Two major changes are profoundly reshaping plant breeding. The first one is genomic selection, i.e. the use of genome-wide markers to establish the relationship between genome-wide polymorphism and phenotype in training sets and thereafter select solely on genomic information, significantly increases breeding efficiency. Genomic selection needs to grapple with classical issues in quantitative genetics such as population genetic structure, genotype by environment interactions, and genetic load. Failing to account for population structure leads to false positive in association mapping studies, to wrong inferences in evolutionary studies and to decreased efficiency in genomic selection. Similarly, genotype by environment interactions are going to play a key role in finding material adapted to new climatic conditions and will need to be accounted for in new breeding strategies that are based on genomic selection. Finally, a breeding program is a closed and finite population, and preventing the accumulation of deleterious mutations is becoming a major issue, especially in forest trees that have strong inbreeding depression. The second change that will force us to reconfigure established breeding programs is global climate change. Global climate change (GCC) will have two direct consequences on breeding programs. First, GCC will force us to redefine breeding zones. The second effect of GCC on breeding programs is an increased uncertainty as to the breeding goals and a more prominent place of fitness related traits (as opposed to production traits) among those. In the present project, a combination of population and quantitative genetics studies will be used to establish genomic selection in birch. The main research questions are: 1. How genetically structured is the Swedish birch population? 2. Is the current genetic structure primarily reflecting past demography or is the current clustering also reflecting local adaptation and genotype*environment interaction? 3. What is the genetic architecture of local adaptation? Are there differences in genetic architecture and genetic load between geographical areas with different demographic histories?