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Phylogenetic and trait analyses are powerful tools for disentangling the mechanisms underlying the structure of plant and animal communities, and their use has become prominent in the last decade. However, few studies have simultaneously incorporated data on species traits or phylogeny, environment, and species co-occurrences. Therefore, the relative importance of these factors as drivers of community assembly is largely unknown. 2.We introduce new and conceptually simple null model tests and appropriate metrics to disentangle the relationships between species co-occurrence, traits or phylogeny and environmental factors not covered by available packages for phylogenetic analysis. We illustrate the methods with an extensive data set on understory plant assemblages sampled in three Polish forests. 3.Benchmark testing indicates that the proposed methods have good error behaviour when tested against a variety of artificial matrix sets covering a wide range of observed patterns. Test results are largely independent of matrix size and matrix fill and have adequate power to detect even weak patterns of non-randomness. The different metrics used are uncorrelated with one another and capture different, and often divergent, patterns expressed within the same matrix. Our case study revealed three distinct patterns in forest understory plant assemblages: (i) multiple patterns of species associations within meta-communities might mask the influence of phylogeny and environmental variables on species occurrences, (ii) the strength of environmental and phylogenetic signals depend on the co-occurrence pattern (segregated, aggregated, clumped) and might vary within a single meta-community, and (iii) a random association of phylogeny and species co-occurrence coupled with significant correlations between environmental factors and phylogeny might reveal species with traits that have passed through environmental filtering. © 2012 The Authors. Methods in Ecology and Evolution © 2012 British Ecological Society.

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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© 2012 The Authors.



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