Understanding co‐occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM )статья из журнала
Аннотация: 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 ( SDM s) 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 . JSDM s 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 JSDM s 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. JSDM s 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.
Год издания: 2014
Авторы: Laura J. Pollock, Reid Tingley, William K. Morris, Nick Golding, Robert B. O’Hara, Kirsten M. Parris, Peter A. Vesk, Michael A. McCarthy
Издательство: Wiley
Источник: Methods in Ecology and Evolution
Ключевые слова: Species Distribution and Climate Change, Ecology and Vegetation Dynamics Studies, Wildlife Ecology and Conservation
Другие ссылки: Methods in Ecology and Evolution (HTML)
Minerva Access (University of Melbourne) (PDF)
Minerva Access (University of Melbourne) (HTML)
Minerva Access (University of Melbourne) (PDF)
Minerva Access (University of Melbourne) (HTML)
Открытый доступ: closed
Том: 5
Выпуск: 5
Страницы: 397–406