Simulating Lithic Raw Material Variability in Archaeological Contexts: A Re-evaluation and Revision of Brantingham’s Neutral Model

Pop, Cornel

doi:10.1007/s10816-015-9262-y

Cited by 26 publications

(27 citation statements)

References 32 publications

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“…One technique used to overcome this limitation and elucidate the stepwise behavioural patterns behind the archaeological record has been to use agent-based modelling. These models examine how a composite record can result from a series of unplanned individual movements [23,24]. Their findings suggest that such tool transport patterns lead to the emergence of a distance-decay effect as a default when the driving factors behind movements are undirected.…”

Section: Introductionmentioning

confidence: 99%

Distance-decay effect in stone tool transport by wild chimpanzees

et al. 2016

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Stone tool transport leaves long-lasting behavioural evidence in the landscape. However, it remains unknown how large-scale patterns of stone distribution emerge through undirected, short-term transport behaviours. One of the longest studied groups of stone-tool-using primates are the chimpanzees of the Taï National Park in Ivory Coast, West Africa. Using hammerstones left behind at chimpanzee Panda nut-cracking sites, we tested for a distance-decay effect, in which the weight of material decreases with increasing distance from raw material sources. We found that this effect exists over a range of more than 2 km, despite the fact that observed, shortterm tool transport does not appear to involve deliberate movements away from raw material sources. Tools from the millennia-old Noulo site in the Taï forest fit the same pattern. The fact that chimpanzees show both complex short-term behavioural planning, and yet produce a landscape-wide pattern over the long term, raises the question of whether similar processes operate within other stone-tool-using primates, including hominins. Where hominin landscapes have discrete material sources, a distance-decay effect, and increasing use of stone materials away from sources, the Taï chimpanzees provide a relevant analogy for understanding the formation of those landscapes.

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Section: Introductionmentioning

confidence: 99%

Distance-decay effect in stone tool transport by wild chimpanzees

et al. 2016

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“…Researchers studying archaeological systems worldwide have adopted this formal modeling technique to approach their research questions (e.g., Cegielski and Rogers 2016;Kohler 2012;Linde and Romanowska 2018;Madella et al 2014;Perry et al 2016; Rogers and Cegielski 2017; Romanowska 2015;Wurzer et al 2015). Archaeologists use agent-based modeling to understand archaeological patterns across a range of temporal and spatial settings (e.g., Angourakis et al 2014;Balbo et al 2014;Morrison and Allen 2017;Perrault and Brantingham 2011;Premo 2015;Wren et al 2014).…”

Section: Palabras Clave: Q2mentioning

confidence: 99%

“…Each of them expands on the base model and leads to new insights, thereby showing how computational modeling facilitates the building up of our understanding in cumulative fashion (later models build upon and improve earlier ones rather than compete with them). For example, Pop (2015) revisited Brantingham's model, arguing that the original model did not fully appreciate the difference between the assemblage of a living forager and an archaeological assemblage, which might have undergone significant changes since the moment of being deposited. Although we acknowledge the usefulness of this extension and find his review helpful, our tutorial HOW TO SERIES 4 Advances in Archaeological Practice | A Journal of the Society for American Archaeology | Month 2019 focuses on Brantingham's original model.…”

Section: The Tutorialmentioning

confidence: 99%

“…Although we acknowledge the usefulness of this extension and find his review helpful, our tutorial HOW TO SERIES 4 Advances in Archaeological Practice | A Journal of the Society for American Archaeology | Month 2019 focuses on Brantingham's original model. A further test of good modeling practice would be applying additions from Pop (2015) and Oestmo and colleagues (2016) to the tutorial presented below, and we encourage students to do just that.…”

Section: The Tutorialmentioning

confidence: 99%

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Agent-Based Modeling for Archaeologists: Part 1 of 3

Romanowska¹,

Crabtree²,

Harris³

et al. 2019

Preprint

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Formal models of past human societies informed by archaeological research have a high potential for shaping some of the most topical current debates. Agent-based models, which emphasize how actions by individuals combine to produce global patterns, provide a convenient framework for developing quantitative models of historical social processes. However, being derived from computer science, the method remains largely specialized in archaeology. In this paper and the associated tutorial, we provide a jargon-free introduction to the technique, its potential and limits as well as its diverse applications in archaeology and beyond. We discuss the epistemological rationale of using computational modeling and simulation, classify types of models, and give an overview of the main concepts behind agent-based modeling.

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“…Among fields in which reproducing study systems is either impossible or unethical, ABMs offer a means of simulating or representing real-world phenomena. However, there are only a few published cases in which archaeological models are replicated (Janssen 2009;Kanters 2018;Pop 2016;Oestmo, Janssen, & Marean 2016), and few if any attempts that use the same programing language or environment.…”

Section: Introductionmentioning

confidence: 99%

Agent-Based Modeling, Scientific Reproducibility, and Taphonomy: A Successful Model Implementation Case Study

Carney¹,

Davies²

2020

Preprint

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There is a growing use of agent-based model (ABM) simulations to reconstruct past human-environment interactions. ABMs are useful in that they offer scientists the opportunity to model processes, phenomena, and study systems that may not be otherwise reproducible or testable. Replication or re-implementation studies of ABMs are, however, infrequently undertaken, and there are few examples within archaeology or other social sciences. This paper documents the process of a successful ABM replication study, as well as two additional modifications to the original model. Results corroborate the findings of the original geoarchaeological model and indicate that episodic geomorphic events significantly affect archaeological deposit formation and the inferences drawn from associated radiocarbon records. One revision of the model further demonstrates that episodic fluvial events can create highly varied radiocarbon distributions. The second modification illustrates that excavation data helps to fill in hiatuses in radiocarbon chronologies on depositional landforms, although there is no effect across landscapes subject to erosion. This successful replication exercise also illustrates the value of open access data and analyses in reproducing, testing, and expanding upon archaeological research and theory building.

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Simulating Lithic Raw Material Variability in Archaeological Contexts: A Re-evaluation and Revision of Brantingham’s Neutral Model

Cited by 26 publications

References 32 publications

Distance-decay effect in stone tool transport by wild chimpanzees

Distance-decay effect in stone tool transport by wild chimpanzees

Agent-Based Modeling for Archaeologists: Part 1 of 3

Agent-Based Modeling, Scientific Reproducibility, and Taphonomy: A Successful Model Implementation Case Study

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