An Experimental Approach to Ceramic Sherd Variation

A thesis submitted to Kent State University in partial fulfillment of the requirements for the Degree of Master of Arts.

Ashley M. Rutkoski

Thesis written by Ashley M. Rutkoski B.S., University of Akron, 2014 M.A., Kent State University, 2019

Approved by

Metin I. Eren , Advisor Mary Ann Raghanti , Chair, Department of Anthropology James L. Blank , Dean, College of Arts and Sciences

TABLE OF CONTENTS TABLE OF CONTENTS………………………………………………………………...iii LIST OF FIGURES…………………………………………………………..……..……iv LIST OF TABLES……..…………………………………………………………………………....v DEDICATION……………………………………………………………………….…...vi ACKNOWLEDGMENT…………………………………….………………….…....….vii CHAPTERS I. INTRODUCTION AND BACKGROUND…………………………….………...1 1.1 Ceramic in the Archaeological Record………………..……….;…...... 1 1.2 Experimental Approaches……………………..……………………………....3 1.3 A Biological Approach to Sherd Variation..…....….………………………...4 II. MATERIALS AND METHODS………………………………….……………..13 2.1 Pottery Design…………………...…………..……………...…...... 13 2.2 Clay Preparation and Processing..…………..……………...…...... 14 2.3 Temper Section and Processing.………..……………………………………18 2.4 Vessel Production…….……..……………………………………………….22 2.5 Firing Conditions………….…………………..……………………………..25 2.6 Experimental Design and Setup……………………….....………...... 26 III. RESULTS………………………………………………………………………..33 3.1 Sherd Counts…………….…..…………….………………...…...... 33 3.2 Sherd Weights...…………………………………………………...... 36 3.3 Sherd Gross Morphology……………………………….….....…………..….37 IV. DISCUSSION AND CONCLUSIONS…….……………………...…………….39 REFERENCES…………………………………………………..…...... 44

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LIST OF FIGURES Figure 1-1. A quantitative genetic model of sherd variation….…………………..……………..12 Figure 2-1. Cleveland Natural History Museum vessel……………...………………....………..13 Figure 2-2. Clay preparation and processing……...…………….……………………………….17 Figure 2-3. Temper preparation and processing……………………………………….……..….20 Figure 2-4. Mixing clay and temper together…...……………………………………...………..21 Figure 2-5. Vessel building process…………...………………..…………………………..…....24 Figure 2-6. Pots after being fired in the kiln………...………………………………………..….25 Figure 2-7. Vessel measurements………………...……………………………..……………….27 Figure 2-8. Breakage experiment………………………………….……..……...... ………30 Figure 2-9. Gross morphometric sherd analysis measurements ………...……...……………….31 Figure 3-1. Sherd type distribution by group…...... ……………………………..……………….35 Figure 3-2. Sherd weights graphs showing the populations are not normally distributed…...... 36 Figure 3-3. Graphed discriminant function analysis showing the two group are identical…..….38

LIST OF TABLES

Table 2-1. Vessel discriminant function analysis results ………………………………..……....28

Table 2-2. Vessel discriminant function classification results ……...…………………………...28

Table 3-1. Std Residuals by Type ……………………………………………………………….34

Table 3-2. Std Residuals Base and Body Sherds Only……….………………………………….34

Table 3-3 Sherd gross morphology discriminant function results……………...………...……...37

Table 3-4. Sherd discriminant function classification results ……….………….……………….37

DEDICATION To Icle Davis, who always believed that things come and go, but an education is something no

one can take away from you.

ACKNOWLEDGMENTS I would like to thank my advisor, Dr. Metin Eren for his continued support and guidance through writing my thesis and beyond. I would also like to thank Dr. Briggs Buchanan for

allowing me to come to Tulsa, Ok to work on this project. I would like to thank the rest of my

committee members, Dr. Mary Ann Raghanti and Dr. Linda Spurlock for their continued support and contributions. A special thank you to Dr. Richard Meindl, who was always willing to answer

my multitude of stats questions. The GSS Research Award provided the funds to complete this

thesis project and the Mark F. Seeman Fund provided funding for the kiln used in this experiment. Last but not least, Michelle Bebber who helped teach me the art of clay processing.

Without everyone’s support, this journey would have been a lot tougher.

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Chapter 1

Introduction and Background

1.1 Ceramics in the Archaeological Record

Ceramics have been manufactured, decorated and used in a variety of cultures around the world for thousands of years (Usman et al., 2005; Skibo et al., 2016; Rice, 2015; Townsend,

1985; Denbow, 1986; Roux and County, 1998; Brown, 1996 Sarjeant, 2014; Cochrane et al.,

2013). The oldest dated vessels come from Eastern Asia almost 20,000 years ago with clay figurines existing even earlier in time (Craig et al., 2013; Soffer et al., 2000). The long-standing tradition of pottery use has been essential for food preservation, cooking, and a form of artistic expression for prehistoric people. The sheer amount of ceramic materials found in the archaeological record has informed our understanding of the past, not solely based on it’s

production, but also how it reflects the changing societal needs and wants. The constant change

in vessel morphology, manufacture, and style throughout time creates a unique glimpse of what

types of behavioral drivers affect the variation in product.

Although understanding human behavior has always been a goal of archaeology, the

beginning of ceramic analysis focused on classification, typology, and seriation. The debates over how to correctly classify artifacts and which methods we should use, have long been disputed within archaeology because of the inability to address the core reason for or the subjective nature of classification (Dunnell, 1986, 1971, 1978; 1980; Fish, 1978; Hill and Evans,

1972; Clarke, 1973). Over time, the popularity of particular ceramic types within an assemblage sparked a decades-long use of pottery seriation to create a timeline (Gelfand, 1971; Cowgill,

1972, Marquardt, 1978; Hatch et al., 1982; LaPorte and Taillefer, 1987). Early archaeological methods aimed to organize the past through the use of these traditional methods. However, the focus on traditional methods has limited the expansion of our knowledge about why prehistoric people were making specific material or stylistic choices.

Recently, archaeological analysis in general has been more focused on using material science and quantitative approaches to understand artifactual change (Clarke, 1973; Aldenderfer,

1998; Smith et al., 2012, Lycett and Shennan, 2018). With respect to ceramics, there has been an influx of studies focusing on technological innovation and migration, compositional analysis, performance characteristics and chemical analyses, all geared toward refining our knowledge of prehistoric human behavior (Hoard et al., 1995; Tite, 1999, 2008; Kampel et al., 2001; Saragusti et al., 2004; Fernández-Ruiz and Garcia-Heras, 2008; Muller et al., 2010, 2016; Bebber, 2017;

Bebber et al., 2018; Frahm, 2018; Cochrane et al., 2013; Galaty, 2008; Berg, 2007; Arnold,

2012; Glascock and Neff, 2003; Ther, 2016; Skibo et al., 2016; Rutkoski et al., 2018). The application of these new techniques within the field of archaeological ceramics can be difficult when we find these vessels in pieces-as is often the case.

Whole vessels are a rare occurrence in the archaeological record, often found as small fragments. Humans in general are rough on pottery which has been documented in many ethnographies; they are used for a variety of tasks that lead to their breakage before being deposited (Kobayashi, 1974; DeBoer et al., 1979; Stark, 1991; LeeDecker, 1994; Wilson,1994;

Underhill, 2003; Williams, 2018). For example, a cooking vessel undergoes many episodes of extreme heating and cooling that leads to the vessel breaking under pressure, and thus being

discarded (Hildebrand and Hagstrum, 1999). The context of discard, accumulation, and breakage

rates within an assemblage and midden maintenance activities have all been examined to

understand the role of discard in the formation of the archaeological record (Pauketat, 1989;

LeeDecker, 1994; Tani, 1995; Shott, 1996; LaMotta and Schiffer, 1999; Varien and Potter, 1997;

Hildebrand and Hagstrum, 1999; Sullivan, 2008; Rosenswig, 2009). The breakage continues

post-depositionally by both physical means of trampling, as well as chemically worn by harsh soils and weather conditions (Nielson, 1991; Skibo and Schiffer, 1987; Blackham, 2000;

Rosenswig, 2009; Kibblewhite et al., 2015). Small fragments are often all that is left to analyze, especially when found in areas not favorable for preservation. Small sherds are thus our main source of knowledge about prehistoric ceramic production and use.

Discard behaviors that have led to ceramic breakage have been previously thought of as

noise that interfered with archaeological analysis (Hatch et al., 1982). These notions have since

changed to reflect discard behavior as a series of complex physical activities that can be used to

make inferences about human behavior (Kobayashi, 1974; Pauketat, 1989; LeeDecker, 1994;

Tani, 1995; Schiffer, 1996; Rice, 1996; Hildebrand and Hagstrum, 1999; Clayton et al., 2005;

Rosenswig, 2009; Blanco-Gonzalez, 2015). Although perspectives have shifted, there still

remains limited research attention on utilizing sherds themselves, except for the use of sherds for

refitting as well as various types of vessel size and volume estimations. Sherd analyses often

focus on the composition and classification of these small fragments. Compositional analysis of

sherds explores variation in minerals within clay by using petrographic analysis, X-ray

fluorescence spectrometers (XRF) and X-ray diffraction (XRD) (Ertem and Demirci, 1999;

Quinn, 2013; Frahm et al., 2018). Classification studies have turned toward computerized

methods of digitizing sherds to create a consistency in assignment (Gilboa et al., 2004; Mara et al., 2007; Di Angelo et al., 2018).

Archaeologists have employed the use of refitting studies to examine sherd frequency, dispersal, and ability to reconstruct vessels in an assemblage as a way to make inferences about human activity and site relationships (Skibo et al., 1989; Blanco-Gonalez, 2014; Blanco-

Gonzalez, 2015; Plutniak et al., 2016). For example, Clayton et al. (2005) try to reconstruct vessels while also considering the original context of the sherds that fit together. The sherds’ dispersion and role in vessel reconstruction led to inferences about human discard behavior at different sites across Mexico. Clayton et al. (2005) is one of the few studies that try to discern a difference between continuous long-term and ritualistic discard based on sherd spatial relationships, ultimately concluding that ritualistic discard is often over cited. Although these studies are trying to infer information about human behavior, they rely on a number of assumptions about discard behavior, site formation, and the accuracy of ethnographic parallels

(Varien and Mills, 1997). Even with these criticisms, sherd refitting studies have value in answering very specific questions about human behavior.

1.2 Experimental Approaches

Scholars have continued to look at sherd assemblages to develop different ways to make inferences about use, population size, and site occupation span by viewing sherds as proxies for learning about the original vessels. Sherd morphology has been examined and evaluated to fit various formulae to predict the original features of the vessel including size, volume, and number of vessels within an assemblage (Egloff, 1973; Orton, 1982; Senior et al., 1995; Pauketat, 1989).

These studies were used in a growing sub-field of ceramic archaeology (i.e., functional analysis), which focused on vessel morphology as a key to understanding its usage. Vessel morphology was used to hypothesize about the function of vessels by correlating specific ceramic attributes to functional advantages. Vessel size and volume were viewed as measures to provide information about what these past pots were used for (Whittlesey, 1974; Smith, 1988; Hally, 1986; Mills,

1989; Hagstrum and Hildebrand, 1990; Whalen, 1998). For this type of analysis, whole vessels were needed which presented a problem since most pots are in pieces. Vessel estimation formulas were constantly being refined to create accurate representations of past pottery. This perspective led to the rise in experimental procedures to create more accurate methods for reconstructing vessel types. Ericson and De Atley (1976) developed a method for estimating morphological characteristics of a vessel from sherds by categorizing each sherd’s shape and size to test how well the classifications correlated with specific vessel segments, ultimately leading to vessel size and volume estimates (Ericson and Stickel, 1973; Ericson and De Atley, 1976). In

1985, Chase explored the relationship between counts and weights of sherds in vessels that varied in size, shape, and thickness. The results showed that various variables produced different types of sherds counts and weights, leading to the conclusion that vessel estimation is more complex than any one single formula (Chase, 1985). Although these studies encouraged the use of experimental methods in the field of archaeological ceramics, the evaluation of sherds was centered on the accuracy of vessel reconstruction over behavioral data. As stated by Rice (1996) the accuracy of sherd to vessel estimation methods have been heavily scrutinized due to the oversimplification of the relationship between pottery morphological attributes and vessel function. The development of a vessel is not solely dictated by function but by a complex mash of influences, choices made by the potter, and the environment in which it was created (Rice,

1996). The complexity of understanding pottery design and the mental processes that lead to their creation must include well-rounded approaches, experimentally test hypotheses, uses ethnographic parallels, and understand the physical properties of clay (Rice, 1996). In order to get away from making “inferred uses” about the complexity of artifactual design, archaeologists must use methods that reflect a conceptual framework that understands artifact variation (Rice,

1996).

1.3 A Biological Approach to Sherd Variation

One of the most influential pieces of literature, On the Origin of Species details descent with modification through the slow gradual change of specific traits via natural selection

(Darwin, 1859). The variation within a population was created by an unknown reproductive mechanism that ultimately helps a certain individual survive and reproduce while others perish.

Since its publication, the biological sciences have continued to explore micro and macro level processes by using new techniques to understand biological change (Morange, 2000; Mesoudi,

2011). Archaeology has been slower to adopt these biological principles of evolution and develop techniques that can be applied to the archaeological record (Dunnell, 1980; Neff, 1992;

O’Brien and Holland, 1990; O’Brien and Lyman, 2000; Eerkens and Lipo, 2008; Mesoudi, 2008;

Mesoudi, 2017). The variation that Darwin saw in biological populations parallels the variation seen in archaeological assemblages. The misuse of evolutionary approaches that explained cultural evolution as progressing toward a racial ideal, led to a hesitation in adopting evolutionary approaches in archaeology (Freeman et al., 1974; Trigger, 2006; Mesoudi, 2017).

Archaeology was at a stalemate with trying to explain cultural change without an evolutionary mechanism (Trigger, 2006). The inability to describe cultural change led to the adoption of select portions of evolutionary theory (Dunnell, 1989; Lyman and O’Brien, 1998; Mesoudi, 2008;

Mesoudi, 2017). However, within the last twenty years there has been a change toward accepting

and applying evolutionary mechanisms to explain ceramic change within the archaeological

record (Neff, 1992; O’Brien et al., 1994; Neiman, 1995; Shennan and Wilkinson, 2001;

Cochrane, 2002; Bentley and Shennan, 2003; McClure, 2007; Eerkens and Lipo, 2008; Shennan,

2011; Roux, 2013; Cochrane and Lipo, 2010).

An evolutionary approach to artifact variation began through exploration of technological innovation (Binford, 1963; Clarke, 1968; Dunnell, 1980; Mesoudi, 2011; Lycett and von

Cramon-Taubadel, 2015). Within the field of ceramics, variation in both style and function were being explored through an evolutionary lens. The production of ceramic variants within a population was attributed to two sources of variation: stylistic preference (or lack thereof) and function (Neiman, 1995; Shennan and Wilkinson, 2001). One of the most notable studies,

Neiman (1995) examined stylistic variation in Illinois Early to Late Woodland period ceramics by using methods borrowed from populations genetics (Crow and Kimura, 1970; Neiman, 1995).

The goal was to evaluate the within and between group interaction of each period by examining the ceramic frequencies. Archaeologists have always thought that innovation and interaction between groups throughout the Woodland Period was in a steady incline, reaching the maximum during the Late Woodland Period. However, Neiman’s analysis showed that the Early and Late

Woodland period sites reflected uniform groups that rarely interacted with other groups/sites.

The Middle Woodland period reflected a time of innovation with continuous networking with

other groups at different locations. This approach reflected varying levels of social interaction

that influenced the outcome of pottery variation at various sites during the Woodland period

(Neiman, 1995; Mesoudi, 2011; Lycett and von Cramon-Taubadel, 2015). In the early 2000s,

Shennan and Wilkinson (2001) applied the same population genetic model to Neolithic German

pottery with a different result (Neiman, 1995; Shennan and Wilkinson, 2001; Mesoudi, 2011;

Lycett and von Cramon-Taubadel, 2015). The Neolithic Pottery frequencies at the two sites

showed a preference for a particular style, reflecting a “selection” approach to decoration instead

of the “genetic drift” scenario in seen Neiman’s Study (Neiman, 1995; Shennan and Wilkinson,

2001; Mesoudi, 2011; Lycett and von Cramon-Taubadel, 2015). However, the population genetic

approach was originally designed to study allele frequency changes in a population and becomes

less effective when applied to populations that are subjected to multiple sources of variation

(Lycett and von Cramon-Taubadel, 2015). Steele et al. (2010) demonstrated the caution of using

this model because of the other factors leading to variation in function. The Hittite rim sherds

showed no selection toward a particular type while other aspects of vessel morphology were

being selected for. The identification of specific sources of variation will not always be evident,

thus viewing variation in discrete units is not adequately showing diversity among ceramic

populations (Steele et al., 2010). These studies integrated a new set of techniques from the

biological sciences to further our understanding of ceramic evolution. However, the need for a

model that incorporates both known and unknown sources of variation is one that can be applied

to the archaeological record.

Within the field of lithic technology, Lycett and von Cramon-Taubadel (2015) detailed multiple sources of variation that affect stone tools. Lithic artifacts are a culmination of variation that is created by Culture (anything inherited through social learning) + Raw material (material and its physical properties) + Reduction (ontogeny: development and senescence: life/use wear).

Social learning is often defined as the way in which simple to complex observations and interactions are passed down from generation to generation, ultimately influencing artifact form

(Lycett and von Cramon-Taubadel, 2015; Shennan, 2011; Bentley and O’Brien, 2011; Neff,

1992). Non-inheritable sources of variation that affect artifact form are umbrellaed under raw

material, development, and aging of an artifact. Lycett’s lithic model documents the multiple

sources of variation in lithic technology by using a “quantitative genetic framework”. The

quantitative genetic model borrowed from biology incorporates inheritable and non-inheritable

sources of variation under one seamless archaeological framework that can be used to study

artifact variation using evolutionary procedures. Although individual artifacts are highly

variable, at the population level, artifact distributions are continuous because of the information

that dictates an artifacts form is inheritable. Inheritability, in both quantitative genetics (DNA)

and cultural evolution (social learning) is what makes a population’s distribution continuous.

These shared features will create an overlapping population distribution that is swayed in

different directions based on each population’s sources of variation. These various factors that

influence the way an artifact looks also affects the overall patterns of variation in each

population. The goal then becomes to statistically test how different the overall variation is

between two populations (Lycett and von Cramon-Taubadel, 2015).

Lycett’s model of variation has furthered the field of lithics by presenting a new approach to understanding how artifacts change over time. Lycett’s work in lithic technology has defined cultural evolution within a modern “quantitative genetics” perspective that is more in tune with the complex reality of multiple sources of variation that dictate their form. Cultural evolution as a concept has received its fair share of criticisms due to the common misconception of artifactual change being viewed in a strict genetic capacity and the misuse of evolutionary theory in the past

(Trigger, 2006; Mesoudi, 2011; Lycett and von Cramon-Taubadel, 2015; Mesoudi, 2017). The point is to use a theoretical framework that views artifacts as representations of complex decision making and environmental factors that occurred in the past. With the use of an evolutionary

approach to archaeology, we can begin to incorporate a new repertoire of techniques to model

artifact change.

Lycett and other scholars have since applied similar techniques to other stone tool

populations (Eren et al., 2015; Eren et al., 2016; Lycett et al., 2016; Schillinger et al., 2017; Key and Lycett, 2017). The advances in lithic research within the last decade have furthered archaeological science as a whole and can thus be applied to the ceramic field. Ceramic artifactual variation can be placed within the quantitative genetic model. Social learning plays a key role in vessel formation, dictating behind the scenes how vessels will ultimately look. Raw material selection of clays and temper create different recipes that affect various aspects of workability, plasticity, and other physical properties that affect vessel form and survivability

(Rye, 1980; Bronitsky, 1986; Rice, 1996; Tite, 1999; Bebber, 2017). The development of a pot and how it is used can be affected by external environmental factors including firing and air temperature (Cogswell et al., 1996). These are small examples of how pottery can be influenced by various factors of variation, presenting a need for a similar “quantitative genetic” approach

(see Figure 1-1). By looking at pottery using a similar “quantitative genetic” framework, we can incorporate techniques that have expanded the field of lithic technology to explore patterns of variation in ceramic populations.

The use of a cultural evolutionary approach to ceramics is a new way of conceptualizing ceramic pot sherd variation. With this in mind, a simple experimental procedure was designed to explore a source of non-inheritable variation (i.e., one not caused by social learning). Thirty hand-built pots were created and separated into two distinct groups: one that was filled with corn and one that was empty. The two groups were then broken to simulate being discarded. By controlling for all other sources of variation, we can thus statically evaluate if the difference in

these experimental conditions creates an overall difference in the distribution of the sherd populations. If this method shows a statistical difference between the two conditions, the method can be refined to be applied to actual archaeological collections. This new avenue of research could lead to a better understanding of what prehistoric people were actually doing with these vessels. This method aims to obtain direct behavioral data that other studies have had trouble obtaining. The combination of using a new theoretical perspective and experimental methods creates a new way of examining human behavior.

Figure 1-1: A quantitative genetic model of sherd variation. Sherd variation can be classified under inheritable and noninheritable sources of variation. Inheritable variation (VCulture) refers to anything that is inherited through social learning which effects vessel formation. Non inheritable sources of variation are separated into Raw Material and Production. VRaw Material refers to the variation caused by the material properties of clay and its additives. Clay can vary by being composed of different minerals and clay particles, effecting its physical properties. Clay is rarely made without temper or a clay additive. Additives refer to variation in material properties of the temper added to clay or a material added to the surface of a vessel. However, Raw materials can also be associated with social learning by potters selecting for specific raw material for workability, reduction in spalling rates etc. Vproduction refers to how a vessel is formed and ultimately used. Vessel formation is both a reductive and additive process. All of these sources of variation add up to a total amount of variation that effects vessel formation and ultimately sherd formation.

Chapter 2

Materials and Methods

2.1 Pottery Design

The importance of utilizing experimental methods to address archaeological questions has been encouraged by many scholars (Skibo, 1992;

Schiffer et al 1994; Roux and Courty, 1998;

Cochrane, 2002; Outram, 2008; Pierce, 2005;

Jeffra, 2015). Most experiments in the past have utilized modern materials to answer various questions about prehistoric ceramics, even though modern materials have different physical properties and are made with different social influences in mind. It is important– depending on the question, of Figure 2-1: Cleveland Natural History course– for archaeologists to recreate past pottery Museum Vessel using similar material and methods to those of prehistoric practitioners. Choosing a pottery design that was actually present in the archaeological record was essential for this study to be applicable to real archaeological sherd collections. In order to create a pot that existed in the past,

I went to the Cleveland Natural History Museum to examine their large collection of Ohio pottery. Within the collection, there were about fifteen vessels that have been collected at

different excavations throughout Ohio. Whole pots are very rare, especially in Ohio. From these

pots, I selected a grit tempered utilitarian vessel from the Early Late Woodland period because it

was both beautiful and practical for holding a significant amount of corn (see below). The model

pot originated from a pit feature within the Rainstorm site, located along the southern shore of

Lake Erie. The vessel used had portions of the base missing which led to the bottom being

estimated by a vessel from Sissung site (20Mr5) due to its similarity (Sthothers and Abel, 2002).

The Rainstorm and Sissung sites have very similar pottery traditions, used similar materials, and

thus also likely similar conical base shapes- that the broken Rainstorm vessel would have had.

Thus, the original vessel was measured and combined with the measurements of the base from

the Sissung vessel, creating the model design.

2.2 Clay Preparation and Processing

In order to understand prehistoric pottery manufacture, local Ohio clays were mined to

create the model pot design. Modern clays have very different properties than local clays because

they are more heavily refined by machinery, creating clays with fewer impurities than those used

by prehistoric people. Using modern clay that has been refined to meet the needs of ceramic

artists removes the trials and tribulations that prehistoric people would have encountered when

processing local clays. In order to create the best replica of an Early Late Woodland vessel, I

obtained clay from a local source in Norton Ohio called Flesher’s Sand and Gravel. The

company mines clay and gravel from the property that would be comparable to what Late

Woodland groups would have been using (i.e., lower quality glacial clay). Nine buckets of clay were collected from Flesher’s and were brought back to the lab to be processed for the experiment.

After obtaining the clay from a local source, the clay needed to be processed to remove

debris, impurities, and coarse grain material that would affect the workability of the clay. The

exact mechanisms for how prehistoric people in Ohio would have processed clay is still

unknown. However, some type of processing would have been required to isolate the small clay

particles from sediment (Rice 2015; Rye;1981; Sillar and Tite, 2000). The clay processing begins

with separating each bucket of clay into three separate buckets so water can be added. The water

serves two purposes: to remove impurities by aiding the sieving process and to hydrate the clay.

After being separated, clay filled buckets sat for at least 48 hours to make sure the water

hydrated the dry clay. The next step was to break up the clay while removing large sediment and

vegetation. To further remove impurities, the process employs the use of multiple sieves starting

with a ½ inch mesh going to ⅟12 inch mesh screen. The sieves were placed over an empty bucket that the watery-clay or slip would be poured into, sieving out the large material. The next size

sieve would then be used, repeating the same process until reaching the smallest size. After each

bucket went through the four sieves, it would sit for 48 hours to aid in separating the clay and

large particle sediment. One final round of sieving through all four sieves would be done before

the levigation process.

Levigation is the natural process of separating clay from the larger sediment and water.

Leaving the watered-down clay to sit for at least 24 hours allows the water to separate from the

clay and the large sediment. The larger sediment which consists of sand and large clay particles

will collect at the bottom of the bucket, leaving the smaller clay particles in the middle to be

collected. The clay can thus be extracted by slowing pouring the water off the top. The clay layer

can then be poured into another bucket, leaving the larger particle sediment stuck to the bottom

of the bucket, to be discarded. This process is important because of the larger particle sediment

and water effect the clay’s workability. The use of sedimentation isolates the clay particles that are better for constructing vessels. The levigation process was completed twice to make sure the larger sediment particles were removed. The last phase of clay processing was to let the clay sit while monitoring the clay over a couple of days to remove the excess water that remained within the clay layer. As the water was removed, the clay was consolidated back into seven buckets.

After removing most of the water, the clay would need to be dried to reach the desired consistency for vessel workability. The drying process included creating a plywood base that was covered in fabric. Clay doesn’t stick to the fabric as it dries, allowing it to be easily removed and collected. The clay slip was thinly spread over the fabric plywood base to be dried out to a plastic, more workable state. The plywood base was situated on bricks to create airflow under and above the base, shortening the drying time. The clay was monitored to make sure it was not drying too quickly. It generally took two days for the clay to become plastic. The clay was then removed from the fabric and placed in a bucket.

2.3 Temper Selection and Processing

Throughout the Woodland period, grit tempered ceramics were continuously used until

they were replaced by limestone at the end of the Late Woodland Period (Prufer, 1968;

Brown,1996; Lepper, 2005;). The use of silicate-based granitic rock was added to clay for some type of production or post-firing benefit. The long-standing idea in ceramic archaeology suggested that adding temper increased vessel strength (Feather, 1989; Hoard, 1995). However, recent ceramic research suggests that adding temper does not add strength to vessels, suggesting some other type of benefit (Bebber, 2017; Bebber et al., 2018). For whatever reason, prehistoric people utilized grit tempered ceramics for thousands of years. The earliest grit tempered vessels come from the Late Archaic period from sites including Johnson II, Rais Rock Shelter, and

Stanford Knoll (Brown, 1996). The long use of this temper and the availability of a grit tempered vessel from the Cleveland Natural History Museum made this a good temper type to use for this experiment.

The granitic rock was sourced from Norton, Ohio from Flesher’s Sand and Gravel. The granitic rock was collected with other types of gravel. In order to ensure all the rock was granitic, each piece was hand selected on sight from a large pile. Three buckets of granitic rock were collected and taken back to the lab to be processed. Granitic rock that was used in prehistoric pots was fired before being crushed up into tiny fragments. Firing the granitic rock aids in the crushing process. In petrographic studies of southern Ohio ceramics, Bebber (2017) recorded a majority of the grit temper within the vessel to be below 2 mm. Crushing this material to this size without firing seems to be nearly impossible without modern machinery. Granitic rock was already being used for cooking and building hearths, suggesting an easy transition to using this abundant resource (Graesch et al., 2014). To prepare the rocks for firing, the granitic rocks were

sorted, washed, and dried. After the rocks were dried, they were placed into the kiln at a

temperature of 763° C, the approximate average temperature of a bonfire (Livingstone-Smith,

2001). Most of the grit temper found in ceramic vessels in Ohio is very small in size, ranging from coarse grit (2 mm) to silt size (0.0625 mm) (Bebber, 2017). Crushing rocks to this size by hand is labor-intensive and time-consuming. In order to save time and energy, as well as increase the consistency of the rocks produced, a manual rock crusher was used. The “Crazy Crusher” as it is referred to colloquially, is a gold mining rock crusher used to break rocks into pebbles in order to extract gold and other minerals. It operates by adjusting the size of the opening so the rocks can pass through by tightening a lever which moves the steel plates closer together. The rocks are placed into the crushing chamber, and then manually crushed by the steel plates that move closer together by lifting a handle up and down. The handle is continuously pulled until all the rocks fall through the small opening at the bottom into a tray below. The lever at the bottom, controlling the opening, was then tightened to the next smaller size. The rocks were crushed in three stages, making it easier to crush the rocks into a 2 mm size or less. Multiple sieves were used to sort the size of the crushed granitic rock, confirming the temper used was below 2 mm. A majority of the rocks were crushed to below 1mm size, following the petrography results of

Bebber (2017). The petrographic analysis from Bebber (2017) looked at the Peter’s Cave site

(33Ro18) in southern Ohio. Peter’s cave is primarily an Early Woodland site, however, temper ratios in Ohio remain consistent at 30%, even when switching to carbonate tempers (Bebber,

2017). With this in mind, the average grit temper ratio of 29% was used to create the experimental recipe (Bebber, 2017). Approximately two and a half buckets were filled with crushed rock to have enough temper for the seven buckets of raw clay.

The grit was measured using a clear tub that had measurements on the side which made it easy to calculate the required ratio. The grit temper was then poured in the tub to the 29% line.

The clay slurry was then added to the top of the tub. The mixture was then poured onto a clean fabric sheet to wedge the clay and temper together. Wedging is a common technique used to remove air bubbles by continuously folding the clay over onto itself or by slamming the clay onto a hard surface. Continuing to wedge the clay, the grit was slowly incorporated into each folding episode until the grit was thoroughly mixed in. The clay is then slammed onto the table, rotating while wedging to make sure all sides of the clay were worked. The grit temper dried the clay to a more workable plastic state which may have served as an advantage to prehistoric clay makers (Rye, 1981; Bronitsky, 1986; Rice, 1996; Tite, 1999; Bebber, 2017).

This process was time-consuming because only a small amount of clay was mixed at a time to ensure the temper was equally mixed. However, the small batches were then wedged with the other clay batches to ensure they were all mixed similarly. A wire tool was used to cut up the small clay batches that were then incorporated into one large bundle, thus being wedged together.

2.4 Vessel Production

There are various types of hand building methods that can be used to build a vessel including slab, pinching, and coiling. A wide variety of methods have been employed to explore

what types of techniques were used to build vessels in different geographic regions (Sanger,

2016; Ther and Toms, 2016; Berg, 2011). Within Ohio, X-raying pottery has been used to identify the primary use of the slab building techniques (Carr, 1990). However, multiple scholars suggest the need for further work to understand pottery manufacture, especially with the development of better X-raying techniques and new technology (Carr, 1990; Sanger, 2016; Berg,

2011). Based on the limited data on Ohio pottery manufacture, the commonly cited technique of slab building was used to be consistent. A slab roller was used to create consistent vessel wall thickness. A slab roller is a common tool in ceramic studios that is basically a table with a large rolling pin attached. The rolling pin is moved by a wheel that allows the clay to be flattened to a consistently thick slab of clay. The slab roller was set to 10 mm to allow for some shrinkage that

happens as the clay dries during and after firing. This thickness fell within the range of the grit

tempered vessels measured at the museum which range from 8 to 11mm. Although, it was on the

higher side which helped in the building process.

Pots were made in sets of four due to the drying time needed to keep the vessel upright.

The vessels were built in three steps: base, body, and rim. Building the pot too quickly without

adequate drying time causes the vessel to fall over. The moisture that makes the clay workable also contributes to the clay being easily deformed. As the clay dries, it becomes stronger and thus able to support the weight of the whole vessel. Building the vessel in stages allowed the clay to dry enough to support the next step in the building process. The base was formed first using strictly hand building techniques. The curved nature of the base made it very difficult to use

slabs to get the desired conical base shape. For consistency, the base was made using a pre- weighed amount of clay (800 grams) that was formed with the guidance of a separate cardboard template. The base was thicker than the body and rim but was consistent for each vessel. The thicker base was also helpful for classifying the sherds by type later on in the experiment. The base would then be flipped upside down to dry until it was stable enough to add a second layer

(i.e., the body). While one base was drying, the other three bases were made to control vessel consistency. The second stage was building the body to the shoulder or the widest part of the vessel. The extreme angle at the middle of the vessel – needs stability, requiring a drying period before finishing the vessel. The last part was from the shoulder to the rim of the vessel. A cardboard template was used to monitor the side profile of the vessel to ensure the correct shape was obtained. It approximately took five hours of manual building per vessel without including drying times.

After each pot was built it was left to dry for seven days. The drying period is important because the moisture in the clay needs to be removed. If too much moisture or water is trapped in the clay, the vessel will fracture in the kiln. The water within the crystalline structure of the clay will turn to steam, causing a rapid expansion, breaking the vessel. This will break the pot and possibly damage the kiln. To reduce the risk of fracturing, a slow gradual drying period was chosen. The finished vessel was first covered with a thin layer of fabric to slow down the drying process. If a vessel reaches the bone-dry state too quickly, it can fracture before reaching the kiln. On day four, the fabric was removed to allow the vessel to completely dry. Once at the bone-dry state, the vessel is no longer cool to the touch and lighter in color which signals it is ready to be fired.

Figure 2-5: Vessel building process a) Slab technique creating the vessels b) Final pots drying c) Pots being built d) slab roller used to control thickness

2.5 Firing Conditions

A Skutt electric kiln was used to fire all thirty vessels to maintain even firing temperatures throughout the entire process. Each vessel no matter their placement in the kiln was fired evenly.

In a different type of kiln or bonfire, the firing temperature varies based on where the fuel source is located. The Skutt kiln, the electric coils are evenly distributed, creating a controlled environment. Based on Livingstone-Smith (2001) primary wood firing temperatures ranged from

600 to 900° C, thus an average temperature of 763° C was chosen. The Figure 2-6: Pots after being fired in the kiln electric kilns are setup using pyrometric cones which are set to specific temperatures. Cone 017 was used because it fell within the range of a bonfire and was close to the average 750° C

(Livingstone-Smith, 2001). The complete firing process would take about twelve hours to reach the maximum temperature and cool to room temperature. The kiln was opened the next morning when the inside temperature reached around 50° C. The lid would remain open to allow the vessels to cool down even more before taking them out of the kiln. The ceramics need to be close to room temperature before being removed. The removal of the vessels too early from the kiln could exacerbate existing cracks in the vessel.

2.6 Experimental Setup

The vessels were separated into two groups to test a simple difference in discard behavior: filled vs empty vessel breakage patterns. The thirty vessels needed to be split into two

groups that were not statistically different from each other. It was important to make sure both

groups were the same to rule out any other factors that would contribute to a difference in sherd

breakage. By making sure all of the pottery was the same before the breakage, we could

eliminate any noise that would interfere with the conclusion of our results. In order to separate the pots into two groups, each vessel was measured by maximum height, neck constriction height, maximum width height, rim width, neck constriction width, base width, and weight. In order to create the two groups, each vessel was paired with another vessel that closely resembled it, based on the eight measurements. The pairs were split up, with one going into group one and the other into group two, with a total of fifteen vessels in each group. The vessels were then

tested using a discriminant function analysis (DFA).

Figure 2-7 Vessel measurements A) Maximum Height B) Maximum Width Height C) Neck Constriction Height D) Maximum Width E) Rim Width F) Base Width

Discriminant function analysis is a powerful multivariate tool that uses all eight measurements to see if it can predict group membership accurately. Based on the eight measurements, the discriminant function was able to accurately classify the groups 63.3% of the time (p=.705) (see Table 2-2). This is a low classification rate with 50 percent being a random chance of classifying either group correctly. When looking at the eight variables individually, all were non-significant at the .05 α level. The canonical correlation (.452) was also low, suggesting a non-significant relationship between the eight variables (see Table 2-1). Overall, the discriminant function was unable to assign group admission accurately because each of the measurements between the groups was not significantly different.

Table 2 -1: Vessel discriminant function analysis results

Table 2 -2: Vessel discriminant function analysis results

After the groups were assigned, the pots in group two needed to be filled with a food source that would have been available during the Late Woodland Period. The use of a commonly utilized food like sunflower seeds, squash or maize would create a more realistic experiment that is applicable to the archaeological record (Simon, 2000). Maize has been documented at a number of sites in the southern Great Lakes region during the Late Woodland period including

Gard Island 2 (20Mr21), Indian Island, and the Sissung site (20Mr5) (Schurr and Redmond,

1991; Crawford et al, 1997; Simon, 2000; Stothers and Abel, 2002). The Sissung site, that has a similar ceramic assemblage to the Rainstorm site where the model pot was found, recorded a pit feature that contained ceramics and maize (Fitting, 1975; Stothers, 1973). The presence of corn in this region began around 500 AD and steadily increased into the later portion of the Late

Woodland period, making maize an excellent choice (Schurr and Redmond, 1991; Stothers and

Yarnell,1976; Simon, 2000; Stothers and Abel, 2002; Crawford et al,1997). The corn kernels at these sites have been described as small whole kernels. To be true as possible to the past, whole kernel corn was purchased at a bird feeder supply store. The vessels were then filled with 2000 grams of corn, approximately ¾ of the pot.

The breaking experiment needed a drop zone that would be similar to surfaces pots were exposed to in the past. A soil floor was constructed using silty topsoil that contained no rocks or other debris. A cardboard box one meter by one meter was created to house the soil floor and also contain the potsherds for collection. The soil floor was formed in layers that were packed down to produce a compact dropping surface. A dropping height of 110 cm was chosen to mimic a discard behavior of being dropped while carrying at waist level.

The pots were broken over the course of two days. Eight of the filled pots and seven of the empty vessels were broken on August 22, while the remaining were broken the following

day. A piece of thin plastic sheeting was placed on top of the soil floor to help collect small sherd fragments and “crumbs”. The small bags of sherd crumbs from the filled vessels were then sieved to remove the corn from the samples. They were then bagged separately and excluded from the analysis. The actual sherds were thus classified by type, counted, weighed, and photographed for each vessel. A total of 1555 sherds were counted and weighted.

The third portion of the analysis evaluated the body sherds morphometrically to see if the shape of the sherds was different between groups, due to the unique breakage conditions. The large number of body sherds created from the experiment allowed 90 sherds to be selected.

Sherds that were less than 2.5 cm were excluded from the analysis because of the lack of confidence in classification and the difficulty in measuring very small fragments (Whalen, 1998). However, if any measure was 2.5 cm, the sherd was included in the analysis. Each vessel contributed three sherds Figure 2-9: Gross Morphometric for the analysis, totaling 45 from each group. For sherd analysis measurements each vessel, the body sherds were assigned a number; selected sherds were randomly chosen by a scientific number generator called “research randomizer”. All 90 sherds were then photographed to be measured in Adobe Illustrator. The photos were first scaled in Abode Photoshop. Lithic analysis generally incorporates the use of morphometric analysis to examine shape difference between projectile points (Shott and Trail, 2010). Length and width measurements are a simple way to understand the general shape of an object. A more commonly used technique called geometric morphometric analysis utilizes landmarks to understand the shape of an object with a better resolution (Buchanan and Collard, 2010; Lycett and von Cramon-Taubadel, 2013). This analysis was a preliminary way to see if there were any differences at all, thus if a significant difference was shown, a finer method could be applied in the future. The term “gross morphometric” analysis reflects the less detailed shape information recorded using these

measurements than other techniques. Borrowing from Lycett and von Cramon-Taubadel (2015),

the sherds were oriented along the long axis, measuring the length and three width measurements

at the 25%, 50% and 75% percent.

In total, three analyses were conducted to assess the difference between the two

populations: filled vs empty vessels. The counts and weights used all 1555 sherds while the

morphometric analysis used 90 body sherds. A chi-squared test was used to analyze the difference between counts of sherds produced for each group. The sherds were explored further by using standardized residuals to look sherd fragmentation distribution. A Mann Whitney U test was used to assess the difference between the weights of the sherds between the two groups. The last analysis examined the body sherds using a discriminant function analysis based on the length and width measurements mentions above.

In total, three analysis were conducted to assess the difference between the two populations: filled vs empty vessels. The counts and weights used all 1555 sherds while the morphometric analysis used 90 body sherds. A chi squared test was used to analyze the difference between counts of sherds produced for each group. The sherds were explored further by using standardized residuals to look sherd fragmentation distribution. A Mann Whitney U test was used to assess the difference between the weights of the sherds between the two groups. The last analysis examined the body sherds using a discriminant function analysis based on the length and width measurements mentions above.

Chapter 3

Results

3.1 Sherd Counts

All of the sherd counts by type were analyzed using a chi-squared test. A two x three contingency table examined the relationship between the base, body, and rim sherds between the filled and empty groups to see if a specific portion of the vessel was more fragmented. The overall chi-squared value was highly significant at .005 χ²= 10.722. Standardized residuals were calculated to assess which sherd type reflected the largest difference between the two groups (see

Table 3-1). Group two (filled) on average had vessels with a more fragmented base while the body and rim sherds remained more intact. Group one vessels, on average had a more consistent breakage throughout with less fragmented bases and more body and rim sherds. A second standardized residual was calculated to look at the difference between the body and base sherds alone. The rims were broken in a limited number of fragments or were left completely intact.

This produced a low number of rim sherds. When removing the rim sherds from the equation, a greater significance is seen in the standardized residual numbers, showing a greater emphasis on the breakage pattern discussed above (see Table 3-2). Overall, there was a significant difference between the two conditions in sherds counts.

Table 3-1: Standardized residuals by type

Base Body Rim Total Group G1- 213 543 38 794 Empty -1.55 +0.68 +1.54

G2-Filled 251 490 20 761 +1.55 -0.69 -1.57 Total 464 1033 58 1555

Table 3-2: Standardized residuals base and body sherds only

Base Body Total Group G1-Empty 213 543 756 -1.94 +0.87 G2-Filled 251 490 741 +1.98 -0.88 Total 464 1033 1497

Figure 3-1: Sherd type distribution by group

3.2 Sherd Weights

All sherd weights between the two groups were analyzed. The weights of the sherds were

not normally disturbed (see Figure 3-2). The non-normal distribution required the use of a non-

parametric alternative to a t-test to examine the two independent populations. A Mann-Whitney

U test failed to reject the null with U=297,000 and p=.56325. The two populations showed no

significant difference between sherd weights. No further analysis of weights was completed due

to the non-significant results. Otherwise, the weight could have been examined by sherd type.

Figure 3-2: Sherd weights graphs showing the populations are not normally distributed

3.3 Sherd Gross Morphology

After the breakage experiment, the sherds were analyzed again using a discriminant

function analysis. DFA works well in this case because of the question being asked. Are the two

populations of sherds significantly different based on the width and long axis measurements?

The groups were equally distributed, confirming the use of a parametric test was valid. The DFA was unable to classify the two groups accurately at 56.7 % (p=.547) (see Table 3-4). The

classification rate was low due to the variables having no significant differences between the

groups, creating difficult criteria for group assignment (see Table 3-3). The canonical correlation

corresponds with the low classification accuracy with .187, suggesting no relationship between

the groups.

Table 3-3: Sherd discriminant function classification results

Table 3-4: Sherd discriminant function classification results

Figure 3-3: Graphed discriminant function analysis showing the two groups are identical

Chapter 4

Discussion and Conclusions

The contents experiment (filled vs empty) that examined counts, weight, and gross morphology of sherds, revealed limited differences between the two experimental conditions. Of the three analyses, the sherd counts showed the only significant difference. Overall, the filled vessels had a higher quantity of base sherds produced due to the excess weight of the corn causing a greater impact force than experienced by empty vessels. The energy of the impact was absorbed by the base of the vessel, producing an increase in fragmentation while reducing the amount of body and rim sherds (Subhash et al., 2008).

The number of sherds produced by a vessel has been previously examined experimentally with vessels of different sizes, shapes, and thicknesses to understand vessel size and volume estimation techniques (Chase,1985). This experiment showed a significant difference in the number of sherds produced across all sherd types. The content experiment (filled vs empty) results are consistent with Chase (1985) which suggest various conditions produce a significant difference in sherd number. Sherd counts have been shown experimentally to vary under different conditions including thickness, size, shape, and now the contents of the vessel (Chase,

1985; Hagstrum and Hildebrand, 1990; Whalen, 1998). The content of a vessel can thus skew our understanding of vessel morphology to reflect a heavier vessel while in reality the vessel was lighter and filled with something heavy. The only sherd variable that seems to correlate with an aspect of whole vessel morphology is vessel weight and the weight of the sherds, shown in

Chase (1985). This correlation seems to be unaffected by vessels having added content weight because there was no significant difference between the filled and empty sherd weights, despite there being a difference in the count.

The result of the filled pots having an increase in base sherds adds another layer of conditions that adds to Chase’s (1985) conclusion that vessel capacity, number of vessels, and weight are not reliably correlated with certain sherd attributes. Chase’s (1985) analysis showed that there are a number of factors that can affect certain sherd measures, affecting vessel size and volume estimations. Since Chase’s (1985) experimental study, a few scholars have continued to develop methods to obtain vessel size and volume estimations, especially with the increase of 3D scanning (Hagstrum and Hildebrand, 1990; Whalen, 1998; Felgate et al.,2013; Di Angelo et al.,

2018). The discussion of what types of sherd measures can accurately reflect different morphological features of a whole vessel has since remained largely theoretical. The increasing use of technology has begun to address some of the issues from past formulae that relied on assumptions, generalized estimation of morphology, and inability to be applied to the archaeological record (Rice, 1996, Pauketat, 1989). However, the issue still remains that these formulae are skewed by various factors including multiple vessel types in an assemblage, limited information about the vessels, and contents of a vessel. The use of vessel size and volume estimations have generally fallen out of favor due to the issues presented above. Developing these types of methods must be done with specific questions in mind, be experimentally tested, and keep in mind the biased nature of the archaeological record (Chase, 1985).

The theoretical perspectives that have guided the use of each of these techniques have shaped our understanding of sherds as objects to be classified, a proxy for vessel function or a means for understanding discard behavior. The experimental investigation of ceramic breakage

began with a functionalist understanding of ceramics and tried to inventively recreate whole

vessel morphology to understand vessel function. The gradual acceptance of multiple sources of

variation in the archaeological record and the idea that sherds could be used to understand

aspects of human behavior led to a need to change how we ultimately analyze and view sherds.

Sherd morphology is a product of multiple sources of variation that can be analyzed through the

use of a quantitative genetic framework. By continuing to experiment with different interactions

between different sources of variation, we can begin to build an understanding of ceramic

variation and ultimately sherd variation. Even though the contents (filled vs. empty) experiment

revealed the only difference in sherd variation was in the count of sherds per vessel, it began to

use sherds populations as a way to examine sources of variation caused by discard behavior. In

this experiment, sherd’s shape was analyzed in a new inventive way. The analysis incorporated

the use of new evolutionary techniques while simultaneously adding to the discussion of past

ceramic experimental studies examining sherd breakage.

In more recent years, lithic studies have incorporated the use of a geometric morphometrics and 3D scanners to examine variation in lithic technology (Lycett et al., 2006;

Buchanan, 2006; Buchanan and Collard, 2007; Buchanan and Hamilton, 2010; Shott and Trail,

2010; Lycett and Von Cramon-Taubadel, 2013; Eren et al., 2016; Ragan and Buchanan, 2018).

The use of geometric morphometrics has been applied to gain a better understanding of lithic variation because the use of traditional length and width measurements presents a less accurate picture of overall shape (Shea 2005; Shott and Trail, 2010). The use of specific landmarks as points of comparison is a better way to gain a more accurate representation of the variation in

lithic technology. The use of geometric morphometrics could be applied to sherds with the aid of

a 3D scanner. Ceramics are uniquely 3D in design which makes general measurements less

reliable in gaining the true aspect of a sherd’s shape. The use of 3D scanning has been

implemented within the ceramic field from classification and vessel estimations (Gilboa et al.,

2004; Felgate et al.,2013; Di Angelo et al., 2018; Zvietcovich et al., 2016). The examination of

sherd gross morphology revealed no significant difference in the content experiment. Further

research could explore sherd morphology by using a 3D scanner and the use of geometric

morphometrics. This technology could refine the results of the content experiment.

Along with better measuring technology, other types of behaviors could be explored to see if a noticeable breakage pattern could be detected. Vessel breakage in the archaeological record reflects different types of dropping situations rather than just straight down (Tani, 1995).

The accumulation of middens in different ethnographic contexts, reflect pots being discarded by being thrown on to other pots or at different angles (Kobayashi, 1974; DeBoer et al., 1979; Stark,

1991; LeeDecker, 1994; Wilson, 1994; Underhill, 2003; Williams, 2018). It would be an interesting project to see if there is a difference between various angles of breakage or if being broken against another vessel would affect breakage pattern. This scenario would more accurately reflect how pots are generally discarded and could have implications for distinguishing between different contexts for breakage that Clayton (2005) examined with sherd refitting.

The content experiment shows that there is a uniformity in breakage patterns among the same vessels with varying weights. With this in mind, it may be better to focus on conditions that look at shape or size differences. The experimental work done previously by Chase (1985) could be reexamined with the quantitative genetic lens. This same experimental approach could be applied to vessels of different sizes, shapes, and thicknesses but not just in terms of counts and

weights but by examining sherd morphology. The key portion of the analysis that needs to change is moving away from functional analysis of sherds.

In conclusion, this simple breakage experiment examined an abundant resource found in the archaeological record, trying to glean more information about human behavior. The examination of sherds as analytical units and not through a traditional lens opened up a new avenue of research that can be expanded in the future with new methods and perspectives. Sherd variation is dictated by multiple variables including social learning, raw material, use, and discard. All individual sources of variation that affect sherd variation cannot be completely accounted for, thus it is important to build toward a quantitative genetic approach that does not require every source of variation to be known. The expansion of the field of lithics with the application of the Lycett and von Cramon-Taubadel (2015) quantitative genetic model has now been applied to the ceramic field to examine sherd variation. Exploring new types of discard behaviors using the same approach will continue to expand the field of ceramics. The use of new models and techniques is imperative for archaeology to continue to grow and better understand technological innovation and aspects of human behavior.

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