Abstract
BackgroundAim of the study was to identify the conditions under which spatial-environmental models can be used for the improved understanding of species distributions, under the explicit criterion of model predictive performance. I constructed distribution models for 17 amphibian and 21 reptile species in Portugal from atlas data and 13 selected ecological variables with stepwise logistic regression and a geographic information system. Models constructed for Portugal were extrapolated over Spain and tested against range maps and atlas data.ResultsDescriptive model precision ranged from 'fair' to 'very good' for 12 species showing a range border inside Portugal ('edge species', kappa (k) 0.35–0.89, average 0.57) and was at best 'moderate' for 26 species with a countrywide Portuguese distribution ('non-edge species', k = 0.03–0.54, average 0.29). The accuracy of the prediction for Spain was significantly related to the precision of the descriptive model for the group of edge species and not for the countrywide species. In the latter group data were consistently better captured with the single variable search-effort than by the panel of environmental data.ConclusionAtlas data in presence-absence format are often inadequate to model the distribution of species if the considered area does not include part of the range border. Conversely, distribution models for edge-species, especially those displaying high precision, may help in the correct identification of parameters underlying the species range and assist with the informed choice of conservation measures.
Highlights
Aim of the study was to identify the conditions under which spatial-environmental models can be used for the improved understanding of species distributions, under the explicit criterion of model predictive performance
This paper presents distribution models for amphibians and reptiles in Portugal build from environmental variables
If nine instead of 13 environmental parameters were available for selection, kappa ranged from 0.26 to 0.86 and Area Under the Curve' statistics (AUC) ranged from 0.68 ± 0.023 to 0.99 ± 0.003 (Table 1)
Summary
Aim of the study was to identify the conditions under which spatial-environmental models can be used for the improved understanding of species distributions, under the explicit criterion of model predictive performance. I constructed distribution models for 17 amphibian and 21 reptile species in Portugal from atlas data and 13 selected ecological variables with stepwise logistic regression and a geographic information system. Models constructed for Portugal were extrapolated over Spain and tested against range maps and atlas data. Atlases of distribution data have provided a popular and successful way of assembling spatial information on a variety of organisms, including amphibians and reptiles. The building of distribution models is not always clearly distinguished from the evaluation of the results. These are serious shortcomings because data plots require interpretation before they can be used for i.e., increased biological understanding, policy making and conservation management [6,7]. Even for the best of empirical data sets, the analysis is not straightforward because one has to choose from a wide variety of spatialstatistical analytical techniques, each of which carries assumptions that are unlikely to be met in full [8,9,10]
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