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The potential existence of a wild bird reservoir for highly pathogenic avian influenza (HPAI) has been recently questioned by the spread and the persisting circulation of H5N1 HPAI viruses, responsible for concurrent outbreaks in migratory and domestic birds over Asia, Europe, and Africa. During a large-scale surveillance programme over Eastern Europe, the Middle East, and Africa, we detected avian influenza viruses of H5N2 subtype with a highly pathogenic (HP) viral genotype in healthy birds of two wild waterfowl species sampled in Nigeria. We monitored the survival and regional movements of one of the infected birds through satellite telemetry, providing a rare evidence of a non-lethal natural infection by an HP viral genotype in wild birds. Phylogenetic analysis of the H5N2 viruses revealed close genetic relationships with H5 viruses of low pathogenicity circulating in Eurasian wild and domestic ducks. In addition, genetic analysis did not reveal known gallinaceous poultry adaptive mutations, suggesting that the emergence of HP strains could have taken place in either wild or domestic ducks or in non-gallinaceous species. The presence of coexisting but genetically distinguishable avian influenza viruses with an HP viral genotype in two cohabiting species of wild waterfowl, with evidence of non-lethal infection at least in one species and without evidence of prior extensive circulation of the virus in domestic poultry, suggest that some strains with a potential high pathogenicity for poultry could be maintained in a community of wild waterfowl.

While high resolution spatial variables contribute to a good fit of spatially-explicit deforestation models, socio-economic processes are often beyond the scope of these models. Such a low level of interest in the socio-economic dimension of deforestation limits the relevancy of these models for decision making and may be the cause of their failure to accurately predict observed deforestation trends in the medium term. This study aims to propose a flexible methodology for taking into account multiple drivers of deforestation in tropical forested areas, where the intensity of deforestation is explicitly predicted based on socio-economic variables. By coupling a model of deforestation location based on spatial environmental variables with several sub-models of deforestation intensity based on socio-economic variables, we were able to create a map of predicted deforestation over the period 2001–2014 in French Guiana. This map was compared to a reference map for accuracy assessment, not only at the pixel scale but also over cells ranging from 1 to approx. 600 sq. km. Highly significant relationships were explicitly established between deforestation intensity and several socio-economic variables: population growth, the amount of agricultural subsidies, gold and wood production. Such a precise characterisation of socio-economic processes allows to avoid overestimation biases in high deforestation areas, suggesting a better integration of socio-economic processes in the models. While considering deforestation as a purely geographical process contributes to the creation of conservative models unable to effectively assess changes in the socio-economic and political contexts influencing deforestation trends, this explicit characterisation of the socio-economic dimension of deforestation is critical for the creation of deforestation scenarios in REDD+ projects.