Adaptive Potential and Genomic Vulnerability of Keystone Forest Tree Species to Climate Change: A Case Study in Scots Pine

A better understanding of the possible adaptive response and genomic vulnerability of forest trees is needed to properly assist future forest management and develop adequate resilience strategies to changing environments. Scots pine (<i>Pinus sylvestris</i> L.), a keystone species with extensive distribution and a broad ecological niche, is expected to be directly impacted by climate change due to maladaptation and associated fitness declines. Despite extensive studies that have clarified the broad-scale history and genetic structure of the species, understanding the genetic basis for local adaptation and the extent of genomic offset in Scots pine remains incomplete. Here, we used thousands of genotyped SNP markers in 39 natural populations (440 trees) along a broad latitudinal gradient of species distribution to examine molecular signatures of local adaptation. Specifically, this landscape genomics approach aimed to assess fine-scale patterns of SNPs associated with environmental gradients, estimate genomic offset as a proxy for exposure and sensitivity components of vulnerability, and evaluate the adaptive response of populations to projected climate shifts. The variation of outlier SNPs, which exhibit selection signatures between genetically very similar populations in the analysed distribution range, was highly correlated with mean annual temperature, a key limiting factor for the growth and survival of tree species. Furthermore, our simulation results indicated a high genomic offset on a large spatial scale in <i>P. sylvestris</i>, with the time frame required to close the offset gap by natural selection estimated to be in the range of hundreds of years. We evaluate the genomic offset in the coming decades and indicate the optimal allelic frequency spectra required in the future to ensure resilience of Scots pine populations. We discuss forest assisted migration (FAM) as a management strategy, involving the relocation of genotypes to areas with matching environmental conditions. By evaluating adaptive responses, the study adds to the discussion on the long-term sustainability of forest ecosystems.