Résumé
A nonparametric approach has recently been proposed for estimating survival in capture-recapture models, which uses penalized splines to achieve flexibility in exploring the relationships with environmental covariates. However, this method is highly time-consuming because it is implemented through a fully Bayesian approach using Markov chain Monte Carlo simulations. To cope with this issue, we developed a two-step approach in which the existing method is used in conjunction with a multivariate normal approximation to the capture-recapture data likelihood. The ability of our approach to capture various nonlinearities in demographic parameters was validated by carrying out a simulation study. Two examples dealing with Snow petrel and Emperor penguin capture-recapture data sets were also considered to illustrate our procedure, including the relationship between survival rate, population size and climatic covariates.