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The Ideal Distribution Model and Archaeological Settlement Patterning

期刊

ENVIRONMENTAL ARCHAEOLOGY
卷 27, 期 4, 页码 349-356

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ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.1080/14614103.2020.1803015

关键词

Ideal free distribution; Allee effect; despotism; social hierarchy; interpersonal cooperation; intergroup competition

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Archaeologists have successfully applied the ideal distribution model (IDM), derived from population and behavioural ecology, to understand human population distribution and movement. This model has generated testable hypotheses that address a wide range of research questions, including colonization, population distribution, cooperation, competition, social hierarchy, and the impact of subsistence on settlement patterns. The IDM's utility is not limited by geography or time, and its application is expanding to diverse settings.
Human populations distribute themselves across landscapes in clearly patterned ways, but accurate and theoretically informed predictions and explanations of that patterning in the archaeological record can prove difficult. Recently, archaeologists have begun applying a unifying theoretical framework derived from population and behavioural ecology to understand human population distribution and movement: the ideal distribution model (IDM). The three variants of this IDM - the ideal free distribution, the ideal free distribution with an Allee effect, and the ideal despotic distribution - are capable of generating testable hypotheses concerning the colonisation of landscapes, the spatial distribution of populations, cooperation and competition, social hierarchy and inequality, and the impacts of subsistence on settlement patterns. Their success in addressing such wide-ranging research questions demonstrates that IDMs are not only helpful for analysing settlement patterns in relation to environmental factors, but for better understanding the social forces that impact population distribution, as well. There seem to be no geographic or temporal bounds to the utility of IDMs, and we look forward to the application of these models in ever more diverse settings.

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