Computational Modeling and Neolithic Socioecological Dynamics: A Case Study from Southwest Asia

Abstract

Archaeology has an opportunity to offer major contributions to our understanding of the long-term interactions of humans and the environment. To do so, we must elucidate dynamic socioecological processes that generally operate at regional scales. However, the archaeological record is sparse, discontinuous, and static. Recent advances in computational modeling provide the potential for creating experimental laboratories where dynamic processes can be simulated and their results compared against the archaeological record. Coupling computational modeling with the empirical record in this way can increase the rigor of our explanations while making more transparent the concepts on which they are based. We offer an example of such an experimental laboratory to study the long-term effects of varying landuse practices by subsistence farmers on landscapes, and compare the results with the Levantine Neolithic archaeological record. Different combinations of intensive and shifting cultivation, ovicaprid grazing, and settlement size are modeled for the Wadi Ziqlab drainage of northern Jordan. The results offer insight into conditions under which previously successful (and sustainable) landuse practices can pass an imperceptible threshold and lead to undesirable landscape consequences. This may also help explain long-term social, economic, and settlement changes in the Neolithic of Southwest Asia.

Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

“…It is estimated that the world's extension of pre-agriculture forests was of 61.51 million km 2 , of which 15.51 million km 2 were lost prior to about 1500 A.D. The historical LCLUC models are relatively scarce and were mostly developed during the past two decades in several parts of the world, mainly in China, the USA, Europe and South America (Figure 1 [7,34,37,39,[62][63][64][65][66][67][68][69][70]). Historical models of change have distinct disciplinary origins and use different space-time scales.…”

In glacial environments beyond glacial terrains: Human eco-dynamics in late Pleistocene Mediterranean Iberia

“…Moreover, modern environmental conditions cannot be used as proxies for past ones. It may be possible to model aspects of past terrain and vegetation (e.g., Barton et al, 2010, but this work has not yet been done for this region and time frame. Still, there are several kinds of geographic data that can provide some indication of spatial variability in environmental context within which to analyze the archaeological data.…”

“…A variety of computational modeling approaches are particularly useful for synthesizing proxy data and representing the dynamics of Pleistocene environmental change. Examples include different approaches to modeling climate, vegetation, and landscape change (Ruter et al, 2004;Clevis et al, 2006;Phillips and Dudík, 2008;Liu et al, 2009;Barton et al, 2010;McDonald and Bryson, 2010;Voinov et al, 2010).…”

Modelling feedbacks between human and natural processes in the land system

“…The MML integrates an agent-based model (ABM) of households practicing subsistence agriculture and/or pastoralism and a cellular automata landscape evolution model (LEM) that simulates the dynamics of surface erosion/deposition, vegetation change, and soil depth/fertility at the scale of local watersheds. Observational or modeled climatic data are used as input to the LEM (Barton et al, 2010(Barton et al, , 2012Mayer and Sarjoughian, 2009;Mitasova et al, 2013;Soto-15 Berelov, 2011). The components of the MML are modular and are dynamically coupled through an interaction model to manage overall model complexity (Davis and Anderson, 2004, p. 200;Gholami et al, 2014;Sarjoughian et al, 2013;Sarjoughian, 2006;Sarjoughian et al, 2015) (See S1 1.1).…”