Endemicity analysis, parsimony and biotic elements: a formal comparison using hypothetical distributions


  • M. Dolores Casagranda,

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  • Leila Taher,

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    • Present address: Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.

  • Claudia A. Szumik

    1. Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto Superior de Entomología, Facultad de Ciencias Naturales, Miguel Lillo 205, 4000, S.M. de Tucumán, Argentina
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Corresponding author:
E-mail address: dolores.casagranda@gmail.com


There is as yet no general agreement regarding the most appropriate solution to the problem of identifying areas of endemism, not even in particular cases. In this study, we compared Endemicity Analysis (EA), Parsimony Analysis of Endemicity (PAE), and Biotic Elements Analysis (BE) based on their ability to identify hypothetical predefined patterns that represent nested, overlapping, and disjoint areas of endemism supported by species with different degrees of sympatry. We found that PAE performs poorly when applied to patterns that either overlap with each other or are supported by species with imperfect sympatry. BE exhibits a counterintuitive sensitivity to the degree of congruence among the distributions of endemic species, being unable to recognize areas of endemism supported by perfectly sympatric species. In contrast, in all cases examined we found that EA results in a high proportion of correctly identified distributional patterns. In addition to highlighting the strengths and limitations of these approaches, our results show how different methods can lead to seemingly conflicting conclusions and caution about the possibility of identifying distributional patterns that are merely methodological artefacts.

© The Willi Hennig Society 2012.