Hotspot identification is a crucial strategy for setting conservation priorities. Since both the total number of species and the number of endemic species tend to increase with area, prioritizing sites according to their overall species richness or endemic species richness can produce rankings that simply mirror the sizes of the sites. Thus, it is important to control for the dependence of species number on site area. For this reason, some authors have proposed that the species–area relationship (SAR) and/or the endemics–area relationship (EAR) should be modelled and then the sites located above the fitted curve(s) (i.e. those having positive residuals) designated as hotspots. However, (1) there may be large uncertainties about which model provides the best fit to the SARs/EARs, (2) the use of residuals may lead to sites being identified as hotspots when they only have very few species and (3) there is no guarantee that the sites selected as hotspots by the SAR really include a large fraction of the overall diversity. Thus, it is important to evaluate the ability of the hotspots designated by these procedures to really conserve total and endemic species diversity; the best strategy may in fact be to use a combination of approaches.

We simulate habitat loss and derive species accumulation curves (SAC) and endemics–area relationship curves (EAR) in order to predict expected extinctions. The EAR may have a very different shape depending on the geometry of habitat loss. If area is lost in a spatially random way we may preserve more species than if area is lost in a clustered way, but with a larger extinction debt. If area is lost continuously inwards (‘inward EAR’) then the immediate loss of species can be much greater than if the same area is lost from the core towards its edge (‘outward EAR’). The main reason for these effects is the spatial autocorrelation of species distributions and the definition of endemics. Spatial autocorrelation means that sampling plots that are clustered are occupied by communities with more similar composition. If endemism is defined in relation to the study area, we can observe great species losses at the edge due to the large numbers of ranges that intersect the study area edge, but most of these species persist outside the study area. If instead we examine endemism on a global scale then the pattern of species losses is not influenced by the geometry of habitat loss.

It is widely acknowledged that we are in the midst of an extinction crisis and habitat loss is generally considered the primary driver. However, providing accurate estimates of extinction rates has proven to be problematic and a range of extinction estimates have been published. Arguably, the most commonly used method for predicting extinctions resulting from habitat loss has been application of the species–area relationship (SAR). The purpose of this chapter is to provide a review of the many ways in which the SAR has been used to predict the number of extinctions resulting from habitat loss. By doing so, we highlight the pitfalls of using the SAR in such a way and discuss how the SAR has been argued to both over-predict and under-predict extinctions. We also provide examples of the myriad ways in which studies have extended and built on standard SAR models and approaches to better model and predict extinctions. We conclude by arguing that there is a need to recognize that any approach based on a single variable (i.e. area), such as the SAR, is unlikely to provide a perfect extinction prediction, regardless of the specific details.