Using species distribution models for IUCN Red Lists of threatened species

Red Lists have been used for years globally and regionally in many countries to highlight species that need special attention because of the rarity or rapid decline of their populations. To ensure homogenized classification at the global and regional level, the International Union for Conservation of Nature (IUCN) defined categories of threat, and criteria to attribute the taxa to these categories. Nevertheless, the strict application of the criteria is not always straightforward, especially for invertebrates, because of the difficulties associated with precise estimates of the size and viability of their populations. This paper presents a method for the estimation of extent of occurrence (EOO) and area of occupancy (AOO) based on species distribution models using multivariate adaptive regression splines. To achieve this, presence data have been modeled against topographical and climatic explanatory variables. Predictions from the statistical distribution models have then been cut using the minimal convex hull around (EOO) or the watersheds in which (AOO) the species have really been observed in recent years. This allows us to delimit the EOO and AOO according to the IUCN criteria, and better take into account the ecological requirements of the species. Furthermore, the method allows for the use of historical data (e.g. from museum’s collections) and the direct comparison of historical and recent distributions of species. The method has been tested on six species of butterflies. The results show the possibility of using species distribution models to define the Red Lists status according to the IUCN guidelines, and shows that the results are consistent with previous Red Lists assessments.