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In this study, we present a modeling approach that investigates how much cultivable land was required to supply a society and whether societies were in need when environmental conditions deteriorated. The approach is implemented for the North-Eastern Peloponnese and is based upon the location of Late Helladic IIIB (1300-1200 BCE) archaeological sites, an assessment of their sizes, and a proposed diet of the people. Based on these information, the areal requirement of each site is calculated and mapped. The results show that large sites do not have sufficient space in their surroundings in order to supply themselves with the required food resources and thus they depended on supplies from the hinterland. Dry climatic conditions aggravate the situation. This indicates that potential societal crisis are less a factor of changing environmental conditions or a shortage of arable land but primarily caused by socio-economic factors.

Agent-based models provide detailed, bottom-up approaches to investigate complex socio-ecological systems. This study presents a first step towards a modular agent-based simulation that is based upon empirical data, as well as environmental suitability maps and an assessment of livestock units. To illustrate the capabilities of our simulation, we use a geographically explicit approach to simulate a component of the production of animal products of a rural settlement in the lower Bakırçay catchment, western Turkey. The model structurally couples various agent types representing several elements and processes of the animal husbandry and food production value chain, such as sedentary herders—practising daily, short-distance pastoralism—and their flocks of goats and sheep, as well as milking and slaughtering. The modelling tool captures the fundamental socio-ecological dynamics of animal husbandry and food production in rural settlements. Therefore, the tool is valuable as a basis to discuss hypotheses regarding the number of animals that are needed to cover the requirements of different growing populations.

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