Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM)

Laura J. Pollock, Reid Tingley, William K. Morris, Nick Golding, Robert B. O'Hara, Kirsten M. Parris, Peter A. Vesk, Michael A. Mccarthy

Research output: Contribution to journalArticleResearchpeer-review

195 Citations (Scopus)

Abstract

Summary: A primary goal of ecology is to understand the fundamental processes underlying the geographic distributions of species. Two major strands of ecology - habitat modelling and community ecology - approach this problem differently. Habitat modellers often use species distribution models (SDMs) to quantify the relationship between species' and their environments without considering potential biotic interactions. Community ecologists, on the other hand, tend to focus on biotic interactions and, in observational studies, use co-occurrence patterns to identify ecological processes. Here, we describe a joint species distribution model (JSDM) that integrates these distinct observational approaches by incorporating species co-occurrence data into a SDM. JSDMs estimate distributions of multiple species simultaneously and allow decomposition of species co-occurrence patterns into components describing shared environmental responses and residual patterns of co-occurrence. We provide a general description of the model, a tutorial and code for fitting the model in R. We demonstrate this modelling approach using two case studies: frogs and eucalypt trees in Victoria, Australia. Overall, shared environmental correlations were stronger than residual correlations for both frogs and eucalypts, but there were cases of strong residual correlation. Frog species generally had positive residual correlations, possibly due to the fact these species occurred in similar habitats that were not fully described by the environmental variables included in the JSDM. Eucalypt species that interbreed had similar environmental responses but had negative residual co-occurrence. One explanation is that interbreeding species may not form stable assemblages despite having similar environmental affinities. Environmental and residual correlations estimated from JSDMs can help indicate whether co-occurrence is driven by shared environmental responses or other ecological or evolutionary process (e.g. biotic interactions), or if important predictor variables are missing. JSDMs take into account the fact that distributions of species might be related to each other and thus overcome a major limitation of modelling species distributions independently.

Original languageEnglish
Pages (from-to)397-406
Number of pages10
JournalMethods in Ecology and Evolution
Volume5
Issue number5
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Keywords

  • Amphibians
  • Biotic interactions
  • Community assembly
  • Correlated residuals
  • Eucalyptus
  • Frogs
  • Species covariance

Cite this

Pollock, Laura J. ; Tingley, Reid ; Morris, William K. ; Golding, Nick ; O'Hara, Robert B. ; Parris, Kirsten M. ; Vesk, Peter A. ; Mccarthy, Michael A. / Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM). In: Methods in Ecology and Evolution. 2014 ; Vol. 5, No. 5. pp. 397-406.
@article{4be019a66a3a4d5da9df4d6ed36f2942,
title = "Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM)",
abstract = "Summary: A primary goal of ecology is to understand the fundamental processes underlying the geographic distributions of species. Two major strands of ecology - habitat modelling and community ecology - approach this problem differently. Habitat modellers often use species distribution models (SDMs) to quantify the relationship between species' and their environments without considering potential biotic interactions. Community ecologists, on the other hand, tend to focus on biotic interactions and, in observational studies, use co-occurrence patterns to identify ecological processes. Here, we describe a joint species distribution model (JSDM) that integrates these distinct observational approaches by incorporating species co-occurrence data into a SDM. JSDMs estimate distributions of multiple species simultaneously and allow decomposition of species co-occurrence patterns into components describing shared environmental responses and residual patterns of co-occurrence. We provide a general description of the model, a tutorial and code for fitting the model in R. We demonstrate this modelling approach using two case studies: frogs and eucalypt trees in Victoria, Australia. Overall, shared environmental correlations were stronger than residual correlations for both frogs and eucalypts, but there were cases of strong residual correlation. Frog species generally had positive residual correlations, possibly due to the fact these species occurred in similar habitats that were not fully described by the environmental variables included in the JSDM. Eucalypt species that interbreed had similar environmental responses but had negative residual co-occurrence. One explanation is that interbreeding species may not form stable assemblages despite having similar environmental affinities. Environmental and residual correlations estimated from JSDMs can help indicate whether co-occurrence is driven by shared environmental responses or other ecological or evolutionary process (e.g. biotic interactions), or if important predictor variables are missing. JSDMs take into account the fact that distributions of species might be related to each other and thus overcome a major limitation of modelling species distributions independently.",
keywords = "Amphibians, Biotic interactions, Community assembly, Correlated residuals, Eucalyptus, Frogs, Species covariance",
author = "Pollock, {Laura J.} and Reid Tingley and Morris, {William K.} and Nick Golding and O'Hara, {Robert B.} and Parris, {Kirsten M.} and Vesk, {Peter A.} and Mccarthy, {Michael A.}",
year = "2014",
month = "1",
day = "1",
doi = "10.1111/2041-210X.12180",
language = "English",
volume = "5",
pages = "397--406",
journal = "Methods in Ecology and Evolution",
issn = "2041-210X",
publisher = "Wiley-Blackwell",
number = "5",

}

Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM). / Pollock, Laura J.; Tingley, Reid; Morris, William K.; Golding, Nick; O'Hara, Robert B.; Parris, Kirsten M.; Vesk, Peter A.; Mccarthy, Michael A.

In: Methods in Ecology and Evolution, Vol. 5, No. 5, 01.01.2014, p. 397-406.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM)

AU - Pollock, Laura J.

AU - Tingley, Reid

AU - Morris, William K.

AU - Golding, Nick

AU - O'Hara, Robert B.

AU - Parris, Kirsten M.

AU - Vesk, Peter A.

AU - Mccarthy, Michael A.

PY - 2014/1/1

Y1 - 2014/1/1

N2 - Summary: A primary goal of ecology is to understand the fundamental processes underlying the geographic distributions of species. Two major strands of ecology - habitat modelling and community ecology - approach this problem differently. Habitat modellers often use species distribution models (SDMs) to quantify the relationship between species' and their environments without considering potential biotic interactions. Community ecologists, on the other hand, tend to focus on biotic interactions and, in observational studies, use co-occurrence patterns to identify ecological processes. Here, we describe a joint species distribution model (JSDM) that integrates these distinct observational approaches by incorporating species co-occurrence data into a SDM. JSDMs estimate distributions of multiple species simultaneously and allow decomposition of species co-occurrence patterns into components describing shared environmental responses and residual patterns of co-occurrence. We provide a general description of the model, a tutorial and code for fitting the model in R. We demonstrate this modelling approach using two case studies: frogs and eucalypt trees in Victoria, Australia. Overall, shared environmental correlations were stronger than residual correlations for both frogs and eucalypts, but there were cases of strong residual correlation. Frog species generally had positive residual correlations, possibly due to the fact these species occurred in similar habitats that were not fully described by the environmental variables included in the JSDM. Eucalypt species that interbreed had similar environmental responses but had negative residual co-occurrence. One explanation is that interbreeding species may not form stable assemblages despite having similar environmental affinities. Environmental and residual correlations estimated from JSDMs can help indicate whether co-occurrence is driven by shared environmental responses or other ecological or evolutionary process (e.g. biotic interactions), or if important predictor variables are missing. JSDMs take into account the fact that distributions of species might be related to each other and thus overcome a major limitation of modelling species distributions independently.

AB - Summary: A primary goal of ecology is to understand the fundamental processes underlying the geographic distributions of species. Two major strands of ecology - habitat modelling and community ecology - approach this problem differently. Habitat modellers often use species distribution models (SDMs) to quantify the relationship between species' and their environments without considering potential biotic interactions. Community ecologists, on the other hand, tend to focus on biotic interactions and, in observational studies, use co-occurrence patterns to identify ecological processes. Here, we describe a joint species distribution model (JSDM) that integrates these distinct observational approaches by incorporating species co-occurrence data into a SDM. JSDMs estimate distributions of multiple species simultaneously and allow decomposition of species co-occurrence patterns into components describing shared environmental responses and residual patterns of co-occurrence. We provide a general description of the model, a tutorial and code for fitting the model in R. We demonstrate this modelling approach using two case studies: frogs and eucalypt trees in Victoria, Australia. Overall, shared environmental correlations were stronger than residual correlations for both frogs and eucalypts, but there were cases of strong residual correlation. Frog species generally had positive residual correlations, possibly due to the fact these species occurred in similar habitats that were not fully described by the environmental variables included in the JSDM. Eucalypt species that interbreed had similar environmental responses but had negative residual co-occurrence. One explanation is that interbreeding species may not form stable assemblages despite having similar environmental affinities. Environmental and residual correlations estimated from JSDMs can help indicate whether co-occurrence is driven by shared environmental responses or other ecological or evolutionary process (e.g. biotic interactions), or if important predictor variables are missing. JSDMs take into account the fact that distributions of species might be related to each other and thus overcome a major limitation of modelling species distributions independently.

KW - Amphibians

KW - Biotic interactions

KW - Community assembly

KW - Correlated residuals

KW - Eucalyptus

KW - Frogs

KW - Species covariance

UR - http://www.scopus.com/inward/record.url?scp=84900561067&partnerID=8YFLogxK

U2 - 10.1111/2041-210X.12180

DO - 10.1111/2041-210X.12180

M3 - Article

AN - SCOPUS:84900561067

VL - 5

SP - 397

EP - 406

JO - Methods in Ecology and Evolution

JF - Methods in Ecology and Evolution

SN - 2041-210X

IS - 5

ER -