Stochastic modeling in biological populations with sexual reproduction through branching models: application to Coho salmon populations.

The motivation behind this research is to develop appropriate mathematical models to describe the demographic dynamics of animal populations with sexual reproduction. We introduce a new class of two-sex branching models where several mating strategies between females and males and a variety of possibilities for the process of reproduction are taken into account. Unlike other classes of two-sex models which assume that mating and reproduction are influenced by the number of couples in the population, we now consider the most realistic case where both biological processes are affected by the numbers of females and males in the population, which may differ. Under a general parametric setting, we deal with inferential questions about the main parameters affecting the reproduction process. By considering the observation over time of the numbers of females and males up to when a certain pre-set generation is reached, we derive Bayes estimators for such parameters. With the purpose of determining highest posterior density credibility sets, we also propose a computational algorithm. As illustration, we include an application to Coho salmon populations.