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Spatio-phylogenetic multispecies distribution models


Kaldhusdal, Arne; Brandl, Roland; Müller, Jörg; Möst, Lisa; Hothorn, Torsten (2015). Spatio-phylogenetic multispecies distribution models. Methods in Ecology and Evolution, 6(2):187-197.

Abstract

1. 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).
2. 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.
3. 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.

Abstract

1. 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).
2. 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.
3. 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.

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4 citations in Web of Science®
5 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Uncontrolled Keywords:environmental gradient;generalized linear array models;null model;phylogenetic community structure;phylogenetic signal;spatial correlation
Language:English
Date:February 2015
Deposited On:11 Dec 2015 09:21
Last Modified:08 Dec 2017 15:22
Publisher:Wiley-Blackwell Publishing, Inc.
ISSN:2041-210X
Publisher DOI:https://doi.org/10.1111/2041-210X.12318

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