Bayesian analysis to correct false-negative errors in capture–recapture photo-ID abundance estimates

Abstract

Capture–recapture methods are largely used for estimating the size of some cetacean populations. The application of those methods for photo-identification data of recognizable individuals is very common. Poor quality photographs may lead the analyst to identify two sightings of the same individual as being different (false-negative errors). This kind of matching error inflates population size estimates. We develop a Bayesian approach to obtain bias corrected estimates of the population size N. The method can be used for M_t type capture–recapture models (Otis et al. Wildlife Monographs 62 (1978) 1–135) involving two or more sampling occasions. We used the methodology for simulated data.