Connectivity, probabilities and persistence: Comparing reserve selection strategies

Reserve selection methods are often based on information on species' occurrence. This can be presence-absence data, or probabilities of occurrence estimated with species distribution models. However, the effect of the choice of distribution model on the outcome of a reserve selection method has been ignored. Here we test a range of species distribution models with three different reserve selection methods. The distribution models had different combinations of variables related to habitat quality and connectivity (which incorporates the effect of spatial habitat configuration on species occurrence). The reserve selection methods included (i) a minimum set approach without spatial considerations; (ii) a clustering reserve selection method; and (iii) a dynamic approach where probabilities of occurrence are re-evaluated according to the spatial pattern of selected sites. The sets of selected reserves were assessed by re-computing species probability of occurrence in reserves using the best probability model and assuming loss of non-selected habitat. The results show that particular choices of distribution model and selection method may lead to reserves that overestimate the achieved target; in other words, species may seem to be represented but the reserve network may actually not be able to support them in the long-term. Instead, the use of models that incorporated connectivity as a variable resulted in the selection of aggregated reserves with higher potential for species long-term persistence. As reserve design aims at the long-term protection of species, it is important to be aware of the uncertainties related to model and method choice and their implications.