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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1111/gcb.15784
|2 doi
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|a pubmed24n1091.xml
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|a (DE-627)NLM327609109
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|a (NLM)34214237
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|a DE-627
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|e rakwb
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|a eng
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| 100 |
1 |
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|a Wang, Yingying X G
|e verfasserin
|4 aut
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| 245 |
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|a Mammal assemblage composition predicts global patterns in emerging infectious disease risk
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|c 2021
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 20.10.2021
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|a Date Revised 22.10.2021
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2021 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
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|a 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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|a Journal Article
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|a assemblage composition
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|a climate change
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|a emerging infectious diseases
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| 650 |
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|a habitat loss
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| 650 |
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4 |
|a infectious disease hotspots
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| 650 |
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4 |
|a species distributions
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| 700 |
1 |
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|a Matson, Kevin D
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Santini, Luca
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Visconti, Piero
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Hilbers, Jelle P
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Huijbregts, Mark A J
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Xu, Yanjie
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Prins, Herbert H T
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Allen, Toph
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Huang, Zheng Y X
|e verfasserin
|4 aut
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| 700 |
1 |
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|a de Boer, Willem F
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t Global change biology
|d 1999
|g 27(2021), 20 vom: 02. Okt., Seite 4995-5007
|w (DE-627)NLM098239996
|x 1365-2486
|7 nnns
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| 773 |
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|g volume:27
|g year:2021
|g number:20
|g day:02
|g month:10
|g pages:4995-5007
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|u http://dx.doi.org/10.1111/gcb.15784
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