Hidden Markov Random Fields and the Genetic Structure of the Scandinavian Brown Bear Population

Spatial Bayesian clustering algorithms can provide correct inference of population genetic structure when applied to populations for which continuous variation of allele frequencies is disrupted by small discontinuities. Here we review works which used Bayesian clustering algorithms for studying the Scandinavian brown bears, with particular attention to a recent method based on hidden Markov random field. We provide a summary of current knowledge about the genetic structure of this endangered population potentially useful for its conservation.