Distance-based parametric bootstrap tests for clustering of species ranges

Christian Hennig and Bernhard Hausdorf

November 2002

Abstract: This paper deals with species range data, i.e., n species (taxa) arecharacterized by their presence or absence on c units into which amap is subdivided. Such data occur often in biogeography. We propose some tests forthe existence of clusters of species according to their ranges. We define some distance-based test statistics for the presence ofclustering, we propose a null model for the generation of a species and analternative model for clustering.The models include a parameter governing the spatial autocorrelation of itsoccurrence in the cells and they account for the species richness ofthe individual cells. The distribution of the test statistics can beestimated by a parametric bootstrap simulation (Monte Carlo with estimatedparameters) from the null model. Thevalidity of the p-values and the power of the tests are considered byexemplary simulations.We discuss also, but do not focus on, the determination of the clusters.

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