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Quantifying spatial phylogenetic structures of fully stem‐mapped plant communities
Author(s) -
Shen Guochun,
Wiegand Thorsten,
Mi Xiangcheng,
He Fangliang
Publication year - 2013
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12119
Subject(s) - phylogenetic tree , spatial ecology , biology , spatial analysis , similarity (geometry) , null model , point pattern analysis , phylogenetics , evolutionary biology , ecology , statistics , mathematics , genetics , artificial intelligence , computer science , gene , image (mathematics)
SummaryAnalysis of the phylogenetic similarity of co‐occurring species at different spatial scales is increasingly used for decoding community assembly rules. Here, we integrated the analysis of phylobetadiversity and marked point pattern analysis to yield a new metric, the phylogenetic mark correlation function, k d ( r ), to quantify spatial phylogenetic structure of fully stem‐mapped communities. k d ( r ) is defined as the expected phylogenetic distance of two heterospecifics separated by spatial distance r , and normalized with the expected phylogenetic distance of two heterospecifics taken randomly from a study area. It measures spatial phylogenetic turnover relative to spatial species turnover and is closely related with the spatially explicit Simpson index. We used simulated fully stem‐mapped plant communities with known spatial phylogenetic structures to assess type I and II errors of the phylogenetic mark correlation function k d ( r ) under a null model of random phylogenetic spatial structure, and to test the ability of the k d ( r ) to detect scale‐dependent signals of phylogenetic spatial structure. We also compared the performance of the k d ( r ) with two existing measures of phylobetadiversity that have been previously used to analyse fully stem‐mapped plots. Finally, we explored the spatial phylogenetic structure of a 24‐ha fully stem‐mapped subtropical forest in China. Simulation tests showed that the new metric yielded correct type I and type II errors and accurately detected the spatial scales at which various processes (e.g. habitat filtering and competition) were invoked to generate spatial phylogenetic structures. The power of the k d ( r ) was not affected by a phylogenetic signal in species abundance and different topologies of the phylogenetic tree. Replacing phylogenetic distance by functional distance allows for application of the k d ( r ) to estimate spatial correlations in functional community structure. Thus, the k d ( r ) allows trait and phylogenetic structure to be analysed in the same framework. The phylogenetic mark correlation function is a powerful and accurate tool for revealing scale‐dependent phylogenetic/functional footprints in community assemblages and allows ecologists to keep up with the increasingly available data of fully stem‐mapped plots, functional traits and community phylogenies.