Show simple item record

dc.contributorChigbrow, Joeen_US
dc.contributorJohnson, Douglas E.en_US
dc.contributorLarson, Larryen_US
dc.contributorNielson, Ryanen_US
dc.contributorLouhaichi, Mouniren_US
dc.contributorRoland, Tyanneen_US
dc.contributorWilliams, Johnen_US
dc.creatorClark, Patrick E.en_US
dc.date2020-01-12en_US
dc.date.accessioned2020-01-29T19:27:34Z
dc.date.available2020-01-29T19:27:34Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/6d6a17f09ee0a6f631657b2f13f466c7en_US
dc.identifier.citationPatrick E. Clark, Joe Chigbrow, Douglas E. Johnson, Larry Larson, Ryan Nielson, Mounir Louhaichi, Tyanne Roland, John Williams. (12/1/2020). Predicting Spatial Risk of Wolf-Cattle Encounters and Depredation. Rangeland Ecology & Management, 75 (1), pp. 30-52.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/10663
dc.description.abstractSpatial variability in terrain, vegetation, and other features affect cattle and wildlife distribution on mountainous grazing lands of the western United States. Yet we have a poor understanding of how this spatial variability influences risk of wolf-cattle encounters and associated depredation. This knowledge gap severely limits our capacity to prevent or mitigate wolf-cattle conflict. Research addressing this problem was conducted in 2009_2011 at four study areas in western Idaho to evaluate models and mapping tools for predicting spatial risk of wolf-cattle encounters. Lactating beef cows grazing these study areas were instrumented with Global Positioning System (GPS) collars and tracked at 5-min intervals throughout the summer grazing season. Resource selection function (RSF) models, based on negative binomial regression, were developed from these GPS data and used to map the relative probability of cattle use in each study area. A wolf RSF model originally developed by Ausband et al. (2010) was applied to map study-area habitat types in terms of their relative suitability as wolf rendezvous sites. Spatial relationships between cattle and wolf selectivity patterns were used to classify and map wolfcattle encounter risk to 5 classes (very high to very low) across each study area during the wolf rendezvous period (15 June_15 August). Validation analyses using GPS-based, wolf-cattle encounter observations (n ¼ 200) revealed 84% of observed encounters occurred in areas of high- or very high_encounter risk (class 4 or 5). About 75% of confirmed wolf depredations recorded among three of four study areas were located in areas of high or very high risk. This new predictive understanding of wolf-cattle encounter risk will greatly aid livestock producers, resource managers, and policy makers in more effectively applying husbandry practices, allocating mitigation resources, and developing conflict mitigation plans and policies applicable throughout the mountainous western United States and potentially other regions of the world where wolves and cattle come into conflict.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherElsevier B.V.en_US
dc.rightsCC-BY-NC-ND-4.0en_US
dc.sourceRangeland Ecology & Management;75,(2019) Pagination 30,52en_US
dc.subjectencounter risken_US
dc.subjectresource selectionen_US
dc.titlePredicting Spatial Risk of Wolf-Cattle Encounters and Depredationen_US
dc.typeJournal Articleen_US
cg.creator.idLouhaichi, Mounir: 0000-0002-4543-7631en_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocmappingen_US
cg.subject.agrovocbehavioren_US
cg.subject.agrovocbos taurusen_US
cg.subject.agrovoccanis lupusen_US
cg.contributor.centerOregon State University - OSU United Statesen_US
cg.contributor.centerUnited States Department of Agriculture, Agricultural Research Service - USDA-ARSen_US
cg.contributor.centerUniversity of Idaho - UIDAHOen_US
cg.contributor.centerEastern Oregon University - EOUen_US
cg.contributor.centerEagle Environmental, Inc. - EEIen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.crpCGIAR Research Program on Livestock Agri-Food Systems - LAFSen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionNorthern Americaen_US
cg.coverage.countryUSen_US
cg.contactpat.clark@ars.usda.goven_US
cg.identifier.doihttps://dx.doi.org/10.1016/j.rama.2019.08.012en_US
dc.identifier.statusOpen accessen_US
mel.impact-factor2.095en_US


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record


DSpace software copyright © 2002-2016  DuraSpace
Disclaimer:
MELSpace content providers and partners accept no liability to any consequence resulting from use of the content or data made available in this repository. Users of this content assume full responsibility for compliance with all relevant national or international regulations and legislation.
Theme by 
Atmire NV