Experimental Investigation of Phytoliths and Combustion Features and Their Relevance for The

Experimental investigation of phytoliths and combustion features and their relevance for the

'Cooking Hypothesis' from East Turkana, Kenya

Georgia Oppenheim

Submitted in Partial Fulfillment of the Prerequisite for Honors in Anthropology under the advisement of Adam Van Arsdale

May 2020

Ó 2020 Georgia Oppenheim

This thesis is dedicated to the Wellesley Red Hot Class of 2020, although we might not finish our

final semester at Wellesley together, I will carry the memories and lessons of our four years

together for the rest of my life

Acknowledgements This thesis would not have been possible without the guidance and support of these extraordinary people.

To my advisor, Professor Adam Van Arsdale, and my thesis committee, Professor Minor and Dean Nunez, for their constant support and encouragement of me, my work, and my aspirations.

To Dr. Sarah Hlubik, Dr. Rahab Kinyanjui, and Dr. David Braun, for putting their trust in me as a scientist and providing wisdom, guidance, and opportunities.

To the National Museums of Kenya and Koobi Fora Field School, for allowing me the opportunity to conduct research in one of the most special places in the world and providing opportunities to work with some of the best scientists in paleoanthropology.

To Dr. Cassandra Pattanayak, Dr. Leah Okumura, Dr. Julie Roden, Dr. Louise Darling, and Dr. Nolan Flynn for providing access to materials and showing me the strength and support of the Wellesley academic community.

To the Wellesley College Science Center and Knapp Fellowship for funding my field and laboratory research in Kenya and at Wellesley.

To Tamara, for being an excellent and enthusiastic student who was always ready to set more fires.

To Sydney and Oumeyma, for having my back during long days in the field and at the NMK.

To Caitlin, for being an expert GIS mapper, copyeditor, and overall amazing friend.

To Audrey Choi and Izzy Starr, for creating space for future biological anthropology students at Wellesley.

To my mom, Mitzi, Dave, and the entire Satran and Harackiewicz family for supporting me as I follow my passion.

And to Louisa, for being my support while I completed my thesis during shelter in place and being an amazing copyeditor, twin sister, and friend.

Table of Contents

Introduction 1

Chapter 1: Why Study Hominin Fire Use? 4

Chapter 2: Phytoliths as Proxies 23

Chapter 3: Methods 30

Chapter 4: Results 38

Chapter 5: Discussion 47

Conclusion 61

References 62

Appendix I: Phytolith Dataset 71

Appendix II: Fire Temperatures 78

Introduction

One major question in Paleoanthropology, the study of human origins, is how and when hominins began to use fire. The use of fire likely had major implications for the evolution of our human lineage, as it changed the ecological and nutritional evolutionary landscape of hominins.

Morphological analyses of hominin fossils suggest that the most likely candidate for these proposed changes is Homo erectus due to their increased brain size and reduced dentition that resulted from the higher nutritional quality and less mechanical demands of cooked food

(Wrangham & Carmody, 2010). But there is a need for direct evidence of hominin fire use in order to support this theoretical explanation. This evidence can be found in younger archaeological contexts, but finding well preserved evidence of ephemeral fire for this behavioral transition in the Early Pleistocene (2-1.8 mya), during the emergence of H.erectus, is difficult due to the open nature of these older archaeological sites.

Most accepted archaeological evidence for hominin fire use comes from cave contexts, like the Middle Paleolithic site of Abric Romani in Spain, that are dated to much later than these morphological changes are hypothesized to take place (Vallverdu et al., 2005). Many Early

Pleistocene sites are found in open air contexts, which, unlike cave sites, are subject to many post-depositional processes, like bioturbation by organisms, that can affect the preservation of fire evidence. The open nature of these sites also leads to potential confusion as to how these fires may have started, as it is difficult to distinguish whether fire signals at these sites are the result of wildfires or hominin-controlled fire. In order to understand the true origins of combustion at possible open-air fire sites, many proxies of evidence must be investigated. Proxy evidence can come in the form of broad spatial analysis, such as GIS mapping of artifacts to look for artifact associations, and microscopic and chemical analysis, such as micromorphology and

Fourier transform infrared spectroscopy (FTIR), to provide evidence of burning. Site FxJj20 AB, the oldest potential locality of hominin fire use (1.6 million years ago) contains evidence of early fire through chemically analyzed burnt bone and sediment spatially associated with evidence for butchery and toolmaking by our hominin ancestors (Hlubik et al., 2017). This site is compelling as it matches up with the time period of emergence of Homo erectus, potentially providing direct evidence of the proposed behavioral transition of hominin fire use. But, due to the great significance and likelihood of post-depositional processing affecting this older, open air site more proxies of evidence are needed to substantiate the claims from the site.

One proxy that can be used to study archaeological fire contexts is phytolith analysis.

Phytoliths are silicate plant particles that are useful for studying archaeological fire evidence because they are resistant to destruction, easily identifiable, and discolor when burned at high temperatures (~700 °C) (Parr, 2006). Developing inferences of behavior from phytolith data requires extensive experimentation to provide expectations regarding the frequency and distribution of phytoliths in high intensity localized fires. These experiments provide a framework of phytolith and fire dynamics that can be used to study the phytolith composition of archaeological fire contexts. This thesis seeks to examine the phytolith composition of experimental controlled fires set in a silty floodplain environment, similar to the environment at the site of FxJj20 AB. These experiments will provide evidence for the spatial distribution of discolored phytoliths within a controlled fire, which can be used as a comparison to the spatial distribution of phytoliths at a possible ancient fire site. These data can then be used as another proxy to supplement the large body of evidence of hominin-controlled fire at site FxJj20 AB.

In chapter one, I will elaborate upon the importance of hominin fire use, the variety of methods used for understanding fire in the archaeological record, and the debates that arise

during these investigations. The second chapter focuses on why phytoliths are a useful proxy for studying past environments and archaeological contexts and the need for strong comparative phytolith data. These sections provide the necessary information to understand the anthropological significance of the experimental study. Chapter three describes the methodological approach of the experimental fires and phytolith analysis and chapter four shows the result of these analyses. Finally, I will discuss the importance of these results to studying fire in early archaeological contexts and tie in existing literature into these examinations in chapter five.

Chapter 1: Why Study Hominin Fire Use?

1.1 Introduction

Fire has played a significant role in the behavioral and morphological evolution of humans. It provides energetic benefits by increasing the nutritional value and reducing toxicity of food, and providing protection against predators. It is especially important to understand how hominins started to use fire, as it likely had significant evolutionary impacts. Researchers can start to understand how and when hominins started using fire through analysis of the fossil and archaeological record. Analysis of morphological fossil evidence suggests that Homo erectus is a likely candidate for the biological impacts of cooking. But, finding well preserved archaeological evidence of ephemeral fire for this behavioral transition in the Early Pleistocene, during the emergence of H.erectus, can prove rather difficult. The FxJj 20 AB site complex provides compelling evidence of hominin fire use during this transition, but there is a need for more proxies of evidence to solidify its claim.

1.2 Cooking and Biology

The Cooking Hypothesis proposes that morphological changes in early Homo erectus indicate a dietary shift most parsimoniously explained by higher dietary returns from consuming cooked foods. This argument is formed by connecting modern laboratory research on human biology and cooking with evidence from the hominin fossil record. It has been shown that animal anatomy can adapt quickly to changes in diet (Gould, 2002). Additionally, it is known that hominins have fast adaptation rates. For example, the ability to digest lactose into adulthood

(lactase persistence) in human populations that have a history of dairy use has evolved at least two times in the last seven thousand years (Bersaglieri et al., 2004; Tishkoff et al., 2007). This

time scale is very rapid, especially when looking at time scales of hundred thousand to millions of years, like the Pleistocene record. This shows that human behavior can have a quick biological impact on humans. Using this same logic, we can infer origins of hominin cooking through the presence of biological traits that are consistent with the consumption of cooked food (Wrangham

& Carmody, 2010).

Cooking is an energetically beneficial process. Research studies on mice have shown that cooking of both meat and tubers increases the energy gained from the food more than nonthermal processing like pounding. The critical positive effects of cooking such as the gelatinization of starch, killing of foodborne pathogens, and denaturing of proteins cannot be achieved by non-thermal processing (Carmody et al., 2011). Cooking also makes food easier to chew and digest. Cooked lipids are more easily digested than raw lipids because they offer a greater surface area for digestion (Wrangham & Caramody, 2010). Studies of modern raw- foodists (i.e. people who only eat a raw diet with minimal processing) have shown that modern

Homo sapiens are biologically adapted to the consumption of cooked food. Even with the benefits of living in a modern society, like less required exercise and a lower risk of disease, average raw-foodists have low BMI and experience chronic energy shortage. Biological women also have difficulty with reproductive performance with fifty percent of women on raw diets unable to reproduce due to incompetent or absent ovulation (Koebnick et al., 1999; Carmody &

Wrangham, 2009). This shows that cooking is energetically beneficial and has an impact on human biology.

Wrangham proposes that the most likely candidate for these biological impacts would be

Homo erectus during the transition from Australopithecines to early Homo due to changes in

H.erectus’ morphology that relate to the energetic benefits from cooking. The small molars and

relatively small gut volume in modern humans are morphological characteristics that prevent humans from utilizing raw food efficiently. H.erectus exhibits facial shortening, which is indicative of reduced masticatory strain, and reduced dentition, which implies a less energetically strenuous diet than in earlier hominins (Carmody & Wrangham, 2009; Wood & Aiello, 1998;

Bramble & Liberman, 2004). Also, the increased brain size of H.erectus supports the concept that H.erectus had a higher energy budget, since the brain is a metabolically expensive tissue

(Aiello and Wheeler, 1995). It is likely that this change resulted from an improved diet like cooking. Also, the gut size of H.erectus conforms to this expected trend. H. erecuts has a barrel shaped thoracic cage that is distinct from earlier hominins and is more similar to later those of

Homo. This leads to reconstructions of the gut of H.erectus being smaller than its predecessors.

This reduced gut volume holds up against comparisons to Australopiths, with H.erectus gut volume to body size proportion being smaller than that of Austrlopiths. But, despite the reduction in digestive anatomy, H. erectus shows signs of increased energy use including large body size, adaptations for long-distance running, and possibly reduced interbirth intervals (Wrangham and

Carmody, 2010; Aiello & Wheeler 1995; Bramble & Lieberman 2004; Aiello & Key 2002). All of these distinct morphological characteristics that display increased energy usage make

H.erectus a likely candidate for early hominin cooking.

In addition to impacting the evolution of hominin morphology, fire and cooking have other advantages and evolutionary impacts. The control of fire by early Homo aided the survival of hominins during the transition to obligate terrestriality because fire provided protection on the ground that height in the trees once provided. Homo erectus, one of the first obligate bipeds, had a low arboreal capability and was likely ground sleeping at night and, therefore, needed protection from predators. One way H.erectus could have protected themselves from these

predators was through the use of controlled fire. This behavior is the principal method used by modern humans today who sleep in the kinds of habitats similarly occupied by H.erectus, which suggests that this hypothesis is plausible. Also, the loss of arboreal adaptations shows that food in arboreal locations became less important than cooked terrestrial food (Wrangham & Carmody,

2010; Wrangham, 2017).

The novel morphology of Homo erectus is consistent with the origins of human cooking.

The origins of hominin cooking practices can be inferred through the presence of biological traits that are consistent with the consumption of cooked food. The presence of reduced dentition and smaller gut indicates a less energetically strenuous diet than in earlier hominins. Cooking gelatinizes starch and and denatures proteins, which softens food, making it easier to chew and digest. This would lead to less adaptive pressure towards larger teeth and gut that are used for the consumption and processing of tougher, more fibrous foods. Also, the larger brain and body size of H.erectus indicates a shift towards higher energy foods. Cooking has been shown to increase the energetic benefits of food, which could explain the higher energy food source. The morphological evidence coupled with the biological significance of cooking indicate that

H.erectus likely used fire to cook food (Wrangham & Carmody, 2010).

If there was another hominin species that showed more convincing morphological evidence of cooking, then an argument could be made that cooking did not greatly impact the development of H.erectus’ morphology. Cooking likely caused significant morphological changes based on its energetic and nutritional benefits. If there was a hominin species later in time that exhibited a morphology that showed a more significant change that could be explained by the impacts of cooking, then the timeline of early fire use would be shifted later to correspond with that species. One plausible candidate for this argument could be H. heidelbergensis. But, the

transition from H.erectus to H.heidelbergensis does not have any major changes in gastrointestinal anatomy or dentition. The anatomical changes are too slight a response to a dietary shift as significant as cooking was likely to have been. This shows that the drastically different morphology of H.erectus from its predecessors was caused by shifts in diet and behavior in accordance with the Cooking Hypothesis (Wrangham & Carmody, 2010).

Other explanations for these morphological changes have been proposed, with one of the leading candidates being increased animal source foods, especially marrow and high fat meat.

This argument can be problematic because dietary reconstruction should not only include preferred foods, but also fallback foods, or foods that are eaten during primary food scarcity.

Such fallback periods often occur annually in modern environments regardless of habitat

(Marshall & Wrangham 2007). H.erectus was no exception and experienced fallback periods of primary food scarcity. If H.erectus did not use fire, they would have had to eat their plants raw when meat was scarce. H.erectus’ morphology, especially their smaller gut and molars, would have prevented them from eating raw plants that are high in structural fiber (Wrangham, 2017).

H.erectus needed to eat cooked food in order to have the calories needed to support its large brain and body size without spending all day chewing raw plants. This chewing is not only energetically expensive, but also prevented H.erectus from using that time to forage for more food (Wrangham, 2017; Fonseca-Azevedo & Herculano-Houzel, 2012). Cooking is an energetically beneficial foraging method because it maximizes energy gain and directly impacts fitness (Wrangham & Carmody, 2010). This shows that the major flaw with the high energy meat diet is that it fails to take foraging decisions and food scarcity into account in its argument.

While these theoretical expectations provide insight into the development of early Homo, there is a need for direct evidence of hominin cooking and fire use. This can be found through

archaeological contexts, but finding well preserved evidence of ephemeral fire for this behavioral transition in the Early Pleistocene, during the emergence of H.erectus, can prove rather difficult.

This makes finding innovative ways to identify fire in the archaeological record important because it provides evidence to support or negate the Cooking Hypothesis.

1.3 Fire in the Archaeological Record

It is generally accepted that hominins used fire habitually as a technological resource starting about 400 thousand years ago (Roebroeks and Villa, 2011a; Shimmelmitz et al. 2014).

But, even during this established time period, there are arguments on the frequency and ubiquity of hominin fire use. For example, evidence of hearth features recovered from a French Middle

Paleolithic site provided strong data on seasonal Neanderthal fire use. These features were found mostly in the lower layers of the site and show that Neanderthals were using fire during warmer periods but evidence declines significantly in layers that correlated to colder periods. The researchers from this site argue that hominins were not obligate fire users and that environmental factors, like evidence of natural fire being more likely in warmer periods, impacted when

Neanderthals could use fire (Dibble et al., 2017). However, other researchers argue that

Neanderthal fire use was prevalent, even during interglacials (Roebrooks & Villa, 2011b). This shows that even during time periods where fire in the hominin technological repertoire is accepted, there is still debate on the ubiquity and prevalence of the use.

In addition to debates on the ubiquity of fire use, there are also arguments as to what constitutes evidence of fire in the archaeological record. What most researchers consider undisputed evidence of hominin fire use comes from Eurasian sites that have persistent evidence of hearths or Middle Eastern cave sites, where evidence is well preserved. For example, there are

187 combustion structures, such as flat hearths surrounded by accumulated archaeological materials, burned wood, and charcoal, in the levels of Abric Romani Middle Paleolithic rock shelter site in Spain (Vallverdu et al., 2005, Roebroeks and Villa 2011a). Clearly, the habitual and technological use of controlled fire happened by at least the second half of the Middle

Pleistocene (Roebroeks & Villa, 2011a). The cave site of Zhoukoudian in China (500 kya-

200kya) also has reliable evidence of hominin fire use though burned and unburned bones in association with hominin stone tool artifacts (Weiner et al., 1998). There is some debate over whether the fire and artifacts were created together or associated by post-depositional factors, but there is consensus that hominin fire use was present (Goldberg et al., 2001). These sites are well preserved in cave contexts which allows for more fire evidence to be preserved and have consistent use, which increases the quantity of fire evidence. Using these Eurasian sites as a standard for what constitutes undisputed fire use creates a bias in how researchers constitute strong fire evidence in the archaeological record.

However, using the classical canon of only prevalent hearth evidence for hominin fire use fails to recognize that fire is omnipresent in nature and hominins likely opportunistically used fire as they encountered it on the landscape. Fire is a natural phenomenon that occurs frequently in nature and has impacted the environment and ecology of ecosystems. Fire has played an important role in the history of life, impacting plant adaptations and the distribution of ecosystems (Pausas & Keeley, 2009). Given its prevalence in the environment, it is likely that early hominins were exposed to natural fire, through sources like lightning and spontaneous combustion. Many researchers suggest that this method is how hominins first came into contact with fire (Clark & Harris, 1985; Roebroeks & Villa, 2011a). For example, the pyrophilic primate hypothesis suggests that, by 2 to 3 million years ago, hominin fire dependence resulted from

adapting to progressively fire-prone environments that eventually led to a more habituated use of fire by early hominins (Parker et al., 2016). This hypothesis is supported by behavioral evidence from chimpanzees which shows that they are curious about, not averse to, fire (Pruetz &

LaDuke, 2010). This evidence suggests that hominins had the capability and affinity for taking advantage of natural fire in the open landscape, but such opportunistic fire use would not have the same archaeological signal as the classic cave setting hearth model that many Eurasian sites have.

This shows that not all hominin fire sites will represent the classical Eurasian model of a hearth fire, which shows a need for proxies that indicate opportunistic controlled hominin fire use. Clear evidence of human controlled fire, like a stone-lined hearth with ash and charcoal layers in association with hominin artifacts, is seen as unequivocal evidence for hominin fire use.

But, using this metric to study all fire sites is flawed, especially since early hominin fire use was likely opportunistic and ephemeral in nature. Evidence of ephemeral fire is not always present post-burning, even in studies of modern foraging societies (Holdaway, 2017). Many modern hunter-gatherers don’t use a classic hearth ring when constructing fire, which further complicates the definition of hearth features (Mallol et al., 2007). Also, as time progresses, there is a decreased probability of finding any type of evidence since traces of fire can vanish quickly

(Wrangham & Carmody, 2010). If we look for evidence of opportunistic fire use using only

Eurasian lines of evidence, we will not be able to investigate these ephemeral sites. But, when we expand our gaze and use different methods to investigate fire use, we can start to look for earlier evidence in the archaeological record.

Most research on early fire use has been concerned with the appearance of controlled fire use without any universal definition of what controlled fire actually means. There is no universal

definition of "controlled fire", which leads to mutual misunderstandings within the academic community (Sandgathe & Berna, 2017). For some researchers, control means any basic handling of fire from a natural source, so any potential evidence of fire is evidence for control. This means that the use of fire is equated with the control of fire. Others make distinctions between use and control, with control of fire equating to creation and maintenance of fire. These discrepancies can be rectified by making distinctions between different potential interpretations of fire in the archaeological record between fire residues that are associated with hominins but have no knowledge of acquisition, fire residues that clearly come from natural sources, and fire residues that come from fire making technology (Sandgathe, 2017). This thesis follows the definition that opportunistic fire use by hominins is considered controlled fire use.

Finding evidence of early hominin fire use becomes especially difficult when you consider that early hominin sites are situated in open areas and not in well preserved cave sites.

Open air contexts are not conducive to strong preservation due to the post depositional processes that impact open air sites (Clark & Harris, 1985). More closed controlled fire sites, like cave sites, have better preservation of macrofire remains due to the fewer depositional processes that impact the site. Open air sites are more susceptible to post-depositional and taphonomic processes that can move, alter, or degrade evidence of fire (Cutts et al., 2019; Holdaway et al.,

2017). There is also a greater possibility of wildfire affecting the site and obscuring any controlled fire evidence or creating a false positive fire site (Cutts et al., 2019). Also, cave sites differ drastically from open-air sites in that they are characterized by long stratigraphic and cultural sequences in which most of the deposits are anthropogenic (Alperson-Afil et al., 2017).

Ephemeral and opportunistic fire use will not have this same long deposit sequence in the archaeological records which results in a lack of artifacts that relate to hominin behavior.

Due to these differences, novel methods need to be used to identify open air fire in the archaeological record. One such approach is soil micromorphology, which integrates a variety of microscopic techniques to study the arrangement and components of sediments and soils. This technique can provide a lens into which sedimentary structures are related to human activities or natural phenomena to help model site formation and provide detailed reconstructions of human paleolandscapes (Macphail et al., 1990). Micromorphology has been used in conjunction with spatial analysis at various early fire sites like Qesem Cave, Israel, and Wonderwerk Cave, South

Africa, to identify if burned artifacts are from human or natural processes (Mentzer, 2014;

Karkanas et al., 2007). Although a powerful technique, micromorphology only gives information about primary context and can lead to false associations if analyzed on its own. It is important to conduct spatial analysis in conjunction with micromorph analysis in order to have a strong association between the evidence and human activities (Mentzer, 2014).

Spatial analysis can be coupled with micro-archaeological evidence to create an association between fire and hominin behaviors. New technologies like more accurate GPS systems allow for more precise and fine grained excavations that can provide more context on the spatial arrangement of artifacts. This can be done through recovery of all possible artifacts that are piece plotted with a total station that make it possible to map small artifacts and features

(McPherron and Dibble, 2002). This data is then analyzed using geographic information systems that can identify and visualize density related patterns (Anselin and Getis, 1992). This method was used at the site FxJj 20 AB in Koobi Fora Kenya, to visualize the spatial distribution of micro-artifacts to analyze if fire evidence at the site has a natural or anthropogenic origin (Hlubik et al., 2017).

In addition to micromorphology and spatial analysis, other micro-archaeological techniques can be used to help reconstruct early transient fire sites. For example, microbotanical analysis, such as phytolith analysis, can identify the types of plants that were used as fuel for the fire or cooked in the fire and can provide a metric of burning through discoloration (Mentzer,

2014; Parr, 2006). Additionally, Fourier Transform Infrared Spectroscopy (FTIR) can be used to determine the mineralogical and chemical composition of archaeological sediments and artifacts, and can also be used as a metric for presence of burning (Mentzer, 2014; Berna et al., 2012). For example, researchers at Wonderwerk Cave (1 mya) performed micromorphological and FTIR analyses of sediments and bone to show that burning took place in association with hominin activity during an early Acheulean occupation (Berna et al., 2012). These methods provide novel ways to address new hypotheses about early fire use on a finer scale that would be unanswered by using conventional methods.

1.4 Evidence for early hominin fire use in Koobi Fora, Kenya

The Koobi Fora region of northern Kenya has a long history of research, stretching back to the 1960s. The Turkana Basin, Kenya is a triangular lowland that lies between the Kenyan and

Ethopian domal uplifts in the middle sector of the East African rift system. This rift system, which stretches back to the Mesozoic Era, is well known for its numerous Plio-Pleistocene artifacts and fossils found in various localities of the region. Today, the region is well known for the presence of Lake Turkana, the third largest lake in Africa. This lake lies in a closed basin that is fed from the Omo River that is sourced in the Ethopian highlands in the north. This feature of a large lake has been an intermittent component of the basin since about 4 million years ago, with Turkana’s predecessor Lake Lonyumum. For the majority of the Pliocene, the proto-omo

river was the primary drainage of the region to the Indian Ocean but intermittent tectonic activity distributed the outflow, which resulted in temporary lakes. But, by 1.9 ma the lake remained a permanent feature of the Basin, although it fluctuated in size. The Lonyumun lake, demonstrated through lacustrine sediments in the Lonyumun Member, is defined as the basal unit of the Koobi

Fora Formation on the north-east side of the lake (Harris, 2006).

Lake Turkana Basin, formerly known as the Lake Rudolf basin, has a long history of research. While there was a history of colonalist research and contact with the region starting in the late 1800s, paleoanthropological research didn’t start in the region until the mid 1960s.

Examples of this research includes terminal Pleistocene and Holocene archaeology of the southwest portion of Lake Turkana by Larry Robbins and expeditions run by Bryan Patterson that recovered fossil hominin material. Later in the 1970s, the East Rudolf Research project was established by Richard Leakey and Glynn Isaac. This project was in collaboration with the government of Kenya who created Sibiloi National Park to close off the region of Koobi Fora from Allia Bay and Ileret to domestic livestock. This act catalyzed continued long term paleoanthropological fieldwork in the region. This resulted in numerous finds in later field seasons, such as hominin fossil material, like KNM-ER 992 (Homo ergaster mandible) and

KNM-ER 1813 (Homo habilis), hominid footprints, and two new early stone tool industries

(KBS industry and the Karari industry). Beginning in 1985, the Koobi Fora base camp was first used as the field station for the Koobi Fora Field School, which led to further research in the region that continues to this day (Harris, 2006).

The FxJj 20 Site complex is situated In the Karari Region of Koobi Fora, in Area 131, and contains the earliest evidence of hominin fire use in the archaeological record (Figure 1).

Excavation in this locality started in 1972, when fragmentary fossil bones and a localized

concentration of artifacts found on an outcrop lead to two test trenches being dug for analysis.

These trenches were labeled FxJj 20 Main and East. In 1974, a third site with similar high artifact density across the gulley from the other sites was opened and named FxJj 20 AB. All three of these sites have artifact concentrations at the same stratigraphic level in brownish floodplain silts of the Okote member which led to the designation of the FxJj 20 Site complex, as they all represent the same depositional time period. These sites represent some of the best preserved artifact assemblages in the Okote member. This site complex also recovered fresh basalt cores and fossilized bone, including the robust mandible KNM-ER 3230 that is identified as Australopithecius boisei in FxJj 20 East. The stone tool artifacts are attributed to the Karari stone tool industry (Harrris, 1997; Clark & Harris 1985).

Figure 1: A, General location of the FxJj20 site complex, located on the Karari Ridge, in Koobi Fora, Northern Kenya. B, Position of the FxJj20 sites in relation to each other. FxJj20 AB is located approximately 150 m northeast of FxJj20 Main and FxJj20 East sites (image from Google Earth). C, Image of the excavation of FxJj20 AB facing southwest across the site. (Hlubik et al. 2017)

In addition to artifacts and hominin fossils, FxJj 20 East and FxJj 20 Main contained consolidated reddened sediment patches that are hypothesized to have discolored as the result of fire at the base of the archaeological horizon. While paleomagnetic data was inconclusive about the presence of controlled fire at the site, other reddened patches were found in the immediate vicinity and investigated for burning (Clark & Harris, 1985). One of these sites, FxJj 20 East, showed evidence of ancient fire through alternate field and thermal demagnetization analysis of samples (Clark & Harris, 1985; Bellomo & Kean, 1997). The work at FxJj 20 East and Main show hominin behavior associated with the patches, but there is no conclusive evidence that the discolor material is burned (Bellomo, 1994). Further investigation of this and adjacent sites in the site complex, show an intersection of these combustion features and hominin behavior at the

FxJj20 Site complex (FxJj20 East, Main, and AB), dated to 1.6 mya. This thesis will focus on the evidence from FxJj 20 AB, as this site has the most current and in depth evidence for fire evidence in the site complex, as it was reopened in 2010 and has been the site of fire research in the region ever since (Hlubik et al., 2017).

First, the recorded artifacts at the site were analyzed to determine if they were burned.

Microarchaeological chemical evidence for the presence of burning at FxJj20 AB is shown through FTIR analysis of bone and sediment. Experimental FTIR analysis of heated sediment shows that presence of burning can be shown through this analysis, but analysis of sediment is more reliable. FTIR can also be used to indicate the presence of burning on bones. At the site, there is 1 example of rubified sediment found 1 meter east of Locus 1 that is in association with

6 FTIR identified burned bones. In addition to this locality, an additional 43 bone specimens from other areas of the site were shown to be burned (Hlubik et al., 2017).

There is also evidence for burning through the presence of thermal curve fragments and pot lids on stone artifacts. Thermal curve fragments and pot lids show statistically distinct intersections of hominin knapped stone tools and exposure to high energy fire (Cutts et al.,

2019). Experimental work has shown that potlids can be ejected several meters from a fire during heating, which explains why the potlid artifacts are scattered around FxJj 20 AB. This indicates the presence of fire but it cannot give us information about the distribution of the fire in the site

(Hlubik et al., 2017). Thermal curve fragments show a direct intersection between burning and hominin activity because only knapped and heated material produce thermal curve fractures, while natural cobbles form potlids but do not produce thermal curve fragments. Thermal curve fragments are present at FxJj 20 AB and match the experimentally produced thermal curved fragments produced under controlled fire conditions. This evidence of burning in association with hominin artifacts suggests that there is an intersection between hominin activity and fire use at the site (Cutts et al., 2019).

Next, the site was spatially analyzed to analyze how combustion features and hominin artifacts are distributed throughout the site. Optimized hot spot analysis showed that artifacts occur in a large dominant cluster in the northeast portion of the site, with smaller clusters to the southeast. A small group of burned material, such as bone, sediment and potlids in the west of

Locus 1 constitute a statistically significant cluster which could be considered the location of a contained fire (Hlubik et al 2017).

The spatial distribution around Locus 1 is compatible with Binford’s (1980;1983) theory of a Toss and Drop zone (Hlubik et al., 2017). Toss and Drop zones are used to identify the location of hearths when direct fire evidence, like ash and charcoal, is not present. This theory draws from evidence from modern ethnographic campfires that shows that unintentionally

produced waste, like small stone or bone, should be found in a drop zone directly in front of the individual working on these items around a hearth while larger intentionally discarded items, should be found in a toss zone located up to several meters away from the individual in any direction (Binford 1983; Hlubik et al., 2017). This pattern is found at FxJj 20 AB, as the spatial distribution of Locus 1 is shown to have small materials and bone close to the locus while larger materials are found more distant from the locus (Figure 2). An additional area of interest, Locus

2, about 1 meter south west of Locus 1, has plausible evidence of fire activity because this area of the site has the highest concentration of burned material and a similar distribution of artifacts as Upper and Middle Paleolithic hearth sites (i.e Tor Faraj and Pincevvent) (Hlubik et al., 2017).

Figure 2: Location of all artifacts and ecofacts found on FxJj20 AB, including chemically analyzed potlids, burned bone, and burned sediment. The orientation all materials from the new excavations are obtained through total station, while materials from original excavation were plotted by hand. (Hlubik et al., 2017)

The evidence presented above is likely in primary context, as spatial evidence and micromorphological analysis from FxJj 20 AB suggests that the site has weak levels of post

depositional disturbance. The FxJj 20 site complex is situated on tuffaceous silts, and the sites were buried in a low energy floodplain environment (Harris, 1997; Hlubik et al 2019). Analysis of soil micromorphology of FxJj 20 AB shows that the site is a fairly rapidly aggrading deposit, with sediments being brought into the site by low energy water (Hlubik et al., 2017). Orientation analysis shows that the artifacts are randomly oriented on a relatively flat surface and show no indication of movement through the site (Hlubik et al. 2019). Also, there is no evidence of artifact winnowing by hydraulic action or deflation (Hlubik et al., 2017).

The evidence from this site has major implications for the influence of fire on the biological and cultural evolution of humans, as this site pushes the timeline back on when hominins started to use fire. FxJj 20 AB is currently the oldest (1.6 mya) archaeological site that has evidence of fire and hominin activity. This evidence supports the theory of the cooking hypothesis because it shows evidence of hominin fire use in the Pleistocene, during the time period of Homo erectus and Homo habilis (Hlubik, 2018). There can be arguments against the conception that there is early fire at FxJj 20 site complex because it does not provide concrete evidence that hominins were involved in the production of the fire, it only provides an association between hominin activity and fire altered materials. But this premise is using

Eurasian views of fire in the archaeological record and projecting it onto a site where fire use was likely more ephemeral and opportunistic. The question then becomes, how can you account for the differences in site use and preservation when comparing later Eurasian sites to early

African open-air fire sites? What artifacts or evidence must be in place to show direct evidence of hominin fire production in a more open air, less preserved environment?

Also, this evidence from these early hominin fire sites has been used to suggest Early

Pleistocene hominins used fire and had some control over combustion processes. These hominins

would have encountered wildfire regularly on the East African savannah landscape, which may have facilitated habituation to fire, and further enhanced the adoption of fire using behaviors. But it is important to note that the presence of hominin controlled fire doesn't prove that it was used for cooking as there are other advantages of fire, such as the provision of warmth and protection against predators that also warrant the use of fire. Also, this evidence does not provide specific information on which hominins (Australopithecus, Homo, or Paranthropus) used the fires (Brain

& Sillent, 1988).

1.5 How new proxies can help further contextualize early ephemeral fire sites

One-way archaeologists can help further contextualize early ephemeral fire sites is through the use of multiple proxies of analysis. The more evidence you have in support of an argument, the stronger the argument is. Providing further proxies for studying the archaeological record requires extensive experiments in order to provide a framework for understanding the results of what is found in the archaeological record. For example, Hlubik (2017) conducted multiple experiments on burned lithics and sediment to understand how fire impacts FTIR spectra and then reflected her findings to artifacts at FxJj 20 AB. There is a need for actualistic fire experiments to help further understand the interaction between fire, its immediate environment and the residues and that result from this interaction. Sangathe et al. (2017) calls for research to be more focused on developing analytical methods and skills to confidently interpret what is found in the archaeological record to help further understand hominin fire use in the archaeological record. This thesis is an attempt to contribute data and findings from phytolith analysis of actualistic open air fire experiments to help further understand how fire signals are left in the environment. By creating a framework to understand phytolith composition in fire

contexts, archaeologists can more confidently interpret if phytolith distributions at the site relate to the actualistic context.

1.6 Conclusion

It is important to study hominin fire use in order to understand how this revolutionary technology impacted hominin evolution, both biologically and culturally. The origin of hominin fire use is hypothesized to have started with Homo erectus, but it is difficult to find well preserved archaeological evidence of ephemeral fire for this behavioral transition in the Early

Pleistocene. The FxJj 20 AB site complex provides compelling archaeological evidence of hominin fire use during this time range, but there is a need for more proxies of evidence. The development of new proxies requires extensive actualistic experimentation in order to create strong frameworks on what constitutes fire evidence in the archaeological record.

Chapter 2: Phytoliths as Proxies

2.1 Introduction

Phytoliths are microscopic silica bodies that form between or within plant cells during the evapotranspiration process. They are resistant to destruction, easily identifiable, and discolor when burned at high temperatures (>500 °C). Phytoliths have been used to successfully reconstruct ancient paleoenvironments and provide context for archaeological sites and artifacts.

But, these investigations of phytoliths are only as good as the reference material they are compared to. Developing inferences of behavior from phytolith data requires extensive experimentation to provide expectations regarding the frequency and distribution of phytoliths within specific conditions. This thesis seeks to create a database of phytolith data from experimental fires then can be used to contextualize possible open-air fire sites, like site FxJj 20

AB.

2.2 What are Phytoliths?

Phytoliths are deposits of solid silica that are formed as a result of the biological and physical processes of plants. They are mainly composed of amorphous (non-crystalline) silicon dioxide (SiO2) and about 4%-9% water (Piperno, 2006, p. 15). This silicon content varies in different species and is regulated by climatic and soil conditions that limit the availability of silicon (Piperno, 2006, p. 7). Environmental factors such as pH levels and iron and aluminum oxide content can impact the levels of dissolved silica. In addition to environmental factors, silica deposition is impacted by the evapotranspiration process in plants. Higher evapotranspiration rates increase the deposition of solid silica due to decreased water movement.

This leads to the precipitation of silica into solid forms which results in more phytolith production (Piperno, 2006, p. 8). Plants can also create high concentrations of phytoliths through

actively taking in water in environments that contain high amounts of silica due to rock and sediment weathering (Piperno, 2006, p. 8). The production of phytoliths is high in ferns

(Pteridophytes), Basal AngioSperms, Monocotyledons (like Sedges and Herbs), and Eudicots.

(Piperno, 2006, p. 7).

Phytolith formation in plants is known to be controlled by genetic and physiological mechanisms, although the specific mechanisms of its formation are still unknown. Phytolith formation can be impacted by environmental factors, like fluctuations of local climate and growing conditions (Piperno, 2006, p. 9). The formation of specific phytolith morphology is controlled by where in the cell and plant body the phytolith is located. Phytolith morphology is a direct reflection of the gross morphology of the plant. In some plants, silica can be unevenly deposited which can lead to phytolith formation being highly localized in a single kind of tissue or single plant structure (Piperno, 2006, p. 19).

The evolutionary and physiological reasons why plants make phytoliths are still unknown, but there are many competing theories for their presence in plants. One reason could be for the protection of plants from herbivores and pathogens. The solidification sites in plants that contain phytoliths are likely to cause discomfort to herbivores that would consume the plant.

Another theory is that phytoliths could be a by-product of physiological functions within plants.

Silicon dioxide may ameliorate the toxic effects of aluminum and other heavy metals that are ingested by plants through the groundwater that results in the formation of phytoliths (Piperno

2006, p. 12-15).

After the plant dies, these silicate particles are deposited into soils and sediments as discrete, microscopic particles. During the deposition process, phytoliths are impacted by taphonomic processes that impact how they are preserved in the record. Phytoliths are first

introduced to sediments through necrolysis or decomposition and disaggregation of plant at the time of death. Then they go through biostratinomy, a process that impacts phytoliths post- deposition but prior to burial, like transport by other systems like wind and water (Madella &

Lancelotti, 2012; Piperno, 2006,p. 21). Transport can impact certain phytolith morphologies by abrading the phytolith and breaking it at its structurally weak points. This leads certain phytolith morphologies being underrepresented in the assemblage due to their higher likelihood of wear

(Madella & Lancelotti, 2012). At this point, the phytoliths are fully incorporated into the sediments. Phytoliths are resistant to decay and can stay preserved in sediments for long periods of time (Piperno, 2006, p. 5). But, there are some physical, chemical, and biological processes that can alter or destroy the buried phytolith fossils. This phenomenon, known as fossil diagenesis, can impact phytoliths through chemical or physical attacks, bioturbation, disruption of sediment by living organisms, and translocation of the phytolith material (Madella and

Lancelotti, 2012). It is important to understand how taphonomic processes affect phytolith preservation, especially when you use phytoliths as proxies for studying the paleoenvironmental and archaeological record.

Fire events can impact phytoliths through discoloration, although dark colored phytoliths also occur naturally. Under the oxidative conditions of an open-air fire, the color of phytoliths can be altered from translucent to a dark brown or black color through the occlusion of carbon.

They can discolor at temperatures above 500 degrees celsius and melt at around 800 degrees celsius (Parr, 2006; Fritzsch et al., 2016). High temperatures are also known to warp phytoliths which change their distinct morphology. For reference, all of the experimental fires set for this thesis reached a temperature of greater than 550 degrees celsius, which is hot enough to discolor phytoliths. The discolored nature of burned phytolith also stays constant even after the phytoliths

are subjected to acid washing, which indicates possible long-term color change. This means that discolored phytoliths can be used as an indicator of fire events in the archaeological record.

Some have refuted these claims, saying that discolored phytoliths occur naturally in the environment. While this statement is true, there is empirical evidence that fire does discolor phytoliths. Also, naturally discolored phytoliths have a transparent and opalescent appearance, as opposed to the dull opaque finish of charred phytoliths. Since discolored phytoliths can occur naturally in the environment, it cannot be assumed that all discolored phytoliths were burned

(Parr, 2006). This creates a lack of certainty in analysis, so this thesis will only describe phytoliths as discolored and not burned.

2.3 Phytolith analysis in archaeological and paleoenvironmental contexts

Phytoliths can be used to study ancient paleoenvironments due to their durability and indicative morphology. There are a variety of methods that can be used in paleoenvironmental reconstruction that all have different strengths and weaknesses. Studies of the sedimentological record can provide broad paleoenvironmental signatures like fluvial, volcanic, dune, or lacustrine settings but cannot give fine-tuned information about the environment. Faunal analysis can give us information about the environment through functional ecomorphology, or how morphology of the animals relates to the environments they live in. This can give us a way to study the openness of the environment and indirectly study the general types of vegetation (i.e open woodland versus bushy grassland). A more direct way to study vegetation is through the deposition of plant remains like pollen or phytoliths (Albert et al., 2006). For example, phytolith analysis has been used to contextualize sediments from the Holocene and Pleistocene at Middle Awash in Ethiopia.

Phytolith ratios from these ancient sites were used to estimate tree cover, aridity, and the

proportion of C3 and C4 grasses. This data showed that the Holocene sample is representative of a grassland environment and the Pleistocene sample is representative of a grassland with scattered woody elements. This analysis is precise enough to show that when compared to a modern phytolith assemblages, the two samples are distinguishable from each other and the modern sample. The analysis also showed that the sites were not impacted by mixing and translocation processes. One issue with this study that the authors call to attention is the need for more modern studies of the vegetation in Ethiopia to confirm the conclusions they came to

(Barboni et al., 1999). Phytoliths are a powerful enough proxy to create a fine tuned view of paleoenvironments but the conclusions are only as strong as the modern collection they are compared to.

In addition to contextualizing paleoenvironments, phytoliths can be used to aid in contextualizing archaeological sites. The main goal of using phytolith analysis in archaeological contexts is to decipher human and natural influences on plant vegetation and climate and how the two relate to one another. Phytoliths have been used to answer a variety of archaeological questions from the dispersal of domesticated plants and the development of agricultural systems to the functions of pottery and stone tools (Piperno, 2006, p. 139). For example, the Middle

Stone Age site of Pinnacle Point in South Africa has used phytoliths analysis to understand the changes in survival strategies of hunter-gatherer populations. Specifically, phytoliths were used as a proxy for the reconstruction of hominin foraging strategies in the Middle to Late Pleistocene with an emphasis on the use of controlled fire and other possible plant uses. The analysis of phytoliths shows evidence of intentional gathering and the introduction of non-native plant material into the site. Phytoliths were also used to study hearths at pinnacle point through the high amount of phytolith variation within the hearth context versus outside of the hearth (Esteban

et al., 2018). This success of this study stemmed from a strong assemblage of comparative modern South African plants, which they could use to help distinguish the different phytolith morphotypes.

2.4 Phytoliths and FxJj 20 AB

Both examples for paleoenvironmental and archaeological reconstructions using phytoliths have highlighted the need for strong modern reference samples in the phytolith studies. One major flaw from Barboni et al. (1999) is that the researchers did not have a strong modern competitive phytolith sample to compare to the modern plant material. The results can only be as strong and precise as the comparative material they have to compare to. This calls for the need for more modern studies of phytoliths in order to contextualize more ancient phytoliths studies. To create these modern samples requires actualistic work to understand how phytolith composition varies in the environment today and what phytoliths morphologies come from specific regional plants.

This is especially important when studying the relationship between prehistoric fire and the resulting archaeological residues. Having an understanding this relationship relies on a deep understanding how fire alters its immediate environment and how this change leaves a signal on the environment via residues. It is important to know how fire alters the environment under variable heat conditions such as the size of the fire, duration of the fire, and different fuel types and how these residues persist in the landscape. Answering these questions requires extensive experimentation and the development of new analytical methods that can be used to confidently interpret what we see in the archaeological record. Currently, there is a deficit of understanding about how fires alter sediments and objects they come into contact with (Sandgathe, 2017). The

main goal of this thesis is to fill these gaps of knowledge so we can start to understand the signals fire leaves on the environment. Specifically, this thesis looks at how controlled fire impacts the discoloration of phytoliths in pre- and post-fire assemblages. These experiments were specifically set in the Koobi Fora region in Kenya so they can provide a direct comparison to archaeological fire sites in the region, like FxJj 20 AB.

2.5 Conclusion

Due to their durability and easy identification, phytoliths are excellent proxies for studying past environments and contextualizing archaeological sites. They also are strong proxies for indicating fire events because they discolor when burned at high temperatures (>500

°C). But, phytolith contextualization is only as good as the reference material the site is compared to. This highlights the need for more modern studies of phytolith assemblages and how they to understand frequency and distribution of phytoliths within specific conditions. This thesis seeks to create a database of phytolith data from experimental fires that can be used to contextualize possible open-air fire sites, like site FxJj 20 AB.

Chapter 3: Methods

3.1 Introduction

Developing inferences of behavior from phytolith data requires extensive experimentation to provide expectations regarding the frequency and distribution of phytoliths in high intensity localized fires. Fires of varying duration were set in 3 different fire sites containing silty sediments in Koobi Fora, Kenya. The sediment samples from these fires as well as pre fire samples from each of the sites were then processed into phytolith samples and analyzed using a modified procedure from Katz et al. (2010).

3.2 Theory behind experimentation

Archaeological knowledge is grounded on the basis of modern observations (Lin et al.,

2018). The study of modern observations as it relates to archaeological contexts is known as

Experimental Archaeology. Using guidance from laboratory experimental studies, actualistic experiments seek to model real life scenarios and investigate activities that might have happened in the past using materials and methods that would have been used. This does not mean all materials and methods need to be authentic, but the goal is to recreate the activity as closely as possible (Outram, 2008).

This thesis seeks to understand changes in the discoloration and count of phytoliths when exposed to controlled fire contexts of variable duration. This question was investigated through the setting of fires of variable duration and analyzing the phytolith composition of pre and post fires sediments. Each of the durations (one hour, twelve hour, stacked one hour fires) chosen were to model different proposed hominin behavior and to assess how time might impact the amount of discolored phytoliths. The one hour fires were used to model more quick opportunistic

fire use while the twelve hour fires were used to model longer hearth like fires. The different durations also can be used as a metric to see how time (i.e how long the fire was left burning for) impacts the proportion of discolored phytoliths. The stacked one hour fires were inspired by

Mallol et al. (2013), who used stacked fires to model repetitive fire setting behavior by hominins.

This thesis also seeks to understand if these stacked fires create a unique signal different from non-stacked one hour fires, which indicate a different hominin behavior. If their signals can be distinguished, then hominin behavior could be inferred from different discolored phytolith signals. The results from these experiments will help provide context for studying phytoliths at archaeological sites, such as FxJj 20 AB.

3.3 Procedure

Experimental fires were set in Koobi Fora, Kenya, with one fire site located in Ileret and two fire sites located in Karari (Figure 3). Fires 1-10 were set in Ileret, Kenya (Ileret Site 1). The site was situated near the well in Ileret and is surrounded by the local Dassanach community.

This site was chosen for its silty sediment and floodplain environment that is similar to the environment characterized by the micromorphology of Site FxJj 20 AB (Hlubik et al., 2017).

This is an important characterization because the experiments are trying to model fire events in an environment as close as possible to the environment of the site. Fires 11-18 were set in Karari,

Kenya with fires 11-16 set in one location (Karari Site 1) and fires 17-18 set about 30 feet away in another (Karari site 2). The Karari sites were situated in Sibiloi National Park in the Koobi

Fora Field School’s living and research camp in an area monitored by Kenyan Wildlife Services.

The Karari sites are also characterized by silty sediment to model the characterization of the sediments at FxJj 20 AB (Figure 4).

Figure 3: Map of the three fire sites (Ileret Site 1, Karari Site 1, and Karari Site 2) in relation to FxJj 20 AB

Figure 4: Both Karari Site 1 (A) and Karari Site 2 (B) were chosen for their silty sediment to accurately model the environment of FxJj 20 AB

In addition to varying in location, the fires differed in duration and frequency (15 minutes, 30 minutes, 1 hour (hr), 2x stacked 1hr fires, 3x stacked 1hr fires, 12 hr (hearth)). The duration times relate to how long the fires were stoked and kept at as high of a temperature as possible before they were left to burn out. For example, one hour fires were stoked for one hour and then left to burn out. The stacked fires (2x and 3x) were one hour fires that were set on top of previously set one hour fires, with 2x relating to the second 1hr fire set in the same localized area and 3x relating to the third 1hr fire set in the same localized area. Table 1 shows the fires that were used for the purposes of this study. Due to time constraints and laboratory restrictions due to COVID-19, none of the 15 min or 30 min fires and only some of the one hour fires (2, 3, 9,

10, 11, 12, 15) were analyzed.

1 hour 2x1 Hour 3x1 Hour 12 Hour (hearth)

Ileret Site 1 2*, 3 **, 9, 10 4*, 7** 6*, 8**

Karari Site 1 11, 12, 15

Karari Site 2 17 Table 1: This table displays the location and fire ID of each of the fires used in this study. * and ** indicate fires set in the same localized area

Before the fires were set, initial sediment samples were taken to characterize the phytolith environment in pre-fire contexts. The samples were taken across the site in 1-meter intervals from north to south direction and in the east west directions (Figure 5). Then, local wood, like acacia, was taken from the area surrounding the site and stacked on top of a location where an initial sample was taken. The fires were initiated with a Bic Lighter and tissue paper.

Once the fires were lit, their temperatures were stoked to maintain at high temperatures (>550

°C) with temperatures being monitored about every 10 minutes with an infrared thermometer

(Appendix II). Once the fires reached their designated high temperature burn time, they were left to burn out. The only fire that deviated from this experimental setup was fire 17, where sediment was poured over the fire when it was done in order to prevent the hot charcoal and ash from flying off and burning the surrounding camp and research area.

Figure 5: Before samples of Ileret Site 1 were taken in the north/south and east/west direction at 1-meter intervals throughout the site (Not to scale)

Once the fires had cooled, the ash layer was brushed away and samples of the sediment directly under the fire were taken in ten centimeters intervals through the fire (Figure 6). Samples were also taken twenty centimeters from the fire edge as well as two meters in the leeward and windward directions in one-meter intervals starting from the edge of the fire but are not included in this current study.

Figure 6: Sediment Samples were taken in 10-centimeter intervals within the fire, with "center samples" being closer to the middle of the fire and "edge samples" being closer to the edge of the fire

After the field season finished, sediment samples were processed at the National

Museums of Kenya (NMK) to isolate the phytoliths to be sent back to the U.S. This was done through a modified Katz et al. (2010) method for phytolith extraction. First, ~1g of sediment was placed in a jar and mixed with 2-3 mL of water. The jars were then sonicated for 6 minutes to suspend the lighter sediments in solution. The solution of lighter sediment was then pipetted into a 0.5 ml microcentrifuge tube and centrifuged for 10 minutes at 5000 RPM to pellet the sediment. After, the top layer of water was removed from the solution and the sediment was weighed. This process was repeated until each of the sediment samples weighed 0.5g (+/- 0.1g).

This modified method of sediment extraction was used to increase the amount of phytoliths in the sample. Then, 250 μL of hydrochloric acid (HCl) was added to the microcentrifuge tubes and left to soak for 10 hours. The samples were then centrifuged at 5000 RPM for 10 minutes to

separate the acid from the sample and then the suspended HCl was removed. Then, 300μL of

Sodium Polytungstate (SPT) was added to the sample tube and was centrifuged at 5000 RPM for an additional 10 minutes. The acid was used to break up the carbonate and organic material in the sediment and the SPT is used as a heavy liquid for the suspension of phytoliths during centrifugation. The supernatant of SPT was removed from the sediment sample tube, placed in a new tube, and was then diluted by adding 350 μL of DI water. This mixture was then centrifuged at 5000 RPM for 10 minutes, and the supernatant of water and SPT was removed, leaving just enough SPT and water mixture to cover the residual pelleted sediment that was originally suspended in the supernatant. Then, the water was added to the mixture to further dilute the sample. This was to prevent the slide from becoming cloudy when the SPT dries. The supernatant of the samples was then pulled out and separated into two different tubes. These samples were then pelletized by myself and researchers at the NMK to keep half of the collection at the NMK and ship the other half of the collection to the U.S. for further analysis.

The phytolith samples were then organized into analysis groups to randomize samples from different conditions during analysis (Appendix Table 1). The pelleted samples were resuspended with 40 μl of deionized water and mixed thoroughly. Then 20 μl of solution were pipetted onto a microscope slide with one drop of glycerine added after to encourage phytolith rotation and movement on the slide. The phytoliths were counted for 20 views of a slide at 400x magnification using a digital microscope. Each phytolith counted was categorized as being either discolored or not. Discolored phytoliths are characterized as having a phytolith shape but having a dark brown/black color that could not be explained by shadows of the microscope (Figure 7).

About half of the samples were also analyzed for phytolith type (Analysis Group 1- Analysis

Group 4), but that information was disregarded in favor of a more focused comparison on just discoloration.

Figure 7: Composite image of unaltered phytoliths and discolored phytoliths from samples 1409, 1466, 1427, Scale Bar = 25μm

3.4 Conclusion

Experimental archaeology seeks to understand past archaeological contexts using actualistic experiments to understand past processes and events. Fires of variable duration and location were set in Koobi Fora, Kenya to understand how duration affects phytolith count and discoloration. The sediment samples from these fires as well as pre-fire samples from each of the sites were prepared into phytolith samples and analyzed using a modified procedure from Katz et al. (2010).

Chapter 4: Results

4.1 Introduction

This chapter displays the results of the investigation on how controlled fire impacts phytolith discoloration and count. First, the data was visualized to look at overall trends, outliers, and to determine if the data needed to be cleaned. Then, statistical analyses were conducted in order to determine if those visual trends hold. The type of statistical tests that were conducted were limited by issues of independence within and between each of the different fires. The results show that fire has an impact on phytolith discoloration and number of discolored phytoliths, although likely do not have an impact on the count of phytoliths.

4.2 Data Visualization

First, the data was visually analyzed to look for overall trends and outliers. Initial data visualization indicated the presence of an outlier in the data from fire 8, a 3x1 hour stacked fire sample, where the proportion of discolored phytoliths is significantly larger than the rest of the dataset (Figure 8). This value is about 0.2 larger than the second highest point and is confirmed as an outlier by a Grubbs test (p < 0.05). This outlier will not be present in any data visualizations or statistical tests.

Figure 8: A plot of Fire ID and proportion of discolored phytoliths highlights the presence of an outlier (circled in red). This point was confirmed as an outlier through a Grubbs test (p < 0.05).

This thesis uses the proportion of discolored phytoliths (number of discolored phytoliths divided by total phytoliths) to control for the different sample sizes of the phytolith assemblages.

Figure 9 shows general trends in fire duration (grouped by Fire ID) and the proportion of discolored phytoliths. Fire ID is the identification number of each of the fires and will be used throughout the data analysis to keep the data as transparent as possible. The pre-fire column represents all of the pre-fire samples taken that are not related to a specific fire. The rest of the samples represent post-fire contexts. In the majority of cases (9 out of 12), more phytoliths were discolored in post-fire contexts relative to pre-fire contexts. When comparing the mean proportion of discolored phytoliths for each fire condition, the pre-fire proportion of discolored

phytoliths is the smallest (0.0282) while the proportion of the 2x1 stacked fires is the largest

(0.0710) (Table 2).

Fire Condition Mean proportion of discolored phytoliths

Pre-Fire 0.02828484

1 Hour 0.06459702

2x1 Hour 0.04469483

3x1 Hour 0.07108154

12 hour (Hearth) 0.03116324 Table 2: Mean proportion of discolored phytoliths for each fire condition

Figure 9: Fire Duration (grouped by Fire ID) and Proportion of Discolored Phytoliths: This graph presents fire duration grouped by fire ID (identification number of each individual fire) by proportion of discolored phytoliths. The black dots represent the individual samples from each fire and the red dots represent the mean values of all those samples. The pre-fire sample represents all of the pre-fire samples taken that are not related to a specific fire and the rest of the samples represent post-fire contexts.

Figures 9 and 10 highlight the large amount of variation in proportion of discolored phytoliths within the samples of each fire condition and individual fire samples. Figure 10 shows a large amount of variation in the proportion of discolored phytoliths within each of the fire duration. For example, in the one-hour condition, the largest proportion of discolored phytoliths is about ten times larger than the smallest proportion of discolored phytoliths. This shows there is no consistent signal within individual fire durations. The group that shows the least amount of variation in the proportion of discolored phytoliths are the two fires in the 2x1 fire duration, with

a difference of only 0.047. Figure 9 highlights the differences between individual samples from the same fire. For example, the highest proportion of discolored phytoliths in post-fire samples from fire 4 is about six times larger than the smallest proportion of discolored phytoliths. This shows that there is large variation within each individual fire.

Figure 10: This graph of each individual fire’s grouped average of the proportion of discolored phytoliths highlights the large amount of variation in proportion of discolored phytoliths even within the same fire condition.

4.3 Statistical Tests

In order to statistically confirm or deny conclusions made through visual analysis of the data, statistical tests were performed. But, before any statistical test could be conducted, issues of independence had to be dealt with. The experimental fire setting procedure gave rise to many issues of independence. One main issue of independence is that all of the fire samples within a fire of a certain condition are more similar to each other than samples of any other fire, even

those with the same duration. This means that samples from different fires but from the same fire condition cannot be grouped together for any statistical tests that rely on independence. Another issue is that samples from the same site location are more related to each other than those from other site locations. This means samples from all three fire site locations cannot be grouped together for statistical tests. This issue of independence gets further complicated by the fact that all of the fires were set directly on top of one specific pre-fire sample. This makes those specific pre-fire samples more related to the individual fires than any of the other pre-fire samples, even those at the same location. Given the limited size of the dataset, there is no concrete way to explore the variability in the environment of the pre-fire samples that could lead us to treat all pre-fire samples in the one location as the same. This causes the pre-fire samples that are directly related to a fire to either be directly compared to only that fire or taken out of the dataset completely depending on the type of statistical test conducted. These issues of independence led to more specific and direct comparisons of the fire samples and limited the type of statistical tests that could reliably be conducted.

In order to counteract these issues of independence, the data from each individual fire was grouped. This was possible because the proportion of discolored phytoliths within each of the fires is not dependent on location within the fire. Specially, there is no large difference between the samples taken from the center of the fire and samples taken from the edge of the fire. Figure 11 highlights the variation between location within the fire and proportion of discolored phytoliths within each of the individual fire distributions. For example, the center proportions from fire two are the largest and smallest values of the samples, but the center values of fire seven are first and third largest. This variation leads to the assumption that all post fire

samples can be grouped together, because location within a fire and proportion of discolored phytoliths do not show a strong association.

Figure 11: A plot of individual fires and proportion of discolored phytoliths with the shape and color of points relating to location within fire highlights the variability of discoloration within individual fires. This allows for fire samples taken from different locations within the fire to be grouped into one value for statistical testing.

Given the number of confounding factors and small sample size, this thesis will not analyze p-values in terms of significance but will discuss trends and directions in order to clarify future directions. There is evidence that suggests that rigid p-value assumptions have led to some inaccurate statistical interpretations which lead this thesis to ignore the traditional 0.05 cutoff of p-values (Bruns & Ioannidis, 2016). A paired Wilcoxon signed rank test comparing values of a direct pre-fire sample of each individual fire and that corresponding fire’s grouped post fire

values was conducted for the proportion of discolored phytoliths, total phytolith count, and the number of discolored phytoliths. Specifically, the pre-fire sample of each individual fire was compared to a grouped value of all the post-fire samples from that same fire. This left many samples out of the analysis, as not all direct pre-fire and post-fire samples were processed and analyzed. Only fires 3, 9, 10, 11, 12 and 15 were analyzed. The Wilcoxon test of the pre-fire proportion of discolored phytoliths and post-fire proportion of discolored phytolith (p = 0.09375) suggests that fire has an impact on the proportion of discolored phytoliths in an assemblage. The

Wilcoxon test of pre- and post- fire phytolith counts (p= .6875) suggests that fire does not have an impact on phytolith count of the post fire assemblage. The Wilcoxon test for the number of discolored phytoliths in pre and post fire phytolith assemblages (p=0.09375) suggests that fire does have a impact on the total number of discolored phytoliths but this metric is not as useful as controlling for size by using number discolored divided by total count (proportion of discolored phytoliths).

An unpaired Wilcoxon signed rank test was used to compare the pre- fire and post- fire assemblages of Ileret Site 1. Due to ties in the dataset, the p-values are not exact. Given this and the fact that p-values aren’t as robust due to a small dataset, p-values will only be used to show general trends and not significance. The unpaired wilcoxon sign rank test of pre- and post-fire proportions of discolored phytoliths (p= 0.1712) suggest that fire could have an impact on the proportion of discolored phytoliths, but the results aren’t as conclusive as the paired Wilcoxon test. The unpaired Wilcoxon sign rank test of the counts of pre- and post- fire samples

(p=0.2129), suggests that fire possibly has an impact on phytolith count.

4.4 Conclusion

This thesis seeks to understand how controlled fire impacts the discoloration and count of phytoliths. Visual analysis shows that there is variability in the proportion of discolored phytoliths within and between each of the different fire conditions. The statistical tests that were conducted were limited due to issues of independence within and between each fire. The trends of the calculated p-values suggest that fire does have an impact on proportion of discolored phytoliths and number of discolored phytoliths while it might not have a large impact on total phytolith count.

Chapter 5: Discussion

5.1 Introduction

The results from this thesis suggest that fire does have an impact on the proportion of discolored phytoliths, specifically impacting the number of discolored phytoliths in the assemblage. These findings can be used to study controlled fire at site FxJj 20 AB, as a high proportion of burnt phytoliths in a localized area of the site can be used to indicate presence of controlled fire. Future directions seek to increase sample size of fires to create a more robust dataset and to tailor fire experiments to answer specific questions about phytolith variability and discoloration.

5.2 Biases in Data

To understand the reliability of the data and strength of the statistical tests, it is important to check potential biases. If there are biases in the data, then the data is less reliable because the data does not reflect the true relationship between variables. This is especially important since counting methods were changed from identifying type and discoloration to just discoloration after analysis group 4, which could lead to biases in the data collected. Figure 12 shows that there is not a strong difference in proportion of discolored phytoliths between each of the analysis groups. This should be the case because each of the different fire conditions are randomly scattered in each of the analysis groups. This leads to the conclusion that changing phytolith counting methods halfway through analysis did not have a large impact on analysis.

But, Figure 13 shows that there could be a bias in the count of total phytoliths as there is a clear upward shift in the total counts of each of the later analysis groups. But, since the proportion of discolored phytoliths is not affected, this increase is not as concerning. This was expected given

that the time-intensive identification of type was no longer being used. But, since the proportion of discolored phytoliths did not change drastically, changing sample methods did not create an overwhelming bias that necessitates reanalysis.

Figure 12: The plot of analysis group by proportion of discolored phytoliths suggests that changing analysis type after group 4 did not greatly alter the proportion of discolored phytoliths.

Figure 13: The plot of analysis group by total phytolith count suggests that changing analysis type after group 4 may have impacted the amount of phytoliths counted

This thesis only used p-values to indicate trends, not significance, in the data due to the issues relating to using rigid p-values as a metric for significance. P-values have led to flawed statistical interpretations leading to inaccurate scientific practices. For example, there have been issues of p-hacking observational data where researchers cherry pick dependent variables, add observations, and report only subsets of the data to achieve a low p value that indicates statistical significance (Bruns et al., 2016). The denotation of significance of with a p-value of 0.05 is an arbitrary metric. Creating a dichotomy of “significant” and “non-significant” creates a loss of information that does not accurately explain the trends seen in the data (Dahiru, 2008). This is why p-values from statistical tests for this thesis will only be used to understand trends in the data and will not denote significance.

5.3 Summary of Results

Statistical, comparative, and visual analysis suggests that fire does impact the proportion of discolored phytoliths. The most compelling fact was that all of the post-fire proportions of discolored phytoliths for each fire condition are higher than the total pre-fire ones. This suggests that fire does increase the proportion of discolored phytoliths. This was then corroborated with the Wilcoxon sign rank test of two different datasets, one with paired pre- and post-fire data (p =

0.09375) and one comparing pre- and post-fire samples from Ileret Site 1 (p= 0.1712) which suggest that the visual analysis is correct. This corroborates with the experimental findings from

Parr 2006, that shows that phytoliths discolor when exposed to high heat from a fire. But a longer fire does not necessarily lead to more discolored phytoliths. This is shown through by longest the burning fire (12 hours) having the smallest proportion of discolored phytoliths of the post-fire contexts. This trend is likely due to phytoliths melting due to prolonged exposure to high heat. Experimental studies have shown that phytoliths have a tendency to melt at temperatures at or above 800 degrees celsius (Fritzsch et al., 2016). This would lead to altered phytoliths disintegrating instead of discoloring, which would decrease the overall number of discolored phytoliths. It is likely that the 12-hour fire did reach this high temperature (800 degrees celsius), but this cannot be certain due to the fact that the thermometer used to measure temperature cannot read about 550 degrees celsius.

Data suggests that count does not change in pre- and post-fire contexts, which is interesting given the fact that new plant material is being introduced to the localized fire area.

When plants die, phytoliths are introduced to sediments as the plant tissue decays and disaggregates (Pinerno, 2006). The decomposition of the plant tissue can happen before or after the tissue is incorporated into the soil matrix. If the tissue decays after it is incorporated into the

soil matrix, the phytoliths are often well preserved if the soil is not disturbed by post-depositional processes (Vrydaghs et al., 2016). There was likely not enough time between the burning event and sampling of sediment (24 hours) to allow for the phytoliths from the fuel plant material to be incorporated into the sediments and create a strong signal of an increase in counts. This phenomenon likely led to the lack of difference between pre-and post-fire phytolith counts.

Different sampling strategies in future experimental studies could try to ameliorate this issue by sampling smaller amounts of sediments that were in closer contact to the fire.

Understanding how total phytolith count and total number of discolored phytoliths change is important to learning how proportion of discolored phytoliths are impacted by fire. The proportion of discolored phytoliths does increase after being exposed to controlled fire. Since this proportion is a combination of two raw data values (total discolored phytoliths and total phytolith count), it is important to parse out which value is impacting the proportion of discolored phytoliths. It is likely that the number of discolored phytoliths are increasing while the count of the phytolith assemblages stays constant. This claim is substantiated by statistical data which suggests that the number of discolored phytoliths is impacted by controlled fire

(p=0.09375), while total phytolith count does not change (p= .6875). This suggests that no new phytoliths were deposited during the fire and the phytoliths under the fire were altered through discoloration.

There were compelling trends pertaining to the stacked one hour fires but not much conclusive evidence can be drawn due to lack of samples for statistical testing. The proportion of discolored phytoliths for each of the stacked fires falls within the range of values of the one hour fires. The data suggests that the effect of the second and third stacked fires don’t vastly impact the proportion of discolored phytoliths. This means that stacked fires are indiscernible from one

hour fires, which suggests that repetitive hominin fire use is not discernible through discolored phytoliths in the archaeological record. Specifically, repetitive fire use, which suggests more habituated and curated fire use, cannot be distinguished from one-time opportunistic use, even though they constitute two different types of behavior. Stacked fires should be investigated further in future studies, as small sample size and limits of independence limited current analyses, and stacked fires have important implications for hominin fire behavior.

The large amount of variation within each of the different phytolith assemblages (with respect to proportion of discolored phytoliths) is caused by environmental factors and a small sample size. There is variation both between and within fire conditions. The variation between the samples from each individual fire might be related to how heat is distributed throughout a fire. The fires, especially those set in Ileret site 1, were set in areas that had high winds. Wind impacts fire behavior due to its fanning effect on fire. It impacts fire conditions by supplying more oxygen to the combustion process and reducing fuel moisture by increasing evaporation. In addition to wind, air temperature influences fire behavior due to the heat requirements for ignition and continuing the combustion process. Also, wind can change direction and intensity throughout the day leading to variable effects (Schneider & Breedlove, 2020). These factors highlight the fact that fire temperature is variable and that it cannot be assumed that the center area of the hearth is receiving the highest heat from the fire at all time (Aldeias et al.,2016). The confounding impacts of air temperature and high winds likely had an impact on the variation of discolored phytolith within individual fire contexts. The large amount of variation in proportion of discolored phytoliths between each of the fires of the same condition may be due to the variability of fire conditions and relatively small sample size of fires. Fire temperatures vary greatly depending on the type and amount of fuel used and frequency of refueling. This was

attempted to be controlled through the constant refueling of the fire to keep its temperature above

550 degrees celsius, but there were likely differences between individual fires. The small sample size of each fire type (2 for each stacked condition, 7 one hour fires, 1 twelve hour fire) likely impacted the variability between each fire condition. A larger number of fires would increase confidence on whether or not this variation actually exists. If this variation does stay as sample size increases, then there are more important factors other than time that impact the discoloration of phytoliths. If trends start to develop that relate duration and proportion of discolored phytoliths then time does have a significant impact on the discoloring of phytoliths.

The fact that there is a signal of discolored phytoliths in the pre-fire assemblage without documented fire events highlights the hyper mobility of phytoliths and the reality that phytoliths can discolor for reasons other than burning. There are samples with burned phytoliths from each of the three fire sites. Ileret site 1 is close to the Daasanach community where they use fire for everyday cooking. The Dassanach people pass through the area of the site to get to other parts of

Ileret and move their herds. This movement likely led to the movement of burnt phytoliths to

Ileret Site 1. Also, phytoliths are also highly mobile and can be transported by wind and water action (Madella & Lancelotti, 2012; Pipeerno, 2006, p.21). Ileret Site 1 is located in a laga where water flow from the rainy season could have easily moved discolored phytoliths into the area.

This movement of people and the high natural mobility of phytoliths explains why discolored phytoliths were found in the before assemblage of Ileret Site 1 but does not explain the presence of burnt phytoliths at both of the Karari sites. The Karari sites are located in Sibiloi National

Park where the Koobi Fora Field School’s living and research camp was located. There were small fires set about 100 meters from sites that were used to cook dinner for the research program, but it is unlikely that the discolored phytoliths from these fires ended up in the pre-fire

samples. Discolored phytoliths occur naturally in various plant species, like Myrtaceae and some

Poaceae. This discoloration is likely caused by occluded carbon or manganese or iron staining from the soil solution (Parr, 2006). Naturally discolored phytoliths are likely found at all fire sites, and can explain the presence of discolored phytoliths at the Karari Sites.

5.4 Comparing results to FxJj 20 AB

These trends in phytolith discoloration and variation have important implications for what we expect to see in the archaeological record. First, the fact that the proportion of discolored phytoliths increases as a result of a controlled fire event can allow us to start studying fire signals in the archeological record. Due to the existence of a background signal of discolored phytoliths in the landscape, likely due to prior burning events or natural discoloration, presence of discolored phytoliths does not indicate presence of fire. Other experimental fire research has shown that only deposits directly underlying a heat source will be thermally altered with little or no alteration in the sediments and artifacts outside the fire area (Aldeias et al., 2016). So, if there is a localized area of a site that has a stronger signal than other areas of the site then that area likely contained a controlled fire event. This would be different from a wildfire that would likely have a less localized signal. Other phytolith studies have incorporated the use of phytolith assemblages with micromorphological analysis (Vrydaghs et al., 2016). Micromorphological analysis would complement phytolith analysis in the context of controlled fire extremely well as it would provide information on whether or not the site is in primary context. This localized approach would work well with a precise, microarchaeological excavation like that at FxJj 20

AB.

When looking to compare this assemblage to FxJj 20 AB, it is best to use the quicker burn one hour fires in the analysis, as these fires represent opportunistic fire use. It is likely that hominin fire use at 1.6 mya was opportunistic in nature, where hominins were taking advantage of fire that came from natural sources, like lightning. Hominins likely interacted with opportunistic fires for a particular purpose, like cooking food, and then let the fire burn out. It is unlikely that hominins in the Early Pleistocene were stoking long term fires like those found at

Qesem Cave 400 thousand years ago (Chazan, 2017). This rules out using the 12 hour hearth fire as a model for early pleistocene hominin fire use. Phytoliths might not be best indicators for understanding longer burning hearth sites as the higher likelihood of melted phytoliths skews proportions of phytoliths in the assemblage even before taphonomic processes impact it. These short fires likely did not get hot enough to melt phytoliths, but got hot enough, around 400 to 600 degrees celsius depending on the phytolith type, to alter the phytoliths through discoloration

(Fritzsch et al., 2016). This is important because these Early Pleistocene archaeological phytolith assemblages will not likely not have any biases attributed to melting phytoliths.

One important caveat to using actualistic experiments to model ancient processes is the fact that this experiment is not impacted by taphonomy while ancient phytoliths are. Taphonomic processes can bias ancient phytolith assemblages through post-depositional movement and chemical altering. A major flaw of actualistic experiments is that they only can recreate ideal conditions. This leads to the assumption that the interpretations apply only to artifacts in primary contexts that have not undergone many post-depositional and diagenetic changes. Even with these flaws, actualistic experiments are important because you cannot begin to understand objects in secondary contexts until you understand them in primary context. Since FxJj 20 AB is in primary context, movement of phytoliths is not a large concern. But, the chemical alteration of

phytoliths through other taphonomic processes might be a concern for this site. Fossil diagenesis can impact phytoliths through chemical or physical attacks, bioturbation, disruption of sediment by living organisms, and translocation of the phytolith material (Madella & Lancelotti, 2012).

Fossil diagenesis impacts ancient phytoliths that have been exposed to long term taphonomic processes but will not impact actualistic experimental methods. Even with these differences, experimental phytolith data provides valuable information that can help us further understand the archaeological record.

5.5 Future Experimental Directions

The broad approach of the experimental fire setting procedure gave rise to many issues of independence. The sampling procedure was very general, where samples were taken within the fire, directly outside the fire, and in the prevailing wind direction. This broad approach was taken as an attempt to answer the general questions about phytolith mobility and variation. This thesis only focused on samples within the fire, but still was limited by issues of independence due to sampling strategy. The issues stem from samples from the same fire or location being more related to each other than samples from other fires or locations. This means that fires with the same duration cannot be analyzed together, because each duration has samples from different fires. Also, samples from different locations cannot be analyzed together because they represent different phytolith assemblages. This issue gets further complicated because all of the fires were set directly on top of one specific pre-fire sample which makes those specific pre-fire samples more related to the individual fires than any of the other pre-fire samples. Given the limited size of the dataset, there is no concrete way to explore the variability in the environment of the pre- fire samples that could lead us to treat all pre-fire samples in the one location as the same. This causes the pre-fire samples that are directly related to a fire to either be directly compared to only

that fire or taken out of the dataset completely depending on the type of statistical test conducted.

These issues of independence led to more specific and direct comparisons of the fire samples and limited the type of statistics that could reliably be conducted. These issues can be alleviated with a more precise experimental design.

Future experiments should be designed to mitigate issues of independence and biases.

The experiments from this thesis were modeled after a pilot study where a variety of different samples were collected in order to answer many of our original broad questions about how fire generally impacts phytolith assemblages. Future fire experiments modeled after this thesis should seek to answer specific unanswered questions. By restructuring primary data collection and designing experiments to test specific questions instead of broad interests, there will be fewer issues of independence and bias in the data. One major question that is still unanswered is if the conclusion that fire alters the proportion of discolored phytoliths will remain the same under a more robust data collection process. This question could be better tested with more one hour fires set in one particular location with more precise sampling methods. Answering this question would require more pre-fire samples, likely sampling every 50 cm through the north/south and east/west direction of the site, and multiple samples from each fire that can then be grouped and compared to the other fires. This sampling procedure negates issues of independence and can show a more direct correlation between burning and proportion of discolored phytoliths.

Another issue of independence that should be addressed in future experiments on the variability of pre-fire samples. This thesis had to remove pre-fire samples that were related to a set fire due to the issues of independence. If there is a strong pre-fire signal in the assemblage, then all pre-fire samples can be treated as the same. This could be tested through a more rigorous pre-fire sample procedure at a variety of different fire locations, likely sampling every 50 cm

through the north/south and east/west directions of the site like the proposed experiment above.

This sampling would create a more robust dataset that then can be used to answer questions about environmental phytolith variability.

The issues of time and data robusticity questions whether or not experimental fires are the best way to provide context for the ancient past. Setting fires in the dry heat of Koobi Fora,

Kenya, processing samples, and analyzing the samples through microscopy is a time-consuming process. On top of that, a decent majority of samples for this thesis were unusable for statistical testing due to issues of independence that came from a general sampling strategy. This loss of robusticity impacted the significance of the study and resulted in a lot of wasted time. In order for future experimental fire procedures to be successful, they must have specific questions that are trying to be answered as well as a well-organized and precise experimental design that creates a streamlined experimental process. This more efficient procedure would allow for more fires to be set, increasing the robusticity of the dataset.

There is also an issue of whether or not investigations of fire and phytolith interactions should be continued in an experimental field setting versus a more controlled laboratory setting.

Controlled laboratory fire experiments are important for understanding the theoretical and fundamental properties of phytoliths. For example, Parr (2006) and Fritzsch et al. (2016) used the experimental burning of phytoliths in a laboratory setting to show how fire can discolor and melt phytoliths. Some controlled laboratory fire experiments don’t even use fire and use an application of direct heat to apply stricter controls on fire variability (Aldeias et al., 2016). These laboratory procedures provide valuable information for understanding the properties of fires and heat impacts phytoliths but don’t give any indication of how fire impacts non-controlled settings.

Actualistic experiments try to understand fire interactions in a non-controlled environment, using

trends from experimental data to guide experimental questions and hypotheses. This is distinct from experimentation because actualistic experiments strive to reproduce what might have happened in the archaeological record (Aldeias et al., 2016; Lin et al., 2018). While helpful for providing information on underlying properties of phytoliths, controlled experiments alone don’t give enough information for understanding the archaeological record. The only way to truly understand how fire manifests itself in phytoliths in the archaeological record is through actualistic experimentation.

In addition to changing experimental procedures, future experiments should look at adding a typological analysis and using refractive oil to confirm discoloration. Phytolith type refers to whether the specific phytolith morphology indicates if the phytolith came from grass, sedges, herbs, or wood (Piperno, 2006). This thesis did not examine phytolith type due to time and laboratory constraints. Type can be an important proxy for understanding how the underlying plant material of an environment can change due to fire events, especially since new plant material is brought into the environment to be used as fuel. This is a partially interesting proxy to examine as this thesis showed that phytolith count does not change due to controlled fire events which suggest that new phytoliths from the fuel might not be deposited during burning. But, this conclusion could change if there is a significant change in the type of phytoliths in the pre- and post-fire assemblages. Type can also be used to get a better signal of environmental variability in the pre-fire assemblages. In addition to adding a typological analysis, adding refractive oil the experimental procedure would help confirm if discolored phytoliths were actually burned. Burning phytoliths causes their refractive index to increase. By using a refractive mineral oil and a petrographic microscope, burnt phytoliths can be distinguished from those that were not burned. This method is more accurate than visual

analysis, which was conducted for this thesis, as it relies on the burnt phytolith’s distinctive chemical properties. This is important because discoloration could be organic matter that's trapped between the phytolith particles that is not fully carbonizing that is not the result of a burning event (Elbaum et al., 2013). Using refractive oil prevents false positives to be attributed to burning and can lead to the classification of discolored phytoliths as burned.

5.6 Conclusion

This thesis shows that controlled fire has an impact on the proportion of discolored phytoliths, specifically impacting the number of discolored phytoliths in the assemblage. Results also show that phytolith composition is variable between and within fire contexts which is likely due to fire condition variability and a small sample size. These findings can be used to discern controlled fire at FxJj 20 AB, as localized areas with a higher proportion of discolored phytoliths than surrounding areas suggest the presence of a controlled fire. Future experiments should seek to specialize experimental procedures to answer discrete questions about phytolith discoloration and variability while also using more specific methods, like identifying type and using refractive oil to clarify discoloration due to burning.

Conclusion

Phytoliths are a reliable proxy of ancient environments because of their durability and easy identification, and are often found in archaeological contexts (Piperno, 2006). The objective of this thesis was to understand how phytoliths change when exposed to controlled fire. This question was investigated through the setting of fires of variable duration and analyzing phytolith color and count in pre- and post-fire sediments. The results show that controlled fire has an impact on the proportion of discolored phytoliths, specifically impacting the number of discolored phytoliths in the assemblage. They also show that phytolith assemblage composition is variable between and within fire contexts which is likely due to the multitude of factors that impact fire temperature and sample size.

The findings from this thesis can be used as a metric for understanding controlled fire in the archaeological record, as a localized area with a higher proportion of discolored phytoliths than the surrounding area can indicate the presence of a controlled fire. This study created a fine- tuned understanding of phytolith discoloration in an open air context which can be applied to early sites, like FxJj 20 AB, as a means to show the presence of controlled fire. Combining phytolith analysis with other types of micro-archaeological analyses, like FTIR analysis of artifacts and micromorphology, can create a higher resolution signal of fire than would be achieved with the classic Eurasian hearth model (Hlubik et al., 2017). As a result, more direct evidence of hominin fire use in the Early Pleistocene can be discovered in open-air sites, which have a higher likelihood of post-depositional disturbances. While this evidence cannot reveal whether hominins created fire or used it opportunistically, it can be used to further investigate the

Cooking Hypothesis, which states that certain morphological changes in H.erectus during the

Early Pleistocene resulted from using fire to cook food (Wrangham & Carmody, 2010).

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Appendix

Appendix I: Phytolith Dataset

Fire Fire Analysis Duration Type Sampl Number Total % Discolored Location ID Group # (hour) e Discolored Phytoliths Numb er Ileret 0 1 0 Pre-Fire 1301 3 43 0.069767442 Well Site 1

Ileret 0 1 0 Pre-Fire 1303 2 61 0.032786885 Well Site 1

Ileret 0 1 0 Pre-Fire 1306 0 70 0 Well Site 1

Ileret 0 3 0 Pre-Fire 1307 3 36 0.083333333 Well Site 1

Ileret 0 8 0 Pre-Fire 1309 2 120 0.016666667 Well Site 1

Ileret 0 8 0 Pre-Fire 1311 0 88 0 Well Site 1

Ileret 0 7 0 Pre-Fire 1470 3 169 0.017751479 Well Site 1

Ileret 0 7 0 Pre-Fire 1472 11 363 0.03030303 Well Site 1

Ileret 0 7 0 Pre-Fire 1477 2 160 0.0125 Well Site 1

Fire Fire Analysis Duration Type Sampl Number Total % Discolored Location ID Group # (hour) e Discolored Phytoliths Numb er Ileret 0 7 0 Pre-Fire 1478 7 226 0.030973451 Well Site 1

Ileret 0 8 0 Pre-Fire 1533 6 178 0.033707865 Well Site 1

Ileret 0 8 0 Pre-Fire 1534 1 86 0.011627907 Well Site 1

Ileret 2 2 1 Center 1335 3 30 0.1 Well Site 1

Ileret 2 1 1 Center 1336 0 48 0 Well Site 1

Ileret 2 1 1 Edge 1342 1 81 0.012345679 Well Site 1

Ileret 2 2 1 Edge 1345 4 46 0.086956522 Well Site 1

Ileret 3 3 0 Pre-Fire 1302 0 55 0 Well Site 1

Ileret 3 3 1 Center 1352 6 53 0.113207547 Well Site 1

Ileret 3 4 1 Center 1353 12 67 0.179104478 Well Site 1

Fire Fire Analysis Duration Type Sampl Number Total % Discolored Location ID Group # (hour) e Discolored Phytoliths Numb er Ileret 3 3 1 Edge 1357 1 40 0.025 Well Site 1

Ileret 3 4 1 Edge 1360 0 28 0 Well Site 1

Ileret 4 5 2x1 Center 1366 2 32 0.0625 Well Site 1

Ileret 4 6 2x1 Center 1367 3 193 0.015544041 Well Site 1

Ileret 4 6 2x1 Edge 1370 5 22 0.227272727 Well Site 1

Ileret 4 5 2x1 Edge 1373 1 108 0.009259259 Well Site 1

Ileret 5 1 0 Pre-Fire 1305 1 49 0.020408163 Well Site 1

Ileret 6 2 3x1 Center 1394 1 83 0.012048193 Well Site 1

Ileret 6 1 3x1 Center 1395 2 45 0.044444444 Well Site 1

Ileret 6 1 3x1 Edge 1399 0 114 0 Well Site 1

Fire Fire Analysis Duration Type Sampl Number Total % Discolored Location ID Group # (hour) e Discolored Phytoliths Numb er Ileret 6 2 3x1 Edge 1402 2 45 0.044444444 Well Site 1

Ileret 7 8 2x1 Center 1409 19 129 0.147286822 Well Site 1

Ileret 7 8 2x1 Center 1410 5 152 0.032894737 Well Site 1

Ileret 7 7 2x1 Edge 1414 4 250 0.016 Well Site 1

Ileret 7 7 2x1 Edge 1417 11 190 0.057894737 Well Site 1

Ileret 8 4 3x1 Center 1427 13 28 0.464285714 Well Site 1

Ileret 8 3 3x1 Center 1428 16 164 0.097560976 Well Site 1

Ileret 8 3 3x1 Edge 1433 5 77 0.064935065 Well Site 1

Ileret 8 4 3x1 Edge 1436 3 61 0.049180328 Well Site 1

Ileret 9 5 0 Pre-Fire 1310 1 301 0.003322259 Well Site 1

Fire Fire Analysis Duration Type Sampl Number Total % Discolored Location ID Group # (hour) e Discolored Phytoliths Numb er Ileret 9 5 1 Center 1444 2 102 0.019607843 Well Site 1

Ileret 9 6 1 Center 1445 3 52 0.057692308 Well Site 1

Ileret 9 6 1 Edge 1448 4 35 0.114285714 Well Site 1

Ileret 9 5 1 Edge 1451 2 141 0.014184397 Well Site 1

Ileret 10 5 0 Pre-Fire 1308 1 48 0.020833333 Well Site 1

Ileret 10 5 1 Center 1458 4 632 0.006329114 Well Site 1

Ileret 10 6 1 Center 1459 4 51 0.078431373 Well Site 1

Ileret 10 5 1 Edge 1463 4 265 0.01509434 Well Site 1

Ileret 10 6 1 Edge 1466 6 89 0.06741573 Well Site 1

Ileret 11 6 0 Pre-Fire 1469 5 135 0.037037037 Well Site 1

Fire Fire Analysis Duration Type Sampl Number Total % Discolored Location ID Group # (hour) e Discolored Phytoliths Numb er Karari 11 5 1 Center 1485 6 181 0.033149171 Site 1

Karari 11 6 1 Center 1486 2 139 0.014388489 Site 1

Karari 11 6 1 Edge 1490 1 108 0.009259259 Site 1

Karari 11 5 1 Edge 1493 0 132 0 Site 1

Karari 12 6 0 Pre-Fire 1471 2 49 0.040816327 Site 1

Karari 12 5 1 Center 1498 4 42 0.095238095 Site 1

Karari 12 5 1 Edge 1506 11 338 0.032544379 Site 1

Karari 15 3 0 Pre-Fire 1476 1 29 0.034482759 Site 1

Karari 15 3 1 Center 1556 9 39 0.230769231 Site 1

Karari 15 3 1 Edge 1563 9 124 0.072580645 Site 1

Fire Fire Analysis Duration Type Sampl Number Total % Discolored Location ID Group # (hour) e Discolored Phytoliths Numb er Karari 17 2 12 Center 1580 4 181 0.022099448 Site 2

Karari 17 1 12 Center 1581 1 118 0.008474576 Site 2

Karari 17 2 12 Edge 1586 3 95 0.031578947 Site 2

Karari 17 1 12 Edge 1589 2 32 0.0625 Site 2

Appendix II: Fire Temperatures

Fire 2 Temperature (1hr) 600 C) ° 400 200 0 0 20 40 60 80 100 120

Temperature ( Time (Minutes)

Center North South East West

Fire 3 Temperatures (1hr) 600 C)

° 400 200 0 0 20 40 60 80 100 Time (Miuntes) Temperature (

Center North South East West

Fire 4 Temperatures (2x1hr) 600 C)

° 500 400 300 200 100

Temperature ( 0 0 20 40 60 80 Time (Miuntes)

Center North South East West

Fire 6 Temperature (3x1hr) 600 C)

° 500 400 300 200 100 Temperature ( 0 0 10 20 30 40 50 60 70 Time (Miuntes)

Center North South East West

Fire 7 Temperature (2x1hr) 600 C)

° 500 400 300 200 100 Temperature ( 0 0 10 20 30 40 50 60 70 Time (Miuntes)

Center North South East West

Fire 8 Temperature (3x1hr) 600 C)

° 500 400 300 200 100 Temperature ( 0 0 10 20 30 40 50 60 70 80 90 Time (Miuntes)

Center North South East West

Fire 9 Temperature (1hr) 600

C) 500 ° 400 300 200 100 Temperature ( 0 0 10 20 30 40 50 60 70 80 90 100 Time (Miuntes)

Center North South East West

Fire 10 Temperature (1hr) 600 C)

° 500 400 300 200 100 Temperature ( 0 0 10 20 30 40 50 60 70 Time (Miuntes)

Center North South East West

Fire 11 Temperature (1hr) 600 C)

° 500 400 300 200 100 Temperature ( 0 0 10 20 30 40 50 60 70 Time (Miuntes)

Center North South East West

Fire 15 Temperature (1hr) 600 C)

° 500 400 300 200 100 Temperature ( 0 0 10 20 30 40 50 60 70 Time (Miuntes)

Center North South East West

Fire 17 Temperature (12 hour) 600 C)

° 500 400 300 200 100 Temperature ( 0 0 100 200 300 400 500 600 700 Time (Miuntes)

Center North South East West