Direct and indirect effects of climate and habitat factors on butterfly diversity

Many factors, including climate, resource availability, and habitat diversity, have been proposed as determinants of global diversity, but the links among them have rarely been studied. Using structural equation modeling (SEM), we investigated direct and indirect effects of climate variables, host-plant richness, and habitat diversity on butterfly species richness across Britain, at 20-km grid resolution. These factors were all important determinants of butterfly diversity, but their relative contributions differed between habitat generalists and specialists, and whether the effects were direct or indirect. Climate variables had strong effects on habitat generalists, whereas host-plant richness and habitat diversity contributed relatively more for habitat specialists. Considering total effects (direct and indirect together), climate variables had the strongest link to butterfly species richness for all groups of species. The results suggest that different mechanistic hypotheses to explain species richness may be more appropriate for habitat generalists and specialists, with generalists hypothesized to show direct physiological limitations and specialists additionally being constrained by trophic interactions (climate affecting host-plant richness).     

Assessing the Impacts of Future Climate Change on Protected Area Networks: A Method to Simulate Individual Species' Responses

Global climate change, along with continued habitat loss and fragmentation, is now recognized as being a major threat to future biodiversity. There is a very real threat to species, arising from the need to shift their ranges in the future to track regions of suitable climate. The Important Bird Area (IBA) network is a series of sites designed to conserve avian diversity in the face of current threats from factors such as habitat loss and fragmentation. However, in common with other networks, the IBA network is based on the assumption that the climate will remain unchanged in the future. In this article, we provide a method to simulate the occurrence of species of conservation concern in protected areas, which could be used as a first-step approach to assess the potential impacts of climate change upon such species in protected areas. We use species-climate response surface models to relate the occurrence of 12 biome-restricted African species to climate data at a coarse (quarter degree-degree latitude-longitude) resolution and then intersect the grid model output with IBA outlines to simulate the occurrence of the species in South African IBAs. Our results demonstrate that this relatively simple technique provides good simulations of current species' occurrence in protected areas. We then use basic habitat data for IBAs along with habitat preference data for the species to reduce over-prediction and further improve predictive ability. This approach can be used with future climate change scenarios to highlight vulnerable species in IBAs in the future and allow practical recommendations to be made to enhance the IBA network and minimize the predicted impacts of climate change.