The subject of this thesis is the study of certain stochastic models arising in Population Genetics. The study of biological evolution naturally motivates the construction and use of sometimes sophisticated mathematical models. We contribute to the study of the so-called Lambda models. Our work is divided into two parts. In Part I, we study non-spatial models, introduced in 1999. Although there is a very rich literature concerning the description of genetic diversity thanks to the genealogies arising in these models, we obtain new results by considering the dynamics of the full population. We also contribute by presenting the first Bayesian method that allows us to reconstruct the genealogies generated by these models from data. In Part II, we study a recent extension of these models to the spatial setting. In particular, we prove a non trivial result concerning the geographical dispersal of a new mutant under this model.</p
