Exploring variability in lithic armature discard in the archaeological record
Introduction
The development of projectile technology is integral to research on human origins for several reasons. Technological changes and the development of complex technologies are some of the earliest archaeologically visible markers of early hominins’ cognitive evolution. The invention of projectile technology, either simple or complex (as defined by Shea and Sisk, 2010; Sisk and Shea, 2010, 2011), had important ramifications for Pleistocene hominin evolution. Projectile technology improved hunting success, expanded prehistoric hominins’ ecological niche (Sisk and Shea, 2011) and may have played a part in the emergence of important cognitive achievements such as foresight and planning (Thieme, 1997). Therefore, better understanding the archaeological record of hafted armatures can provide insight into our species’ broad evolutionary adaptations.
The number of stone points—which remain the best evidence of projectile technology—fluctuates highly across archaeological assemblages. Retouched Still Bay points are rare or even absent in certain Middle Stone Age (MSA) archaeological sites such as Pinnacle Point 5–6 (Wilkins et al., 2017) and Klasies River Mouth (Singer and Wymer, 1982), but they are found in relatively high numbers at Apollo 11 Rock Shelter (n = 25; Lombard and Högberg, 2018), Umhlatuzana Rock Shelter (n = 102; Kaplan, 1990; Högberg and Lombard, 2016), and Blombos Cave (n = 371; Villa et al., 2009). Similarly, the number of unretouched points also fluctuates among MSA archaeological sites (e.g., n = 212 at Holley Shelter, Bader et al., 2015; n = 380 at Pinnacle Point 13B, Thompson et al., 2010; and n > 3000 at Klasies River Mouth, Singer and Wymer, 1982). Although it can be tempting to argue that those numbers indicate different frequencies of projectile weapons usage, recent research has shown that high numbers may instead result from widespread misclassifications of the function of the points, based solely on morphology (Schoville, 2010; Bouzouggar and Barton, 2012; Tomasso and Rots, 2018). Given the importance of quantifying the use of hafted armatures to understand human evolution, we use an agent-based model (ABM) to present an alternative perspective on this topic. Our ABM explores the impact of human and environmental factors—hunting behavior, tool curation, population size, and biome size and productivity—on the count and spatial distribution of simple projectile armatures found in archaeological sites.
Archaeological ABMs are becoming robust middle-range research tools (as advocated by Binford, 1981) because they allow us to connect the archaeological record to the behaviors that could have created that record (see, for example, Mithen, 1990; Lake, 2000; Brantingham, 2003; Barton and Riel-Salvatore, 2014; Davies et al., 2016; Oestmo et al., 2016; Coco et al., 2020). This is important because the archaeological record is not made of behavior but rather of discarded materials. In addition, human behavior is spatially continuous (Foley, 1981), but the location of archaeological sites is constrained by taphonomy and visibility, making the traces of such behavior spatially imbalanced (Dunnell, 1992).
Inferring behavior from the patchy archaeological record using traditional archaeological methods relies on assumptions and interpretations that are prone to biases. Here, we use an ABM to explore the link between behavior and the archaeological record in a controlled setting, where our assumptions are clearly explained and where the artifact record is not affected by taphonomy or restricted sampling. We take advantage of the capacity of ABMs to create complex, data-informed, realistic models to test hypotheses (Lake, 2014) in ways that are similar to the Artificial Anasazi (Axtell et al., 2002) or the MedLand project (Barton et al., 2010). This approach enables us to simulate hunter-gatherers’ daily subsistence practices with controlled variables, probabilities, and constraints that can be altered to explore the effects of different interactions between humans and the environment. Through this, we can explore the complex patterns that occur when human decisions affect common resources, which cannot easily be modeled using simple mathematical equations (Janssen and Hill, 2014). Furthermore, this approach allows us to visualize the outcome of our simulations on a reconstructed paleo-landscape and uncover spatial patterns that may be archaeologically invisible due to the patchy nature of the MSA archaeological record. However, we must clarify that our goal is not to reproduce lithic assemblage composition across South African MSA sites but rather to explore the impact of different human and environmental factors on general counts of simple projectile armatures.
Simple projectile technology—projectile weapons that use human energy for propulsion (Shea and Sisk, 2010)—was found in both Europe and Africa during the late Lower Paleolithic and Earlier Stone Age (ESA; Thieme, 1997; Villa and Lenoir, 2009; Wilkins et al., 2012; Sahle et al., 2013). To date, the ∼500 ka points used for hafted trusting spears from Kathu Pan, South Africa, constitute the earliest evidence of such simple projectiles (Wilkins et al., 2012; but see Rots and Plisson, 2014), whereas ∼400 and ∼300 ka wooden spears and sticks have been found in Mousterian assemblages at Clacton-on-Sea, the UK, and Schöningen, Germany, respectively (Thieme, 1997; Milks et al., 2019; Conard et al., 2020). Given that simple projectile technology has been documented in both modern humans and Neandertals archaeological contexts, it may have been invented by their common ancestor (Wilkins et al., 2012), thus pushing the timing of its conception to before the appearance of major ‘behavioral modernity’ traits. Therefore, as the invention of projectile technology likely had important impacts on ESA hominins’ hunting success, meat consumption, and thus, social behavior, it is not surprising that studying projectile tools and their evolution is a major part of paleoanthropology. Unfortunately, documenting the frequency and changes in lithic armatures is complicated by methodological and taphonomic constraints, which are discussed below.
Many MSA cave and rock shelter sites report numbers of various types of points (e.g., unretouched, retouched, and tanged [points with basal retouch]). However, as lithic coding systems vary between regions, sites, and even researchers (Will et al., 2019), it is often difficult to compare assemblages. This is best illustrated by Högberg and Lombard’s (2016) restudy of the Umlhatuzana lithic assemblage previously published by Kaplan (1990), where they state: “The numbers of points in our study and in Kaplan’s vary because our definition of a point differs from his” (Högberg and Lombard, 2016: p. 5). Differing excavation protocols further complicate the issue, as the extent and quality of excavations have a strong impact on artifact counts. Therefore, it is problematic to compare point counts of sites that had widely different quantities of sediment removed or were excavated using widely different plotting size thresholds.
In addition to the challenges faced when trying to compile and compare point counts over time and space, there is uncertainty about the function of most reported points because use-wear and residue studies—which would help define tool function—rarely accompany site reports. This is important because recent research shows that points previously thought to be used for projectile weapons might, in fact, have been handheld, e.g., the tanged Aterian tools of North Africa primarily thought to be hafted projectile points (Clark, 1970) are now assumed to have been handheld hafted scrapers (Iovita, 2011; Bouzouggar and Barton, 2012; Tomasso and Rots, 2018). Similarly, Still Bay points appear to have been used for both knives and projectile weapons (Lombard, 2006, 2007; Villa et al., 2009; Högberg and Larsson, 2011; Soriano et al., 2015), and experimental edge damage studies have shown that most MSA unretouched points found at Pinnacle Point 13B (PP13B), South Africa, were used as knives rather than projectiles (Schoville, 2010; Schoville et al., 2016). These studies show that single tool shapes likely had more than one use, making tool classification difficult. This suggests that we should not rely solely on tool morphology to document the evolution of projectile technology (Douze et al., 2020). Because of these challenges, it is difficult to evaluate the timing and intensity at which projectile weapons were used in the past. In turn, this leads us to wonder: do the fluctuations in ‘point’ numbers reported in published articles reflect fluctuations in the usage of projectiles?
Here, we use an ABM to explore this question. We test two hypotheses: H1: there are high counts of armatures in archaeological sites because most of the armatures used for hunting are discarded at archaeologically visible habitation sites, and H2: the counts of armatures found at MSA archaeological sites reflect the frequency with which projectiles were used for hunting. The alternative hypothesis for H2 is that other factors such as hunting behavior, tool curation, population size, and biome size and productivity have an impact on those counts. We predict that the results of the ABM will reject both null hypotheses for two reasons. First, recent research has shown that points found in archaeological sites were more often used as handheld or for multipurpose activities (Lombard, 2006; Schoville, 2010; Högberg and Larsson, 2011; Bouzouggar and Barton, 2012; Tomasso and Rots, 2018). Second, ethnographic research shows that human behavior is spatially continuous (Foley, 1981; Dunnell, 1992); therefore, the number of armatures used primarily for hunting and discarded at habitation sites should correlate with environmental productivity and hunting behavior.
Section snippets
Materials and methods
This research focuses on the results of a discard module added to the PaleoscapeABM, which is a component of the Paleoscape model explained in Marean et al. (2015) and illustrated in a recent special issue of Quaternary Science Review (e.g., Cleghorn et al., 2020; Cowling et al., 2020; Kraaij et al., 2020; Marean et al., 2020; Wren et al., 2020). The different models i.e., Paleoscape, PaleoscapeABM, and projectile submodel, are explained below.
Summary statistics of projectiles discarded at habitation camps
The results of the simulations show that, on average, 4.5% of armatures used in a simulation are brought back to habitation camps while the remaining 95.5% are lost or discarded where the hunt took place. As each simulation runs for one year and produces an average of ∼40 armatures, this suggests that ∼2 armatures are discarded at habitation camps every year. However, as simulations produce an average of ∼205 sites per year—either multicomponent or used only as habitation camps—most of those
Low counts of projectile armatures in archaeological sites are expected
Our modeling results show that low counts of hafted armatures in archaeological sites should be viewed as normal if prehistoric hunter-gatherers followed the OFT principles modeled here. The model results show that most projectile armatures end up in locations with low archaeological visibility (either lost at hunting sites or discarded at rarely reoccupied habitation sites). For the MSA archaeological record, this suggests that low counts could still be interpreted as a sign that projectile
Conclusions
This paper presents an ABM that focuses on the connection between past behavior and its archaeological traces. Our modeling results show that hafted armatures were most probably used regularly during the MSA, despite their low counts in archaeological sites. In fact, this paper shows that the equifinality created by the interaction of multiple socio-behavioral and ecological factors suggests that hunting tool frequency at habitation sites may not directly reflect the rate at which hunting took
Declaration of competing interest
The authors declare there is no conflict of interest.
Acknowledgments
The authors recognize the support of a grant from the National Science Foundation (BCS-1138073), Hyde Family Foundations, the Institute of Human Origins at Arizona State University, and the John Templeton Foundation to the Institute of Human Origins at Arizona State University. The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of any of these funding organizations. Sincere thanks to Erik Otárola-Castillo (Department of Anthropology,
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