Show simple item record

Files in this item


Item metadata

dc.contributor.authorBayandonoi, Gantulga
dc.contributor.authorSharma, Koustubh
dc.contributor.authorShanti Alexander, Justine
dc.contributor.authorLkhagvajav, Purevjav
dc.contributor.authorDurbach, Ian
dc.contributor.authorBuyanaa, Chimeddorj
dc.contributor.authorMunkhtsog, Bariushaa
dc.contributor.authorOchirjav, Munkhtogtokh
dc.contributor.authorErdenebaatar, Sergelen
dc.contributor.authorBatkhuyag, Bilguun
dc.contributor.authorBattulga, Nyamzav
dc.contributor.authorByambasuren, Choidogjamts
dc.contributor.authorUudus, Bayarsaikhan
dc.contributor.authorSetev, Shar
dc.contributor.authorDavaa, Lkhagvasuren
dc.contributor.authorAgchbayar, Khurel-Erdene
dc.contributor.authorGalsandorj, Naranbaatar
dc.contributor.authorMacKenzie, Darryl
dc.identifier.citationBayandonoi , G , Sharma , K , Shanti Alexander , J , Lkhagvajav , P , Durbach , I , Buyanaa , C , Munkhtsog , B , Ochirjav , M , Erdenebaatar , S , Batkhuyag , B , Battulga , N , Byambasuren , C , Uudus , B , Setev , S , Davaa , L , Agchbayar , K-E , Galsandorj , N & MacKenzie , D 2021 , ' Mapping the ghost : estimating probabilistic snow leopard distribution across Mongolia ' , Diversity and Distributions , vol. Early View .
dc.identifier.otherRIS: urn:2BA83B0EB41094FDAD79CEE787962184
dc.identifier.otherORCID: /0000-0003-0769-2153/work/100549773
dc.descriptionWe are grateful to Global Environment Facility, United Nations Development Program and Snow Leopard Trust for supporting the Global Snow Leopard and Ecosystem Protection Program and development of tools and methods for Population Assessment of the World's Snow leopards (PAWS).en
dc.description.abstractAim Snow leopards are distributed across the mountains of 12 countries spread across 1.8 million km2 in Central and South Asia. Previous efforts to map snow leopard distributions have relied on expert opinions and modelling of presence-only data. Expert opinion is subjective and its reliability is difficult to assess, while analyses of presence-only data have tended to ignore the imperfect detectability of this elusive species. The study was conducted to prepare the first ever probabilistic distribution map of snow leopards across Mongolia addressing the challenge of imperfect detection.  Location We conducted sign-based occupancy surveys across 1,017 grid-cells covering 406,800 km2 of Mongolia's potential snow leopard range.  Methods Using a candidate model set of 31 ecologically meaningful models that used six site and seven sampling covariates, we estimate the probability of sites being used by snow leopards across the entire country.  Results Occupancy probability increased with greater terrain ruggedness, with lower values of vegetation indices, with less forest cover, and were highest at intermediate altitudes. Detection probability was higher for segments walked on foot, and for those in more rugged terrain. Our results showed broad agreement with maps developed using expert opinion and presence-only data but also highlighted important differences, for example in northern areas of Mongolia deemed largely unfavourable by previous expert opinion and presence-only analyses.  Main conclusions This study reports the first national-level occupancy survey of snow leopards in Mongolia and highlights methodological opportunities that can be taken to scale and support national-level conservation planning. Our assessments indicated that 0.5) probability of being used by snow leopards. We emphasize the utility of occupancy modelling, which jointly models detection and site use, in achieving these goals.
dc.relation.ispartofDiversity and Distributionsen
dc.subjectImperfect detectionen
dc.subjectLarge carnivoresen
dc.subjectPredictive modellingen
dc.subjectSign surveysen
dc.subjectSnow leoparden
dc.subjectSpecies distributionen
dc.subjectGE Environmental Sciencesen
dc.subjectQH301 Biologyen
dc.subjectQA Mathematicsen
dc.titleMapping the ghost : estimating probabilistic snow leopard distribution across Mongoliaen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.description.statusPeer revieweden

This item appears in the following Collection(s)

Show simple item record