Dialects occur in a range of species, from human language to bird song. This project will focus on dialect evolution in killer whales. Each pod of killer whales shares a unique repertoire of discrete calls a vocal dialect, which passes from mother to offspring through social learning. It is commonly accepted that killer whale dialects change gradually with time by accumulation of stochastic copying errors, but some observations suggest that call evolution is much more complex phenomenon. The goal of the proposed research is to reveal the principles of killer whale dialect evolution. The distribution of various call features in dialects on intra- and inter-population level will be described using the linguistic methodology developed for the description of human languages. This distribution will be analysed using the computational methods from the evolutionary biology. The phylogeny of dialects will be constructed by the amount of shared call features using Bayesian methods. The phylogenetic tree obtained by the dialect comparison will be calibrated with genetic analysis using complete mitochondrial genome sequences. It will allow to estimate the speed of dialect evolution and test for its homogeneity. The project will lead to better understanding of the general principles of cultural evolution and yield a model of killer whale dialect evolution that will allow to determine the population structure of killer whales by vocal dialects, which will significantly help conservation and management of killer whale populations. Killer whales are listed with other Cetacea in Annex IV of the Habitats Directive as a species of community interest in need of strict protection. In recent decades Northeast Atlantic killer whales have been subject to a number of anthropogenic threats. Identifying killer whale populations is a key goal for conservation and management of the species, because any impact must be primarily accessed on the population rather than on species level.