ABSTRACT

How might subsistence strategies structure the costs and benefits of habitat selection and, therefore, drive settlement patterning? We explore this question within an Ideal Distribution framework, arguing that (i) a habitat can be decomposed into its environmental covariates, (ii) their relative contributions to suitability can vary as a function of subsistence strategy, and (iii) the resulting differences will in turn lead to different population distributions across habitats. To evaluate these claims, we apply a Poisson point-process modelling approach known as maximum entropy (MaxEnt) to Archaic hunter-gatherer and Formative maize-farmer sites within the Grand Staircase-Escalante National Monument. Our results show that environmental covariates vary in their importance for each strategy and that the strategies themselves vary in their land use and habitat distribution, with Archaic foragers being widely distributed across space, Formative farmers more densely packed into areas indicative of higher maize productivity. The approach itself also has wide application to other subsistence strategies, including horticulture and pastoralism, across a range of environmental conditions.

摘要

生计战略如何构建栖息地选择的成本和收益，从而推动定居模式？我们在理想分布框架内探讨了这个问题，认为 (i) 栖息地可以分解为其环境协变量，(ii) 它们对适宜性的相对贡献可能因生存策略而异，以及 (iii) 产生的差异将反过来又导致不同栖息地的种群分布不同。为了评估这些说法，我们将称为最大熵 (MaxEnt) 的泊松点过程建模方法应用于 Grand Staircase-Escalante 国家纪念碑内的古代狩猎采集者和形成性玉米农民遗址。我们的研究结果表明，环境协变量对每种策略的重要性各不相同，而且这些策略本身的土地利用和栖息地分布也各不相同，古代觅食者广泛分布在空间中，形成性农民更密集地聚集在表明玉米生产力较高的区域。该方法本身也广泛应用于其他生计策略，包括园艺和畜牧业，在一系列环境条件下。