PREMISE OF THE STUDY Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatia...

Species distribution models (SDMs) are widely used to hindcast or forecast suitable habitat conditions during climate change. Although distant populations of a given species may show local adaptations diverging environmental conditions, traditional SDMs disregard intraspecific variation. Yet, incorporating genetic information into could improve predictions. Here we aimed at investigating whethe...

Coral reefs and their associated fauna are largely impacted by ongoing climate change. Unravelling species responses to past climatic variations might provide clues on the consequence of ongoing changes. Here, we tested the relationship between changes in sea surface temperature and sea levels during the Quaternary and present-day distributions of coral reef fish species. We investigated whethe...

Controlling for imperfect detection is important for developing species distribution models (SDMs). Occupancy-detection models based on the time needed to detect a species can be used to address this problem, but this is hindered when times to detection are not known precisely. Here, we extend the time-to-detection model to deal with detections recorded in time intervals and illustrate the meth...

Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often u...

Invasive plants are an increasing threat to global biodiversity. Effective management depends on accurate predictions of their spread. However, modelling the geographic distribution invasive species, particularly with correlative species models (SDMs), is challenging. SDMs assume that in equilibrium environment (i.e. they occur all suitable environments); this assumption likely be violated for ...

Methods We compared two community modelling approaches: the classical method of stacking binary prediction obtained from individual species distribution models (binary stacked species distribution models, bS-SDMs), and various implementations of a recent framework (spatially explicit species assemblage modelling, SESAM) based on four steps that integrate the different drivers of the assembly pr...

Species distribution models (SDMs) are one of the most widely used approaches to predict changes in habitat suitability response climate change. However, as typically implemented, SDMs treat species genetically uniform throughout their ranges and thereby ignore potentially important genetic differences between populations. While numerous studies have model based subgroupings within species, abi...

Species delimitation is a major research focus in evolutionary biology because accurate species boundaries are a prerequisite for the study of speciation. New species delimitation methods (SDMs) can accommodate nonmonophyletic species and gene tree discordance as a result of incomplete lineage sorting via the coalescent model, but do not explicitly accommodate gene flow after divergence. Approx...

12 1. Species distribution models (SDMs) can be used to predict how individual species—and 13 whole assemblages of species—will respond to a changing environment. Until now, these 14 models have either assumed (1) that species’ occurrence probabilities are uncorrelated, 15 or (2) that species respond linearly to preselected environmental variables. These two 16 assumptions currently prevent eco...