Genomic discovery in forest trees follows paradigms from both agricultural crop and livestock improvement and human medicine. Forest trees in a domesticated state can be improved using genomic-based breeding technologies, whereas the health of trees in a natural and undomesticated state might be managed using those same technologies. These applications begin by first dissecting complex traits in trees to their individual gene components and for that the association genetics approach is quite powerful in trees. This is true for several reasons including large, random mating, and unstructured populations and the rapid decay of linkage disequilibrium in many tree species. Once marker by trait associations are discovered, they can be used in genomic-based breeding and forest health diagnostics. Initial studies in trees have found ample nucleotide diversity in candidate genes to perform association studies and single nucleotide polymorphisms have been associated with economic and adaptive traits. Population genetic neutrality tests have been applied to identify genes probably under natural selection and thus make good candidates for developing forest health diagnostic tools.