Mammal assemblage composition predicts global patterns in emerging infectious disease risk
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...
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creator | 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. Boer, Willem F. |
description | 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.
Emerging infectious diseases are serious global threats. Most of these diseases originate from wildlife, particularly mammals, which face an ongoing biodiversity crisis. Using predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk by calculating community‐level R0. High values in temperate European, Asian, and North American locations point to risks beyond the tropics. Forecasted effects of climate change and habitat loss from 2015 to 2035 suggested many mammal assemblages will change considerably in their composition, even without local extinctions. Simultaneously, most areas were predicted to have decreased density‐dependent disease risk but i |
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Emerging infectious diseases are serious global threats. Most of these diseases originate from wildlife, particularly mammals, which face an ongoing biodiversity crisis. Using predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk by calculating community‐level R0. High values in temperate European, Asian, and North American locations point to risks beyond the tropics. Forecasted effects of climate change and habitat loss from 2015 to 2035 suggested many mammal assemblages will change considerably in their composition, even without local extinctions. Simultaneously, most areas were predicted to have decreased density‐dependent disease risk but increased frequency‐dependent disease risk.</description><identifier>ISSN: 1354-1013</identifier><identifier>EISSN: 1365-2486</identifier><identifier>DOI: 10.1111/gcb.15784</identifier><identifier>PMID: 34214237</identifier><language>eng</language><publisher>Oxford: Blackwell Publishing Ltd</publisher><subject>Abundance ; assemblage composition ; Biodiversity ; Climate change ; Climate effects ; Composition ; Density ; Disease hot spots ; emerging infectious diseases ; Habitat loss ; Health risks ; Hot spots ; infectious disease hotspots ; Infectious diseases ; Mammals ; Net losses ; Pathogens ; Primary ; Primary s ; species distributions ; Species extinction ; Species richness ; Tropical climate ; Wildlife ; Wildlife habitats</subject><ispartof>Global change biology, 2021-10, Vol.27 (20), p.4995-5007</ispartof><rights>2021 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2021. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4204-2a4b0d86db35ba1c6410331a118b9c0d0461ab0c51b46c78fd20c1c475bac4fb3</citedby><cites>FETCH-LOGICAL-c4204-2a4b0d86db35ba1c6410331a118b9c0d0461ab0c51b46c78fd20c1c475bac4fb3</cites><orcidid>0000-0002-9401-589X ; 0000-0002-8761-3787 ; 0000-0001-6823-2826 ; 0000-0003-1131-5107 ; 0000-0003-3066-197X ; 0000-0002-4373-5926 ; 0000-0003-3208-8521 ; 0000-0002-7037-680X ; 0000-0003-4580-091X ; 0000-0003-4420-6353 ; 0000-0002-5418-3688</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fgcb.15784$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fgcb.15784$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Wang, Yingying X. G.</creatorcontrib><creatorcontrib>Matson, Kevin D.</creatorcontrib><creatorcontrib>Santini, Luca</creatorcontrib><creatorcontrib>Visconti, Piero</creatorcontrib><creatorcontrib>Hilbers, Jelle P.</creatorcontrib><creatorcontrib>Huijbregts, Mark A. J.</creatorcontrib><creatorcontrib>Xu, Yanjie</creatorcontrib><creatorcontrib>Prins, Herbert H. T.</creatorcontrib><creatorcontrib>Allen, Toph</creatorcontrib><creatorcontrib>Huang, Zheng Y. X.</creatorcontrib><creatorcontrib>Boer, Willem F.</creatorcontrib><title>Mammal assemblage composition predicts global patterns in emerging infectious disease risk</title><title>Global change biology</title><description>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.
Emerging infectious diseases are serious global threats. Most of these diseases originate from wildlife, particularly mammals, which face an ongoing biodiversity crisis. Using predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk by calculating community‐level R0. High values in temperate European, Asian, and North American locations point to risks beyond the tropics. Forecasted effects of climate change and habitat loss from 2015 to 2035 suggested many mammal assemblages will change considerably in their composition, even without local extinctions. Simultaneously, most areas were predicted to have decreased density‐dependent disease risk but increased frequency‐dependent disease risk.</description><subject>Abundance</subject><subject>assemblage composition</subject><subject>Biodiversity</subject><subject>Climate change</subject><subject>Climate effects</subject><subject>Composition</subject><subject>Density</subject><subject>Disease hot spots</subject><subject>emerging infectious diseases</subject><subject>Habitat loss</subject><subject>Health risks</subject><subject>Hot spots</subject><subject>infectious disease hotspots</subject><subject>Infectious diseases</subject><subject>Mammals</subject><subject>Net losses</subject><subject>Pathogens</subject><subject>Primary</subject><subject>Primary s</subject><subject>species distributions</subject><subject>Species extinction</subject><subject>Species richness</subject><subject>Tropical climate</subject><subject>Wildlife</subject><subject>Wildlife habitats</subject><issn>1354-1013</issn><issn>1365-2486</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><recordid>eNp1kT9PwzAQxS0EolAY-AaRmBjS-mznDwsSVFCQilhgYbFsxwkuSRzsBNRvj0sqJAZuuSfd796d9BA6AzyDUPNKyRkkWc720BHQNIkJy9P9rU5YDBjoBB17v8YYU4LTQzShjAAjNDtCr4-iaUQdCe91I2tR6UjZprPe9Ma2Ued0YVTvo6q2MmCd6HvtWh-ZNtKNdpVpq6BLrQI--KgwXguvI2f8-wk6KEXt9emuT9HL3e3z4j5ePS0fFterWDGCWUwEk7jI00LSRApQKQNMKQiAXF4qXGCWgpBYJSBZqrK8LAhWoFgWaMVKSafoavTtBtnoQum2d6LmnTONcBtuheF_J61545X95HkCeQo0GJzvDJz9GLTv-doOrg0_c5JkJCEYAwTqYqSUs947Xf5eAMy3MfAQA_-JIbDzkf0ytd78D_Ll4mbc-Aa5oImx</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Wang, Yingying X. G.</creator><creator>Matson, Kevin D.</creator><creator>Santini, Luca</creator><creator>Visconti, Piero</creator><creator>Hilbers, Jelle P.</creator><creator>Huijbregts, Mark A. J.</creator><creator>Xu, Yanjie</creator><creator>Prins, Herbert H. T.</creator><creator>Allen, Toph</creator><creator>Huang, Zheng Y. X.</creator><creator>Boer, Willem F.</creator><general>Blackwell Publishing Ltd</general><general>John Wiley and Sons Inc</general><scope>24P</scope><scope>WIN</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H97</scope><scope>L.G</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-9401-589X</orcidid><orcidid>https://orcid.org/0000-0002-8761-3787</orcidid><orcidid>https://orcid.org/0000-0001-6823-2826</orcidid><orcidid>https://orcid.org/0000-0003-1131-5107</orcidid><orcidid>https://orcid.org/0000-0003-3066-197X</orcidid><orcidid>https://orcid.org/0000-0002-4373-5926</orcidid><orcidid>https://orcid.org/0000-0003-3208-8521</orcidid><orcidid>https://orcid.org/0000-0002-7037-680X</orcidid><orcidid>https://orcid.org/0000-0003-4580-091X</orcidid><orcidid>https://orcid.org/0000-0003-4420-6353</orcidid><orcidid>https://orcid.org/0000-0002-5418-3688</orcidid></search><sort><creationdate>202110</creationdate><title>Mammal assemblage composition predicts global patterns in emerging infectious disease risk</title><author>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. ; Boer, Willem F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4204-2a4b0d86db35ba1c6410331a118b9c0d0461ab0c51b46c78fd20c1c475bac4fb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Abundance</topic><topic>assemblage composition</topic><topic>Biodiversity</topic><topic>Climate change</topic><topic>Climate effects</topic><topic>Composition</topic><topic>Density</topic><topic>Disease hot spots</topic><topic>emerging infectious diseases</topic><topic>Habitat loss</topic><topic>Health risks</topic><topic>Hot spots</topic><topic>infectious disease hotspots</topic><topic>Infectious diseases</topic><topic>Mammals</topic><topic>Net losses</topic><topic>Pathogens</topic><topic>Primary</topic><topic>Primary s</topic><topic>species distributions</topic><topic>Species extinction</topic><topic>Species richness</topic><topic>Tropical climate</topic><topic>Wildlife</topic><topic>Wildlife habitats</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Yingying X. G.</creatorcontrib><creatorcontrib>Matson, Kevin D.</creatorcontrib><creatorcontrib>Santini, Luca</creatorcontrib><creatorcontrib>Visconti, Piero</creatorcontrib><creatorcontrib>Hilbers, Jelle P.</creatorcontrib><creatorcontrib>Huijbregts, Mark A. J.</creatorcontrib><creatorcontrib>Xu, Yanjie</creatorcontrib><creatorcontrib>Prins, Herbert H. T.</creatorcontrib><creatorcontrib>Allen, Toph</creatorcontrib><creatorcontrib>Huang, Zheng Y. X.</creatorcontrib><creatorcontrib>Boer, Willem F.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Wiley Online Library (Open Access Collection)</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Global change biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Yingying X. G.</au><au>Matson, Kevin D.</au><au>Santini, Luca</au><au>Visconti, Piero</au><au>Hilbers, Jelle P.</au><au>Huijbregts, Mark A. J.</au><au>Xu, Yanjie</au><au>Prins, Herbert H. T.</au><au>Allen, Toph</au><au>Huang, Zheng Y. X.</au><au>Boer, Willem F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mammal assemblage composition predicts global patterns in emerging infectious disease risk</atitle><jtitle>Global change biology</jtitle><date>2021-10</date><risdate>2021</risdate><volume>27</volume><issue>20</issue><spage>4995</spage><epage>5007</epage><pages>4995-5007</pages><issn>1354-1013</issn><eissn>1365-2486</eissn><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.
Emerging infectious diseases are serious global threats. Most of these diseases originate from wildlife, particularly mammals, which face an ongoing biodiversity crisis. Using predicted distributions and abundances of 4466 mammal species, we estimated global patterns of disease risk by calculating community‐level R0. High values in temperate European, Asian, and North American locations point to risks beyond the tropics. Forecasted effects of climate change and habitat loss from 2015 to 2035 suggested many mammal assemblages will change considerably in their composition, even without local extinctions. Simultaneously, most areas were predicted to have decreased density‐dependent disease risk but increased frequency‐dependent disease risk.</abstract><cop>Oxford</cop><pub>Blackwell Publishing Ltd</pub><pmid>34214237</pmid><doi>10.1111/gcb.15784</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-9401-589X</orcidid><orcidid>https://orcid.org/0000-0002-8761-3787</orcidid><orcidid>https://orcid.org/0000-0001-6823-2826</orcidid><orcidid>https://orcid.org/0000-0003-1131-5107</orcidid><orcidid>https://orcid.org/0000-0003-3066-197X</orcidid><orcidid>https://orcid.org/0000-0002-4373-5926</orcidid><orcidid>https://orcid.org/0000-0003-3208-8521</orcidid><orcidid>https://orcid.org/0000-0002-7037-680X</orcidid><orcidid>https://orcid.org/0000-0003-4580-091X</orcidid><orcidid>https://orcid.org/0000-0003-4420-6353</orcidid><orcidid>https://orcid.org/0000-0002-5418-3688</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Abundance assemblage composition Biodiversity Climate change Climate effects Composition Density Disease hot spots emerging infectious diseases Habitat loss Health risks Hot spots infectious disease hotspots Infectious diseases Mammals Net losses Pathogens Primary Primary s species distributions Species extinction Species richness Tropical climate Wildlife Wildlife habitats |
title | Mammal assemblage composition predicts global patterns in emerging infectious disease risk |
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