Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring

Table 4 Summary of the best models explaining wolf pack density from spatially explicit capture-recapture data collected during sessions 2014 and 2015 (Arezzo province, Italy). a) parameters estimated by the Bayesian approach in SPACECAP; b) parameters estimated by the maximum likelihood approach in secr

NE and HN indicate, respectively, the negative exponential and half normal detection function. TP and NULL indicate, respectively, model with or without a behavioural trap effect as covariate. Density is expressed as number of wolf packs/100 km². In SPACECAP the parameter σ is a “range parameter” of the species, λ_ο is the expected encounter frequency of an individual (i.e., focal animal) whose activity centre is exactly at trap location, Nsuper is the estimated number of individuals (i.e., focal animals) located in the state-space S, Ψ is the ratio between Nsuper and the maximum allowable number of individuals (i.e., focal animals) in S set by the user during data augmentation. Density is obtained dividing Nsuper by the surface of the state-space S. In secr, parameters σ and g_o are analogous to σ and λ_ο in SPACECAP

ISSN: 1742-9994