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Generalized linear mixed models can detect unimodal species-environment relationships.

ABSTRACT: Niche theory predicts that species occurrence and abundance show non-linear, unimodal relationships with respect to environmental gradients. Unimodal models, such as the Gaussian (logistic) model, are however more difficult to fit to data than linear ones, particularly in a multi-species context in ordination, with trait modulated response and when species phylogeny and species traits must be taken into account. Adding squared terms to a linear model is a possibility but gives uninterpretable parameters. This paper explains why and when generalized linear mixed models, even without squared terms, can effectively analyse unimodal data and also presents a graphical tool and statistical test to test for unimodal response while fitting just the generalized linear mixed model. The R-code for this is supplied in Supplemental Information 1.

SUBMITTER: Jamil T

PROVIDER: S-EPMC3709111 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Generalized linear mixed models can detect unimodal species-environment relationships.

Jamil Tahira T Ter Braak Cajo J F CJ

PeerJ 20130709

Niche theory predicts that species occurrence and abundance show non-linear, unimodal relationships with respect to environmental gradients. Unimodal models, such as the Gaussian (logistic) model, are however more difficult to fit to data than linear ones, particularly in a multi-species context in ordination, with trait modulated response and when species phylogeny and species traits must be taken into account. Adding squared terms to a linear model is a possibility but gives uninterpretable pa ...[more]

PMID: 23862108

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