An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo‐absence data

Summary Few examples of habitat‐modelling studies of rare and endangered species exist in the literature, although from a conservation perspective predicting their distribution would prove particularly useful. Paucity of data and lack of valid absences are the probable reasons for this shortcoming. Analytic solutions to accommodate the lack of absence include the ecological niche factor analysis (ENFA) and the use of generalized linear models (GLM) with simulated pseudo‐absences. In this study we tested a new approach to generating pseudo‐absences, based on a preliminary ENFA habitat suitability (HS) map, for the endangered species Eryngium alpinum . This method of generating pseudo‐absences was compared with…