The future of biodiversity is likely to undergo profound changes as a result of global changes induced by humans, hence there is a pressing need to assess the potential responses of species to global change. This response can be assessed by the use of species distribution models (SDMs; also named environmental niche modeling), which provide a very important opportunity of using “presence only” occurrence data from biodiversity databases. To my mind, there are two very relevant opportunities of applying SDMs for conservation, in order to develop proactive management strategies. First, their application to predict the risk for additional threats of future global change on threatened species. Second, the application of SDMs to invasive species to predict the current and future risks of invasions.
The responses of many taxa of vertebrates and plants to the effects of future changes were evaluated and predicted. However, the majority of invertebrate groups have been neglected in these analyses. Yet, the few existing studies highlighted a potential strong response. Hence, I developed a robust application of SDMs on the taxon of spiders, and I was able to provide the first assessment of the effects of future changes on a threatened species of this taxon. I developed this application in the context of a French conservation program, the “Strategy Creation of Protected Areas” ( SCAP ), which aims at protecting 2% of the French metropolitan area by 2020, on the basis of selected species.
I developed the first application on the vulnerable species Dolomedes plantarius (Clerck), which is, in addition to the SCAP, subject to a conservation program and translocation in the UK . The application of predictive models proved to be relevant by the high performance models and significant response of the species to the selected environmental variables. The models predicted significant negative effects of global change for this species, according to two global change scenarios, with a predicted decrease in the potential range and a predicted negative response of populations to local changes in climate and land use (Leroy et al. 2013).