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dc.contributor.authorUeno, Mayumi
dc.contributor.authorSolberg, Erling Johan
dc.contributor.authorIijima, Hayato
dc.contributor.authorRolandsen, Christer Moe
dc.contributor.authorGangsei, Lars Erik
dc.coverage.spatialNorwayen_US
dc.date.accessioned2023-07-10T13:06:03Z
dc.date.available2023-07-10T13:06:03Z
dc.date.created2014-03-14T15:27:16Z
dc.date.issued2014
dc.identifier.issn2150-8925
dc.identifier.urihttps://hdl.handle.net/11250/3077492
dc.description.abstractWildlife managers are often asking for reliable information of population density across larger spatial scales. In this study, we examined the spatiotemporal relationships between moose density as estimated by cohort analysis and the density indices (1) harvest density (HD; hunter kills per km2), (2) moose seen per unit effort (SPUE), seen moose density (SMD; seen moose per km2), and density of moosevehicle accidents (MVA density; e.g., traffic kills per km2) in 16 areas in Norway with 13–42 years of data. HD showed a close positive relationship with moose density both within and between regions. However, the temporal variation in HD was best explained as a delayed reflection of moose density and tended to overestimate its growth and decline. Conversely, SMD and SPUE were unable to predict the spatial variation in moose density with high precision, though both indices were relatively precise temporal reflectors of moose density. However, the SPUE tended to underestimate population growth, probably because of a decrease in searching efficiency with increasing moose density. Compared to the other indices, MVA density performed poor as an index of moose density within regions, and not at all among regions, but may, because of its independent source of data, be used to cross-check population trends suggested by other indices. Our study shows that the temporal trends in moose density can be surveyed over large areas by the use of cheap indices based on data collected by hunters and local managers, and supports the general assumption that the number of moose killed per km2 provides a precise and isometric index of the variation in moose density at the spatial scale of our study. cohort analysis; isometric index; management; monitoring; population reconstruction; precision; saturation; seen per unit effort (SPUE).en_US
dc.description.abstractPerformance of hunting statistics as spatiotemporal density indices of moose (Alces alces) in Norwayen_US
dc.language.isoengen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectcohort analysisen_US
dc.subjectisometric indexen_US
dc.subjectmanagementen_US
dc.subjectmonitoringen_US
dc.subjectpopulation reconstructionen_US
dc.subjectprecisionen_US
dc.subjectsaturationen_US
dc.subjectseen per unit effort (SPUE)en_US
dc.titlePerformance of hunting statistics as spatiotemporal density indices of moose (Alces alces) in Norwayen_US
dc.title.alternativePerformance of hunting statistics as spatiotemporal density indices of moose (Alces alces) in Norwayen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2014 The Authorsen_US
dc.source.volume5en_US
dc.source.journalEcosphereen_US
dc.source.issue2en_US
dc.identifier.doi10.1890/ES13-00083.1
dc.identifier.cristin1122251
dc.relation.projectNorges forskningsråd: 184036en_US
dc.relation.projectNorges forskningsråd: 223257en_US
dc.source.articlenumber13en_US
cristin.unitcode7511,2,0,0
cristin.unitnameAvdeling for terrestrisk økologi
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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