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dc.contributor.authorSchleicher, Judithen
dc.contributor.authorEklund, Johannaen
dc.contributor.authorD Barnes, Meganen
dc.contributor.authorGeldmann, Jonasen
dc.contributor.authorOldekop, Johan Aen
dc.contributor.authorJones, Julia PGen
dc.date.accessioned2019-10-11T23:30:15Z
dc.date.available2019-10-11T23:30:15Z
dc.date.issued2020-06en
dc.identifier.issn0888-8892
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/297757
dc.description.abstractThe awareness of the need for robust impact evaluations in conservation is growing, and statistical matching techniques are increasingly being use to assess the impacts of conservation interventions. Used appropriately, matching approaches are powerful tools, but they also pose potential pitfalls. We present important considerations and best practice when using matching in conservation science. We identify three steps in a matching analysis. The first step requires a clear theory of change to inform selection of treatment and controls, accounting for real world complexities and potential spill-over effects. The second step involves selecting the appropriate covariates and matching approach. The third step is assessing the quality of the matching by carrying out a series of checks. The second and third steps can be repeated and should be finalized before outcomes are explored. Future conservation impact evaluations could be improved by increased planning of evaluations alongside the intervention, better integration of qualitative methods, considering spill-over effects at larger spatial scales, and more publication of pre-analysis plans. This will require more serious engagement of conservation scientists, practitioners and funders to mainstream robust impact evaluations into conservation. We hope that this paper will improve the quality of evaluations, and help direct future research to continue to improve the approaches on offer.
dc.format.mediumPrint-Electronicen
dc.languageengen
dc.publisherWiley-Blackwell
dc.rightsAll rights reserved
dc.rightsAttribution 4.0 International
dc.rights.uri
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectConservation of Natural Resourcesen
dc.titleStatistical matching for conservation science.en
dc.typeArticle
prism.endingPage549
prism.issueIdentifier3en
prism.publicationDate2020en
prism.publicationNameConservation biology : the journal of the Society for Conservation Biologyen
prism.startingPage538
prism.volume34en
dc.identifier.doi10.17863/CAM.44810
dcterms.dateAccepted2019-09-19en
rioxxterms.versionofrecord10.1111/cobi.13448en
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2020-06en
dc.contributor.orcidSchleicher, Judith [0000-0001-7817-4295]
dc.contributor.orcidEklund, Johanna [0000-0003-1263-8151]
dc.contributor.orcidD Barnes, Megan [0000-0002-8300-0975]
dc.contributor.orcidGeldmann, Jonas [0000-0002-1191-7610]
dc.contributor.orcidOldekop, Johan A [0000-0003-0565-812X]
dc.contributor.orcidJones, Julia PG [0000-0002-5199-3335]
dc.identifier.eissn1523-1739
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (676108)
cam.orpheus.successThu Jan 30 10:37:12 GMT 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2100-01-01


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