Drivers of geographical patterns of North American language diversity
Drivers of geographical patterns of North American language diversity
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DOI：
10.1098/rspb.2019.0242
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发表时间：
2019-03
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通讯作者：
Marco Túlio Pacheco Coelho;E. Pereira;H. Haynie;T. Rangel;Patrick H. Kavanagh;K. Kirby;Simon J. Greenhill;Claire Bowern;R. Gray;Robert K. Colwell;N. Evans;M. Gavin
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作者：
Marco Túlio Pacheco Coelho;E. Pereira;H. Haynie;T. Rangel;Patrick H. Kavanagh;K. Kirby;Simon J. Greenhill;Claire Bowern;R. Gray;Robert K. Colwell;N. Evans;M. Gavin
尽管人们提出了许多假设来解释为什么人类会说这么多语言，为什么语言在地球仪上分布不均匀，但对塑造文化和语言多样性地理模式的因素仍然知之甚少。以前的研究往往侧重于确定语言多样性的普遍预测因素，而没有考虑当地因素和多个预测因素如何相互作用。在这里，我们使用一个独特的组合路径分析，机械模拟建模，地理加权回归调查广泛描述，但了解甚少，在北美语言多样性的空间格局。我们表明，语言多样性的生态驱动因素并不普遍或完全直接。最强的关联意味着先前开发的假设驱动程序，如人口密度，资源多样性和承载能力与组大小限制的作用。这个因素网络的预测能力随空间而变化，从我们的模型预测约86%的多样性变化的区域到解释不到40%的区域。
Although many hypotheses have been proposed to explain why humans speak so many languages and why languages are unevenly distributed across the globe, the factors that shape geographical patterns of cultural and linguistic diversity remain poorly understood. Prior research has tended to focus on identifying universal predictors of language diversity, without accounting for how local factors and multiple predictors interact. Here, we use a unique combination of path analysis, mechanistic simulation modelling, and geographically weighted regression to investigate the broadly described, but poorly understood, spatial pattern of language diversity in North America. We show that the ecological drivers of language diversity are not universal or entirely direct. The strongest associations imply a role for previously developed hypothesized drivers such as population density, resource diversity, and carrying capacity with group size limits. The predictive power of this web of factors varies over space from regions where our model predicts approximately 86% of the variation in diversity, to areas where less than 40% is explained.