Climate change is motivating a reassessment of how seeds are selected for reforestation, as rapid environmental change can lead to local maladaptation in trees. Genetic association studies and past seed source climate both have the potential to help identify appropriate planting stock, but these techniques have not been compared and tested as part of an operational planting program. In this study, we combined an analysis of SNPs associated with environmental gradients in sugar pine (P. lambertiana) with an analysis of post-fire seedling survival and growth in a restoration experiment. Our genotype-environment association (GEA) tests revealed 829 SNPs (single nucleotide polymorphisms) with significant association with climate gradients – especially April snowpack – 323 of which either had annotations that suggested potential functional importance or were identified by two different methods. We then built Bayesian models of survival and growth for all seedlings to test the effects of source elevation, a common proxy for climate. For the subset of seedlings alive and genotyped in 2020 (1–3 years after planting), we tested the relative predictive ability of source elevation versus the proportion of seedling alleles expected to be locally advantageous. We found that source elevation was generally better at predicting seedling performance than genotype indices, perhaps because of the limited scope of the association analysis. Seed sources from 500–1500 feet lower in elevation and one seed zone further south generally performed as well or better than local seed sources. This is likely because the temperatures in the planting area closely resemble that of those source regions in the mid-20^th century, allowing seedlings to survive and exhibit the higher growth potential often seen in warmer-climate populations. By contrast, seedlings from cooler, wetter sources tended to perform poorly. This result, and those of similar previous studies, suggest that “climate matching” using past climate information for existing seed sourcing units is a reasonable starting point for finding seedlings suited to already-altered planting site climate conditions. However, further tests with more extensive genomic and performance data may improve the utility of genotype information for seed selection.