The transition from dispersed to aggregated forms of settlement reflects a critical shift in the relative value of social and primary (food) modes of production. However, investigating trade-offs between these different forms of settlement requires estimates of the extent of community territories, including their nearby arable land. Here we demonstrate a simple algorithm to do that. Our algorithm is analogous to that used to define core-based statistical areas for the US census, though instead of central business districts, we rely on community centers (or areas of known and persistent interaction between unrelated individuals). We provide examples of our algorithm by applying it to archaeological sites in the central Mesa Verde, northern Rio Grande, and Cibola regions in the US Southwest. A sensitivity analysis is also conducted to demonstrate how each tuning parameter contributes to the algorithm.

中文翻译：

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一种定义分散社区区域的方法


从分散的定居形式向聚集形式的转变反映了社会和初级（食物）生产方式的相对价值的重大转变。然而，调查这些不同形式的定居点之间的权衡需要估计社区领土的范围，包括他们附近的耕地。在这里，我们演示了一个简单的算法来做到这一点。我们的算法类似于用于为美国人口普查定义基于核心的统计区域的算法，尽管我们依赖于社区中心（或不相关的个体之间已知且持续互动的区域），而不是中央商务区。我们通过将算法应用于美国西南部 Mesa Verde 中部、Rio Grande 北部和 Cibola 地区的考古遗址来提供算法的示例。此外，还进行了敏感性分析，以演示每个优化参数对算法的贡献。