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dc.contributor.authorHofmeester, Tim R.
dc.contributor.authorCromsigt, Joris P.G.M.
dc.contributor.authorOdden, John
dc.contributor.authorAndrén, Henrik
dc.contributor.authorKindberg, Jonas
dc.contributor.authorLinnell, John Durrus
dc.description.abstractObtaining reliable species observations is of great importance in animal ecology and wildlife conservation. An increasing number of studies use camera traps (CTs) to study wildlife communities, and an increasing effort is made to make better use and reuse of the large amounts of data that are produced. It is in these circumstances that it becomes paramount to correct for the species‐ and study‐specific variation in imperfect detection within CTs. We reviewed the literature and used our own experience to compile a list of factors that affect CT detection of animals. We did this within a conceptual framework of six distinct scales separating out the influences of (a) animal characteristics, (b) CT specifications, (c) CT set‐up protocols, and (d) environmental variables. We identified 40 factors that can potentially influence the detection of animals by CTs at these six scales. Many of these factors were related to only a few overarching parameters. Most of the animal characteristics scale with body mass and diet type, and most environmental characteristics differ with season or latitude such that remote sensing products like NDVI could be used as a proxy index to capture this variation. Factors that influence detection at the microsite and camera scales are probably the most important in determining CT detection of animals. The type of study and specific research question will determine which factors should be corrected. Corrections can be done by directly adjusting the CT metric of interest or by using covariates in a statistical framework. Our conceptual framework can be used to design better CT studies and help when analyzing CT data. Furthermore, it provides an overview of which factors should be reported in CT studies to make them repeatable, comparable, and their data reusable. This should greatly improve the possibilities for global scale analyses of (reused) CT data. animal characteristics, detectability, environmental variables, mammal monitoring, reuse of data, trail cameranb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.subjectanimal characteristicsnb_NO
dc.subjectenvironmental variablesnb_NO
dc.subjectmammal monitoringnb_NO
dc.subjectreuse of datanb_NO
dc.subjecttrail cameranb_NO
dc.titleFraming pictures: A conceptual framework to identify and correct for biases in detection probability of camera traps enabling multi‐species comparisonnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.rights.holder© 2019 The Authors.nb_NO
dc.subject.nsiVDP::Zoologiske og botaniske fag: 480nb_NO
dc.subject.nsiVDP::Zoology and botany: 480nb_NO
dc.source.journalEcology and Evolutionnb_NO
dc.relation.projectNorges forskningsråd: 251112nb_NO
dc.relation.projectAndre: Statens Naturvårdsverk NV-00695-17, NV-03047-16, NV-01337-15nb_NO
dc.relation.projectNorges forskningsråd: 281092;nb_NO
dc.relation.projectAndre: Miljødirektoratetnb_NO
cristin.unitnameAvdeling for terrestrisk økologi

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal