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Incorporating imperfect detection into joint models of communites: A response to Warton et al.

October 20, 2016

Warton et al. [1] advance community ecology by describing a statistical framework that can jointly model abundances (or distributions) across many taxa to quantify how community properties respond to environmental variables. This framework specifies the effects of both measured and unmeasured (latent) variables on the abundance (or occurrence) of each species. Latent variables are random effects that capture the effects of both missing environmental predictors and correlations in parameter values among different species. As presented in Warton et al., however, the joint modeling framework fails to account for the common problem of detection or measurement errors that always accompany field sampling of abundance or occupancy, and are well known to obscure species- and community-level inferences.

Citation Information

Publication Year 2016
Title Incorporating imperfect detection into joint models of communites: A response to Warton <i>et al.</i>
DOI 10.1016/j.tree.2016.07.009
Authors Steven R. Beissinger, Kelly J. Iknayan, Gurutzeta Guillera-Arroita, Elise Zipkin, Robert Dorazio, Andy Royle, Marc Kery
Publication Type Article
Publication Subtype Journal Article
Series Title Trends in Ecology and Evolution
Series Number
Index ID 70177753
Record Source USGS Publications Warehouse
USGS Organization Patuxent Wildlife Research Center