ARPHA Preprints, doi: 10.3897/arphapreprints.e217001
Applications of joint species distribution models in community ecology: a systematic literature review
expand article infoMargaux Rojat‡, Ghislain Vieilledent§, Sylvain Schmitt§, Raphaël Pélissier‡, Robin Pouteau‡
‡ Institut de Recherche pour le Développement, Montpellier, France§ CIRAD, Montpellier, France
Open Access
Abstract

Joint species distribution models (JSDMs) have emerged as a key biogeographic tool for incorporating multispecies co-occurrence data into species distribution modeling, yet a comprehensive synthesis of their applications is still lacking. Here, we present a systematic review of peer-reviewed JSDM applications, encompassing 246 articles describing 314 distinct JSMs. Growth in JSDM publications outpaced that of classical SDMs by nearly sevenfold, with research efforts concentrated in Europe (Finland alone accounting for 12% of all studies), United States, and southeastern Australia. Extra-tropical, terrestrial, and island systems were overrepresented relative to their global surface area, whereas tropical, marine, and continental systems were comparatively overlooked. Plants, birds, fishes, mammals, and amphibians were studied disproportionately to their described diversity, while arthropods and molluscs remained underrepresented. Among plant-focused JSDMs, naturalized alien species were incorporated in roughly half of all cases, and competition emerged as the most frequently discussed interaction type, followed at a distance by facilitation and seed dispersal. Presence-absence datasets collected at a single point in time were more widely used than abundance and longitudinal data, although the latter appeared more often than would be expected given the scarcity of long-term monitoring programmes. Notably, studies relying on abundance data were more likely to interpret JSDM residuals as evidence of species interactions than those based on presence-absence data. These findings expose persistent geographic, taxonomic, and methodological biases in JSDM research, and highlight clear opportunities for extending applications toward tropical, marine, and invertebrate systems while harnessing quantitative and longitudinal datasets to better capture biotic interactions.

Keywords
Biotic interaction, community ecology, co-occurrence dataset, geographical gap, methodological gap, research bias
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