Black grouse Tetrao tetrix is a bird species composed of large, continuous as well as severely reduced and fragmented populations, making it an optimal species to investigate how genetic diversity is affected by habitat fragmentation. I have focused on genetic diversity in the Major Histocompatibility Complex (MHC) to measure the ability of the black grouse to respond to environmental changes. I partly characterized MHC class II in black grouse and found striking similarities with chicken MHC class II. I demonstrated that black grouse possess a similar compact MHC as chicken with few MHC class II B (BLB) and Y (YLB) loci. I did not find evidence of balancing selection in YLB so I concentrated further studies on BLB. I developed a PCR-based screening method for amplifying and separating expressed BLB alleles in European black grouse populations. Small fragmented populations had lost neutral genetic diversity (based on microsatellites and SNPs) compared to samples from the historical distribution and contemporary large populations. There was also a trend, albeit less pronounced, for reduced MHC diversity in these populations. Neutral markers in small isolated populations were affected by increased levels of genetic drift and were therefore genetically differentiated compared to other populations. MHC markers on the other hand, were not subjected to genetic drift to the same extent probably due a long historic process of balancing selection. Inferences of heterozygosity and evolutionary patterns as well as detailed correlations to reproductive success and diseases cannot be performed until MHC can be amplified in a locus-specific manner. Therefore, I developed a single locus sequence-based typing method for independently amplifying MHC class II B loci (BLB1 and BLB2). I found that BLB1 and BLB2 were duplicated in a common ancestor to chickens and black grouse and that these loci are subjected to homogenizing concerted evolution due to inter-genetic exchange between loci after species divergence.  I could also verify that both BLB1 and BLB2 were transcribed in black grouse and under balancing selection. This collection of work has significance for future conservation of black grouse as well as research and management of zoonotic diseases.

The Bag of Little Bootstraps (BLB) was introduced to make the bootstrap method more computationally efficient when used on massive data samples. Since its introduction, a broad spectrum of research on the application of the BLB has been made. However, while the BLB has shown promising results that can be used for logistic regression, these results have been for well-balanced data. There is, therefore, an obvious need for further research into how the BLB performs when the dependent variable is unbalanced and whether possible performance issues can be remedied through methods such as Firths's Penalized Maximum Likelihood Estimation (PMLE). This thesis shows that the dependent variable's imbalances severely affect the BLB's performance when applied in logistic regression. Further, this thesis also shows that PMLE produces mixed and unreliable results when used to remedy the drops in performance.