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Species co-occurrence analysis predicts management outcomes for multiple threats

dc.contributor.authorTulloch, Ayesha
dc.contributor.authorChadès, Iadine
dc.contributor.authorLindenmayer, David B
dc.date.accessioned2020-01-23T02:18:33Z
dc.date.issued2018
dc.date.updated2019-11-25T07:23:19Z
dc.description.abstractMitigating the impacts of global anthropogenic change on species is conservation’s greatest challenge. Forecasting the effects of actions to mitigate threats is hampered by incomplete information on species’ responses. We develop an approach to predict community restructuring under threat management, which combines models of responses to threats with network analyses of species co-occurrence. We discover that contributions by species to network co-occurrence predict their recovery under reduction of multiple threats. Highly connected species are likely to benefit more from threat management than poorly connected species. Importantly, we show that information from a few species on co-occurrence and expected responses to alternative threat management actions can be used to train a response model for an entire community. We use a unique management dataset for a threatened bird community to validate our predictions and, in doing so, demonstrate positive feedbacks in occurrence and co-occurrence resulting from shared threat management responses during ecosystem recovery.en_AU
dc.description.sponsorshipD.B.L. is supported by an ARC Laureate Fellowship. A.I.T.T. is funded by the Australian Research Council Centre of Excellence for Environmental Decisions (CEED). The monitoring program was coordinated by D. Florance from The Australian National University (ANU) and approved by the Australian National University Animal Ethics Committee, and field staff from ANU and volunteers from the Canberra Ornithologists Group assisted with surveys.en_AU
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2397-334Xen_AU
dc.identifier.urihttp://hdl.handle.net/1885/199507
dc.language.isoen_AUen_AU
dc.provenanceSherpa/Romeo - viewed 18/10/2018 Author's Pre-prints:can Author can archive pre-print (ie pre-refereeing) Author's Post-prints:restricted Subject to Restrictions below, author can archive post-print (ie final draft post-refereeing) Publisher's Version:cannot Author cannot archive publisher's version/PDF
dc.publisherNature Publishing Groupen_AU
dc.rights© 2018 Macmillan Publishers Limited, part of Springer Natureen_AU
dc.sourceNature Ecology & Evolutionen_AU
dc.titleSpecies co-occurrence analysis predicts management outcomes for multiple threatsen_AU
dc.typeJournal articleen_AU
dcterms.accessRightsOpen Access
local.bibliographicCitation.issue3en_AU
local.bibliographicCitation.lastpage474en_AU
local.bibliographicCitation.startpage465en_AU
local.contributor.affiliationTulloch, Ayesha, College of Science, ANUen_AU
local.contributor.affiliationChadès, Iadine, CSIROen_AU
local.contributor.affiliationLindenmayer, David, College of Science, ANUen_AU
local.contributor.authoruidTulloch, Ayesha, u5697774en_AU
local.contributor.authoruidLindenmayer, David, u8808483en_AU
local.description.notesImported from ARIESen_AU
local.identifier.absfor050205 - Environmental Managementen_AU
local.identifier.absfor050211 - Wildlife and Habitat Managementen_AU
local.identifier.absfor050202 - Conservation and Biodiversityen_AU
local.identifier.ariespublicationa383154xPUB9385en_AU
local.identifier.citationvolume2en_AU
local.identifier.doi10.1038/s41559-017-0457-3en_AU
local.identifier.scopusID2-s2.0-85041593091
local.publisher.urlhttps://www.nature.com/en_AU
local.type.statusAccepted Versionen_AU

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