How Ebola impacts social dynamics in gorillas: a multistate modelling approach.
Identifieur interne : 003203 ( PubMed/Corpus ); précédent : 003202; suivant : 003204How Ebola impacts social dynamics in gorillas: a multistate modelling approach.
Auteurs : Céline Genton ; Amandine Pierre ; Romane Cristescu ; Florence Lévréro ; Sylvain Gatti ; Jean-Sébastien Pierre ; Nelly Ménard ; Pascaline Le GouarSource :
- The Journal of animal ecology [ 1365-2656 ] ; 2015.
English descriptors
- KwdEn :
- MESH :
- geographic : Congo.
- virology : Ape Diseases, Hemorrhagic Fever, Ebola.
- Animals, Female, Gorilla gorilla, Male, Models, Biological, Population Dynamics, Social Behavior.
Abstract
Emerging infectious diseases can induce rapid changes in population dynamics and threaten population persistence. In socially structured populations, the transfers of individuals between social units, for example, from breeding groups to non-breeding groups, shape population dynamics. We suggest that diseases may affect these crucial transfers. We aimed to determine how disturbance by an emerging disease affects demographic rates of gorillas, especially transfer rates within populations and immigration rates into populations. We compared social dynamics and key demographic parameters in a gorilla population affected by Ebola using a long-term observation data set including pre-, during and post-outbreak periods. We also studied a population of undetermined epidemiological status in order to assess whether this population was affected by the disease. We developed a multistate model that can handle transition between social units while optimizing the number of states. During the Ebola outbreak, social dynamics displayed increased transfers from a breeding to a non-breeding status for both males and females. Six years after the outbreak, demographic and most of social dynamics parameters had returned to their initial rates, suggesting a certain resilience in the response to disruption. The formation of breeding groups increased just after Ebola, indicating that environmental conditions were still attractive. However, population recovery was likely delayed because compensatory immigration was probably impeded by the potential impact of Ebola in the surrounding areas. The population of undetermined epidemiological status behaved similarly to the other population before Ebola. Our results highlight the need to integrate social dynamics in host-population demographic models to better understand the role of social structure in the sensitivity and the response to disease disturbances.
DOI: 10.1111/1365-2656.12268
PubMed: 24995485
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pubmed:24995485Le document en format XML
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France.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2015">2015</date><idno type="RBID">pubmed:24995485</idno><idno type="pmid">24995485</idno><idno type="doi">10.1111/1365-2656.12268</idno><idno type="wicri:Area/PubMed/Corpus">003203</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">003203</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">How Ebola impacts social dynamics in gorillas: a multistate modelling approach.</title><author><name sortKey="Genton, Celine" sort="Genton, Celine" uniqKey="Genton C" first="Céline" last="Genton">Céline Genton</name><affiliation><nlm:affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</nlm:affiliation></affiliation></author><author><name sortKey="Pierre, Amandine" sort="Pierre, Amandine" uniqKey="Pierre A" first="Amandine" last="Pierre">Amandine Pierre</name><affiliation><nlm:affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</nlm:affiliation></affiliation></author><author><name sortKey="Cristescu, Romane" sort="Cristescu, Romane" uniqKey="Cristescu R" first="Romane" last="Cristescu">Romane Cristescu</name><affiliation><nlm:affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</nlm:affiliation></affiliation></author><author><name sortKey="Levrero, Florence" sort="Levrero, Florence" uniqKey="Levrero F" first="Florence" last="Lévréro">Florence Lévréro</name><affiliation><nlm:affiliation>ENES/CNPS CNRS UMR 8195, Université de Saint-Etienne, Equipe Neuro-Ethologie Sensorielle, 42023, Saint-Etienne, France.</nlm:affiliation></affiliation></author><author><name sortKey="Gatti, Sylvain" sort="Gatti, Sylvain" uniqKey="Gatti S" first="Sylvain" last="Gatti">Sylvain Gatti</name><affiliation><nlm:affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</nlm:affiliation></affiliation></author><author><name sortKey="Pierre, Jean Sebastien" sort="Pierre, Jean Sebastien" uniqKey="Pierre J" first="Jean-Sébastien" last="Pierre">Jean-Sébastien Pierre</name><affiliation><nlm:affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</nlm:affiliation></affiliation></author><author><name sortKey="Menard, Nelly" sort="Menard, Nelly" uniqKey="Menard N" first="Nelly" last="Ménard">Nelly Ménard</name><affiliation><nlm:affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</nlm:affiliation></affiliation></author><author><name sortKey="Le Gouar, Pascaline" sort="Le Gouar, Pascaline" uniqKey="Le Gouar P" first="Pascaline" last="Le Gouar">Pascaline Le Gouar</name><affiliation><nlm:affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</nlm:affiliation></affiliation></author></analytic><series><title level="j">The Journal of animal ecology</title><idno type="eISSN">1365-2656</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Animals</term><term>Ape Diseases (virology)</term><term>Congo</term><term>Female</term><term>Gorilla gorilla</term><term>Hemorrhagic Fever, Ebola (virology)</term><term>Male</term><term>Models, Biological</term><term>Population Dynamics</term><term>Social Behavior</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Congo</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Ape Diseases</term><term>Hemorrhagic Fever, Ebola</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Female</term><term>Gorilla gorilla</term><term>Male</term><term>Models, Biological</term><term>Population Dynamics</term><term>Social Behavior</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Emerging infectious diseases can induce rapid changes in population dynamics and threaten population persistence. In socially structured populations, the transfers of individuals between social units, for example, from breeding groups to non-breeding groups, shape population dynamics. We suggest that diseases may affect these crucial transfers. We aimed to determine how disturbance by an emerging disease affects demographic rates of gorillas, especially transfer rates within populations and immigration rates into populations. We compared social dynamics and key demographic parameters in a gorilla population affected by Ebola using a long-term observation data set including pre-, during and post-outbreak periods. We also studied a population of undetermined epidemiological status in order to assess whether this population was affected by the disease. We developed a multistate model that can handle transition between social units while optimizing the number of states. During the Ebola outbreak, social dynamics displayed increased transfers from a breeding to a non-breeding status for both males and females. Six years after the outbreak, demographic and most of social dynamics parameters had returned to their initial rates, suggesting a certain resilience in the response to disruption. The formation of breeding groups increased just after Ebola, indicating that environmental conditions were still attractive. However, population recovery was likely delayed because compensatory immigration was probably impeded by the potential impact of Ebola in the surrounding areas. The population of undetermined epidemiological status behaved similarly to the other population before Ebola. Our results highlight the need to integrate social dynamics in host-population demographic models to better understand the role of social structure in the sensitivity and the response to disease disturbances.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">24995485</PMID><DateCreated><Year>2015</Year><Month>08</Month><Day>05</Day></DateCreated><DateCompleted><Year>2016</Year><Month>05</Month><Day>11</Day></DateCompleted><DateRevised><Year>2015</Year><Month>08</Month><Day>05</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1365-2656</ISSN><JournalIssue CitedMedium="Internet"><Volume>84</Volume><Issue>1</Issue><PubDate><Year>2015</Year><Month>Jan</Month></PubDate></JournalIssue><Title>The Journal of animal ecology</Title><ISOAbbreviation>J Anim Ecol</ISOAbbreviation></Journal><ArticleTitle>How Ebola impacts social dynamics in gorillas: a multistate modelling approach.</ArticleTitle><Pagination><MedlinePgn>166-76</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1111/1365-2656.12268</ELocationID><Abstract><AbstractText>Emerging infectious diseases can induce rapid changes in population dynamics and threaten population persistence. In socially structured populations, the transfers of individuals between social units, for example, from breeding groups to non-breeding groups, shape population dynamics. We suggest that diseases may affect these crucial transfers. We aimed to determine how disturbance by an emerging disease affects demographic rates of gorillas, especially transfer rates within populations and immigration rates into populations. We compared social dynamics and key demographic parameters in a gorilla population affected by Ebola using a long-term observation data set including pre-, during and post-outbreak periods. We also studied a population of undetermined epidemiological status in order to assess whether this population was affected by the disease. We developed a multistate model that can handle transition between social units while optimizing the number of states. During the Ebola outbreak, social dynamics displayed increased transfers from a breeding to a non-breeding status for both males and females. Six years after the outbreak, demographic and most of social dynamics parameters had returned to their initial rates, suggesting a certain resilience in the response to disruption. The formation of breeding groups increased just after Ebola, indicating that environmental conditions were still attractive. However, population recovery was likely delayed because compensatory immigration was probably impeded by the potential impact of Ebola in the surrounding areas. The population of undetermined epidemiological status behaved similarly to the other population before Ebola. Our results highlight the need to integrate social dynamics in host-population demographic models to better understand the role of social structure in the sensitivity and the response to disease disturbances.</AbstractText><CopyrightInformation>© 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Genton</LastName><ForeName>Céline</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pierre</LastName><ForeName>Amandine</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cristescu</LastName><ForeName>Romane</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>School of Biological, Earth and Environmental Sciences, University of New South Wales, Kensington, NSW, 2052, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lévréro</LastName><ForeName>Florence</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>ENES/CNPS CNRS UMR 8195, Université de Saint-Etienne, Equipe Neuro-Ethologie Sensorielle, 42023, Saint-Etienne, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gatti</LastName><ForeName>Sylvain</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pierre</LastName><ForeName>Jean-Sébastien</ForeName><Initials>JS</Initials><AffiliationInfo><Affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ménard</LastName><ForeName>Nelly</ForeName><Initials>N</Initials><AffiliationInfo><Affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Le Gouar</LastName><ForeName>Pascaline</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>UMR 6553, ECOBIO: Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Station Biologique de Paimpont, 35380, Paimpont, France.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>07</Month><Day>24</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>J Anim Ecol</MedlineTA><NlmUniqueID>0376574</NlmUniqueID><ISSNLinking>0021-8790</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018420" MajorTopicYN="N">Ape Diseases</DescriptorName><QualifierName UI="Q000821" MajorTopicYN="Y">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003223" MajorTopicYN="N" Type="Geographic">Congo</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006071" MajorTopicYN="Y">Gorilla gorilla</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019142" MajorTopicYN="N">Hemorrhagic Fever, Ebola</DescriptorName><QualifierName UI="Q000821" MajorTopicYN="Y">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008954" MajorTopicYN="Y">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011157" MajorTopicYN="N">Population Dynamics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012919" MajorTopicYN="Y">Social Behavior</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Gorilla gorilla gorilla</Keyword><Keyword MajorTopicYN="N">capture–recapture</Keyword><Keyword MajorTopicYN="N">demographic crash</Keyword><Keyword MajorTopicYN="N">emerging infectious disease</Keyword><Keyword MajorTopicYN="N">recovery</Keyword><Keyword MajorTopicYN="N">sociality</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2013</Year><Month>07</Month><Day>04</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>06</Month><Day>30</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>7</Month><Day>5</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>7</Month><Day>6</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>5</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">24995485</ArticleId><ArticleId IdType="doi">10.1111/1365-2656.12268</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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