An improved method for the identification of areas of endemism using species co-occurrences

Aim To develop a simple method that (1) combines the notions of biotic elements (groups of taxa with ranges significantly more similar to each other than to the ranges of other taxa) and of areas of endemism (AoE, areas of non-random distributional congruence among taxa), and (2) overcomes the constraints of a previously suggested null model-based method that cannot deal with disjunctions and is strictly grid-dependent. Location We used test data sets from southern Africa and Crete. Methods First, we used a null-model approach to detect pairs of species that have a significant degree of co-occurrence, in order to determine biotic elements. Subsequently, we used a parsimony analysis of endemicity to delineate candidate AoE, and multivariate analysis to define groups of biotic elements on the basis of species interactions (co-occurrence, mutual exclusion, neutral) using only the species detected in the previous step. We applied this method to the well known data set for Sciobius in southern Africa, as well as to endemic invertebrates of Crete (Greece), in order to evaluate its performance. Results Our results are very similar to those of previous analyses, and produce meaningful delineation of AoE and biotic elements in both data sets. The method is flexible regarding null models and significance levels, and eliminates noise in the data. Main conclusions We offer a simple method that provides reasonable identification of both biotic elements and AoE, produces good-fit statistics, reduces uninformative or junk output, and reduces computational time.