| dc.description.abstract | Understanding how genomic adaptation shapes species’ responses to climate change is essential for developing climate-resilient forests, as shifting conditions increasingly drive range shifts and maladaptation. This study investigates adaptive genomic variation in Betula alleghaniensis (yellow birch), a widely distributed hardwood of eastern North America. Genome-wide single-nucleotide polymorphism (SNPs) variation from 27 populations was analyzed using 3D-genotype-by-sequencing and two genotype-environment association methods: redundancy analysis (a multivariate ordination method) and Gradient Forest (a machine learning algorithm). 124 putatively adaptive loci were identified, linked to extreme minimum temperature, degree-days below 0°C, winter precipitation, and snowfall. Functional annotation revealed roles primarily in stress response and transcriptional regulation. Patterns of adaptive variation showed a latitudinal gradient tied to winter severity and spatially heterogeneous responses to snowfall. Two distinct clusters of adaptive loci were identified along the climate gradients, suggesting winter climate plays a dominant role in shaping local adaptation. Future climate projections (SSP5-8.5, 2041-2070) predict substantial shifts in adaptive alleles in the Northeastern Appalachians, Maritimes, and St. Lawrence River regions. Nevertheless, genetic offset, the Euclidean distance between the current and future adaptive genomic composition, across the range was relatively low, suggesting genomic resilience potentially supported by yellow birch’s allohexaploid genome and extensive gene flow, including adaptive introgression from hybridization with other Betula members. These findings highlight the importance of integrating genomic data into forest management strategies.
Keywords: Betula alleghaniensis, Yellow Birch, local genetic adaptation, genotype-environment association (GEA), genetic offset, climate change | en_US |
