Atlas versus range maps: robustness of chorological relationships to distribution data types in European mammals

Aim: Chorological relationships describe the patterns of distributional overlap among species. In addition to revealing biogeographical structure, the resulting clusters of species with similar geographical distributions can serve as natural units in conservation planning. Here, we assess the extent...

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Published in:	Journal of biogeography 2012-08, Vol.39 (8), p.1391-1400
Main Authors:	Márcia Barbosa, A., Estrada, Alba, Márquez, Ana L., Purvis, Andy, Orme, C. David L.
Format:	Article
Language:	eng
Subjects:	Animal and plant ecology Animal, plant and microbial ecology Biodiversity conservation Biogeography Biological and medical sciences Chorology conservation biogeography Contributions from the International Biogeography Society meeting, Crete, 2011 data mismatch data quality Data ranges Data types Datasets distributional relationships Europe Fundamental and applied biological sciences. Psychology fuzzy similarity General aspects Mammalia Mammals resolution scale Species Synecology Vertebrates: general zoology, morphology, phylogeny, systematics, cytogenetics, geographical distribution Wildlife conservation
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Summary:	Aim: Chorological relationships describe the patterns of distributional overlap among species. In addition to revealing biogeographical structure, the resulting clusters of species with similar geographical distributions can serve as natural units in conservation planning. Here, we assess the extent to which temporal, methodological and taxonomical differences in the source of species' distribution data can affect the relationships that are found. Location: Western Europe. Methods: We used two data sets — the Atlas of European mammals and polygon range maps from the IUCN Global Mammal Assessment — both as presence—absence data for UTM 50 km × 50 km squares. We performed pairwise comparisons among 156 species for each data set to build matrices of the similarity in distribution across species, using both Jaccard's and Baroni-Urbani & Buser's indices. We then compared these similarity matrices (chorological relationships), as well as the species richness and occurrence patterns from the two data sets. Results: As expected, range maps increased both the mean prevalence per species and mean species richness per grid cell in comparison to atlas data, reflecting the general view that these data types respectively over- and underestimate species occurrence. However, species richness and occurrence patterns in atlas and range map data were positively associated and, most importantly, the chorological relationships underlying the two data sets were highly similar. Main conclusions: Despite many methodological, temporal and taxonomical differences between atlas data and range maps, the chorological relationships encountered between species were similar for both data sets. Chorological analyses can thus be robust to the data source used and provide a solid basis for analytical biogeographical studies, even over broad spatial scales.
ISSN:	0305-0270 1365-2699