Spatio-phylogenetic multispecies distribution models
Spatio-phylogenetic multispecies distribution models
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DOI：
10.1111/2041-210x.12318
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发表时间：
2015-02-01
影响因子：
6.6
通讯作者：
Hothorn, Torsten
中科院分区：
文献类型：
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作者：
Kaldhusdal, Arne;Brandl, Roland;Hothorn, Torsten
生态学家越来越多地考虑群落组成和群落空间安排的系统发育相关性。本研究同时考虑了多物种间的系统发育相关性和多样地未观测到的空间异质性所引起的空间相关性。为此，我们引入了系统发育空间广义线性混合模型（psglmm），它是系统发育广义线性混合模型（pglmm）的扩展。我们使用广义线性阵列模型的框架来同时模拟物种和图维。这种模型有可能解释所观察物种的系统发育关系和样地的空间接近性，或两者的相关性。我们提出了基于适当分数的模型选择策略，并利用鸟类计数数据进行了实证研究。在我们的分析中，我们侧重于两个特殊的案例：群落组成模型和环境敏感性模型。我们的模拟研究表明，当系统发育相关性较低时，当研究稀有或普遍物种的存在-缺失或计数数据时，可能难以正确识别系统发育信号。
Ecologists increasingly consider phylogenetic relatedness in both community composition and spatial arrangements in communities. Here we considered both the phylogenetic correlation between multiple species and the spatial correlation induced by unobserved spatial heterogeneity on multiple plots. For this analysis, we introduced phylogenetic spatial generalised linear mixed models (PSGLMMs), which are an extension of phylogenetic generalised linear mixed models (PGLMMs). We used the framework of generalised linear array models to simultaneously model species and plot dimension. Such models have the potential to explain the correlation of the phylogenetic relationship of the observed species and of the spatial proximity of the plots, or both. We proposed model selection strategies based on proper scores and empirically evaluated them in a case study using bird count data. In our analysis, we focused on two special cases: the community composition model and the environmental sensitivity model. Our simulation study indicated that it might be difficult to correctly identify phylogenetic signals when the phylogenetic correlation is rather low and when studying presence-absence or count data of rare or pervasive species.