The stakes of capture-recapture models with state uncertainty

The development of the use of CR multistate models is a major feature of the last 5 years. However, concerns have rightfully appeared about uncertainty in state assignment. I examine situations where uncertainties seem to be intrinsic such as with breeding status. But I also argue that uncertainty is not just a liability, it can be an opportunity - for instance, to exploit more fully the data at hand and limit disturbance. Then I examine the methodological answers that have been proposed. They mainly concern the models conditional on first release and are of a more or less general applicability. I advocate a general approach that can be adapted to each particular case and be used to expand extant specialized approaches. I will also consider how uncertainty could be incorporated into non-conditional models such as models of stopover duration. I conclude that, with the advent of genetic sampling, the new challenges for CR models will be uncertainty in individual identity and dependence among individuals.