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首页> 外文期刊>Zoological Studies >An autoregressive model for global vertebrate richness rankings: long-distance dispersers may have stronger spatial structures
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An autoregressive model for global vertebrate richness rankings: long-distance dispersers may have stronger spatial structures

机译:全球脊椎动物丰富度排名的自回归模型:长距离分散体可能具有更强的空间结构

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摘要

Background Spatial autocorrelations are one of the most prevalent natural phenomena in ecological data. It is generally assumed that short-distance dispersers are spatially limited and thus have stronger spatial autocorrelation patterns than do long-distance dispersers. To test this hypothesis, I quantified and compared spatial autocorrelation patterns of global richness rankings of amphibians, mammals, and birds using an autoregressive model. A species richness ranking was used as a proxy of species richness, which was obtained through a digital image processing method from published world maps of species richness.
机译:背景空间自相关是生态数据中最普遍的自然现象之一。通常认为,短距离分散器在空间上受到限制,因此比长距离分散器具有更强的空间自相关模式。为了检验该假设,我使用自回归模型对两栖动物,哺乳动物和鸟类的全球丰富度排名进行了空间自相关模式的量化和比较。使用物种丰富度等级作为物种丰富度的代理,该等级是通过数字图像处理方法从已发布的世界物种丰富度地图中获得的。

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