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dc.contributor.authorPotts, Joanne Marie
dc.contributor.authorBuckland, Stephen Terrence
dc.contributor.authorThomas, Len
dc.contributor.authorSavage, Anne
dc.date.accessioned2017-04-17T23:33:47Z
dc.date.available2017-04-17T23:33:47Z
dc.date.issued2016-06
dc.identifier.citationPotts , J M , Buckland , S T , Thomas , L & Savage , A 2016 , ' Estimating Key Largo woodrat abundance using spatially explicit capture–recapture and trapping point transects ' Wildlife Society Bulletin , vol. 40 , no. 2 , pp. 331-338 . https://doi.org/10.1002/wsb.651en
dc.identifier.issn1938-5463
dc.identifier.otherPURE: 242039257
dc.identifier.otherPURE UUID: 36ae9818-f615-4fec-bd04-80c5afbf233d
dc.identifier.otherBibtex: urn:ec945379e98d6772c046bb94f25bb0b1
dc.identifier.otherScopus: 84963516741
dc.identifier.otherORCID: /0000-0002-7436-067X/work/29591657
dc.identifier.urihttp://hdl.handle.net/10023/10625
dc.descriptionJMP was funded by Disney's Animal Programs, the US Fish and Wildlife Service and University of St Andrews.en
dc.description.abstractThe Key Largo woodrat (Neotoma floridana smalli) is an endangered rodent with a restricted geographic range and small population size. Establishing an efficient monitoring program of its abundance has been problematic; previous trapping designs have not worked well because the species is sparsely distributed. We compared Key Largo woodrat abundance estimates in Key Largo, Florida, USA, obtained using trapping point transects (TPT) and spatially explicit capture–recapture (SECR) based on statistical properties, survey effort, practicality, and cost. Both methods combine aspects of distance sampling with capture–recapture, but TPT relies on radiotracking individuals to estimate detectability and SECR relies on repeat capture information to estimate densities of home ranges. Abundance estimates using TPT in the spring of 2007 and 2008 were 333 woodrats (CV = 0.46) and 696 (CV = 0.43), respectively. Abundance estimates using SECR in the spring, summer, and winter of 2007 were 97 (CV = 0.31), 334 (CV = 0.26), and 433 (CV = 0.20) animals, respectively. Trapping point transects used approximately 960 person-hours and 1,010 trap-nights/season. Spatially explicit capture–recapture used approximately 500 person-hours and 6,468 trap-nights/season. Significant time was saved in the SECR survey by setting large numbers of traps close together, minimizing time walking between traps. Trapping point transects were practical to implement in the field, and valuable auxiliary information on Key Largo woodrat behavior was obtained via radiocollaring. In this particular study, detectability of the woodrat using TPT was very low and consequently the SECR method was more efficient. Both methods require a substantial investment in survey effort to detect any change in abundance because of large uncertainty in estimates.en
dc.language.isoeng
dc.relation.ispartofWildlife Society Bulletinen
dc.rights© 2016, Publisher / the Author(s). This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at onlinelibrary.wiley.com / https://dx.doi.org/ 10.1002/wsb.651en
dc.subjectAbundanceen
dc.subjectDistance samplingen
dc.subjectKey Largo woodraten
dc.subjectNeotoma floridana smallien
dc.subjectSmall mammalsen
dc.subjectSpatially explicit capture–recaptureen
dc.subjectTrapping point transectsen
dc.subjectGE Environmental Sciencesen
dc.subjectQH301 Biologyen
dc.subjectNDASen
dc.subject.lccGEen
dc.subject.lccQH301en
dc.titleEstimating Key Largo woodrat abundance using spatially explicit capture–recapture and trapping point transectsen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. St Andrews Sustainability Instituteen
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.identifier.doihttps://doi.org/10.1002/wsb.651
dc.description.statusPeer revieweden
dc.date.embargoedUntil17-04-20


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