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Mammal assemblage composition predicts global patterns in emerging infectious disease risk.
Wang, Yingying X G; Matson, Kevin D; Santini, Luca; Visconti, Piero; Hilbers, Jelle P; Huijbregts, Mark A J; Xu, Yanjie; Prins, Herbert H T; Allen, Toph; Huang, Zheng Y X; de Boer, Willem F.
Afiliação
  • Wang YXG; Wildlife Ecology and Conservation Group, Wageningen University and Research, Wageningen, The Netherlands.
  • Matson KD; Department of Biological and Environmental Science, University of Jyväskylä, Jyväskylä, Finland.
  • Santini L; Wildlife Ecology and Conservation Group, Wageningen University and Research, Wageningen, The Netherlands.
  • Visconti P; Department of Biology and Biotechnologies "Charles Darwin", Sapienza University of Rome, Rome, Italy.
  • Hilbers JP; Institute of Research on Terrestrial Ecosystems (CNR-IRET), National Research Council, Monterotondo (Rome), Italy.
  • Huijbregts MAJ; Department of Environmental Science, Radboud University, Nijmegen, The Netherlands.
  • Xu Y; International Institute for Applied System Analysis, Laxenburg, Austria.
  • Prins HHT; Institute of Zoology, Zoological Society of London, London, UK.
  • Allen T; Department of Environmental Science, Radboud University, Nijmegen, The Netherlands.
  • Huang ZYX; Department of Environmental Science, Radboud University, Nijmegen, The Netherlands.
  • de Boer WF; Wildlife Ecology and Conservation Group, Wageningen University and Research, Wageningen, The Netherlands.
Glob Chang Biol ; 27(20): 4995-5007, 2021 10.
Article em En | MEDLINE | ID: mdl-34214237
ABSTRACT
As a source of emerging infectious diseases, wildlife assemblages (and related spatial patterns) must be quantitatively assessed to help identify high-risk locations. Previous assessments have largely focussed on the distributions of individual species; however, transmission dynamics are expected to depend on assemblage composition. Moreover, disease-diversity relationships have mainly been studied in the context of species loss, but assemblage composition and disease risk (e.g. infection prevalence in wildlife assemblages) can change without extinction. Based on the predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk through the calculation of the community-level basic reproductive ratio R0, an index of invasion potential, persistence, and maximum prevalence of a pathogen in a wildlife assemblage. For density-dependent diseases, we found that, in addition to tropical areas which are commonly viewed as infectious disease hotspots, northern temperate latitudes included high-risk areas. We also forecasted the effects of climate change and habitat loss from 2015 to 2035. Over this period, many local assemblages showed no net loss of species richness, but the assemblage composition (i.e. the mix of species and their abundances) changed considerably. Simultaneously, most areas experienced a decreased risk of density-dependent diseases but an increased risk of frequency-dependent diseases. We further explored the factors driving these changes in disease risk. Our results suggest that biodiversity and changes therein jointly influence disease risk. Understanding these changes and their drivers and ultimately identifying emerging infectious disease hotspots can help health officials prioritize resource distribution.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Transmissíveis Emergentes Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Revista: Glob Chang Biol Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Transmissíveis Emergentes Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Animals Idioma: En Revista: Glob Chang Biol Ano de publicação: 2021 Tipo de documento: Article