Multiple observation processes in spatial capture–recapture models: How much do we gain?

摘要: Population monitoring data may originate from multiple methods and are often sparse fraught with incomplete information due to practical economic constraints. Models that can integrate survey able cope help investigators exploit available more thoroughly. Here, we developed an integrated spatial capture-recapture (SCR) model incorporate sources imperfect individual identification. We contrast inferences drawn this alternate models incorporating only subsets of the available. Using extensive simulations empirical example multi-method brown bear (Ursus arctos) northern Pakistan, quantified benefits including in SCR terms parameter precision bias. Our observation processes (MOP) yielded a complete picture underlying processes, reduced bias, led precise estimates. results suggest greatest gains be expected situations where detection probability is low, large proportion detections not attributable individuals, degree overlap between home ranges low.