Hdl Handle:
http://hdl.handle.net/10034/620554
Title:
Animal Social Network Theory Can Help Wildlife Conservation
Authors:
Snijders, Lysanne ( 0000-0003-0911-3418 ) ; Blumstein, Daniel ( 0000-0001-5793-9244 ) ; Franks, Daniel Wayne ( 0000-0002-4832-7470 ) ; Stanley, Christina ( 0000-0002-5053-4831 )
Abstract:
Many animals preferentially associate with certain other individuals. This social structuring can influence how populations respond to changes to their environment, thus making network analysis a promising technique for understanding, predicting and potentially manipulating population dynamics. Various network statistics can correlate with individual fitness components and key population-level processes, yet the logical role and formal application of animal social network theory for conservation and management have not been well articulated. We outline how understanding of direct and indirect relationships between animals can be profitably applied by wildlife managers and conservationists. By doing so, we aim to stimulate the development and implementation of practical tools for wildlife conservation and management and to inspire novel behavioral research in this field.
Affiliation:
University of Chester; Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin; Wageningen University & Research; University of California; University of York
Citation:
Snijders, L., Blumstein, D. T., Stanley C. R. & Franks, D. W. (2017). Animal Social Network Theory Can Help Wildlife Conservation. Trends in Ecology and Evolution.
Publisher:
Elsevier
Journal:
Trends in Ecology & Evolution
Publication Date:
22-Jun-2017
URI:
http://hdl.handle.net/10034/620554
DOI:
10.1016/j.tree.2017.05.005
Additional Links:
http://dx.doi.org/10.1016/j.tree.2017.05.005
Type:
Article
Language:
en
Description:
Review paper
ISSN:
1872-8383
Appears in Collections:
Biological Sciences

Full metadata record

DC FieldValue Language
dc.contributor.authorSnijders, Lysanneen
dc.contributor.authorBlumstein, Danielen
dc.contributor.authorFranks, Daniel Wayneen
dc.contributor.authorStanley, Christinaen
dc.date.accessioned2017-07-05T11:51:44Z-
dc.date.available2017-07-05T11:51:44Z-
dc.date.issued2017-06-22-
dc.identifier.citationSnijders, L., Blumstein, D. T., Stanley C. R. & Franks, D. W. (2017). Animal Social Network Theory Can Help Wildlife Conservation. Trends in Ecology and Evolution.en
dc.identifier.issn1872-8383-
dc.identifier.doi10.1016/j.tree.2017.05.005-
dc.identifier.urihttp://hdl.handle.net/10034/620554-
dc.descriptionReview paperen
dc.description.abstractMany animals preferentially associate with certain other individuals. This social structuring can influence how populations respond to changes to their environment, thus making network analysis a promising technique for understanding, predicting and potentially manipulating population dynamics. Various network statistics can correlate with individual fitness components and key population-level processes, yet the logical role and formal application of animal social network theory for conservation and management have not been well articulated. We outline how understanding of direct and indirect relationships between animals can be profitably applied by wildlife managers and conservationists. By doing so, we aim to stimulate the development and implementation of practical tools for wildlife conservation and management and to inspire novel behavioral research in this field.en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urlhttp://dx.doi.org/10.1016/j.tree.2017.05.005en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectSocial network analysisen
dc.subjectWildlife conservationen
dc.subjectAnimal behaviouren
dc.subjectBehavioural ecologyen
dc.titleAnimal Social Network Theory Can Help Wildlife Conservationen
dc.typeArticleen
dc.contributor.departmentUniversity of Chester; Leibniz-Institute of Freshwater Ecology and Inland Fisheries, Berlin; Wageningen University & Research; University of California; University of Yorken
dc.identifier.journalTrends in Ecology & Evolutionen
dc.date.accepted2017-05-18-
or.grant.openaccessYesen
rioxxterms.funderUnfundeden
rioxxterms.identifier.projectUnfundeden
rioxxterms.versionAMen
rioxxterms.licenseref.startdate2018-06-22-
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