Browsing by Autor "Rahel Sollmann"

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    Comparing capture-recapture, mark-resight, and spatial mark-resight models for estimating puma densities via camera traps
    (Oxford University Press, 2014) Lindsey N. Rich; Marcella J. Kelly; Rahel Sollmann; Andrew J. Noss; Leonardo Maffei; Rosario Arispe; Agustín Paviolo; Carlos De Angelo; Yamil E. Di Blanco; Mario S. Di Bitetti
    Camera-trapping surveys, in combination with traditional capture-recapture or spatially explicit capture-recapture techniques, have become popular for estimating the density of individually identifiable carnivores. When only a portion of the population is uniquely identifiable, traditional and spatial mark-resight models provide a viable alternative. We reanalyzed a data set that used photographic capture-recapture methods to estimate the densities of pumas (Puma concolor) across 3 study sites in Belize, Argentina, and Bolivia using newer, more-advanced modeling including spatial and nonspatial mark-resight techniques. Additionally, we assessed how photo identification influenced density estimates by comparing estimates based on capture histories constructed by 3 independent investigators. We estimated the abundances of pumas using mark-resight models in program MARK and then estimated densities ad hoc. We also estimated densities directly using spatial mark-resight models implemented in a Bayesian framework. Puma densities did not vary substantially among observers but estimates generated from the 3 statistical techniques did differ. Density estimates (pumas/100 km2) from spatial mark-resight models were lower (0.22–7.92) and had increased precision compared to those from nonspatial capture-recapture (0.50–19.35) and mark-resight techniques (0.54–14.70). Our study is the 1st to estimate the density of a population of carnivores, where only a subset of the individuals are naturally marked, using camera-trapping surveys in combination with spatial mark-resight models. The development of spatial mark-resight and spatially explicit capture-recapture techniques creates the potential for using a single camera-trapping array to estimate the density of multiple, sympatric carnivores, including both partially marked and uniquely marked species.