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Erschienen in: Urban Ecosystems 3/2019

08.02.2019

Estimating density of an elusive carnivore in urban areas: use of spatially explicit capture-recapture models for city-dwelling bobcats

verfasst von: Julie K. Young, Julie M. Golla, Derek Broman, Terry Blankenship, Richard Heilbrun

Erschienen in: Urban Ecosystems | Ausgabe 3/2019

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Abstract

An important first step in managing urban carnivores or the habitat in which they live to reduce risk of conflicts with humans is to understand their basic ecology and population dynamics. Traditional density estimators may be inappropriate in urban areas because of extensive areas of impermeable development but new techniques that include spatial structure could be useful within large urban metropolitan areas. Yet to date, these techniques have largely remained untested. We evaluated whether spatially explicit capture-recapture models (SECR) could provide a reliable density estimate of bobcats (Lynx rufus) in the Dallas Fort-Worth metroplex, Texas, USA. We obtained 1003 photographs of bobcats in an urbanized landscape from June–November 2014, using 41 double camera stations spaced approximately 1.05 km apart. We individually identified bobcats from their distinct pelage patterns and used SECR to predict density throughout the study area. The overall density was at least one bobcat per km2, which calculated to approximately 43 independent-aged bobcats across the entire camera grid, an estimate higher than documented bobcat densities in both rural and peri-urban studies in Texas. Our study revealed a high density of bobcats in an urban landscape despite most assumptions that bobcats require large areas of habitat and are sensitive to fragmentation.

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Metadaten
Titel
Estimating density of an elusive carnivore in urban areas: use of spatially explicit capture-recapture models for city-dwelling bobcats
verfasst von
Julie K. Young
Julie M. Golla
Derek Broman
Terry Blankenship
Richard Heilbrun
Publikationsdatum
08.02.2019
Verlag
Springer US
Erschienen in
Urban Ecosystems / Ausgabe 3/2019
Print ISSN: 1083-8155
Elektronische ISSN: 1573-1642
DOI
https://doi.org/10.1007/s11252-019-0834-6

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