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Chorotypes—statistically significant groups of coincident distribution areas—constitute biogeographic units that are fuzzy by nature. This quality has been referred to in the literature but has not been analyzed in depth or methodologically developed. The present work redefines chorotypes as fuzzy sets from a pragmatic perspective and basically focuses on the methodological and interpretative implications of this approach. The amphibian fauna in the Iberian Peninsula was used as an example to explore the fuzzy nature of chorotypes. The method on which this article is based is a widely used technique to define chorotypes. This method involves the fuzziness that is inherent to the identification between degree of similarity and degree of membership and includes a probabilistic analysis of the classification for the objective delimitation of chorotypes. The main innovation of this paper is a procedure to analyze chorotypes as fuzzy biogeographic units. A set of fuzzy parameters to deal with the biogeographic interpretation of fuzzy chorotypes is also described. A computer program has been developed and is freely available. History may be related to the degree of fuzziness of chorotypes. In our example, with amphibian distributions in Iberia, less fuzzy chorotypes could have a historical explanation, and the internal fuzziness of chorotypes increases with their distance to hypothetical Pleistocene refugia. [ABSTRACT FROM PUBLISHER]

Transferring distribution models between different geographical areas may be problematic, as the performance of models outside their original scope is hard to predict. A modelling procedure is needed that gets the gist of the environmental descriptors of a distribution area, without either overfitting to the training data or overestimating the species’ distribution potential. We tested the transferability power of the favourability function, a generalized linear model, on the distribution of the Iberian desman (Galemys pyrenaicus) in the Iberian territories of Portugal and Spain. We also tested the effects of two of the main potential constraints on model transferability: the analysed ranges of the predictor variables, and the completeness of the species distribution data. We modelled 10km×10km presence/absence data from Portugal and Spain separately, extrapolated each model to the other country, and compared predictions with observations. The Spanish model, despite arguably containing more false absences, showed good predictive ability in Portugal. The Portuguese model, whose predictors ranged between only a subset of the values observed in Spain, overestimated desman distribution when transferred. We discuss possible reasons for this differential model behaviour, and highlight the importance of this kind of models for prediction and conservation applications. [Copyright &y& Elsevier]

BackgroundWest Nile virus (WNV) is a flavivirus with an enzootic cycle between birds and mosquitoes; humans and horses are incidental dead-end hosts. In 2020, the largest outbreak of West Nile virus infection in the Iberian Peninsula occurred, with 141 clusters in horses and 77 human cases.AimWe analysed which drivers influence spillover from the cycle to humans and equines and identified areas at risk for WNV transmission.MethodsBased on data on WNV cases in horses and humans in 2020 in Portugal and Spain, we developed logistic regression models using environmental and anthropic variables to highlight risk areas. Models were adapted to a high-resolution risk map.ResultsCases of WNV in horses could be used as indicators of viral activity and thus predict cases in humans. The risk map of horses was able to define high-risk areas for previous cases in humans and equines in Portugal and Spain, as well as predict human and horse cases in the transmission seasons of 2021 and 2022. We found that the spatial patterns of the favourable areas for outbreaks correspond to the main hydrographic basins of the Iberian Peninsula, jointly affecting Portugal and Spain.ConclusionA risk map highlighting the risk areas for potential future cases could be cost-effective as a means of promoting preventive measures to decrease incidence of WNV infection in Europe, based on a One Health surveillance approach.

We modelled the distributions of two toads (Bufo bufo and Epidalea calamita) in the Iberian Peninsula using the favourability function, which makes predictions directly comparable for different species and allows fuzzy logic operations to relate different models. The fuzzy intersection between individual models, representing favourability for the presence of both species simultaneously, was compared with another favourability model built on the presences shared by both species. The fuzzy union between individual models, representing favourability for the presence of any of the two species, was compared with another favourability model based on the presences of either or both of them. The fuzzy intersections between favourability for each species and the complementary of favourability for the other (corresponding to the logical operation "A and not B") were compared with models of exclusive presence of one species versus the exclusive presence of the other. The results of modelling combined species data were highly similar to those of fuzzy logic operations between individual models, proving fuzzy logic and the favourability function valuable for comparative distribution modelling. We highlight several advantages of fuzzy logic over other forms of combining distribution models, including the possibility to combine multiple species models for management and conservation planning.

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter (Lutra lutra), in the Iberian Peninsula. The models, built from presence-absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures., (© 2010 Society for Conservation Biology.)