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HOLOCENE CHEMOSTRATIGRAPHY OF SPRING SEDIMENTS

IN RANGE CREEK CANYON, UTAH

Danielle Marie Ward

A thesis submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of

Master of Science

Department of Geography

The University of Utah

December 2016

The University of Utah Graduate School

STATEMENT OF THESIS APPROVAL

The thesis of Danielle Marie Ward has been approved by the following supervisory committee members:

Andrea R. Brunelle , Chair 05/04/16 Date Approved

Simon C. Brewer , Member 05/04/16 Date Approved

Brenda Bowen , Member 05/04/16 Date Approved

and by Andrea R. Brunelle , Chair/Dean of the Department/College/School of Geography and by David B. Kieda, Dean of The Graduate School.

ABSTRACT

Range Creek Canyon in southeastern Utah is the location of hundreds of well- preserved Fremont archeological sites. To determine what living conditions for the Fremont were like during their occupation of Range Creek from 200 AD and 1350 AD, elemental ratios and grain size data were used as proxies for precipitation-induced erosion. These proxies, along with previously analyzed pollen and charcoal data from the spring, were hypothesized to help characterize moisture availability over the last 8,500 years in Billy

Slope Bog, a wetland spring within the canyon. Additionally, to create a chronology of climatic events in the canyon, an attempt was made to find tephra from the Mazama eruption of Crater Lake, Oregon, dated 7625 ± 150 cal. yr BP Finally, as a check to the accuracy of the elemental data, the chemostratigraphy of a sediment core from Billy Slope

Bog was collected twice, then compared to determine repeatability of the results.

The results proved that the elemental data and pollen ratios analyzed had a strong positive relationship, and together reveal a clear picture of how precipitation fluctuated in

Range Creek Canyon. Based on the data, the Fremont entered the canyon during a period of high precipitation, and left during drought conditions. However, grain size data did not follow the same trend, and therefore is not an accurate proxy for paleoprecipitation within the canyon. Additionally, based off of spikes in Al, Y, and Ti, a potential location of the

Mazama eruption within the core was found. While this data cannot be confirmed without the presence of volcanic glass, the fact that the concentration of yttrium is fifty times higher

in this location than anywhere else in the core indicates a sudden depositional event, such as from a volcanic eruption. Finally, the two chemostratigraphies of the sediment core as a whole were positively correlated. The level of positive correlation among individual elements varied, but this difference is probably derived from differences in scanning methodology. Therefore, overall the results indicate that portable XRF data is accurate and repeatable.

iv TABLE OF CONTENTS

ABSTRACT……………………………………………………………….……………..iii

.LIST OF FIGURES………………………….…………………………………….…….vii

LIST OF TABLES………………………………………………………………………viii

ACKNOWLEDGEMENTS………………………………………………………………ix

INTRODUCTION…………………….…………………………………………………..1

Objectives …………………….…….…………….….….………...... ……...... 2 Background and Theoretical Framework....……………………..………………...3

SITE DESCRIPTION…..……...…………………………………..……………….……10

Geology…………………………………………………………...……….……..10 Modern Climate………………..……………………………………………...…11 Past Populations…………………..……….…………..…………………………12

METHODS……………………………….……………………………………...………14

Fieldwork………………………….……………………………….……….…....14 Previous Lab Work………………….……………..…………………………….14 Lab Work……….……..…………….…………………………………………...15

RESULTS…………………………….……………………………………………....….20

BSB14A Correlation and Principle Component Analysis………….…..….....…..20 Lateral Heterogeneity Between BSB14A and BSB09B…………....…………….22 Stratigraphy of Weathering Indices and Element Ratios…………….……...... 23 Grain Size Analysis………………….….....……………………………………..25 Ti Comparison to Pollen Based Climate Reconstructions…...... …26 Element Ratio and Grain Size Comparison to Pollen Data…………………….....27 Tephra Identification……………………………………………………………..28

DISCUSSION……………………………………………………………….……..…….44

BSB14A Correlation…………………………………………...... 44 Lateral Heterogeneity of BSB14A and BSB09B………………..…………..……45 Ti as a Proxy for Precipitation…………………………….…….………...….…..47 Vegetation and Sediment Influx……………………………………………....….48 Stratigraphy of Weathering Indices and Element Ratios…………………..……..49 Precipitation During Fremont Occupation of Range Creek Canyon…….….…….51 XRF as a Means to Identify Cryptotephra….…………………………….…..…...51

CONCLUSION...………………………………………………………………………...55

REFERENCES………………………………………………………..…………………58

vi LIST OF FIGURES

1. Map of Crater Lake, Oregon, and Mazama eruption tephra extent……………..……...9

2. Map of Range Creek Canyon, Utah…………………….…………..….…………..…13

3. Age-depth model for Billy Slope Bog, Utah…………..………….……..……..…...... 19

4. Principle component analysis versus depth for BSB14A ...…………………...... 30

5. Principle component analysis biplot of BSB14A ……………..……………………...31

6. Lateral heterogeneity of BSB14A and BSB09B………………….…….…………….32

7. K/Al, Al/Si, Ca/(Ti+Fe+Al), and CIA stratigraphy for BSB14A………….……….....33

8. A-CN-K diagram for BSB14A ……...... …………....34

9. Grain size fluctuation for BSB14A ……………………………………….………….35

10. Stratigraphies of Al, Ti, Y, Mn, and Si in BSB14A………….………………………36

11. Comparison of weathering indices and element ratios to pollen based climate reconstructions …………………………………………...………………….………37

LIST OF TABLES

1. Correlation Analysis for Multiple Scans of BSB14A…………………….……….....37

2. Summary Statistics for BSB14A…….…………………………...……………...... 38

3. Summary Statistics for BSB09B……….………………………....…….……………39

4. Difference in Average Between BSB09B and BSB14A……………..……...………..40

5. Correlation Coefficients Between BSB09B and BSB14A………….………………...41

6. Correlation Coefficients Between Individual Meters of BSB09B and BSB14A...... 41

7. Correlation Matrix for Pollen and Detrital Elements Comparison……………...... 42

8. P-Values for Pollen and Detrital Elements Comparison…………………….…...... 42

9. Mazama Ash Elemental Concentrations...……………………………………………43

ACKNOWLEDGEMENTS

Thanks to Dr. Andrea Brunelle for her support both as an advisor and a friend.

Additionally, thanks to Dr. Brenda Bowen and Dr. Simon Brewer for being a part of my committee and helping me with this project. Thanks to Isaac Hart for doing charcoal and pollen analysis on BSB09B, without him this project would not have been possible. Thanks must also go to Dr. Barbara Nash for her assistance in processing and analyzing tephra samples. I also have to thank my fellow RED labbers because I’ve learned so much from them regarding both paleoclimates and cats. A special thanks to my mom and dad for supporting me even though they effectively had no idea what I was doing, but trusting that

I would figure it out. Thanks to my loving boyfriend for mental stability, and also, my roommate Alyssa Hynes for providing emotional support. Thanks to the staff at Range

Creek for the opportunity to work on this project and helping me with fieldwork. Thanks to the Global Change and Sustainability center for funding the first year of my graduate career, and thanks to the University of Utah Geography Department for funding my second.

Last but not least, thank you to Dr. Bruce Kaiser for teaching me how to use the x-ray fluorescence spectrometer and for all his help along the way.

INTRODUCTION

For over a decade, anthropologists working at Range Creek Canyon field station have been interested in understanding how prehistoric Fremont culture responded to paleoenvironmental change (Rittenour, Coast, & Metcalfe, 2014). In particular, researchers seek to confirm whether or not the departure of the Fremont from Range Creek Canyon in the 12th century was climate related, such as from an extended period of drought (Kloor,

2007). One way to determine what living conditions for the Fremont people were like, and why they may have left, is to determine the paleoenvironment and paleoclimate of Range

Creek Canyon. By reconstructing the conditions in which the Fremont people lived, the circumstances behind their departure will also become clearer. Many studies by University of Utah faculty and colleagues have taken place in Range Creek Canyon. These projects center on environmental reconstruction and include archeological excavations, analysis of alluvial profiles, bog sediment analysis, and tree-ring chronology. However, attempts to create a cohesive age model for environmental events in Range Creek Canyon through accelerator mass spectrometry (AMS) have been problematic due to interference from old carbon deposits. Therefore, alternative methods must be employed to refine the region’s chronology.

The focus of my research is the examination of a sediment core taken from Billy

Slope Bog, a wetland spring within Range Creek Canyon, using elemental analysis.

Elemental analysis is the quantification of the amount and type of molecular elements in a

2 sample. The specific method of elemental analysis used for this study is x-ray fluorescence

(XRF) from a portable Bruker Tracer III-SD pXRF Spectrometer. X-ray fluorescence measures the energy spectrum from the photoelectric fluorescence of secondary x-rays

(Boyle, 2000; Potts & West, 2008). The x-rays are generated by a high energy source (e.g., a rhodium x-ray tub). The x-rays bombard the sediment samples, exciting the atoms and causing inner shell electrons to fall out of their shell. Outer shell electrons take their place, and energy is released by this movement in the form of secondary x-rays (Boyle, 2000;

Potts & West, 2008). The energy released by the electrons is characteristic of a specific element, such as Ca or Fe, and is picked up by a detector within the spectrometer. The rate of detection of an element is controlled by the concentration of outgoing x-rays received

(Boyle, 2000; Potts & West, 2008). The spectrometer measures both major elements, such as Ca, and trace elements, such as Y. Trace elements occur in much smaller quantities than major elements, so a filter on the spectrometer is used when scanning for trace elements so only a specific range of elements is detected. XRF is a valuable tool for scientific research due to how rapidly results are produced: with a core scanner, in a single day over two thousand measurements can be made. Additionally, the nondestructive component of XRF is an advantage to preserve samples for later research (Rowe, Hughes, & Robinson, 2012).

Objectives

This research will focus on the paleoenvironmental reconstruction of Billy Slope

Bog in southeastern Utah by using x-ray fluorescence on two bog cores collected between

2009 and 2014. The research objectives are:

1. Determine if XRF results are repeatable by collecting chemostratigraphic data

for sediment core BSB14A twice and correlating the results.

2. Describe how allochthonous input and moisture availability in Billy Slope Bog

has changed over the last 8,500 years by using Ti, element ratios, and a grain

size analysis as proxies for precipitation-induced erosion.

3. Isolate volcanic events by comparing Al, Ti, Mn, and Si spikes from BSB14A

to the same elements in tephra control samples in order to verify the current

chronology for Range Creek Canyon.

Background and Theoretical Framework

X-ray florescence has been used in a variety of applications, from dating artwork to analyzing ore grades in mining, but only within the last fifteen years has it been used in paleolimnology (Potts & West, 2008). While still a relatively new method, one of the most popular applications of XRF in paleolimnology is to quantify the degree and nature of detrital sediment into a catchment. The influx of these sediments is inferred to be caused by changes in precipitation, which impacts the level of physical erosion into the catchment

(Metcalfe, Jones, Davis, Noren, & MacKenzi, 2010; Roy et al., 2012). The ease of this interpretation lies in the ability to link the composition of elements derived from weathering to the surrounding bedrock. During physical erosion, soluble cations and oxyanions such as Ca+2, Na+, and K+ are leached (Nesbitt & Young, 1982; Roy et al., 2012;

Taylor & McLennan, 1985). This leaves an enriched portion of Al-3 and Ti-, both insoluble hydrolysates, in the remaining sediments (Nesbitt & Young, 1982; Roy et al., 2012; Taylor

& McLennan, 1985). Therefore, in a sediment core, increases or decreases in detrital elements indicate changes in the rate of sediment transport (Metcalfe et al., 2010).

A variety of elements have been used as a proxy for weathering by themselves, all with advantages and disadvantages. For example, while fluctuations in K can be used as

4 an indicator of weathering, K is susceptible to reabsorption into secondary minerals, making its origin difficult to determine (Hahn, Kliem, Oehlerich, Ohlendorf, & Zolitschka,

2014; Roy et al., 2012). On the other hand, Al is an insoluble hydrolysate and a more reliable indicator of erosion, but high organic matter can affect its concentration (Metcalfe et al., 2010). However, Metcalfe et al. (2010) proved that Ti could be a high-resolution proxy for precipitation by comparing Ti fluctuations to historical records of precipitation over the past 2000 years in Laguna de Juanacatalán, Mexico. Consistently, high concentrations of Ti, which was inferred to be from bedrock weathering, corresponded to periods of higher rainfall (Metcalfe et al., 2010). Therefore, Ti will be evaluated as a proxy for paleo-precipitation in Range Creek Canyon. However, Ti in Bakke et al. (2009) was linked to aeolian input, and was also used as an indicator for tephra in Kylander et al.

(2011). Ultimately, while it will be evaluated as a proxy for precipitation, there are a variety of other inputs for Ti in the catchment.

Therefore, in conjunction with Ti, several element ratios and weathering indices will also be used to estimate paleo-precipitation in Range Creek Canyon. Element ratios are a useful proxy, as they normalize element concentrations and minimize variability from other potential bog inputs (Brown, Le Callonnec, & German, 2000; Burnett, Soreghan,

Schloz, & Brown, 2011; Thompson, Croudace, & Rothwell, 2006). Additionally, by using a relative value, any errors in the xrf calibration or scanning procedure become negligible.

The element ratios that will be examined in BSB14A are Al/Si, K/Al, and Ca/(Ti+Fe+Al).

Al/Si is being used as a representation of the degree of weathering intensity, with increases in Al/Si corresponding to an increase in weathering (Drever, 2005). K/Al was chosen to represent changes in illite in relation to kaolinite, as K is found in the crystalline structure

5 of illite, but not kaolinite (Burnett et al., 2011; Yarincik, Murray, & Peterson, 2000). Illite is the product of physical weathering, while kaolinite forms during chemical weathering.

Therefore, if K/Al is low, then there is more kaolinite than illite, and more chemical weathering is occurring (Bonatti & Gartner, 1973). Finally, Ca/(Ti+Fe+Al) was used by

Muller et al. (2009) to represent the dryness of the climate. In this ratio, Ca represents authigenic carbonate precipitation, while Fe, Ti and Al represent detrital material. Lower rainfall would cause a decrease in the level of detrital materials, which would leave a higher amount of authigenic carbonate. Therefore, if the ratio of Ca/(Ti+Fe+Al) is low, the climate at the time of deposition was drier, and if the ratio was high, the climate was wetter.

Regarding the element ratios, the most widely used is the chemical index of alteration (CIA), which measures the level of chemical weathering in clastic sediments

(Nesbitt & Young, 1982; Roy, Caballero, Lozano, & Smykatz-Kloss, 2008). The chemical index of alteration uses the equation [(Al2O3/ Al2O3+Ca+Na+K2O3)x100] (Nesbitt &

Young, 1982). The benefit of using the chemical index of alteration is that it includes both immobile and mobile elements, and is therefore ideal for analyzing detrital elements as a whole. The CIA assumes that the dominate process of chemical weathering is the degradation of feldspars into clay minerals. If there is largely unaltered feldspar, physical weathering is the dominant force (Nesbitt & Young, 1982). The degree of chemical weathering in an area is dependent on both temperature and precipitation (Nesbitt & Young,

1989). Modern Range Creek Canyon is a semiarid environment, with the majority of its precipitation occurring in the winter months, so, in this setting, temperature is not a large control on the rate of chemical weathering. Instead, the amount of chemical weathering is largely based on precipitation, with increased levels of precipitation resulting in high levels

6 of chemical weathering, and low precipitation levels causing the reverse (Nesbitt & Young,

1989). Therefore, in conjunction with Ti and the element ratios, the chemical index of alteration will shed further light on climate during Fremont occupation of Range Creek.

As an additional validation of the elemental analysis results, grain size will also be used for comparison as a proxy for detrital input. Grain size on its own is a valuable addition to multiproxy analyses as the variations in grain size reflect changes in the process and energy of sediment transport. While the relationship between grain size and geochemistry is different for each catchment, generally certain elements are more likely to be concentrated around a specific grain size. For example, coarser grain sizes correlate to elements commonly found in carbonates, like Ca, and indicate high-energy inputs into a catchment (Cuven, Francis, & Lamourex, 2010; Koinig, Shotyk, Lotter, Ohlendorf, &

Sturm, 2003). Similarly, smaller grain sizes correlate to elements found in clay minerals, like Si, indicate a low-energy environment (Cuven et al., 2010, Koinig et al., 2003). An important factor as to if an environment is high-energy or low-energy are changes in precipitation amount. Therefore, spikes in Ti will be compared to grain size increases, to together reconstruct a pattern of precipitation in Range Creek Canyon.

The most experimental aspect of this study, as well as the one that could have the most impact on research in Range Creek Canyon, is identifying volcanic events within the sediment core using the using XRF data. Tephrochronology is a valuable method for dating, especially in locations where other methods have limited value. Only recently has XRF been applied to identify tephra within paleolimnology, with its appeal lying in the nondestructive and rapid aspects of XRF (Balascio et al., 2015). Additionally, the potential of using XRF to locate cryptotephra, or tephra layers unseen to the visible eye, is

7 advantageous as it could reveal volcanic events even from low concentrations of tephra.

When volcanic events occur, the chemistry of the tephra from each eruption is different from the next, giving the event a distinct elemental signal. If the ratio of elements matches the known elemental signature of the volcanic ash from an eruption, and the age of the eruption is known, this can provide age control to the core. For example, tephra from the

Mt. Mazama eruption, now Crater Lake, OR, dated 7,627 ± 150 cal. yr BP has a specific elemental concentration unique to any of Mt. Mazama’s other eruptions (Zdanowicz,

Zielinski, & Germani, 1999). Tephra from the Mt. Mazama eruption has been found in

Utah, as seen in Figure 1. Additionally, the Mazama tephra overlaps with the proposed age of sediment cores taken from Billy Slope Bog, and therefore could be used as an age marker for Range Creek Canyon.

It should be noted that there are several drawbacks of using XRF to identify tephra, the most important being that tephra signals in sediment cores are most easy to identify if the background signal has little compositional variation, so that instances of tephra are more easily distinguished (Balascio et al., 2015). If there is significant compositional variation in the core, the tephra signal is more difficult to distinguish (Kylander et al.,

2011). Even in instances where the background signal is purposefully minimal, such as in

Balascio et al. (2015), not all tephra are identified. However, with rhyolitic tephra such as

Mt. Mazama, the best results from multiple studies were from cores with very fine grain size, as the smaller material is more densely packed, making more samples available for detection (Balascio et al., 2015). The elements most likely to represent to rhyolitic tephra were Ti, Mn, and Si. In Balascio et al. (2015), Al is also suggested as being a potential identifier as it is common in rhyolite, but with their detection time methodology only being

20 s per sample it was not picked up. Using longer detection times and working with very fine grained material, the Mazama ash signal will hopefully be identified within the Billy

Slope Bog cores. Therefore, this study could provide independent age control of environmental events in Range Creek Canyon where earlier radiocarbon efforts could not.

The success of the tephra chronology and the accuracy of the XRF data as a whole will determine its’ importance in future research within Range Creek Canyon.

Figure 1: Map of Crater Lake, Oregon, and Mazama eruption tephra extent. The extent of the Mazama eruption is pictured in yellow. Additionally, the locations of Crater Lake (CL) and Range Creek Canyon (RCC) are represented by the black stars. Crater Lake is 1,092 km from Range Creek Canyon. Modified from Sarna-Wojicicki and Davis, 1991.

SITE DESCRIPTON

Range Creek Canyon is located near the town of Price on the Colorado Plateau, and is bordered by the Books Cliffs to the south and east (Figure 2). The canyon is north- northwest trending with flat lying bedrock and the creek itself is a tributary to the Green

River (Rittenour et al., 2014). Elevations within the canyon range from 3084-1290m, with the canyon walls at times rising up to 300 m in height. The study site, Billy Slope Bog, located within Range Creek Canyon at 1862 m asl, is a wet meadow located at longitude:

110° 12’ 51.893’’ W and latitude: 39° 25’ 41.701’’ N. It was selected as a study area because of the long-standing bog water, indicating a depositional area with an undisturbed sediment record. Such depositional environments like Billy Slope Bog can register small changes in regional climate (Roy et al., 2012).

Geology

Range Creek Canyon is composed of two geologic formations which span from the Late Paleocene to the Early Eocene, or 48-58 million years ago (Nieminski & Johnson,

2014; Pitman, Anders, Fouch, & Nichols, 1986). The lower unit, the Flagstaff Formation, is fossiliferous limestone, but only has outcrops downstream of Billy Slope Bog, and is therefore outside the range of this study. On top of the Flagstaff Formation is the Colton

Formation, which is split into the Upper and Lower Colton (Marcantel & Weiss, 1968).

Billy Slope Bog is located entirely on the Colton Formation (Figure 2).

The Lower Colton is a mix of interbedded quartzose sandstone and mudstone that

11 has been stained red from iron oxide, while the Upper Colton is made entirely of quartzose sandstone (Nieminski & Johnson, 2014). The Colton Formation was likely deposited in a former river channel or floodplain. In the Lower Colton however, there is a higher concentration of mudstone in comparison to the Upper Colton, indicating that the depositional environment of the Lower Colton was low-energy. The erosional differences between the sandstone and shale of the Colton Formation created the steep canyon outcrops the Fremont utilized for granary placement (Metcalfe, 2008; Rittenour et al., 2014; Towner,

Salzer, Parks, & Barlow, 2009). The dominant mineral in the Colton Formation sandstone is quartz (SiO2). In the mudstone, feldspar, mica, and other clay minerals are more common. The Green River Formation also is found in Range Creek Canyon, but only in small quantities at the northwest top of the canyon. The Green River Formation is composed of sandstone and green shale.

Modern Climate

The modern climate regime of Range Creek is semiarid, and derives half of its precipitation from Pacific storms in the winter (Bares, 2014; Rittenour et al., 2014). The other half of Range Creek’s precipitation comes from summer convective storms with moisture originating from the Gulf of Mexico (Bares, 2014). According to a Vaisala

HMP50 temperature and relative humidity probe located midcanyon, summer temperatures in Range Creek Canyon range between 34.7° maximum and 10.9° C minimum, while winter maximums are 9.5° C and minimum are -14.8° C (Global Historical Climatology

Network USC00428476, AD2008-2015; Rittenour et al., 2014). Range Creek Canyon is uniquely poised at the intersection of several different precipitation regimes, meaning that depending on the location within the canyon, varying amounts of moisture are available at

12 different times of the year (Bares, 2014; Mock, 1996). Overall, Range Creek Canyon receives approximately 10-12 in. of rain a year (Towner et al., 2009). However in the northwest end of the canyon, the maximum precipitation is during November-October, while in the east the dominant moisture source is spring precipitation in March-April

(Mock, 1996).

Past Populations

The Fremont were an indigenous pre-Columbian culture of hunters and farmers who lived between 200 AD and 1350 AD (Metcalfe, 2008; Rittenour et al., 2014). While mostly found in Utah, artifacts have also been found in Idaho, Wyoming, northwestern

Colorado, and Nevada (Barlow, 2002; Morris, 2010). There are many differences among

Fremont sites, but what links them are four characteristics: the representation of humans in prehistoric art, thin grey ceramics, baskets in a single-rod-and-bundle style, and moccasins derived from deer or sheep (Barlow, 2002). One of the largest sites of Fremont occupation is Range Creek Canyon, located in southeastern Utah (Morris, 2010). Fremont occupation of Range Creek Canyon extends from 500 AD to 1350 AD, however, peak occupation is most evident in the Late Fremont era, between 1000-1200 AD (Bares, 2014; Green, 2008).

Since Range Creek Canyon has been under private ownership since 1844 AD, the canyon has escaped much of the looting and degradation typical of most archaeological sites in

Utah. Additionally, many more sites may be found in the future, since as of 2010 only 10% of the canyon had been explored (Nieminski & Johnson, 2014). These sites contain petroglyphs, pit houses, and stone granaries built into the canyon walls (Metcalfe, 2008;

Morris, 2010; Rittenour et al., 2014).

Figure 2: Map of Range Creek Canyon, Utah. Billy Slope Bog coring site is indicated with a black circle. While other rock layers surround Range Creek Canyon, for the most part the canyon is composed of Colton Formation sandstone and mudstone. The background digital elevation model is adapted from the United States Geological Society, the geologic layer information is from Nieminski and Johnson (2014).

METHODS

Fieldwork

In June 2009, a core was removed from Billy Slope Bog of Range Creek Canyon,

Utah by researchers from the Records of Environment and Disturbance (RED) Lab at the

University of Utah under the direction of Dr. Andrea Brunelle. The core was removed from the bog using a modified Livingstone piston corer. The core, BSB09B, was 5.10 m long, and its lithology was described in the field as clearly stratified. The core was extruded, then wrapped in both plastic wrap and aluminum foil for transport. Afterwards, the core was brought to the RED Lab at the University of Utah where it was stored and refrigerated at

33°F (0.56°C). In October 2014, a second core was taken out of Billy Slope Bog by RED lab researchers using a vibracorer powered by a gas motor. An aluminum tube three inches in diameter was pushed 4.84 m into the bog, then filled with water and capped to prevent movement of sediment before being extracted. This core was not taken from its aluminum tube and was refrigerated at 33°F (0.56°C) in the RED lab cooler. BSB14A remained undisturbed until June 2015, where its tubing was cut in half with a radial saw, and each half was wrapped in plastic wrap followed by aluminum foil. Upon splitting the core, it was photographed and the lithology was recorded.

Previous Labwork

In the RED lab, BSB09B was cut into one centimeter sections, totaling five hundred and ten samples. These samples were numerically labeled, placed into whirlpacks, and then

15 refrigerated at 33°F (0.56°C). After, charcoal, pollen, and magnetic susceptibility for

BSB09B was completed by Isaac Hart, a PhD student in the University of Utah’s

Anthropology Department. Additionally, three of the samples from BSB09B, centimeters

147-148, 299-300, and 473-474, were sent to the University of Georgia’s Center for

Applied Isotope Studies (CAIS) to be radiocarbon dated. From these dates and the R script

CLAM an age model for BSB09B was created, as seen in Figure 3.

Labwork

XRF of BSB09B

Between October 2014 and November 2014 all individual samples of BSB09B were scanned with a portable Bruker Tracer III-SD series pXRF spectrometer. The spectrometer was fixed to a stand so that with a switch, it would rise up and down, removing the need to hold it. Before scanning, a filter was added to the spectrometer to focus results on elements between Al and Ti on the periodic table. Groups of samples in numerical order from centimeters 1-510 were removed from their plastic packaging with tweezers, then set onto a plate. All samples were scanned once for major element concentrations at a current of 15 keV, 25 µA and a time span of 30 s per trial. Some trials had to be performed multiple times as the XRF tracer would not be close enough to the sample, which led to a smaller than normal photon count. Photon counts of 15,000 keV were the baseline for a rescan, lower photon counts were discarded.

When all samples were scanned at the appropriate parameters for major elements, they were scanned again at a current of 40 keV, 12 µA for trace elements. These trials were

60 s long instead of 30 and used a higher power setting in order to pick up trace elements.

Unlike the previous trial, these trials used no filters but incorporated a helium gas purge,

16 the purpose of which was to replace the air surrounding the x-ray tube and detector. Helium was provided by air balloon tanks, which were hooked by plastic tubes into the portable

XRF machine and blew through the machine onto the sample. This allowed the direct analysis of trace elements without the potentially contaminating effect of the surrounding air.

XRF of BSB14A

In July of 2015 and May of 2016, XRF scans of BSB14A were performed, again using a portable Bruker Tracer III-SD series pXRF spectrometer. However, the two XRF scans also made use of a MCS-100E Automatic 1-meter Core Scanner, which over a period of twelve hours scanned every two millimeters of a one meter core section. In order to fit the 4.84 m of BSB14A onto the core scanner, the core was cut into 1 m sections. Etnom

Ultra-Polyester film was placed over the core to prevent drying and potential contamination of the scanner. In July 2015, BSB14A was first scanned with a yellow filter at 40 keV and

30 µA. A second scan with no filter and a helium purge scanned all samples at high voltage

15 keV and 25 µA in August. The scan in May 2016 only performed the helium scan, with the same parameters as when BSB14A was scanned in July 2015. The purpose of performing the helium scan twice was to ensure the portable XRF results were reliable, so accurate conclusions based on the data could be made. As an additional check, the elemental data were also be compare to more a traditional paleoenvironmental proxy, pollen data, to determine if they were correlated. The addition of these proxy records to the

XRF data was also used to refine when environmental fluctuations in Billy Slope Bog occurred.

Grain Size Analysis

In November 2015, samples from each centimeter of BSB14A were prepared for laser diffraction analysis. Laser diffraction is a method of grain size analysis done by measuring changes in the wavelength direction of a laser beam when sediment is exposed to it. The changes in wavelength direction and intensity reveal the dimensions of the exposed sediment down to a submicron level. The end result of laser diffraction is a record of changing grain size throughout the core, which can be interpreted as changes in sediment deposition due to environmental changes. For example, a period dominated by large grain size would indicate a high energy environment from either precipitation or stream flow.

Laser diffraction is an ideal method of grain size analysis for the Billy Slope Bog because laser diffraction can detect grain size down to a submicron. Therefore, it is the most precise proxy to compare to XRF measurements made on a molecular scale.

In preparation for laser diffraction, the following methodology was used as detailed by Dr. Richard Langford of the University of Texas in El Paso in a personal correspondence. One gram samples were taken from each centimeter of core, weighed, and then placed into whirlpack bags. Each sample was then placed in a beaker containing hydrogen peroxide and set onto a hot plate until all organics had burned off, which was indicated by a lack of foaming. Organics were removed because they form in situ

(autochthonous), while the focus for laser diffraction is on the sediment being transported into the bog (allochthonous). Samples were then put through a 1000 µm sieve and washed with distilled water. Finally, the samples were sent to Dr. Langford, who split and suspended the samples, then analyzed them using a Malvern Mastersizer 2000 Laser

Diffraction Particle Sizer.

Tephra and Rock Analysis

In October 2015, Dr. Barbara Nash of the University of Utah Geology and

Geophysics department gave a tephra sample representative of the Mount Mazama eruption

(dated at 7,627 ± 150 cal. yr BP in Zdanowicz et al., 1999) to the RED lab for analysis. The sample was scanned a total of six times with the XRF spectrometer. Three of the scans were with a yellow filter at 40.00 keV and 30.00 µA. The other three were scanned with a helium purge at 15.00 keV and 25.00 µA. The results of the scan were then averaged.

Once an area with a potential tephra was identified, a smear slide was taken from

4.445 m in the core, and was 1 cm in length. Silica solution was added to the smear slide so that the sample would be more spread out and glass shards would be easier to identify.

The sample was examined under a microscope, and when sediments that were potentially glass shards were located, more samples were taken to be given Dr. Nash for further analysis. Five samples were taken, one of the target area and the other four representing five centimeter increments around the target are. The samples were taken from the following areas: 4.540-4.448 m, 4.448-4.444 m, 4.444-4.440 m, and 4.440-4.390 m. The sediment samples were dried, then disaggregated with a mortar and pestle. The sample was then sieved to capture the 60-120 µm and the >120 µm fractions. Each sample fraction was then rinsed and until all runoff water was clear, after which it was treated with a dilute

(10%) nitric acid in a sonic bath to eliminate carbonates. Additionally, the sample was also treated with dilute (5%) hydrofluoric acid for 30 s in sonic bath in order to clean clays off glass. Finally, the sample was rinsed and dried in a low temperature oven, then examined under a petrographic microscope.

Figure 3: Age-depth model for Billy Slope Bog, Utah. Model created by Hart (2017). The model was created with three pollen radiocarbon dates, represented by the black dots. These dates then underwent a smooth-spline interpolation using CLAM, a modeling package in R (Blaauw, 2010). The top of the y-axis at 0 represents the surface of Billy Slope Bog.

RESULTS

BSB14A Correlation and Principle Component Analysis mm

To determine if the Bruker Tracer series III portable x-ray fluorescence spectrometer produced repeatable results, BSB14A was scanned twice and then analyzed in RStudio using the “cor” function to determine if the level of correlation between the scans (Table 1). Additionally, t-tests on the stratigraphy of each element were performed in order to measure the difference of the variation between the two scans. The null hypothesis for the t-tests was that there would be no difference between the two scans, as it was the same core being analyzed. The result of this test was that the two scans of

BSB14A were positively correlated, however, the levels of correlation between each element varied drastically. The highest correlation was Ca at 0.91, followed by Ti at 0.90.

Out of the ten elements analyzed, eight had a positive correlation over 0.50. Two of the elements, Si and Mg, had weak positive correlations, 0.42 and 0.33, respectively (Table 1).

Unlike the high correlation values, the result of the t-tests for every element was

<2.2e-16. As the p-values were below five percent, the difference between the two cores is significant. Therefore, the null hypothesis, that the two cores would have the same results, was rejected. However, the low p-values are most likely due to differences in the magnitude of the XRF results, which can be attributed to using two different scanners to collect data.

The aforementioned similarity in correlation between each scan is proof that the scan results for BSB14A are comparable. To further validate the conclusion that the scan results

21 are comparable, additional tests on variability throughout the core were performed.

To further compare differences in trend, a principle component analysis (PCA) was performed on both scans of BSB14A, again using RStudio (Figure 4). The assumption was that the trends would be similar, as they are from the same core. This assumption was proven correct, as the two trends were similar, albeit with minor differences. For example, one of the most noticeable similarity between the two cores are large spikes in the variance of the principle component analysis at 3.5 m, 4 m, and 4.4 m. These spikes in the 2016 trend are positive, and the spikes for 2014 are negative, however, they are in the same location. In a principle component analysis, the main factor is the degree that the variance strays from zero, and the spikes both vary a similar amount from each other. Another similarity is that in the 2016 scan, until 2.5 m the PCA versus depth graph is underneath 0, which represents no collective variance. After 2.4 m, the trend moves to above zero. The graph from 2014 shows the mirror of this trend, until 2.4 m the graph is over zero, but after

2.4 m the trend drops. However, while the shifts in trend are in the same spot, the changes in trend during this period is more pronounced than in the 2016 scan. The results of the

PCA were also analyzed as a biplot, in order to quantify element covariance (Figure 5).

Like the results of the PCA versus depth graph, the two biplots are similar, but with a few distinct differences. For example, in both biplots, P, S, Ca cluster together, indicating that these elements have a relationship together. However, S and Ca have a much closer relationship in the 2014 scan. Similarly, Mn, Fe, and Ti cluster together, but Mn and Fe have a closer relationship in the 2016 biplot. The two elements with the most change between the two scans are Si and Mg. In the 2016 biplot, Mg and Si are both in the bottom right corner of the PCA biplot. Then in the 2014 biplot, Mg is in the top right corner of the

22 biplot, and is close to Fe and Ti. However Si has remained in the bottom right corner, and is near none of the other elements.

Lateral Heterogeneity Between BSB09B and BSB14A

When comparing the average element concentration of BSB09B and BSB14A, in both cores Si has over five times the concentration of the next highest element, Al (Tables

2 and 3). Most of the major elements between BSB14A and BSB09B had similar concentrations, with an average difference of less than 15% (Table 4). The only major element to have an extremely large difference in average is P, which had a difference of

96% (Table 4). However, the discrepancy may be explained by P having one of the lowest element percentages in the two cores, with only 545 out of 2413 measurements of P in

BSB14A being above 0. With such a small concentration, any small change, such as comparing a tenth of a percent to a hundredth, will show up proportionally as a larger difference in average.

To get a sense of how similar BSB09B was to BSB14A, the stratigraphies of the two cores were analyzed in RStudio using the “cor” function (Table 5). The stipulation of the “cor” function is that datasets must be the same length, therefore, BSB14A was modified to have a resolution of 1 cm instead of 2 mm. Additionally, the last 0.25 m of

BSB09B were not included, as BSB14A only reaches 4.84 m in length. Therefore, 484 measurements of every element in BSB09B and BSB1 4A were compared. Even though

BSB09B and BSB14A were extracted less than 1 m from each other, the elemental data from each core are uncorrelated. The highest correlation was S at 0.3283, followed by P at

0.21. However, all other elements have less than ten percent correlation. Indeed, several elements, including Al, Na, U, Nb, and Zr, are negatively correlated.

The results for this correlation analysis is not unexpected, given that the two cores were being compared on a depth scale rather than an age scale. However, given that

BSB14A did not have samples sent in for radiocarbon dating, comparing the two cores on an age scale was not possible. To pinpoint the depth in two cores with the most correlation, the six most common elements in each core were correlated by meter, instead of comparing the entire core (Table 6). The most correlated meter is meter 0-1, followed by meter 1-2.

The meter with the least amount of correlation is meter 2-3, with correlation amounts rising slightly in meters 3-4 and 4-5, although not rising to the levels of the first two meters. When looking for causes for the lack of correlation between cores, it was observed that there was a large spike in Ca observed in both cores. In BSB14A, this peak can be seen at 3.476 m, and at 3.960 m in BSB09B. It is clear the two events are related, as are the trends in the first two meters of the core, which line up quite well (Figure 6). To better visualize any potential discrepancies in the data, two gaps in BSB14A was added, one between 1.666-

1.956 m and the other between 3.65-3.804 m. This caused the trends in both cores to visually line up.

Stratigraphy of Weathering Indices and Element Ratios

In BSB14A, the ratio of elements in the chemical index of alteration span a wide range, causing the CIA to be as high as 74% and as low as 4% (Figure 7). When interpreting the chemical index of alteration (CIA), values below 50% indicate fresh rock with no chemical weathering, values below 60% are indicative of low chemical weathering, and values between 60% and 80% indicate moderate chemical weathering (Nesbitt & Young,

1982; Roy et al., 2008). Over half of the CIA values for BSB14A are below 50%, and nearly all are 60%, indicating that there has been very little chemical weathering in Billy

Slope Bog. However, while the majority of the core fluctuates around 50%, there are two occasions where the CIA increases above 60%. The first is from .6 to 1 m, and then again at 3.55-3.6 m, and represent increased periods of chemical weathering. On the other hand, from 3.4-3.5 m, the CIA briefly plummets to 4%, the lowest value in the entire core, and no chemical weathering is occurring at this time.

To better understand the distribution of elements composing the CIA within

BSB14A, a A-CN-K ternary plot of the elements was created, based off of the ternary plots first used in Nesbitt and Young (1982). The ternary plot, shown in Figure 8, indicates that the elements in BSB14A all fall on a linear array controlled by Ca concentrations, which range from 7 to 95 wt% Ca throughout the entirety of the core. The samples with the lowest

CIA values are those highest in Ca, indicating a lack of chemical weathering in these sediments. The samples that have the most chemical weathering have the most Al and the least Ca. There is very little K in the core, as evidenced by the lack of CIA measurements towards the K2O3 end of the A-CN-K diagram.

Observing the element ratios, the trend of Ca/(Ti+Fe+Al) mirrors the trend of the

CIA. The two periods of the core where the CIA is above 60% are also when the ratio of

Ca/(Ti+Fe+Al) are lowest, indicating these periods are very wet. Additionally, spikes in the ratio of Ca/(Ti+Fe+Al) correspond to drops in the CIA, indicating dry periods where very little chemical weathering was occurring. On the other hand, the ratios of K/Al and

Al/Si are the opposites of one another. Both Al/Si and K/Al were very noisy, necessitating a smoothing curve being placed over both to better observe changes in trend. When Al/Si increases, indicating a rise in weathering intensity, K/Al decreases, indicating more kaolinite than illite. Kaolinite is formed from more intense weathering than illite, hence

25 why its increase indicates higher weathering intensity. Al/Si is higher than average from .6 to 2.3 m in the core, and afterward from 2.3 to 4.2 m remains lower than average. This indicates that from.6 to 2.3 m was a period of intense weathering, but then from 2.3 to 4.2 m weathering intensity was greatly reduced. Correspondingly, K/Al shows the same trend, with K/Al having below average values from .6 to 2.3 m, indicating increased levels of kaolinite relative to illite.

Grain Size Analysis

Throughout BSB14A, mean grain size of the core as a whole varies considerably

(Figure 9). From 0-66 cm, grain size fluctuates around 200 μm, but after 66 cm drops to 50

μm. After, BSB14A stays at 50 μm until 100 cm, after which grain size steadily increases.

Grain size reaches a peak at 175 cm, and afterward BSB14A goes into a period of great variability, with grain size ranging from 70 to 400 μm. The variable period lasts until 290 cm, after which grain size rapidly decreases to 76 cm, and then gradually increases until

397 cm. From 397 cm to the end of the core, grain size ranges around 130 μm.

Analyzing the distribution of grain size classes throughout the core, from 0-66 cm,

BSB14A is composed of mostly sand with very little variability. Then, from 66-119 cm the core is mostly composed of silt, with a smaller amount of sand. Past 119 cm, the rest of the core is again predominantly composed of sand, however, unlike the first 66 cm of the core, in this section, there is much more variability, including short periods where silt is the dominant grain size. The most notable are from 185-203 cm, from 289 to 300 cm, and a large silt spike at 474 cm. This last spike is unique because it also features the highest clay concentration, and the lowest sand concentration. There is very little clay in the core.

Ti Comparison to Pollen Based Climate Reconstructions

To assess the quality of Ti as a proxy for precipitation, the stratigraphy of Ti was compared to pollen-based reconstructions of climate in Range Creek Canyon, which go back 2,500 cal. yr BP (Hart., 2017). The pollen ratio that would most accurately indicate precipitation would be Pinus: Juniperus, as more Pinus requires a high amount of precipitation to grow, and thus indicates wetter climate conditions (Hart, 2017; Howard,

2015; Louderback & Rhode, 2009). Juniperus on the other hand, thrives in a dry climate with little precipitation. It was anticipated that the trend in Ti would closely follow the ratio of Pinus: Juniperus in Billy Slope Bog, with Ti increasing as the ratio of Pinus to Juniperus also increased.

However, the trend in Ti did not follow the Pinus: Juniperus ratio, and did not increase in concentration as Pinus levels increased. Instead, Ti concentrations most closely followed the ratio of Amaranthaceae + Artemisia: Conifers (AA:C). The AA:C ratio represents both moisture and forest development, with more conifer pollen indicating a wetter climate so that pine can be grown, while more Artemisia and Amaranthaceae indicate a drier climate where only shrubs are grown (Howard, 2015; Louderback & Rhode,

2009). The expectation was that as Ti increased, so would conifers, indicating an increase in moisture. However, the Ti stratigraphy of BSB14A follows the trend of Artemisia and

Amaranthaceae, indicating that as dry conditions increased, so did Ti influx into Billy

Slope Bog. Not only that, but Ti also had an inverse trend to total pollen influx (TPI) into

Billy Slope Bog. Total pollen influx is a proxy for the vegetation density. As TPI increases,

Ti concentration decreases, demonstrating that the strongest control on sediment influx into

Billy Slope Bog is vegetation. For example, at approximately 1100 cal. yr BP, there is a

27 peak in the concentration of Ti. Mirroring this peak, the ratio Artemisia and Amaranthaceae also reaches a peak. However, the ratio of Pinus to Juniperus decreases, and total pollen influx is very low during this time period.

To further demonstrate the significance of the relationship between the Artemisia and Amaranthaceae: conifer ratio and the elemental stratigraphy of Ti, a correlation matrix was created (Table 7 and Table 8). Ti had a weak negative correlation to TPI and the Pinus:

Juniperus ratio, indicating that as the ratio of Pinus increased, the wetter climate caused an increase in vegetation, which in turn led to a decrease in sediment influx. The opposite was true for the ratio of Artemisia and Amaranthaceae: conifer, as Ti had a weak positive correlation to this ratio. Therefore, as the amount of Artemisia and Amaranthaceae increased, so did Ti.

Element Ratio and Grain Size Comparison to Pollen Data

Starting at the beginning of the core, from -50 cal. yr BP to 1250 cal. yr BP, an increase in mean grain size coincides with an increased ratio of Artemisia and

Amaranthaceae to conifers. Additionally, chemical index of alteration (CIA) values fluctuate slightly below 50% during this time period, indicating fresh rock being weathered into the bog. CIA levels help to explain the higher ratio of K/Al, indicating more illite than kaolinite weathering into the bog, as well as a decrease in Al/Si, which represents a decrease in weathering intensity. From -50 cal. yr BP to 1250 cal. yr BP, there are also the lowest levels of recorded total pollen influx, and the ratio of Pinus to Juniperus is low.

Therefore, from modern day to 1300 years ago, there was a dry period in Billy Slope Bog characterized by shrubs and junipers. The dryness of the climate, in turn, caused less vegetation to be grown in the catchment, allowing an increase in grain size that was

28 weathered into the bog. The dry climate also accounts for the lack of chemical weathering during this period. As further evidence, mean grain size has a strong positive correlation to the AA:C ratio, while the CIA has a strong negative correlation to both the AA:C ratio and mean grain size.

Then, from 1250 cal. yr BP to 2500 cal. yr BP, the chemical index of alteration fluctuates around 60%. This is the longest period of time where the CIA is over 60% for the entire core, and includes the highest values for the CIA throughout the core. The increased levels of the CIA during this period coincide with the lowest levels of mean grain size, K/Al, and Ca/(Ti+Fe+Al) concentration. Additionally, during the same time period total pollen influx, and the ratio of Pinus to Juniperus are both at their highest. This indicates that from 1250 cal. yr BP to 2500 cal. yr BP there was a wet period with increased levels of chemical weathering, causing the formation of kaolinite. The increased levels of vegetation, indicated by the high TPI, are the cause of the decrease in mean grain size during this period. The relationship between vegetation and grain size can also be seen through the results of the correlation matrix in Table 6a. Mean grain size has a strong negative correlation of -.56 to P:J, and an even weaker negative correlation to TPI. On the other hand, the CIA has a strong correlation to TPI and PJ, at .66 and .53, respectively.

Tephra Identification

Based on the results of Balascio et al. (2015), Mn, Si, Ti, and Al were chosen as elements representative of rhyolitic tephra. Therefore, these were the elements examined in BSB14A and the Mazama tephra standards. Mn and Si had no visible spikes in the lower half of BSB14A to indicate the presence of a tephra (Figure 10). On the other hand, Ti showed more positive results, with its largest concentration spike in the last half of the core

29 occurring at 4.44 meters. Ti rose to 0.23 weight percent, when the average Ti concentration is 0.16 weight percent, making the event 70% higher than the average Ti concentration. In the same area, Al has an even larger spike at 4.39 m. The spike in Al is 6.0% in the control, while the average concentration of Al is 3.04%, making the event 51% higher than the average Al concentration. This compares to the Mazama ash as the average Al percentage was 6.00%, making the event comparable to the standard (Table 9). Unexpectedly, there was also an extreme rise in Y concentrations at 4.428 m. Y ppm were 56.1 ppm, while the average was 5.40%, making the spike ten times the normal average for Y. After the target area using Ti, Al, and Y was identified, a smear slide of the target area was created to find volcanic glass. The results were inconclusive, so five sediment samples were taken from the target area and five centimeter intervals around the target area. After processing to remove organic matter and splitting the samples by grain size into the 120-60 µm fraction and the >120 µm fraction. All samples were examined under a petrographic microscope to look for volcanic glass shards. However, none were found.

4A.

4B.

Figure 4: Principle component analysis versus depth for BSB14A. Figure 4A shows the data from the 2016 scan, while Figure 4B shows data from the 2014 scan. Figures were created using the R-package Vegan (Oksanen et al., 2013).

5A.

5B.

Figure 5: Principle component analysis biplot of BSB14A. Biplots based on principal component analyses of concentrations of major and trace elements in BSB14A from 2016 (5A) and 2014 (5B).

Figure 6: Lateral heterogeneity of BSB14A and BSB09B. The stratigraphy of Ca in wt % is shown for BSB09B (left) and BSB14A (right). Gaps have been inserted into the BSB14A to better line up events between the two cores, indicating that diagenesis may have altered the sediment record of BSB14A.

Figure 7: K/Al, Al/Si, Ca/(Ti+Fe+Al), and CIA stratigraphy for BBS14A.

Figure 8: A-CN-K diagram for BSB14A. The ternary diagram shows the distribution of elements which compose the chemical index of alteration.

Figure 9: Grain size fluctuation in BSB14A. Starting from the left is mean grain size for the whole core. Following that are the weight percent of clay, silt, and sand.

Figure 10: Stratigraphies of Al, Ti, Y, Mn, and Si in BSB14A. The above elements were hypothesized to be accurate indicators for the Mazama eruption. The grey area is where spikes in several of the stratigraphies indicate Mazama Ash is presumed to be located

Table 1

Correlation Analysis for Multiple Scans of BSB14A. Also included are t-values, p-values, and the mean value for each element.

Element Correlation T Df p-value Mean of x Mean of y S .54 25.33 2798.92 <2.2e-16 31762.73 16450.89 P .79 118.75 4505.58 <2.2e-16 13911.88 8114.66 Ca .91 21.77 4260.47 <2.2e-16 387143 266295.8 K .81 109.87 4074.66 <2.2e-16 162746.7 108419.6 Si .42 11.89 4261.98 <2.2e-16 356325.9 332147.1 Al .50 27.783 4223.32 <2.2e-16 38472.98 32963.99 Ti .90 75.41 4238.83 <2.2e-16 73491.55 46859.68 Mn .83 91.07 4224.84 <2.2e-16 8823.79 9212.07 Mg .33 270.64 4469.68 <2.2e-16 9945.25 5086.36 Fe .88 76.6421 3657.26 <2.2e-15 961158.7 499303.9

Table 2

Summary Statistics for BSB14A. Major elements are shown in weight percentage, trace elements are shown in parts per million.

Element Min Max Mean SD Al (wt.%) 0.53 6 3.04 0.32 Si (wt.%) 2.19 26.31 15.36 1.96 P (wt.%) 0 0.06 0.00 0.00 S (wt.%) 0.45 1.2 0.55 0.05 K (wt.%) 0.19 2.1 1.21 0.15 Ca (wt.%) 0.27 11.6 1.94 0.23 Ti (wt.%) 0.03 0.29 0.16 0.02 Fe (wt.%) 0.52 2.53 1.42 0.08 Na (wt.%) 0 0.24 0.01 0.05 Mg (wt.%) 0 0.31 0.06 0.05 Ni (ppm) 0 37.09 18.37 2.14 Cr (ppm) 20.68 94.67 64.62 4.92 Mn (ppm) 0.98 252.6 25.18 2.60 Co (ppm) 5.79 5.89 6.49 0.33 Cu (ppm) 0.00 60.33 5.14 1.86 Zn (ppm) 7.9118 859.9219 32.35 2.77 Ga (ppm) 4.62 9.45 7.27 0.21 Pb (ppm) 2.78 16 6.63 1.59 Rb (ppm) 25.48 98.27 75.50 2.76 Sr (ppm) 0 237.25 65.31 8.71 Y (ppm) 0 56.1 5.40 1.72 Zr (ppm) 37 946.57 156.35 21.53 Nb (ppm) 0.54 34.92 7.65 1.01 Mo (ppm) 1.35 48.38 8.39 1.62

Table 3

Summary Statistics for BSB09B. Major elements are shown in weight percentage, trace elements are shown in parts per million.

Element Min Max Mean SD Al (wt.%) 0.55 5.57 3.58 0.90 Si (wt.%) 2.44 30.27 16.36 4.96 P (wt.%) 0.05 0.13 0.08 0.01 S (wt.%) 0.05 5.04 0.61 0.55 K (wt.%) 0.09 2.98 1.42 0.51 Ca (wt.%) 0.51 9.06 2.19 1.13 Ti (wt.%) 0.02 0.38 0.18 0.06 Fe (wt.%) 0.43 4.29 1.65 0.53 Na (wt.%) 0.2 0.49 0.36 0.05 Mg (wt.%) 0 1.55 0.18 0.31 Ni (ppm) 3 310 21.60 18.74 Cr (ppm) 33 154 89.99 17.81 Mn (ppm) 103 442 194.52 51.18 Co (ppm) 2 31 5.64 2.68 Cu (ppm) 0 216 2.70 10.01 Zn (ppm) 0 241 28.56 19.92 Ga (ppm) 0 67 7.30 4.59 Pb (ppm) 7 30 9.17 2.19 Rb (ppm) 39 134 105.01 13.36 Sr (ppm) 65 263 155.57 23.05 Y (ppm) 0 52 29.66 5.89 Zr (ppm) 62 507 184.37 50.85 Nb (ppm) 3 91 8.45 7.74 Mo (ppm) 0 50 7.62 4.22

Table 4

Difference in Average Between BSB09B and BSB14A. Major elements are shown in weight percentage, trace elements are shown in parts per million.

Element % Diff. in AVG

Al (wt.%) 15.0746 Si (wt.%) 6.1416 P (wt.%) 96.3214 S (wt.%) 9.2786 K (wt.%) 14.7066

Ca (wt.%) 11.8087 Ti (wt.%) 10.7888 Fe (wt.%) 13.9646 Na (wt.%) 96.8633 Mg (wt.%) 68.4845

Ni (ppm) 14.9446 Cr (ppm) 28.1838 Mn (ppm) 87.0564 Co (ppm) 14.9144

Cu (ppm) 90.4507 Zn (ppm) 13.2691 Ga (ppm) 0.4484 Pb (ppm) 27.7375 Rb (ppm) 28.1006 Sr (ppm) 58.0205

Y (ppm) 81.7895 Zr (ppm) 15.2000 Nb (ppm) 9.4715 Mo (ppm) 10.1246

Table 5

Correlation Coefficients Between BSB14A and BSB09B. Also included are t-values, p-values, and the mean value for each element.

Element Correlation T Df p-value Mean of X Mean of Y S 0.33 1.81 514.72 0.07 5856.65 5381.38 P 0.21 151.58 941.46 2.20E-16 754.14 26.78 Ca 0.07 3.96 941.20 7.90E-05 21790.36 18880.47 K 0.05 7.14 827.89 2.07E-12 13874.15 11870.72 Si 0.05 3.26 937.18 0.00 160342.4 150238.2 Al -0.01 9.82 923.11 < 2.2e-16 35149.58 29833.61 Cu 0 -4.65 722.88 3.98E-06 2.71 5.22 U -0.1 -12.72 481.95 2.20E-16 11.98 14.65 Rb 0.09 39.86 758.62 2.20E-16 104.56 75.54 Co 0.09 -5.94 591.71 5.00E-09 5.69 6.48 Sr 0.09 60.18 939.19 2.20E-16 155.50 65.38 Nb -0.08 2.47 574.20 0.01 8.56 7.60 Zr -0.08 7.01 898.09 4.55E-12 181.95 155.87 Mg -0.06 7.80 505.70 3.68E-14 1619.08 557.11 Fe 0.06 8.78 851.14 2.20E-16 16625.01 13983.62 Pb 0.05 20.29 814.37 2.20E-16 9.16 6.63 Zn 0.04 -2.49 697.74 0.013 2.29 278 Ga 0.02 -0.23 482.26 0.82 7.22 7.27 Na -0.02 133.45 778.78 2.20E-01 1.04 1.02 Mo 0.02 -2.95 914.89 0.00 7.57 8,36 Y 0.02 73.02 834.93 2.20E-16 29.69 5.38

Table 6

Correlation Coefficients Between Individual Meters of BSB09B and BSB14A. Grey indicates most correlated, with subsequent lighter shades of grey indicating less correlation, and white representing the least amount of correlation

Element 0 to 1 1 to 2 2 to 3 3 to 4 4 to 5 S 0.0174 -0.0064 0.1644 0.0716 0.1033 P 0.2307 0.2298 -0.0366 -0.1134 -0.1195 Ca 0.4751 0.4294 -0.3121 -0.0793 0.355 K 0.119 0.2775 -0.0554 -0.1065 0.1334 Si -0.1584 0.1634 -0.024 -0.1725 0.1147 Al 0.2961 0.1106 -0.0708 -0.1393 -0.0066

Table 7

Correlation Matrix for Pollen and Detrital Element Comparison (Figure 11)

Mean Ca/ TPI PJ AAC Ti CIA K/Al Al/Si Grain (Ti+Fe+Al) TPI 1.00 0.48 -0.58 -0.02 -0.28 0.66 -0.50 0.11 0.26 PJ 0.48 1.00 -0.44 -0.14 -0.56 0.53 -0.36 0.41 -.027 AAC -0.58 -0.44 1.00 0.14 0.39 -0.42 0.08 -0.27 -0.23 Ti -0.02 -0.14 0.14 1.00 -0.14 0.10 0.16 -0.02 0.31 Mean -0.28 -0.56 0.39 -0.14 1.00 -0.64 0.24 -0.52 0.26 Grain CIA 0.66 0.53 -0.42 0.10 -0.64 1.00 -0.63 0.55 -0.09 K/Al -0.50 -0.36 0.08 0.16 0.24 -0.63 1.00 -0.22 0.23 Al/Si 0.11 0.41 -0.27 -0.02 -0.52 0.55 -0.22 1.00 -0.60 Ca/ (Ti+Fe 0.26 -0.27 -0.23 0.31 0.26 -.09 0.23 -0.60 1.00 +Al)

Table 8

P-Values for Pollen and Detrital Elements Comparison (Figure 11)

Mean Ca/ TPI PJ AAC Ti CIA K/Al Al/Si Grain (Ti+Fe+Al) TPI .03 .0` .95 .22 .00 .02 .65 .26 PJ .03 .04 .55 .01 .01 .11 .06 .23 AAC .01 .04 .54 .08 .06 .73 .23 .32 Ti .95 .55 .54 .54 .68 .50 .94 .17 Mean .22 .01 .08 .54 .00 .28 .02 .26 CIA .00 .01 .06 .68 .00 .00 .01 .70 K/Al .02 .11 .73 .50 .28 .00 .35 .32 Al/Si .65 .06 .23 .94 .02 .01 .35 .00 Ca/ (Ti+Fe+ .26 .23 .32 .17 .26 .70 .32 .00 Al)

Table 9

Mazama Ash Elemental Concentrations. Major and trace element concentrations for a Mazama Ash tephra sample on loan from the University of Utah volcanology lab

Element Value Al (wt.%) 6.08 Si (wt.%) 29.72 S (wt.%) 0.54 K (wt.%) 2.41 Ca (wt.%) 0.65 Fe (wt.%) 1.65 Ti (wt.%) 0.26 Y (ppm) 15.95 Co (ppm) 9.05 Ba (ppm) 909.22 V (ppm) 47.15 Cr (ppm) 59.34 Mn (ppm) 638.39 Ni (ppm) 62.4 Cu (ppm) 140.48 Zn (ppm) 249.32

DISCUSSION

The purpose of this study was to reconstruct the paleoenvironment of Range Creek

Canyon, UT by performing x-ray fluorescence (XRF) on two bog cores from the canyon.

The first step in this reconstruction was to determine the reliability of measurements taken by a portable XRF spectrometer, which was done by statistically comparing the elemental concentrations of two helium scans of BSB14A. Then, using element ratios and a grain size analysis as proxies for precipitation-induced erosion, the XRF results were used to describe how allochthonous input and moisture availability in Billy Slope Bog have changed over the last 9,000 years. Finally, to establish a chronology of events in Range

Creek Canyon, there was an effort to isolate volcanic events by comparing Al, Ti, Mn, and

Si spikes from BSB14A to the same elements in tephra control samples.

BSB14A Correlation

The result of the correlation analysis on the two helium scans of BSB14A showed that there was a positive correlation with varied levels of correlation between each element

(Table 1). The majority of elements had strong positive correlations, indicating that the scan was repeatable and verifying the accuracy of the Bruker spectrometer. The weak positive correlation for Si and Mg was unexpected, as was the low t-tests results, which proved that the difference between each of the elements was significant. However, the differences are most likely from alterations in scanning methodology. For instance, while

45 the same spectrometer scanned BSB14A both times, the emissions tube within the spectrometer was replaced in Fall 2015, when the two scans occurred. Therefore, as the inner workings to the spectrometer were altered, this difference would most likely affect results. Human error may also be a factor in the varying correlation values between the elements. While the starting point for scanning on each meter of core was marked, through repeated handling, the edges of the cores began to crumble, therefore, the stratigraphies of both cores.

The results of the principle component analysis further proves that the Bruker XRF is repeatable, as evidenced by the similarities in trend. The major difference is the magnitude in the spikes at 3.6, 4, and 4.4 m. The most important aspect of a PCA versus depth figure is the degree to which the PCA diverts from zero. This indicates more collective variance in all of the elements. In other words, a significant event is occurring at that location in the core. In both core scans, the same spikes appear. However, in the 2016 scan, the spikes rise much farther than the two trends are similar. The most noticeable similarities are large spikes in PCA in both cores at 3.5 m, 4 m, and 4.4 m. The overall trend in both cores is also similar. In the 2016 scan, until 2.5 m the PCA versus depth graph is underneath 0, or the average. After 2.4 m, the trend stays mostly above zero. The graph from 2014 shows the reverse trend. Until 2.4 m the graph is over zero, but after 2.4 m the trend drops. However, the changes and spikes in the 2016 scan are more pronounced than in 2014, indicating more of a change.

Lateral Heterogeneity of BSB14A and BSB09B

Comparing BSB09B and BSB14A was crucial to future observations made regarding Billy Slope Bog, as the elements from both cores were compared to the pollen

46 data taken from BSB09B. Additionally, BSB09B was the only core to have an age model created, therefore, knowing its’ relation to BSB14A was important in order to better have an idea of this core’s age-depth relationship. Most elements between BSB09B and

BSB14A had an average difference of 10% to 15% (Table 4). The difference in correlation can be attributed to several potential causes (Table 5). A likely cause behind the difference in average is that the two cores were each scanned using a different method. BSB09B was cut into centimeter long sections while BSB14A was cut into meter long sections. BSB14A was scanned at 2mm resolution with the ITRAX core scanner. BSB09B samples (1 cm resolution) were all manually scanned by having the tracer rest over the center of the sample, which was placed in a petri dish. The difference in scanning technique between the cores may have affected the results, causing some of the discrepancy in correlation.

What is more interesting is the results of the correlation analysis between the two cores. The strongest correlation between cores occurs in the first meter, while the weakest occurs in the third (Table 6). The strong correlation at the beginnings of both cores indicate that they experienced similar events at the same time, and consequently, at some period in time one of the cores was altered. A likely cause of the alteration could be compaction during the extraction of BSB14A from Billy Slope Bog, resulting in the decrease in correlation. Unlike BSB09B, which was extracted using a Livingston corer, BSB14A was extracted using a vibracorer. While vibracorers make cores easier to extract by vibrating the surrounding material, these vibrations also cause compaction in the core (Smith, 1998).

The evidence points to the compaction occurring in the third meter of the core, as correlation between most elements becomes stronger in the fourth and fifth meters, although never to the level of the first two meters. As Ca values in BSB14A and BSB09B

47 only line up when gaps are inserted into BSB14A, it can be assumed that compaction only occurred in the BSB14A (Figure 6). The largest spike in Ca can be seen in BSB9B at 3.960 m, and also in BSB14A further up in the core at 3.476 m. However with the inserted gaps into BSB14A the two spikes line up, as well as the rest of the trends in Ca. Therefore, differential compaction could have disrupted the soil record in the third meter of BSB14A, causing the difference in correlation between BSB14A and BSB09B. The gaps inserted into BSB14A’s datasheet so that it would line up with BSB09B are included in all inter- core comparisons, in order to standardize the ages of both cores.

Ti as a Proxy for Precipitation

The second objective of this study was to describe how allochthonous input and moisture availability in Billy Slope Bog have changed over the last ~9,000 years using Ti as proxy for precipitation-induced erosion. The fact that the trend Ti concentrations did not reflect Pinus: Juniperus concentrations indicates that at least in Range Creek Canyon, Ti is not representative of precipitation. This is further confirmed by the weak correlation of

Ti to TPI and PJ. The expected outcome was that as the Juniperus ratio, which indicates as a wet period in Range Creek Canyon, increases, Ti concentrations would also increase.

This would have confirmed that Ti concentrations are related to moisture. However, when

Juniperus concentrations were at their highest, Ti concentrations were at their lowest, indicating that when the canyon was wetter, there was less sediment influx into Billy Slope

Bog. The decrease in sediment influx when the canyon was in a period of high moisture and precipitation is further confirmed by the negative correlation Ti and had towards the conifer portion of the AA:C ratio (Table 7). Therefore, Ti cannot provide additional information on precipitation fluctuation during the time the Fremont people lived.

This begs the question then, why Ti did not work as a proxy for precipitation in

Billy Slope Bog, but did in Metcalfe et al. (2010). One possible reason could be the degree of stratification of sediments within the cores. In Metcalfe et al. (2010), the lake core from

Laguna del Mar was clearly stratified, and spikes in Ti coincided with pink clay bands that were distinctly different from the sand strata in the core. However, in the Billy Slope Bog cores, while there are different layers, they are not clearly stratified. Additionally, when observing the grain size data, the majority of the core is less than 10% clay. Therefore, the absence of large amounts of clay in absence in Billy Slope Bog makes Ti a poor proxy for precipitation in this setting.

Vegetation and Sediment Influx

Instead of precipitation, the amount of vegetation surrounding the catchment has the strongest influence on sediment influx into Billy Slope Bog. The relationship between vegetation and sediment influx is reflected by the negative correlation between mean grain size and total pollen influx (Table 7). A visual representation of this relationship can be observed at 1250 cal. yr BP, where a sharp decrease in TPI coincides corresponds to a rapid increase in grain size. The different in trend between the two proxies indicates that as the level of vegetation cover around Billy Slope Bog increased, the level of sediment sharply decreases. Mean grain size also decreases with increases in conifer and Pinus ratio, indicating that the type of vegetation as well as the amount of cover play a role in sediment influx into Billy Slope Bog (Figure 11). Conifer and Pinus both represent dense forests suited for a moist climate, with a deep root system that would lead to increased soil stabilization (Koinig et al., 2003). Modern forests communities in Billy Slope Bog are composed of Douglas fir, pinyon pine, and juniper on the canyon walls, while box elder

49 and narrow leaf cottonwood populate the gallery forest around Range Creek (Hart, 2017).

This reflects what the composition of a paleoforest surrounding Billy Slope Bog would be like.

Stratigraphy of Weathering Indices and Element Ratios

The low values of the chemical index of alteration indicates that very little chemical weathering is occurring within Billy Slope Bog. Over half of the values for the CIA were below 50%, indicating that they were fresh rock, and the large majority of the values were below 60%, indicating only minor chemical weathering was occurring. Therefore, it can be inferred that the main process for sediment influx into the bog is physical weathering of mostly fresh rock. This is further evidenced by the low values of K/Al, indicating that more illite, a product of physical weathering, is coming into the bog over kaolinite. The low levels of chemical weathering in this catchment is most likely the result of the arid climate it is located in. Therefore, given the lack of moisture it is unsurprising that physical weathering is the dominant method of erosion.

What is more intriguing about these results are the few times where there is significant chemical weathering occurring in Billy Slope Bog. For the majority of

BSB14A, the CIA ratio fluctuates around 50%, indicating that the majority of run off into the bog is fresh rock. However, the two areas of the core where the CIA rises past 60%, at

0.60-1.00 m, 3.55-3.60 m, and 4.27 and 4.36 m, tell a much different story. The rise in the

CIA at 3.55-3.60 and from 4.27 to 4.36 are both very brief. However, both times they are accompanied by a rise in Al/Si, indicating an increase in weathering intensity, as well as a decrease in K/Al, indicating the formation of more Kaolinite. In advance of the other spike in the CIA from 0.60-1.00 m, K/Al gradually decreases from 3.00-1.00 m, while Al/Si

50 gradually increases. Therefore, at these three moments a major environmental shift is happening causing an increase in chemical weathering, and weathering intensity as a whole.

Focusing in on the period from 0.60-1.00 m in the core, which translates on the age- depth model to 1250-2500 cal. yr BP, the relationship between the element ratios tells an interesting story. As previously stated, changes in the rate of chemical weathering are derived from changes in either temperature or precipitation (Nesbitt & Young, 1986). The rise in total pollen influx and the ratio of Pinus to Juniperus from 0.60-1.00 m indicates that the cause of these increases in the CIA are the result of the latter. Additionally, the ratio of Ca/(Ti+Fe+Al), which increases as dryness of the surrounding catchment also increases, is at its lowest levels throughout BSB14A during this time. This further indicates that the period between 0.60-1.00 m was the wettest period recorded in BSB14A. Then, from 1250 cal. yr BP to 500 cal. yr BP, Ca/(Ti+Fe+Al) increases back to the average level it maintained for the majority of the core. This increase in the ratio of Ca/(Ti+Fe+Al) signifies a return to drier conditions in the catchment. Supporting this theory, the ratio of

K/Al is higher than average, which indicates that more illite in relation to kaolinite is being produced as a result of a decrease in physical weathering in relation to precipitation- induced chemical weathering. Similarly, the ratio of Al/Si falls during this time period, indicating less intense weathering conditions were occurring.

Finally, an unsolved mystery in this research is the event that occurs between 3.50 and 3.60 m, where the CIA drops to 4%, and the ratio of Ca/(Ti+Fe+Al) is three times larger than at any other area of BSB14A. Such a drastic change was hypothesized to be from a flood event, however, it would be expected that a flood event would be accompanied

51 by an increase in mean grain size. Mean grain size does not have a drastic spike between

3.50 and 3.60 m, therefore the large influx of Ca during this time in the core is puzzling.

Magnetic susceptibility was not calculated at this depth, therefore, the presence of a flood cannot be ruled out entirely. Future research will perform limited magnetic susceptibility on the area of the core showing the monumental increase in Ca.

Precipitation During Fremont Occupation of Range Creek Canyon

Based on the aforementioned proxy data, a much clearer picture of Range Creek

Canyon’s climate during Fremont occupation can be created. The earliest recorded period of Fremont occupation at 1450 cal. yr BP falls under the tail end of the high period of chemical weathering and total pollen influx. Therefore, the earliest Fremont moved into

Range Creek in a wet period with higher than average precipitation. This period of increased precipitation lasts until 1350 cal. yr BP, after which a dramatic drop of TPI and

CIA occurs, where TPI drops to almost zero. This indicates a dry environment with low precipitation, which continues into the period of peak Fremont occupation in Range Creek,

950-750 cal. yr BP. However, at 850 cal. yr BP, TPI, Pinus, and the CIA all increase slightly until 750 cal. yr BP, indicating a slightly wetter period, although not nearly as wet as 1450 cal. yr BP. Total pollen influx and the CIA gradually decrease after 750 cal. yr BP, indicating a continuous decrease in precipitation during this period. However, the ratio of

Pinus to Juniperus remains stable.

XRF as a Means to Identify Cryptotephra

Due to the importance of establishing a chronology in Range Creek Canyon, the last objective of this study was to isolate volcanic events in BSB14A by comparing Al, Ti,

Mn, and Si spikes in the core the same elements in tephra control samples. When comparing the tephra spikes of Al, Y, and Ti within BSB14A to the age model created by

Hart (2017), the elements are ideally placed to be considered representative of Mazama

Ash. The Mazama eruption is dated at 7,627 ± 150 cal. yr BP (Zdanowicz et al., 1999).

The Ti spike in BSB14A is occurs at 7,896 cal. yr BP, the Al spike at 7,760 cal. yr BP and the Y spike at 7,948 cal. yr BP (Figure 10). Given some allowance for errors in the age model, these three elements are well within the ideal range and timeframe to be considered representative of Mazama ash. The spike in Y in particular is strong evidence for the presence of Mazama ash at this location within the core. Y does not form naturally, and therefore, the fact that Y at 7,948 cal. yr BP is fifty times higher than any other area of the core is significant. Mn and Si, on the other hand, while recommended for tephra identification in Balascio et al., (2015) were not effective. A large contributing factor is that Billy Slope Bog is in an intensely silica rich area, making Si not an ideal element for identifying events or features.

Unfortunately, when samples were examined under a petrographic microscope, no volcanic glass was found. Therefore, the target area cannot be absolutely confirmed as the site of the Mazama eruption. However, there are a number of reasons why glass shards might not have been found. The eruption occurred 1088 km from Range Creek Canyon, therefore, if there was glass it would be in an extremely small size fraction, potentially so fine that it degraded to its mineralogical components. Additionally, the frequency of glass would decrease as distance from the eruption site increased. The most likely explanation is that the volcanic glass could have degraded into its clay parts, making it impossible to distinguish from the surrounding soil. Andosols, or soils formed from volcanic ejecta, are

53 characterized by their high organic carbon content, Al-humus complexes, and high water retention capacity (Colombo et al., 2014). These qualities can be extensively modified by pedogenesis, especially as they undergo mixing with parent material, or the underlying bedrock from which soil is formed. While Billy Slope Bog is set in mollisol, not andosol, this soil type is also characterized by high organic carbon and high water retention

(Boettinger, Howell, Moore, Hartemink, & Kienast-Brown, 2010). Additionally, of the components in tephra, including lapilli and ash, volcanic glass is the most vulnerable to weathering, due to the glass being thermodynamically unstable (Takahashi & Shoji, 2002).

Therefore, it is not unreasonable to propose that the large spikes in Al, Ti, and especially Y, signify the presence of Mazama Ash in Billy Slope Bog. The lack of volcanic glass shards accompanying the tephra can be explained by degradation through weathering.

In this case, the increase in these elements would be the only physical signature of the tephra’s presence. Again, the presence of Y alone is enough to confirm the tephra’s location, which also validates the age-depth model of Billy Slope Bog. Therefore, while future research will continue to look for volcanic glass shards, it will only be to confirm this method of tephra identification, so that future researchers may confidently use portable

XRF for easier cryptotephra identification.

Figure 11: Comparison of weathering indices and element ratios to pollen based climate reconstructions. The stratigraphy of mean grain size, the chemical index of alteration, Ca/(Ti+Fe+Al), K/Al, Al/Si, and Ti in weight percent over the last 2500 years. Also shown are several pollen ratios for BSB09B, the total pollen influx, the ratio of Pinus:Junpierus and the ratio of Amaranthaceae + Artemisia: Conifers. This period is of interest as it encompasses when the Fremont lived in Range Creek Canyon.

CONCLUSION

The overall purpose of this study was to reconstruct the paleoenvironment of Billy

Slope Bog, UT, using x-ray fluorescence (XRF) on sediment cores from a wetland spring.

The first step of the study was to compare the data taken from two scans of BSB14A, in order to determine if the data taken with a portable x-ray fluorescence spectrometer was accurate and repeatable. The null hypothesis for the correlation was that the two scans would have a strong positive relationship. The two cores overall did have a positive relationship, however, the individual elements within each core had a wide range in correlation, potentially due to differences in scanning methodology. However, the similarity in the relationship between the elements as shown by the principle component analysis proves that the XRF results actually were accurate.

The second objective of using XRF to reconstruct the paleoenvironment of Billy

Slope Bog was to use a variety of proxies to describe how moisture availability in Billy

Slope Bog has fluctuated. The first proxy tested was Ti, which was hypothesized to be representative of precipitation induced erosion. Unfortunately, chemostratigraphy of Ti did not positively correlate to the ratio of Pinus: Juniperus, and did not follow the trend of conifer ratios, both proxies that represent moisture and precipitation. Therefore, Ti cannot provide any additional information on precipitation fluctuations during the time period in which the Fremont lived in Range Creek. Instead, the dominant control on sediment influx into Billy Slope Bog was changes in catchment vegetation. This was proven by comparing

56 grain size to the amount of pollen influx into Billy Slope Bog. As the amount of total pollen influx increased, mean grain size decreased. Conversely, as the ratio of Amaranthaceae +

Artemisa increased, so did grain size, indicating that when the catchment vegetation was less developed, more sediment would run into Billy Slope Bog.

On the other hand, element ratios and the chemical index of alteration proved to be much better proxies for precipitation in Range Creek Canyon. The chemical index of alteration, the ratio of K/Al, and the ratio of Ca/(Ti+Al+Fe) indicated that Range Creek has been mostly arid for the past 8,000 years. However, a period between 2500 and 1250 cal. yr BP was confirmed by increases in chemical weathering to be much wetter than average.

The tail end of this period, at 1350 cal. yr BP, was when the first Fremont settled into Range

Creek Canyon. However, this the wet period in Range Creek ended at 1250 cal. yr BP, and afterward the canyon gradually became even drier, as indicated by the decrease in CIA values. There was a brief interlude at 750 cal. yr BP where moisture levels increased slightly. However overall, the majority of the Fremont occupation of Range Creek Canyon was characterized by drought that only worsened with time. This may be the cause behind their inevitable departure from Range Creek Canyon.

The last objective was to establish a chronology of events in Range Creek Canyon by identifying cryptotephra using XRF data. While Mn and Si were not ideal for tephra identification in the Si-rich environment of Range Creek, Al, Y, and Ti all had large spikes at the appropriate core depth to qualify as potentially being due to Mazama ash. The large rise of Y in particular, is very persuasive evidence, as this element does not occur naturally in large quantities, but was fifty times higher in this location than anywhere else in the core.

Based on the extreme rise in Y, the presence of Mazama ash in Billy Slope Bog is

57 confirmed. However, as no volcanic glass shards were found, future research will search more thoroughly in BSB14A to confirm this method of cryptotephra identification.

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