The use of spatial ecological modelling as a tool for improving the assessment of geographic range size of threatened species

We analysed endemic threatened tree and reptile species of Socotra Island (Yemen), characterised by different ecological requirements and spatial distribution, in order to evaluate the usefulness of spatial ecological modelling in the estimation of species extent of occurrence (EOO) and area of occupancy (AOO). Point occurrences for the entire species range were used to model their spatial distribution by Random Forest (RF) and Generalised Linear Model (GLM). For each species the suitability area (SA) was obtained by applying the 0% omission error criterion on the probability map, and compared or integrated with EOO and AOO area obtained by topological methods such as the minimum convex polygon (MCP), alpha-hull and 2 km x 2 km grid. RF showed a lower prediction error than GLM. Higher accuracy was achieved for species with higher number of occurrences and narrower ecological niche. SA was always greater than AOO measured with the 2 km x 2 km grid method. SA was greater than EOO, measured by both MCP and alpha-hull methods, for species with localised distribution, while it was smaller for widely distributed species. EOO-alpha-hull area was equal or smaller than that calculated by MCP depending on the spatial distribution of species. AOO measured considering the SA within the EOO-MCP was greater than that measured using the standard 2 km x 2 km grid. Conversely, AOO calculated considering the suitable area within the EOO-alpha-hull showed variable results, being smaller or greater than the 2 km x 2 km grid AOO depending on the ecological niche and spatial distribution of species. According to our results, SEM does not provide an effective alternative to topological methods for the estimate of EOO and AOO. However, it may be considered a useful tool to estimate AOO within the boundaries of EOO measured by the alpha-hull method, because it reduces some potential sources of inconsistency and bias