Using Landscape Genomics to Define Species Distributions, Delineate Seed Zones, and Predict Genomic Offset to Future Climate for the Interior Spruce Hybrid Complex (Picea glauca, Picea engelmannii, and Their Hybrids)

Understanding how tree species adapt to climate is crucial for forest management under climate change. This study employs landscape genomics to investigate climate adaptation in the interior spruce complex (Picea glauca, P. engelmannii, and their hybrids) across western Canada. Using Gradient Forest modeling with 41,253 SNPs genotyped in 1684 natural interior spruce individuals from 252 populations, we found that winter temperature and moisture-related variables were the variables most strongly associated with genomic variation. Both adaptive and neutral genetic variation showed similar patterns along climatic gradients, suggesting that population structure largely follows environmental clines. We successfully delineated three species and 11 seed zones based on genomic variation and climate relationships, achieving 88.2% concordance with previous genetic studies in defining species boundaries. Analysis of genomic offsets under future climate scenarios revealed potential maladaptation risks, particularly in northern and eastern British Columbia. These predictions were validated using fitness-related measurements from common-garden experiments, which showed negative correlations between genomic offsets and traits, such as height and diameter at breast height (DBH). Maladaptation predictions based on genomic offsets showed some differences compared with common-garden-based assessments in several regions, offering new perspectives on population vulnerability. Our results demonstrate the effectiveness of landscape genomics as a complementary approach to traditional methods for assessing climate adaptation in tree species. Our findings provide a scientific foundation for climate-smart reforestation strategies and offer practical guidance for forest management in the context of climate change.