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dc.contributor.authorWauchope, HS
dc.contributor.authorAmano, T
dc.contributor.authorGeldmann, J
dc.contributor.authorJohnston, A
dc.contributor.authorSimmons, BI
dc.contributor.authorSutherland, WJ
dc.contributor.authorJones, JPG
dc.date.accessioned2020-12-03T12:56:06Z
dc.date.issued2020-12-10
dc.description.abstractHumanity’s impact on the environment is increasing, as are strategies to conserve biodiversity, but a lack of understanding about how interventions affect ecological and conservation outcomes hampers decision-making. Time-series are often used to assess impacts, but ecologists tend to compare average values from before to after an impact; overlooking the potential for the intervention to elicit a change in trend. Without methods that allow for a range of responses, erroneous conclusions can be drawn. This is especially so for large, multi-time-series datasets which are increasingly available. Drawing on literature in other disciplines and pioneering work in ecology, we present a standardised framework to robustly assesses how interventions, like natural disasters or conservation policies, affect ecological time series.en_GB
dc.description.sponsorshipRoyal Commission 1851en_GB
dc.description.sponsorshipCambridge Trust Poynton Scholarshipen_GB
dc.description.sponsorshipCambridge Department of Zoology J.S. Gardiner Studentshipen_GB
dc.description.sponsorshipCambridge Philosophical Societyen_GB
dc.description.sponsorshipAustralian Research Council (ARC)en_GB
dc.description.sponsorshipUniversity of Queenslanden_GB
dc.description.sponsorshipEuropean Union Horizon 2020en_GB
dc.description.sponsorshipVillum Fondenen_GB
dc.description.sponsorshipArcadiaen_GB
dc.description.sponsorshipLeverhulme Trusten_GB
dc.identifier.citationPublished online 10 December 2020en_GB
dc.identifier.doi10.1016/j.tree.2020.11.001
dc.identifier.grantnumberRF511/2019en_GB
dc.identifier.grantnumberFT180100354en_GB
dc.identifier.grantnumber706784en_GB
dc.identifier.grantnumberVKR023371en_GB
dc.identifier.grantnumberRPG-2014-056en_GB
dc.identifier.urihttp://hdl.handle.net/10871/123894
dc.language.isoenen_GB
dc.publisherElsevier (Cell Press)en_GB
dc.rights© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
dc.subjectBefore-After-Control-Interventionen_GB
dc.subjectLongitudinal dataen_GB
dc.subjectCounterfactualen_GB
dc.subjectInterrupted Time Seriesen_GB
dc.subjectCausal Inferenceen_GB
dc.subjectDifference in Differencesen_GB
dc.titleEvaluating impact using time-series dataen_GB
dc.typeArticleen_GB
dc.date.available2020-12-03T12:56:06Z
dc.identifier.issn0169-5347
dc.descriptionThis is the final version. Available on open access from Elsevier via the DOI in this recorden_GB
dc.identifier.journalTrends in Ecology and Evolutionen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2020-11-05
exeter.funder::Royal Commission 1851en_GB
exeter.funder::Royal Commission 1851en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2020-11-05
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2020-12-03T12:15:13Z
refterms.versionFCDAM
refterms.dateFOA2020-12-18T10:56:21Z
refterms.panelAen_GB


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© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).