Encounter history modeling of joint mark-recapture, tag-resighting and tag-recovery data under temporary emigration

Abstract

We describe a joint analysis of mark-recapture, tag-resight and tag-recovery data that directly models the encounter history of an animal. The probability of the encounter history for each animal is partitioned into survival, recapture, resighting, and recovery components, and a component for the probability that the animal is never encountered again. Temporary migration enters into the likelihood through the recapture component, and movement of marked animals in and out of the area where they are subject to capture is modeled using a Markov chain. Random temporary emigration and permanent emigration are special cases. An important feature of directly modeling the encounter histories is that covariates that are specific to individuals can be included in the analysis. The model is applied to a brown trout tagging data set and provides strong evidence of Markovian temporary emigration. The new model is needed to provide correct estimates of trout survival probabilities which are shown to depend on the length of the fish at first capture.