Araucaria angustifolia has high economic, social, and ecological importance in Brazil, although it is critically threatened with extinction. To understand araucaria’s adaptation, we used a genome-wide association studies (GWAS) to identify markers with signatures of selection associating genomic variation to phenotypic and climatic variables. We also used landscape genomics to identify geographic regions at the highest risk of extinction for the species due to climate change. We used phenotypic and genotypic data of 859 adult trees from a provenance-progeny trial (15 populations), 1,304 SNPs, climatic variables, and growth traits. The GWAS analyses were performed using a general linear model, the Wald test, and a Bayesian method based on population divergence. BLAST techniques were used to gather information about the selected markers. We estimated the proportion of variance explained by regression of genomic data against phenotypic and climatic variables. To estimate vulnerability to climate change, we used the gradient forests. We identified outlier SNPs associated with the climatic and phenotypic traits. Considering the climatic features as drivers of araucaria adaptation, we see that precipitation in the dry season is the leading and most predictable adaptation trait for araucaria. Genomic offset (Goff) for the most optimistic scenario shows that the main critical area is the transition between the tropical and temperate climates in Brazil. In Goff’s most pessimistic scenario, the entire temperate region presents a change in allele turnover. In this context, we propose strategies like assisted migration and targeted reforestation management to accelerate the adaptation of araucaria to the predicted scenarios.
