A comparison of joint species distribution models for presence–absence data

David P. Wilkinson, Nick Golding, Gurutzeta Guillera-Arroita, Reid Tingley, Michael A. McCarthy

Research output: Contribution to journalArticleResearchpeer-review

17 Citations (Scopus)

Abstract

Joint species distribution models (JSDMs) account for biotic interactions and missing environmental predictors in correlative species distribution models. Several different JSDMs have been proposed in the literature, but the use of different or conflicting nomenclature and statistical notation potentially obscures similarities and differences among them. Furthermore, new JSDM implementations have been illustrated with different case studies, preventing direct comparisons of computational and statistical performance. We aim to resolve these outstanding issues by (a) highlighting similarities among seven presence–absence JSDMs using a clearly defined, singular notation; and (b) evaluating the computational and statistical performance of each JSDM using six datasets that vary widely in numbers of sites, species, and environmental covariates considered. Our singular notation shows that many of the JSDMs are very similar, and in turn parameter estimates of different JSDMs are moderate to strongly, positively correlated. In contrast, the different JSDMs clearly differ in computational efficiency and memory limitations. Our framework will allow ecologists to make educated decisions about the JSDM that best suits their objective, and enable wider uptake of JSDM methods among the ecological community.

Original languageEnglish
Pages (from-to)198-211
Number of pages14
JournalMethods in Ecology and Evolution
Volume10
Issue number2
DOIs
Publication statusPublished - Feb 2019
Externally publishedYes

Keywords

  • biotic interactions
  • community assembly
  • hierarchical models
  • joint species distribution model
  • latent factors
  • presence–absence
  • residual correlation

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