Forest trees have gained much attention in recent years as nonclassical model eukaryotes for population, evolutionary and ecological genomic studies. Because of low domestication, large open-pollinated native populations, and high levels of both genetic and phenotypic variation, they are ideal organisms to unveil the molecular basis of population adaptive divergence in nature. Population genomics, in its broad-sense definition, is an emerging discipline that combines genome-wide sampling with traditional population genetic approaches to understanding evolution. Here we briefly review traditional methods of studying adaptive genetic variation in forest trees, and describe a new, integrated population genomics approach. First, alleles (haplotypes) at candidate genes for adaptive traits and their effects on phenotypes need to be characterized via sequencing and association mapping. At this stage, functional genomics can assist in understanding gene action and regulation by providing detailed transcriptional profiles. Second, frequencies of alleles in native populations for causative single-nucleotide polymorphisms are estimated to identify patterns of adaptive variation across heterogeneous environments. Population genomics, through deciphering allelic effects on phenotypes and identifying patterns of adaptive variation at the landscape level, will in the future constitute a useful tool, if cost-effective, to design conservation strategies for forest trees.