averaging technique widely used by ecologists to find major factors typical of ecological community data (Hill and Gauch, 1980). DCA was created to address two issues that were inherent in most other multivariate analyses when applied to gradient data: edge effect and arch effect (Hill and Gauch, 1980). ‘Edge effect’ is the term for how the variance of scores at the beginning and end of species succession would be sizably smaller than in the middle, and ‘arch effect’ is a term for the horseshoe shape curve that often appeared when the points were put into a graph (Hill and Gauch, 1980). DCA addresses these issues by running a standard ordination or reciprocal average to remove these effects by division of the first axis from correspondence analysis into segments and subtracting the within-segment mean of the site scores on the second axis. This is repeated until results are averaged to determine the axis score (Jackson and Somers, 37

1991). Some authors argue that DCA is worse than traditional methods at ordination when correcting the arch structure due to influence of data curvature and scaling, and detrending procedures are interpretably unstable (e.g. Kenkel and Orloci 1986;

Wartenberg et al., 1987; Peet et al., 1988). In contrast, others argue detrending is essential for interpreting dimensions beyond the first axis to remove extreme compression at the end of axes (Peet et al., 1988; Jackson and Somers, 1991).

DCA was run on Pancake Field data to determine if any climate gradients could be discerned. DCA produces an eigenvalue when performed. The eigenvalue results from the 3-dimensional space created by a DCA measures the strength of an axis and the amount of variation along the axis. Therefore, the eigenvalue numerically qualifies the fitness of that axis to illustrate attributes of an ecological gradient. The eigenvalue consequently determines the quality of ecological information that can be inferred from that axis, if any at all.

CHAPTER 4: RESULTS

Stalagmite

CCC-003 is an unpublished record collected by G. S. Springer in 2010. The positions inside the speleothem that were tested for 230Th age dating can be found in

Figure 7. Age dates are in chronological order, with youngest at the top of the speleothem

(left side of image). There are no age reversals present that fall beyond the margin of error in reported ages. Error ranges from 32 years to 225 years. Duplicate samples are

Figure 7. Halved CCC-003 with 230Th age date sample location marked in red and numbered.

39 designated by the occurrence of two sample indicators within a single lamina to check for dating quality.

230Th Age Dates

A total of 37 230Th age dates were obtained, and 8% of these were duplicate samples. Appendix A includes a table of all the data acquired from age dating, and the resulting graph in Figure 7 is a result of the sample location within the stalagmite being plotted against its calibrated age. The age models were plotted using the StalAge algorithm (Scholz and Hoffmann, 2011) as described in the Methods chapter, Chronology subsection. Figure 8 shows a) original age data, b) age data refined for outliers, and c) final age model with refined errors. These age date locations from the speleothem are used in constructing ages for stable isotope samples from within the stalagmite. 40

Figure 8a: Original age data as produced by the StalAge algorithm with distance from top on the x-axis and calculated calendrical age on the y-axis. 41

Figure 8b: Final age data including errors, with breadth of error measurements represented by two yellow lines, and linear interpolation of age dates represented by one green line, as produced by the StalAge algorithm with distance from top on the x-axis and calculated calendrical age on the y-axis.

Figure 8c: Final age data screened for errors with breadth of error measurements represented by two yellow lines, and linear interpolation of age dates represented by one green line, as produced by the StalAge algorithm with distance from top on the x-axis and calculated calendrical age on the y-axis.

Stable Isotope Analysis

In order to test for isotopic disequilibria, the stable isotopic fractionation values of

δ13C and δ18O from discrete samples of CCC-003 isotopic analysis are plotted in Figure 9

(Hendy, 1971). The low correlation coefficient (r2) demonstrates the low degree of 43 disequilibrium with respect to the isotopic values. The clustering of values is seemingly random, with no obvious grouping or segmentation, indicating continuous growth of the stalagmite or continuous equilibrium (Hendy, 1971).

R² = 0.0694 1

-1

-2 C permil 13 δ

-3

-4

-5

-6 -7 -6 -5 -4 δ18O per mil

18 13 Figure 9. δ O and δ C with corresponding linear correlation coefficient values.

Figure 10 illustrates the carbon and oxygen stable isotope values at assigned ages according to the sample’s location in the stalagmite (Figure 7). Oxygen has been 44 corrected for glacial ice by ice volume-free seawater (IVF). IVF correction is necessary because 16O is preferentially taken up by ice during glacial periods while the ocean becomes 18O enriched, thereby skewing the oxygen record by enriching precipitation in

18O relative to interglacial periods.

Figure 10. Time series of carbon (green) and oxygen (blue) stable isotopes from CCC- 003. Oxygen is corrected for glacial ice volumes (IVF).

Browns Pond

Kneller and Peteet (1999) created pollen abundance graphs from Browns Pond cores BR91 and BR92 (Figure 11) and published their results. Their results are re- examined here. All core depths are for both BR91 and BR92 unless otherwise stated.

From these two cores, they recognized eight discrete pollen zones: BR1, BR2, BR3a,

BR3b, BR3c, BR4, BR5, and BR6 (Figure 12). Zone BR1 ranges from >14,180 14C yr BP

(>16,616 cal yr BP) and is called the Picea-Abies zone due to Picea pollen making up 42-

46% and Pinus 29-38% of the core ranging from 445 to >485 cm in depth. Zone BR2 ranges from 14,180-12,730 14C yr BP (16,616-14,833 cal yr BP) and is named the Alnus-

Picea-Abies zone due to A. rugosa pollen consisting of 26%, Picea 32%, and Abies 5.6% of the core ranging from 445-346 cm in depth. Zone BR3a ranges from 12,730-12,260

14C yr BP (14,833-14,021 cal yr BP) and is termed the Picea-Abies-Ostrya/Carpinus-

Quercus zone due to Quercus comprising a maximum of 13.6% of the zone and

Ostrya/Carpinus 3.8%, while Picea and Abies remain strong components of the core from 346-266 cm. Zone BR3b covers 12,260-12,200 14C yr BP (14,021-13,988 cal yr BP) and is titled Abies-Picea-diploxylon-Pinus zone because of an influx of Abies, Picea and

Pinus-diploxylon pollen within 266-245 cm (Kneller and Peteet, 1999).

Zone BR3c ranges from 12,200-11,280 14C yr BP (13,988-13,115 cal yr BP) and is also called the Picea-Abies-Ostrya/Carpinus-Quercus zone, owing to its compositional similarity to zone BR3a at core depth 245-195 cm. Zone BR4 covers 11,280-10,050 14C yr BP (13,115-10,029 cal yr BP) and is named Tsuga-Betula-Pinus strobus zone as a result of a dominance of Tsuga pollen at 23-62%, an increase in Betula to a maximum of 46

9.5% and the second highest peak of Pinus at core depths 225-203 cm in BR91 and 194-

173 cm in BR92. Zone BR5 ranges from 10,050-8,410 14C yr BP (10,029-9,400 cal yr

Figure 11. Diagram from selected taxa in core BR92 of pollen accumulation rate (PAR or pollen influx). Age axis is founded on the notion of a continual accumulation rate between radiocarbon dates. Note that the horizontal axis changes scale for each pollen taxon. Units of PAR are in number of pollen grains per cm2 per year. Figure 5 from Kneller and Peteet (1999).

Figure 12. Browns Pond pollen zones, as designated by Kneller and Peteet (1999), according to their depth in the core and date retrieved from zone borders, and recalculated calendar ages. 48

BP) and is termed Nyssa-Tsuga-Quercus zone because of how Quercus replaces Tsuga as the dominant pollen taxa, and Nyssa abundance increases to 10.5% over the course of depths 203-<143 cm in BR91 and 173-134 cm in BR92. Zone BR6 covers 8,410 to

<4,870 14C yr BP (9,400 to <6,000 cal yr BP) and is titled Quercus-Carya zone owing to an increase in Carya pollen from 1% in previous zones to a maximum of 11%, and

Quercus ranges from 40-71% over the course of depths 134 to <65cm in BR92 (Kneller and Peteet, 1999).

Pancake Field

Pancake Field is a pollen study similar to that of Kneller and Peteet (1999) but unpublished. Pollen identification and dating was performed by Christopher Bernhardt and the USGS lab at Reston, VA. A table containing the abundance percentages of taxa from Pancake Field can be found in Appendix B and the results are discussed below.

Statistics

The data in Appendix B from Pancake Field was run as a CCA in PAST. The resulting dendrogram is constrained to show similarities controlled by stratigraphy and therefore time (Figure 13). This separates the pollen into many groupings, but makes five distinct zones, which were used to help create the pollen zones seen in Figure 14 and defined in Figure 15. The breaks in similarities between sampling depths (d) depicted by the CCA that are of note are between d1261 and d1289, d1371 and d1383, d1457 and d1481, and d1521 and d1601 cm. 49

Figure 15 depicts pollen abundance percentages found in Pancake Field from drill core 10-8-31-2. Only clay sections of the core included pollen, which is why pollen

Figure 13. Constrained Cluster Analysis of 18 non-normalized pollen abundances at 18 depths from Brown’s Pond core 10-8-31-2. Horizontal axis represents distance (similarity) between clusters. Dashed yellow lines indicate zone separation depths.

abundances are only available between the depths 1000 and 1800 cm (relative to top of core). Figure 15 separates the pollen abundances into zones by depth (also visible in

Figure 14) according to their distinct groupings defined by the CCA. The zone titles for the Pancake Field pollen core were determined by the prevalence of taxa in the discrete 50 groups defined by the CCA as compared to that taxon’s abundance throughout the rest of the core. Dating of the core was completed by the USGS radiocarbon lab in Reston, VA.

Dating quality for Pancake Field suffered from a lack of abundant organic material,

Figure 14. Pancake Field core 10-8-41-2. Illustrates percent abundance of major taxa (>2%). Horizontal lines indicate pollen zones. Zones do not cover entire portion of core where pollen exists due to uncertainty at the beginning and end of deposition. Yellow ovals on y-axis indicate locations of radiocarbon dating depths. 51 consequently, dates are tenuous but combining carbon dates and depth allows for reasonable time interpretation. Radiocarbon dates taken in bulk for 1608-1610 cm depth is 17,820 + 60 14C yr BP, and the date for depth 1322-1324 cm is 21,710 + 90 14C yr BP.

Zone PF1 ranges from 22,430-20,920 cal yr BP and is entitled Lycopodium-

Sphagnum-Polygonaceae-Ferns-Herbs zone owing to the drastic abundance of these mosses and flowering plants when compared to younger in the core, and the marked absence of tree taxa at the base of the core from 1700-1660 cm. Zone PF2 covers 20,920-

19,910 cal yr BP and is termed Picea-Jack Pine-Abies-Pinus zone due to a stark decline in mosses and herbs but a marked increase in soft woody taxa, and the highest amount of

Abies seen in the record, from a depth of 1660-1470 cm. Zone PF3 ranges from 19,910-

18,830 cal yr BP and is titled Abies-Poaceae-Woody taxa due to the low but constant presence of Abies and woody taxa, and the largest amount of Poaceae pollen present in the record is at the end of the zone, in the middle of the core (1470-1370 cm).

Zone PF4 covers 18,800-17,800 cal yr BP and is named Lycopodium-Pinus-

Asteraceae-Woody taxa because it is the last period in the record in which Lycopodium dominates and Pinus and woody taxa are present in such numbers, and which contains the largest amount of Asteraceae seen over the course of the record from a depth of 1370-

1270 cm. Zone PF5 ranges from 17,800-16,900 cal yr BP and is called Picea-Jack Pine-

Cyperaceae due to the second largest amount of Picea and Jack Pine pollen in the record, and the largest amount of Cyperaceae pollen found in the core, at a depth of 1270-1200 cm. 52

Figure 16 depicts a vibracore collected in the streambed of Pancake Field (see

Methods, page 35) which roughly correlates with the clay section in the drill core abundance, the total number of taxa found in each measured section, and a lithological description of the core.

Figure 15. Pancake Field pollen zones, as determined in this study, according to their depth in the core and dates estimated from two radiocarbon samples (Figure 13) taken for the core. (Christopher Bernhardt, USGS, personal correspondence).

Figure 16. Vibracore results from Pancake Field. Zones from the vibracore were created based on soil texture, not pollen abundance, and are therefore different from pollen zones in Figure 13 and 14. Figure provided by Christopher Bernhardt, USGS.

The DCA in Figure 17 was run in PAST and depicts groupings of taxon based on the main factors or gradients that influence their abundance. The eigenvalues for the axes are 0.2265, 0.04501, 0.01987, and 0.005422, and percent variance for the axes are 76%,

15%, 7%, and 2% for axes 1 through 4 respectively. Axis 1 represents the transition from

C3 to C4 plants (a gradual change from cold weather softwoods, to warm weather hardwoods, to sedges, herbs and mosses). Due to the quality of the eigenvalues and percent variance, only axis can be solidly determined to represent a variable of ecological variance.

Abies Asteraceae

Cyperaceae Polygonaceae Woody taxa

Pinus Poaceae Herbs Picea Sphagnum Ferns

Lycopodium Jack Pine Seligenalla

Figure 17. Detrended Correspondence Analysis of percent abundance pollen from Pancake Field. 55

CHAPTER 5: DISCUSSION

Stalagmite Interpretations

The Last Glacial Maximum

Late-glacial climate trends in ECNA were recorded in CCC-003 (Figure 18). The last glacial began ~115 ka due to declining summer insolation in the northern latitudes.

Insolation was 40 W m-2 less than present (Rahmstorf, 2002). The LGM is the coldest period within the last ice age and the time of greatest ice sheet extent. The LGM lasted from 26.5 to ~20 ka, which is evident in the CCC-003 record. LGM temperatures were significantly cooler than at present and averaged 5o + 1.5oC colder than today based on more negative δ18O ratios in planktonic foraminifera from the west North Atlantic Ocean, than during the post-glacial period (IPCC, 2007, Russell et al., 2009), also reflected in the oxygen ratios depicted from this study after IVF correction using VSMOW. The relationship between δ18O and temperature is depicted in Figure 19.

As the LGM came to a close, multiple repeating climate events made their mark on the progression of glacial retreat. At ~27 ka and ~23 ka, Dansgaard-Oeschger (D/O) events initiated drastic climate changes. Though some climate records place these two

D/O events at alternative dates (Jouzel et al., 2007, for example, puts the D/O events at

~24 and ~28 ka), CCC-003 displays them at the slightly younger times (~24 and ~27 ka).

Considered one of the most pronounced climate changes to occur in the last 120 ka, they are abrupt, decade-scale warming events that are large in amplitude followed by gradual, century-scale cooling, and show up in CCC-003 records as sharp spikes in both the carbon and oxygen record (Rahmstorf, 2002). The cause of these events is not concretely 56 known and often debated (Broecker et al., 1985, 1990, Bond et al., 1999, Rahmstorf,

1994, 1996, 2002), but such episodes show up well in the CCC-003 record as a brief but intense trend toward more negative values for δ18O and especially δ13C. Overall, high carbon values during the first half of the CCC-003 record indicate, with a few exceptions, relatively dry conditions, potentially brought on by the glacial front pushing the jet stream south, meaning precipitation would primarily be

Figure 18. Climate events transpiring over the course of the stalagmite record. Age axis is in calendar years BP. ACR = Antarctic Cold Reversal, A = AllerØd oscillation, AMOC (W) or (S) = Weak or Strong AMOC, B = BØlling oscillation, BE = Bond Event, D/O = Dansgaard-Oeschger event, H1/2 = Heinrich event, HGR = Holocene Glacial Retreat, LGM = Last Glacial Maximum, MP1A/B = Meltwater Pulse, YD = Younger Dryas.

Figure 19. 18O percent-temperature graph. The concentration of 18O in precipitation decreases with temperature. For example, colder locations have on average 5 percent less 18O than ocean water. Data adapted from Greenland (Jouzel et al., 1994, Figure 3).

brought in by the NHW. The exceptions where conditions are wetter in CCC-003 coincide well with D/O events. In fact, low δ13C values are known to correspond to warmer conditions and higher precipitation during D/O events (Genty et al., 2003).

The second Heinrich event, another major type of climate excursion during the

LGM, also shows up well in the record of CCC-003 at 24 ka (H2). Heinrich events are episodic calving events of the Laurentide Ice Sheet (LIS) that occur on massive scales. 58

They are recognized by distinctly coarse layers in North Atlantic sediments that could only have come from ice rafted debris (IRD) (Broecker et al., 1992, Rahmstorf, 2002).

Heinrich events appear globally in climate records as cold intervals with amplitudes as large as or larger than D/O warmings. They are believed to be driven by massive iceberg discharge from LIS through the Hudson Strait into the North Atlantic leading to a weakening of Atlantic Meridional Overturning Circulation (AMOC) (Greene et al.,

2008). Many studies (Hemming, 2004) have found that Heinrich-congruous events are caused by changing winds in the form of stronger tropical trade winds (Arz et al., 1998), stronger winter monsoon winds in China (Wang et al., 2001) and the Arabian Sea (Schulz et al., 1998), and stronger northerly winds in the western Mediterranean (Cacho Lascorz et al., 1999).

An important fact to be taken from these two intense climate episodes are that each Heinrich event is followed by an especially warm D/O event, and successive D/O events get progressively cooler until the next Heinrich event (Rahmstorf, 2002).

Additionally, Heinrich events always occur during cold stadials, never during warm D/O phases (Rahmstorf, 2002), which the stalagmite data shows well. Schulz (1998) also suggested that the mild D/O interstadials reflect global warm periods that resulted in high levels of tropospheric moisture, which is reflected by positive swings in the δ18O record, which could indicate a brief change in the origin of precipitation falling on ECNA from the NHW to the GOM.

The conclusion of the LGM in the CCC-003 record is punctuated by reversals in

AMOC strength, directly impacted by LIS activity. AMOC brings warm water from the 59 tropics north into the North Atlantic and Arctic, and periods of strong or weak AMOC activity greatly affect ocean temperatures and ocean surface activity. Reversals from a strong to weak, strong, and weak again occur at ~ 20.5, 19.75, 19, and 18.5 respectively

(Gil and Keigwin, 2018). Interestingly, these shifts to a weak AMOC occur concurrently with negative drops in carbon isotopes in the stalagmite record, indicating an abrupt and brief shift to moist conditions in ECNA every time AMOC slows down and is providing less warm water to the North Atlantic. This could indicate warm water, instead of being transported as far as the Arctic, was halting closer to the west central Atlantic, allowing a warm, moist climate to exist over ECNA, potentially coupled with moisture input from the GOM. Also, different during the glacial period was the jet stream, which was directed south of its present location over ECNA (Alder and Hostetler, 2015). During glacial retreat, the jet stream slowly tracked the glacial front north, bringing associated storm tracks and moisture from the GOM with it (Alder and Hostetler, 2015).

Glacial Retreat

As the LGM was coming to an end at ~20 ka, the oxygen record of CCC-003 records a positive trend in δ18O, indicating increased summer precipitation or decreased winter precipitation as the Holocene approaches. A series of climate events followed, including stadials, periods of colder climate, and interstadials, periods of warmer climate.

The first post-glacial climate event to have occurred is the Oldest Dryas, a stadial which is recorded primarily in European proxies and is not documented to have occurred in

North America. CCC-003 agrees with this, showing a general warming and moistening trend where the stadial should be. Instead, North America is known to have experienced 60 the Mystery Interval (MI), which lasted from 17.5 to 14.5 ka. This period was titled the

MI due to the observation that while the north Atlantic remained cold over this time period, the glaciers in East Greenland, the European Alps, and North America retreated substantially (Williams et al., 2012), and the Great Basin experienced severe drought followed by the wettest period of the last 25 ka (Broecker et al., 2009, Broecker and

Putnam, 2012). The Midwest is also reported to have experienced major arid conditions at the beginning of the MI from 17.6-16.5 ka (Wang et al., 2012), but the CCC-003 record clearly displays a continuous moistening over this 1,000-year period, which would indicate a distinctively different climate pattern over Appalachia than the Midwest, possibly brought on by GOM precipitation. The oxygen ratio varies throughout the MI, but moistening continues, interrupted only by another Heinrich event (H1) near 15.5 ka before returning to moist conditions followed by drying as the MI ends and the climate moved into the Bølling interstadial.

Bølling oscillation – often combined with the Allerød to be termed the Bølling-

Allerød period (B-A) – was a warm, temperate climatic interstadial arising at ~14.5 ka, with medial precipitation, though it was much dryer than the moistening that occurred during the MI. The period coincides with summer insolation levels of 4-8% higher than present day (Alt et al., 2018). The B-A is characterized by a warming of ~2oC, sudden glacial melt, and a sea level rise of 35 meters (Peteet, 2000). There is also a decrease in

AMOC strength over this period that was not associated with an increase in glacial discharge (Peteet, 2000, Obbink et al., 2010). Despite the disassociation, Bølling oscillation was followed immediately by Meltwater Pulse 1A (MP1A), an abrupt 20 m 61 increase in sea level that occurred between 14.3 and 14 ka (Weaver et al., 2003). In CCC-

003 this is recorded as a positive jump in δ18O and δ13C, indicating a brief dry, warm period for ECNA. The Allerød oscillation was another warm and moist global interstadial, known as the Two Creeks Interval in North America (Kaiser, 1994). From

13.9-12.9 ka, the Allerød raised temperatures in the north Atlantic to almost present-day levels, and would have enhanced freshwater discharge into the North Atlantic (Obbink et al., 2010). In CCC-003 the result of the warming appears as a positive trend in both oxygen and carbon, indicating a drying climate in ECNA over the thousand-year interstadial.

The Younger Dryas stadial immediately followed the Allerød warm period. The

YD (12.9-11.6 ka) is a widely studied return to glacial conditions that temporarily reversed the post-LGM warming trend. The change was relatively sudden and resulted in cooling, glacial advance, and drier conditions over much of the temperate northern hemisphere (Broecker, 2010). The cause is generally accepted to be a decline in the strength of AMOC which transports warm water north from the equator, which is thought to have been caused by an inflow of fresh cold water from the LIS to the Atlantic

(Carlson, 2010). But the cause of that influx is unclear and still a matter of debate

(Lowell, 2005, Broeker, 2010, Carlson, 2010). North Atlantic cooling weakened the

Northern Hemisphere monsoon (Carlson, 2010), and southeastern North America saw a slight warming (Carlson, 2013). CCC-003 displays an extremely variable proxy record over the YD. In the oxygen record, there is an abrupt negative trend in oxygen at the onset of the YD by 1‰ over the course of roughly 200 years, followed by 1,100 years of 62 a 2‰ increase, and a final 1‰ decrease before entering the Holocene. Carbon, however, is far more interesting. The ratio experiences rapid and consistent variation that starts with a 5‰ negative decline from -1‰ and varies between -1‰ and -5‰ until a rapid

2‰ increase into the Holocene. This implies that during the YD, ECNA experienced rapid cooling followed by an overall warming trend, then another rapid cooling event before the end of the YD, whereas precipitation was highly variable as the last of the LIS retreated. Though it was highly variable, there was an overall increase in moisture over

ECNA during the YD, most likely due to the decrease in AMOC strength and variations in the jet stream and therefore precipitation source changing from NHW to primarily

GOM.

There were also several other climatic factors affecting oxygen and carbon isotopes in ECNA during the YD. Another D/O event takes place that coincides well with one of the rapid carbon depletions at 12 ka. MWP1B affects the AMOC again at the conclusion of the YD (~11.6 ka) during which CCC-003 again shows drying followed by warming. Coinciding with the onset of MWP1B is a Bond event, which has been described as the Holocene version of a Heinrich event as it is also a period during which sediments show a large amount of IRD, however lake levels in the Mid-Atlantic region are known to have lowered during these events (Li, 2007), which reaffirms the drying shown in CCC-003.

The remainder of the record shows the beginning of Holocene warming, characterized by a gradually positive trend in the oxygen record. Another Bond event 63 occurs at the end of the stalagmite record circa 10.5 ka, during which carbon spikes heavily and rapidly toward dryer conditions.

Correlations Between CCC-003 and Pollen

A composite record of stalagmitic stable carbon and oxygen isotope data from

CCC-003 and pollen community composition data from the two sediment cores Virginia provide a comprehensive view of climate in ECNA from an isotopic and biome perspective. Figure 20 aligns these two proxies based on age dates taken from the cores.

The Last Glacial Maximum

The single disadvantage to the pollen record is that it does not record the period covered by the stalagmite data from 27 ka to 22 ka. Tundra is thought to have been common south of the glacial front during this period (Jackson et al., 2000), however, and any drastic changes in isotopes are explained by climate events, not vegetation changes.

Less negative carbon values, associated with the establishment of C4 plants, supports this assumption. However, just before 22 ka at a depth of 1760 cm in core 10-8-31-2 (Figure

14), zone P1 in the pollen record begins. From roughly 22,400 to 20,900 cal yr BP,

Lycopodium (clubmoss), Sphagnum (peat moss), Polygonaceae (buckwheat), ferns and herbs are the most prevalent pollen sources in the core. Again, the C4 plants would sequester more C13 than a C3 plant, aligning well with a less negative δC13 ratio during this period. Lycopodium prefers a moist climate, low sunlight, and little competing vegetation (Seward, 1963). Sphagnum prefers a boggy habitat in conifer forests or tundra areas, and are now commonly found farther north in Canada and other Arctic locations.

Polygonaceae mostly grows in moist, temperate regions of the northern hemisphere

Figure 20. Composite figure of stable isotope data and pollen zones with depths and calendar age dates aligned to scale. (USDA). Paired with the isotope data this indicates that prior to 20.9 ka there was a cool forest tundra biome due to the low levels of trees including Picea (spruce) and jack pine moving in during this period in ECNA as the LIS began to retreat, and Pancake Field, along with many other lowlands, was most likely a wetland environment inundated with sedges and herbs. This conclusion is supported by the paleosol study completed by Driese et al. (2005) which determined a dominant presence of conifer and sedge pollen circa

27,540 + 434 cal yr BP in Pocohontas County, WV. In the vibracore, charcoal abundances and the total number of taxa are counted, and it is easy to see that charcoal abundance closely parallels the total number of pollen taxa in the core at each depth.

However, during this early pollen record, charcoal does not match the total number of taxa, dropping from a large abundance to low abundance and back again in comparison to the total number of taxa seen in the core, indicating low fire frequency. However, in the following zones, the vibracore depicts charcoal abundance closely tracking total proxy biomass availability.

Tree pollen became much more common from 20,900-19,900 cal yr bp. Zone P2 is dominated by an influx of Picea, Jack pine, Abies (fir), and Pinus (pine). This drastic change in dominant species from wet prairie species to forest species required a change to warmer temperature and increased moisture availability in the climate. Picea are coniferous evergreens that are found in the northern temperate regions (USDA). These regions experience wide temperature and seasonal changes. Jack pine is found today east of the Rocky Mountains from Canada to northwest Pennsylvania and Indiana, again preferring the cooler temperate zones (USDA). Abies and Pinus, however, are generalists and have a wider range throughout North America. The dominance of these species 66 suggests a warming but still relatively cool climate as the glaciers began to permanently recede, which led to an influx of species that are tolerant of a wide range of climate conditions. This is reflected in the stalagmite record as carbon levels drop toward -3‰ and oxygen moves down toward -6‰. Here we see the environment beginning to change from forested tundra to spruce pine forest and parkland, as the less cold-tolerant Pinus moves in.

Glacial Retreat

Once the glacial retreat began fully, the various climate events that are discussed in the stalagmite interpretations section would have had some effect on vegetation, depending on the length and severity of each climatic episode. Zone P3 lasts from 19,900 to 18,800 cal yr bp and covers the true end of maximum glacial extent in North America.

While oxygen remains reasonably steady at -6‰, carbon experiences a severe positive spike followed by an even more severe negative one during this period of greater Abies,

Poaceae (grasses), and woody taxa. The woody taxa include Quercus (oak), Fraxinus

(ash), Alnus (alder), etc. Given the warming climate and wide range of carbon (from -1‰ to -4‰) over a 1,100-year time period, a mix of both prairie grasses and temperate trees would have cohabited the landscape. This would have been a parkland environment where there was a balance between grassland and trees the likes of which there is no analog today, and deciduous (woody) taxa such as Quercus would have been moving into the area for the first time since glacial advance (Grimm et al., 2001).

At 18,800 cal yr bp the Pancake Field record overlaps with the Browns Pond record for the first and only time. The overlap is minimal but the two records are 67 consistent with one another. Zones P4 and P5 both overlap with Kneller and Peteet’s zone BR1. P4 includes a dominance of Lycopodium, Pinus, Asteraceae (aster, daisy, or sunflower family), and the largest number of woody taxa yet. Zone P5 is dominated by

Picea, jack pine, and Cyperaceae (sedges). Overlapping with these two zones from

Pancake Field, zone BR1 is described as Picea and Abies dominant. Together, these three zones last ~2,200 years from 18,800 to 16,600 cal yr bp and include another instance of organic remobilization and the beginning of the Mystery Interval. While the American

West was starting a drought phase, according the CCC-003 and pollen records, ECNA was experiencing gradual warming and moistening during the 2,200-year period. Both pollen records agree that Picea is at its height, but the rest of the records indicate an invasion of more woody taxa, as well as Asteraceae, and Cyperaceae into the wet, mossy, conifer parkland.

After 16,600 cal yr bp trees are the dominant vegetation taxa in ECNA. The carbon record reflects this in a nearly constant δ13C ratio of -2 to -4‰, indicating a higher number of C3 plants. Although the Browns Pond record does not include the breadth of prairie taxa in its reports that Pancake Field does, Diospyros (persimmons), Cyperaceae, and Tubuliflorae (a subfamily of Asteroideae) are reported and not considered dominant.

From 16,616 to 14,833 cal yr bp, Alnus, Picea, and Abies are predominant on the landscape in zone BR2. This time period includes the majority of the Mystery Interval.

Heinrich Event 1 and another D/O event line up reasonably well with relatively quick carbon and oxygen reversals in a landscape with relatively uniform vegetation composition according to the pollen data. No drastic change in vegetation is inferred for 68 this time interval despite the presence of the Mystery Interval and varying isotopic ratios, due to the continued presence of species such as Abies, Asteraceae, Cyperaceae, and

Picea from the last zone.

Zone BR3 was split into subsections a, b, and c by Kneller and Peteet (1999), and were deposited during the Bølling-Allerød interstadials as well as MP1A. There is a boom in woody taxa deposition in Browns Pond during this time, which aligns well with the presence of the warm interstadial in the Northern Hemisphere. Zone BR3a, the Picea,

Abies, Ostrya (hop-hornbeam) zone, begins at 14,833 ka and ends at 14,021 ka. The appearance of Ostrya is consistent with the Bølling oscillation occurring at ~14.5 ka.

Also rising in abundance at this time is Fagus grandifolia (American beech) and

Cyperaceae. The presence of both Ostrya and Fagus grandifolia suggest a medial precipitation range that is not as dry as dry prairie nor as moist as a more tree-dominant landscape, and promoted the reappearance of Cyperaceae. MP1A would have also occurred in this time frame, slowing AMOC and potentially prolonging the abundance of spruce and fir in ECNA for a few hundred more years. Zone BR3b, the Abies, Picea, and

Pinus zone, lasted only 30 years (Kneller and Peteet, 1999), but is important due to the perfect alignment of this zone with a brief but sharp negative trend in carbon but no drastic change in oxygen. Despite this, the species would indicate a brief period of cooler temperatures and more of a closed forest setting, as Kneller and Peteet (1999) suggested, though there is no apparent climatic reason unless it is a delayed result of MP1A and cooling in the north due to the slowing of AMOC. Zone BR3c is a return to warm conditions like those of BR3a, and the pollen is again dominated by Picea, Abies, and 69

Ostrya. This time, however, there is not quite the same presence of Fagus grandifolia or

Cyperaceae, but Tsuga begins to appear instead, foreshadowing the next zone.

Zone BR4 is the last zone that falls within the same timeframe as the CCC-003 data. This zone is dominated by an influx of Tsuga (hemlock), Betula (birch) and pine

(Kneller and Peteet, 1999). Birch is a thin-leaved deciduous hardwood tree in the same family as hornbeams, and is considered a pioneer species in the northern areas of temperate and boreal climates that form even-aged stands on well-drained acidic soils

(Ashburner and McAllister, 2013). The existence of birch aligns well with the presence of hemlock and pine, whose needles would make the soil acidic, and hemlocks prefer cool temperate areas with high rainfall and cool summers and would be susceptible to drought, which is logical considering that the first half of this zone occurs during the

Younger Dryas stadial. The climate record of CCC-003 concurs with Kneller and Peteet

(1999) that there would be a temperature increase in a humid environment, notable due to the increase of birch, hemlock, and pine and decrease of fir. This is supported by the paleosol study of Driese et al. (2005) which recorded cooler than present-day climate conditions dominated by spruce, fir, and pine circa 10,859 + 1,143 cal yr BP. What the pollen record does not explain is the high amplitude, low frequency shifts in carbon isotopic ratios, nor the increase in oxygen from -7‰ to -5‰ during this period. The closed forest nature of this species combination could be indicative of higher frequency, low intensity fires at this time (firescience.gov). The Younger Dryas was a globally cool stadial in an overall warming environment, and both the oxygen record and the vegetation indicate that ECNA was actually an overall warming environment during the Younger 70

Dryas, and was therefore potentially a refugia for warm-weather vegetation during this cool period.

At the end of the YD a more broad-leaf temperate forest becomes dominant in the form of Nyssa (tupelo/dogwood), Tsuga, and Quercus in Zone BR5 and adds Carya

(hickory) and Diospyros (ebony) in Zone BR6, once the record is firmly in the warm

Holocene. Beginning with the YD, ECNA became a warmer region. Though the area moved steadily toward more tree dominant over the course of CCC-003’s record, there is a return to drier conditions at the very end of zone BR4 which coincide with MP1B and two Bond Events, both of which would have resulted in a drying of the area, like the last

Meltwater Pulse and Heinrich Events did in the Pleistocene. Table 2 displays a generalized timeline of both stalagmite and pollen interpretations.

Table 1

Timeline of climate events and dominant vegetation Calendar yr BP Climate events Dominant Vegetation 10,000 Bond Event

11,000 Younger Meltwater Pulse 1B Tsuga-Betula Pinus str. Dryas 12,000 Dansgaard-Oeschger event 13,000 Allerød interstadial Picea-Abies-Ostrya 14,000 Bølling oscillation Abies-Picea-Pinus Meltwater Pulse 1A Picea-Abies-Ostrya Mystery 15,000 Dansgaard-Oeschger event Heinrich event Alnus-Picea-Abies 16,000 Interval 17,000 Picea-Jack pine- Picea- Cyperaceae Abies 18,000 Lycopodium- Strong AMOC Pinus- Asteraceae- Woody taxa 19,000 Strong AMOC Abies-Poaceae-Woody Weak AMOC taxa 20,000 Strong AMOC Picea-Jack pine-Abies- Last Pinus 21,000 Lycopodium-Sphagnum- Polygonaceae-Ferns- 22,000 Herbs 23,000 Glacial Dansgaard-Oeschger event

24,000 Heinrich event

25,000 Maximum Tundra

26,000

27,000 Dansgaard-Oeschger event 72

Implications for Megafauna and Humans

It is important to note that not all Late Pleistocene mammals of North America belonged to a single biotic community, but included many discrete paleocommunities, and extinctions did not all occur at the same time before getting too deep into a discussion of the impacts of climate and vegetation change on megafauna and humans in the Late Pleistocene (noted in Table 1). The extinction of one large mammal would not necessarily have had a cascading effect to cause the extinction of all the others (Grayson,

2007). However, the biome network in ECNA was interrelated in many ways, and ripple effects would be possible depending on the dependency one species or family – plant or animal – had on another.

Studies in Africa show that the loss of megafauna immediately affects the physical structure of ecosystems, due to the fact that megafaunal browsers (e.g., proboscideans) destroy vegetation via consumption and trampling, altering the competitive balance between woody and prairie vegetation (Malhi et al., 2015). Loss of keystone species prompts a trophic domino effect that is followed by habitat alteration, changing the richness of other species, and can generate more extinctions (Malhi et al.,

2015).

Loss of megafauna would cause an abundance of fuel loads on the landscape, and the direct effects of megafauna loss appear in fire regimes, nutrient cycling, and soil properties (Ripple et al., 2015). Fire is an influential disturbance regime that would have effects on vegetation and fauna, and is integral in many biomes (Bowman et al., 2011).

Since the appearance of fuel provided by plants in the Silurian and Devonian 400 million 73 years ago, there has been a fossil charcoal record spanning at least the last 350 million years (Bowman et al., 2011, Bond and Keane, 2017). The fire regime is also observed to change in the fossil record during periods of climate change, increasing during maximum oxygen levels of the Upper Carboniferous, the spread of angiosperms in the Cretaceous and savanna in the Miocene, while decreasing during the wet Eocene (Bond and Keane,

2017). Mortality of large vertebrates would not be an effect of most fires; only severe and rare ones would cause drastic structural change and local extirpation of fauna (Bond and

Keane, 2017). Megafauna loss preceding enhanced fire regimes would be the only reason for fires to have an effect on the remaining megafauna in the area. Megafauna alter the quantity and distribution of fuel supplies by consuming biomass and reducing fuel loads, thereby controlling the frequency, intensity, and spatial distribution of fires across a landscape (Ripple et al., 2015, Bond and Keane, 2017). At ~12 ka the megafauna controlled ecosystem of eastern North America directly transitioned to an enhanced fire regime ecosystem, and replacement of parkland by woodland was observed (Malhi et al.,

2015). The loss of megafauna and enhanced spatial pattern of the fire regime would have changed extinction risks for different faunal elements, affecting vegetational and faunal ability to recolonize post-burn (Bond and Keane, 2017).

Human use of fire could have also been a contributing factor to vegetation controls. The vibracore from Pancake Field in Figure 15 indicates a charcoal record that depicts fire frequency and intensity roughly correlating with the number of taxa found in the core, indicating that mixed prairie-conifer forests burned consistently. That data is consistent through the record, but the Brown’s Pond record differs in that respect. 74

Though not presented in Figure 10, Kneller and Peteet (1999) report an increase of charcoal abundance above normal background levels in Brown’s Pond core BR91 beginning in zone BR2 at roughly over 13 ka, and jumping to an even higher level over the transition from zone BR4 to BR5, roughly an age of 10.1 ka in both core BR91 and

BR92. Both of these increases in charcoal abundance correlate reasonably well first with known human inhabitance of ECNA by 13ka. Zone BR4’s increase in fire frequency and

Tsuga and Betula dominance match well with a closed canopy forest experiencing frequent burning.

Humans’ use of fire has been documented well in nearby caves at later dates

(Springer at al., 2010). Novel anthropogenic ignition sources from even small populations would have resulted in a burn-susceptible but ignition-limited closed canopy landscape building up to have high frequency, low intensity burns after losing megaherbivory biomass control (Pinter et al., 2011).

CONCLUSIONS

Data from speleothem isotopes provides a high-resolution palaeoclimatic and palaeoecological record that supports local variations in climate tracking global and northern hemisphere climate events in some cases, such as Heinrich and Dansgaard-

Oeschger events, but also differing regionally in others including local response to changes in AMOC and an individualistic response to the Mystery Interval, and no evidence of the Oldest or Older Dryas. This data is complimented by the pollen and macrofossil studies of Browns Pond and Pancake Field, which show vegetation closely tracking glacial advance and retreat as well as stadial-interstadial conditions. Specifically, there are several cases where the stalagmite data and pollen record match well and few where they do not.

From 27,000-22,400, the stalagmite record stands alone without support from the pollen record. However, when oxygen is Ice Volume Corrected to take glacial ice into account, the oxygen record indicates cool and dry glacial conditions, with Heinrich and

Dansgaard-Oeschger events causing short but high amplitude changes in carbon sequestration. From here, CCC-003 and the pollen records have complementary data in zones P2, P3, P4, P5, BR1, BR3a, and BR3c which all depict carbon and oxygen isotopes that would reflect the suitable climate conditions for the overlying vegetation. The differences in zones P1, BR2, BR3b, and BR4 vary in different ways from CCC-003.

Zone P1 aligns well with the stalagmite data in all except the vibracore charcoal abundance data, indicating a period of an abnormal and potentially low fire regime. 76

Zone BR2 is different due to there being no change in vegetation despite variable isotopic ratios, which warrants further investigation into the climate that was brought about by the Mystery Interval in eastern North America, as it seems to have been different from the west. Carbon values in CCC-003 correlate well with zone BR3b, however the notable difference here is in the absence of change in oxygen, despite the influx of cool weather species. Due to the fact that this pollen zone covers a 30-year period, it is likely that such a period was too brief to record a high level of oxygen isotope change in the hydrologic process between epikarst and stalagmite. Zone BR4 also is only slightly off from CCC-003 due to the fact that the large amplitude shifts in 13C is not explained by large amplitude shifts in pollen during the Younger Dryas. It is possible that these large shifts are evidence of refugia which would be indicative of a no-analog ecosystem, or a change in the fire regime as fires reached their highest point in the

Browns Pond record.

This study assists in filling the gap of our understanding of the relationship between global and regional climate, and local vegetation change in ECNA during the

Late Pleistocene. The limitations of this project included the time available to conduct local charcoal studies, which is where future work must come into play. More charcoal studies need to be completed in the surrounding area to understand wildfire history in

ECNA, and when Paleoindians began influencing the fire regime in central Appalachia.

Though the Mystery Interval is well studies in the Great Basin, there is a large gap in research on its effects in southeastern North America (Broecker et al., 2009, Williams et al., 2012). A study by Springer (2010) covers fire history in the CCC area up to 8 ka, but 77 research needs to continue covering older periods, at least through 15 ka so that the total time frame of Paleoindian immigration may be covered. 78

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APPENDIX A: U/TH DATA TABLE AND 230TH AGES FOR CCC-003

Table A

Title 238 232 234 230 238 230 232 230 230 234 Sample U (ppb) Th (ppt) δ U [ Th/ U] [ Th/ Th] Th Age Th Age Δ Uinitial measured activityc ppma (yr BP) (yr BP) corrected a uncorrected corrected c,e CCC3-29 737.7 +1.1 13435 668.3 +1.8 0.1023 +0.0004 93 +2 6873 +28 6497 +225 681 + 2 +269 CCC3-30 1091.1 +1.8 709 +15 704.8 +1.9 0.1312 +0.0004 3328 +69 8686 +31 8614 +232 722 + 2

CCC3-1 1143.8 +2.2 639 +13 694.8 +2.2 0.1647 +0.0005 4861 +99 11072 +35 11003 +36 717 + 2

CCC3-31 770.3 +1.7 357 +8 718.9 +1.8 0.1695 +0.0005 6032 +130 11240 +39 11171 +40 742 + 2

CCC3-32 783.6 +1.2 684 +14 725.2 +1.9 0.1733 +0.0005 3272 +68 11461 +40 11385 +42 749 + 2

CCC3-33 512.3 +0.7 103 +3 807.1 +1.8 0.1908 +0.0006 15672 +474 12071 +41 12007 +41 835+ 2

CCC3-34 1175.1 +2.1 111 +4 721.3 +2.0 0.1894 +0.0006 33017 +1107 12615 +42 12552 +42 747 + 2

CCC3-3 970.1 +1.5 237 +5 720.3 +1.8 0.1969 +0.0006 13278 +309 13145 +43 13080 +43 748 + 2

CCC3-4A 1356.1 +2.2 34 +2 766.7 +2.1 0.2113 +0.0005 140717 13766 +39 13705 +39 797 + 2 +9030 CCC3-5 1211.3 +1.8 42 +2 837.1 +1.9 0.2256 +0.0005 1075104 14153 +38 14092 +38 871 + 2 +6232 CCC3-6 942.8 +1.5 46 +3 903.5 +2.2 0.2402 +0.0007 81158 +4745 14561 +47 14499 +47 941 + 2 103

CCC3-7 894.9 +1.4 25 +3 944.2 +2.2 0.2521 +0.0007 149987 14983 +45 14921 +45 985 + 2 +15354 CCC3-8 702.3 +1.1 118 +4 973.0 +2.1 0.2627 +0.0007 25798 +805 15403 +48 15340 +48 1016 + 2

CCC3-9 1057.9 +1.8 121 +4 966.4 +2.3 0.2667 +0.0007 38553 +1190 15712 +49 15649 +49 1010 + 2

CCC3-10 857.6 +1.3 78 +3 954.7 +2.2 0.2699 +0.0007 49226 +1821 16013 +49 15951 +49 999 + 2

CCC3-11 1161.1 +2.0 19 +3 902.5 +2.3 0.2657 +0.0007 267668 16216 +51 16155 +51 945 + 2 +37148 CCC3-12 1252.8 +2.2 35 +3 893.1 +2.3 0.2663 +0.0007 155460 16342 +50 16281 +50 935 + 2 +11008 CCC3-13 797.8 +1.2 19 +3 960.4 +1.9 0.2782 +0.0008 197696 16487 +51 16426 +51 1006 + 2 +29582 CCC3-14 1031.6 +1.6 40 +3 898.6 +1.8 0.2784 +0.0007 119590 17082 +52 17020 +52 943 + 2 +8265 CCC3-15 830.9 +1.3 81 +3 914.9 +2.3 0.2927 +0.0007 49304 +1752 17860 +52 17798 +52 962 + 2

CCC3-16 707.3 +1.1 170 +4 881.5 +2.2 0.2944 +0.0007 20224 +509 18318 +55 18253 +55 928 + 2

CCC3-17 570.8 +0.9 136 +4 896.5 +2.1 0.3037 +0.0008 21032 +608 18779 +61 18714 +61 945 + 2

CCC3-18 641.5 +1.0 46 +3 737.8 +1.9 0.2857 +0.0009 66367 +4402 19342 +67 19280 +67 779 + 2

CCC3-19 468.0 +0.7 51 +3 738.3 +2.2 0.2910 +0.0009 44387 +2586 19727 +74 19664 +74 781 + 2

CCC3-20 891.2 +1.3 199 +5 685.5 +1.8 0.2876 +0.0007 21190 +511 20151 +59 20086 +59 726 + 2

CCC3-21 798.5 +1.3 134 +4 668.7 +2.3 0.2992 +0.0008 29441 +809 21268 +72 21204 +72 710 + 2 104

CCC3- 771.9 +1.1 261 +6 635.5 +1.7 0.3106 +0.0008 15144 +344 22660 +70 22593 +70 677 + 2 22A CCC3- 595.6 +0.9 145 +4 641.7 +1.9 0.3119 +0.0009 21195 +600 22667 +75 22602 +75 684 + 2 22B CCC3-23 799.7 +0.7 581 +12 618.6 +1.9 0.3169 +0.0009 7193 +150 23432 +77 23358 +77 661 + 2

CCC3-24 785.9 +1.2 327 +7 669.6 +1.9 0.3418 +0.0010 13561 +296 24603 +84 24535 +84 718 + 2

CCC3- 876.6 +1.4 385 +8 653.6 +2.0 0.3470 +0.0009 13040 +277 25287 +80 25219 +80 702 + 2 25A CCC3- 925.7 +1.6 382 +8 653.3 +2.2 0.3461 +0.0010 13822 +300 25220 +87 25152 +87 701 + 2 25B CCC3-26 745.5 +1.0 1693 +34 733.6 +1.8 0.3687 +0.0009 2677 +54 25641 +74 25543 +74 789 + 2

CCC3-2 765.0 +1.3 1376 +28 679.6 +2.1 0.3637 +0.0009 3333 +67 26175 +81 26085 +81 732 + 2

CCC3-27 901.6 +1.6 129 +4 776.8 +2.3 0.3890 +0.0010 44762 +1344 26460 +86 26397 +86 837 + 2

CCC3-28 1088.2 +1.8 273 +6 813.7 +2.0 0.4021 +0.0011 26430 +604 26826 +85 26761 +85 878 + 2

105

APPENDIX B: PANCAKE FIELD PERCENT ABUNDANCE

Table B1

Title Depth Picea Jack Pine Abies Pinus Lycopodium Cyperaceae Asteraceae

1213 0.33703704 0.25925926 0.01111111 0.09259259 0.0962963 0.09259259 0.04444444 1249 0.44178082 0.28424658 0.01027397 0.04794521 0.09931507 0.02054795 0.05136986

1261 0.36805556 0.40972222 0.00694444 0.03819444 0.07638889 0.02083333 0.01736111

1289 0.16556291 0.23178808 0.00331126 0.03642384 0.40066225 0.02649007 0.01986755

1331 0.2877193 0.16140351 0.00701754 0.12631579 0.30877193 0.0631579 0.01052632

1343 0.35526316 0.10526316 0.02302632 0.10197368 0.16776316 0.0625 0.06578947

1360.5 0.33006536 0.0620915 0.01633987 0.08496732 0.28431373 0.0751634 0.04248366

1371 0.2585034 0.1122449 0.00680272 0.06802721 0.21428571 0.0952381 0.06122449

1383 0.36428571 0.34642857 0.01785714 0.02857143 0.16785714 0.01071429 0.00714286

1429 0.22137405 0.14122137 0.01908397 0.12213741 0.30916031 0.0610687 0.03816794

1439 0.30821918 0.36643836 0.02054795 0.10616438 0.14726027 0.00342466 0.00684932 1457 0.26132404 0.26132404 0.00696864 0.08013937 0.26829268 0.04181185 0.01045296 106

1481 0.27891157 0.4659864 0.01020408 0.0952381 0.1292517 0.00340136 0.00340136 1507 0.41258741 0.43706294 0.01748252 0.03146853 0.08041958 0 0 1521 0.45421245 0.21978022 0.07326007 0.14285714 0.05128205 0.01465202 0.00732601 1601 0.1875 0.12152778 0.00347222 0.02083333 0.47222222 0.05555556 0 1639 0.03345725 0.01858736 0 0.02230483 0.74349442 0.03345725 0.01115242

Table B2

Title Depth Poaceae Sphagnum Polygonaceae Seligenalla Ferns Woody taxa Herbs

1213 0.02222222 0.00740741 0 0 0.0037037 0.01111111 0.01481482 1249 0.00342466 0.00342466 0.00342466 0 0 0.01712329 0.01027397

1261 0.00694444 0.00694444 0 0 0.00694444 0.00694444 0.01736111

1289 0.05298013 0.00331126 0 0 0.02317881 0.01986755 0.00993378

1331 0.00701754 0.00701754 0.00350877 0 0.00350877 0.00350877 0.00350877

1343 0.02631579 0.00657895 0.00657895 0 0.01644737 0.02631579 0.01644737

1360.5 0.02287582 0 0.00326797 0 0.02941177 0.02614379 0.0130719 107

1371 0.07823129 0.01360544 0.00680272 0 0.03061225 0.01360544 0.0170068

1383 0.02857143 0.00357143 0 0 0 0.00357143 0.01071429

1429 0.00381679 0.00763359 0.00381679 0.01145038 0.01526718 0.01908397 0.00763359

1439 0.01369863 0 0.00342466 0 0 0.01027397 0.01027397 1457 0.02439024 0.00696864 0 0.00348432 0.00696864 0.01393728 0.00348432 1481 0 0 0 0 0.00340136 0.00340136 0.00680272 1507 0 0 0 0.0034965 0.01398601 0 0 1521 0.01465202 0 0.00732601 0 0 0.003663 0 1601 0.00694444 0.03472222 0 0.01388889 0.02430556 0.01041667 0.02777778 1639 0.01115242 0.01858736 0.01858736 0 0.04460967 0 0.02973978 APPENDIX C: NEOTOMA DATA

Table C

Neotoma data from Virginia and West Virginia Site Name Lat, Lon Species Bone type Max age Min age (years BP) (years BP) Thompson’s 37.25, Homo Bone/tooth 10,000 1,150 Shelter, VA -80.5 sapiens Strain 38.470556, Mammut Bone/tooth 29,870 17,880 Canyon, VA -79.511667 americanum Equus sp. Ripplemead 37.25, Mylohyus Bone/tooth 10,000 7,000 Quarry, VA -80.866667 sp. Clark’s 38.086111, Canis dirus Bone/tooth 20,000 11,000 Cave, VA -79.656944 Bison sp. Bootherium bombifrons Cervalces sp. Equus sp. 36.866667, Saltville, VA Bone/tooth 27,000 13,500 -81.766667 Mammut americanum Mammuthus primigenius Ovibos sp. Megalonyx jeffersonii Hidden Valley Homo 38, -79.75 Bone/tooth 10,000 1,150 Rockshelter, sapiens VA Patton 37.543333, Platygonus 13,350; 13,350; Bone/tooth Cave, WV -80.398889 compressus 22,260 22,260 New Trout Canis dirus 38.602778, Cave, WV Megalonyx Bone/tooth 31,100 16,840 -79.368889 sp. Organ- 37.717222, Mylohyus Tooth, Hendricks -80.437222 fossilis tooth, left 110,000 11,500 Cave, WV mandible, tooth Data from Peterson, 1917, Handley, 1956, Ray, 1967, MacCord, 1972, MacCord, 1973, Guilday et al., 1977, Weems and Higgins, 1977, McDonald and Bartlett, 1983, Anderson, 1984, Fay, 1984, McDonald, 1984, Eshelman and Grady, 1986, and Grady, 1988. ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

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