Using imputation and mixture model approaches to integrate multi-state capture–recapture models with assignment information



In this article, we first extend the superpopulation capture–recapture model to multiple states (locations or populations) for two age groups., Wen et al., (2011; 2013) developed a new approach combining capture–recapture data with population assignment information to estimate the relative contributions of in situ births and immigrants to the growth of a single study population. Here, we first generalize Wen et al., (2011; 2013) approach to a system composed of multiple study populations (multi-state) with two age groups, where an imputation approach is employed to account for the uncertainty inherent in the population assignment information. Then we develop a different, individual-level mixture model approach to integrate the individual-level population assignment information with the capture–recapture data. Our simulation and real data analyses show that the fusion of population assignment information with capture–recapture data allows us to estimate the origination-specific recruitment of new animals to the system and the dispersal process between populations within the system. Compared to a standard capture–recapture model, our new models improve the estimation of demographic parameters, including survival probability, origination-specific entry probability, and especially the probability of movement between populations, yielding higher accuracy and precision.