Impact of Geographical and Environmental Structures on Habitat Choice, Metapopulation Dynamics and Genetic Structure for Hazel Grouse (Bonasa bonasia)

In this work suitable habitats for hazel grouse (Bonasa bonasia) were identified using ecological niche factor analysis (ENFA). The results from ENFA reveal that hazel grouse utilize a different and more restricted niche than what is generally available in the study area. When a landscape is fragmented the amount of edge increases, which is negative for many species and thus will affect the amount of available area. The perimeter-area ratio was used to analyze the relative importance of geometric shape. In order to estimate a correlation between incidence of hazel grouse and landscape features census data and land cover maps were analyzed with logistic regression models. It is concluded that hazel grouse is tied to coniferous forest and avoid open areas. However, the result indicates that there is a scale effect that should be considered. The amount of edge in a landscape seems to be important and shape of patches could be a better measure in metapopulation dynamics. In this study the Incidence function model was used to estimate occupancy levels and capacity of a landscape to sustain a metapopulation according to four different area measurement scenarios. Results from the simulations indicate that perimeter-area related measures of patch size combined with capacity could be a more important measure for estimation of population dynamics compared to a basic area measurement. Using a landscape genetic approach, hazel grouse genetic structure, neighbourhood size and dispersal distance were estimated. Genetic estimates of dispersal were in concordance with previous ecological estimates. The results indicate evidence of a population structure reminiscent of what has been found in many other Scandinavian animals with a basic north-south divide. No evidence was found that geographic and environmental structures affected gene flow and dispersal patterns for the hazel grouse