A robust distance coefficient between distribution areas incorporating geographic distances.

At a biogeographical scale, incomplete sampling is a hardly avoidable problem. Incomplete sampling can result in artefacts in R-mode analysis of biogeographic data, i.e., in the quantification of the similarity or dissimilarity of distribution areas of different organisms. Consider, for example, the hypothetical case shown in Figure 1. There are four distribution areas. Three taxa have similar distribution areas (A, B, C) in the northwest of the study region, whereas the fourth distribution area (D) is far away in the southeast. A similarity or distance measure is necessary to quantify the similarity or dissimilarity. A wealth of binary similarity and distance coefficients is available for that purpose (e.g., Cheetham and Hazel, 1969; Hubalek, 1982; Gower and Legendre, 1986; Shi, 1993). In Figure 2 the resulting distance matrices for some distance coefficients are shown. We denote distribution areas as sets A of geographic units, which are subsets of the total region under study R = [r\,..., r^} with k geographic units. |y4| denotes the number of elements in A The Jaccard distance

[1]  N. L. Johnson,et al.  Multivariate Analysis , 1958, Nature.

[2]  J. Kruskal Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis , 1964 .

[3]  J. Hazel,et al.  BINARY (PRESENCE-ABSENCE) SIMILARITY COEFFICIENTS , 1969 .

[4]  Taxonomy, phytogeography and evolution , 1973 .

[5]  Z. Hubálek COEFFICIENTS OF ASSOCIATION AND SIMILARITY, BASED ON BINARY (PRESENCE‐ABSENCE) DATA: AN EVALUATION , 1982 .

[6]  J. Gower,et al.  Metric and Euclidean properties of dissimilarity coefficients , 1986 .

[7]  G. Shi Multivariate data analysis in palaeoecology and palaeobiogeography—a review , 1993 .

[8]  Juan J. Morrone,et al.  On the Identification of Areas of Endemism , 1994 .

[9]  Roger L. H. Dennis,et al.  Faunal structures among European butterflies: evolutionary implications of bias for geography, endemism and taxonomic affiliation , 1998 .

[10]  Adrian E. Raftery,et al.  How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis , 1998, Comput. J..

[11]  A. P. Martinich,et al.  Using a Null Model to Recognize Significant Co-Occurrence Prior to Identifying Candidate Areas of Endemism , 2003 .

[12]  Christian Hennig,et al.  Biotic element analysis in biogeography. , 2003, Systematic biology.

[13]  C. Hennig,et al.  Does vicariance shape biotas? Biogeographical tests of the vicariance model in the north‐west European land snail fauna , 2004 .

[14]  Christian Hennig,et al.  Distance-based parametric bootstrap tests for clustering of species ranges , 2004, Comput. Stat. Data Anal..