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Volume 98, Issue 1 p. 198-210
Article

Phylogenetic occupancy models integrate imperfect detection and phylogenetic signal to analyze community structure

Luke O. Frishkoff

Corresponding Author

Luke O. Frishkoff

Department of Biology, Stanford University, 371 Serra Mall, Stanford, California, 94305 USA

Department of Ecology and Evolutionary Biology, University of Toronto, 25 Wilcocks, Toronto, Ontario, M5S 3B2 Canada

E-mail: [email protected]Search for more papers by this author
Perry de Valpine

Perry de Valpine

Department of Environmental Science, Policy and Management, University of California, 130 Mulford Hall, Berkeley, California, 94720 USA

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Leithen K. M'Gonigle

Leithen K. M'Gonigle

Department of Biological Science, Florida State University, Tallahassee, Florida, 32306 USA

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First published: 27 October 2016
Citations: 17
Corresponding Editor: Paul B. Conn

Abstract

Biological communities are structured phylogenetically—closely related species are typically more likely to be found at the same sites. This may be, in part, because they respond similarly to environmental gradients. Accurately surveying biological communities is, however, made difficult by the fact that detection of species is not perfect. In recent years, numerous statistical methods have been developed that aim to overcome deficiencies in the species detection process. However, these methods do not allow investigators to assess phylogenetic community structure. Here, we introduce the phylogenetic occupancy model (POM), which accounts for imperfect species detection while assessing phylogenetic patterns in community structure. Using simulated data sets we show that the POM grants less biased estimates of phylogenetic structure than models without imperfect detection, and can correctly ascertain the effects of species traits on community composition while accounting for evolutionary non-independence of taxa. Integrating phylogenetic methods into widely used occupancy models will help clarify how evolutionary history influences modern day communities.