Natural populations of forest trees exhibit striking phenotypic adaptations to diverse environmental gradients, thereby making them appealing subjects for the study of genes underlying ecologically relevant phenotypes. Here, we use a genome-wide data set of single nucleotide polymorphisms genotyped across 3059 functional genes to study patterns of population structure and identify loci associated with aridity across the natural range of loblolly pine (Pinus taeda L.). Overall patterns of population structure, as inferred using principal components and Bayesian cluster analyses, were consistent with three genetic clusters likely resulting from expansions out of Pleistocene refugia located in Mexico and Florida. A novel application of association analysis, which removes the confounding effects of shared ancestry on correlations between genetic and environmental variation, identified five loci correlated with aridity. These loci were primarily involved with abiotic stress response to temperature and drought. A unique set of 24 loci was identified as F(ST) outliers on the basis of the genetic clusters identified previously and after accounting for expansions out of Pleistocene refugia. These loci were involved with a diversity of physiological processes. Identification of nonoverlapping sets of loci highlights the fundamental differences implicit in the use of either method and suggests a pluralistic, yet complementary, approach to the identification of genes underlying ecologically relevant phenotypes.