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International travellers are exposed to pathogens not commonly found in their countries of residence, including West Nile virus (WNV). Due to the difficulty of its diagnosis, little is known about its distribution in Africa. Understanding the geographic extent of risk of WNV infections is a necessity for both travellers and clinicians who advise and treat them, since there is no human vaccine. To date, there is no risk map for WNV infections in humans in Africa. Having a high-resolution risk map for the virus could be of relevance before the trip, to take preventive measures, and after the trip, for appropriate diagnosis of the disease. Virus detection in humans along the African continent were collected from official reports, and published scientific research for the period 1940 to 2020, and then geo-referenced in order to use biogeographical modelling for WNV. Models were based on fuzzy logic and machine learning algorithms and were designed to identify the environmental drivers that explain the distribution of human cases and to locate favourable areas for infections. We elaborated a high-resolution risk map for WNV infections that highlights favourable areas for infections in Africa. Although WNV infections are widely spread across Africa, the risk of the disease is not homogenously distributed. Popular tourist destinations such as Morocco, Tunisia, and South Africa, are high-risk areas for WNV infection. • The first risk map for human West Nile virus infection in Africa has been developed. • High-risk areas have been detected where West Nile virus infection has not yet been detected. • The highest risk areas coincide with major tourist destinations on the African continent. • The risk map could help clinicians to advice departing travellers and properly diagnose travellers returning from Africa. [ABSTRACT FROM AUTHOR]

Abstract: The effectiveness of selecting umbrella species or groups of species to protect other groups is a key and unresolved issue in conservation planning. We detected areas important to the four groups of terrestrial vertebrates inhabiting Andalusia (southern Spain) according to four conservation-value criteria, i.e., richness, rarity, vulnerability, and endemicity. We calculated coincidences between criteria and taxa by the degree of correlation and fuzzy overlap between the different criteria for the same group (intra-group coincidence) and between the different groups of species for the same criteria (inter-group coincidence). For the groups to be appropriate umbrella species, inter-group coincidence should be high. The results showed that intra-group coincidence was high, but inter-group coincidence was low. Thus, zones of importance to each group of species tended to be located in different places compared to the other groups, and therefore none of them should be used as an indicator or umbrella group to protect the others. This result has implications for conservation policy, as the Andalusian authorities should not assume that protecting a site important to one group of species will also be relevant to conserve the other groups. Nevertheless, we identified the areas of relatively high conjoint importance for all the groups, and the best umbrella group in this region, which proved to be reptiles. [Copyright &y& Elsevier]

We used the results of the Spanish Otter Survey of 1994–1996, a Geographic Information System and stepwise multiple logistic regression to model otter presence/absence data in the continental Spanish UTM 10×10-km squares. Geographic situation, indicators of human activity such as highways and major urban centers, and environmental variables related with productivity, water availability, altitude, and environmental energy were included in a logistic model that correctly classified about 73% of otter presences and absences. We extrapolated the model to the adjacent territory of Portugal, and increased the model''s spatial resolution by extrapolating it to 1×1-km squares in the whole Iberian Peninsula. The model turned out to be rather flexible, predicting, for instance, the species to be very restricted to the courses of rivers in some areas, and more widespread in others. This allowed us to determine areas where otter populations may be more vulnerable to habitat changes or harmful human interventions. [Copyright &y& Elsevier]