Comparing capture-recapture, mark-resight, and spatial mark-resight models for estimating puma densities via camera traps

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 cameratrapping array to estimate the density of multiple, sympatric carnivores, including both partially marked and uniquely marked species.Fil: Rich, Lindsey N.. Virginia Polytechnic Institute And State University; Estados UnidosFil: Kelly, Marcella J.. Virginia Polytechnic Institute And State University; Estados UnidosFil: Sollmann, Rahel. North Carolina State University; Estados UnidosFil: Noss, Andrew. University of Florida; Estados UnidosFil: Maffei, Leonardo. Wildlife Conservation Society; PerúFil: Arispe, Rosario L.. Museo de Historia Natural Noel Kempff Mercado; BoliviaFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; ArgentinaFil: de Angelo, Carlos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Di Blanco, Yamil Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Di Bitetti, Mario Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; Argentin