Lamothe, M. | Search bioRxiv

bioRxiv2025

Testing genomic offset with common gardens in genetically structured black spruce (Picea mariana)

Boreal forests play a crucial role in regulating climate via storage and release of carbon. Anticipated changes in climate are expected to increase mortality and reduce biomass in many boreal tree species, putting at risk the functioning of this ecosystem and hence its role in carbon sequestration. Genomic offset methods leverage spatial distribution of genomic diversity and its association with environmental variables to predict population vulnerability to projected changes in climate. Here, we analyse over 60 populations and more than 1400 individuals of black spruce (Picea mariana (Mill.) B.S.P), a dominant boreal forest species, to compare population-level genomic offsets calculated using Gradient Forest and redundancy analysis (RDA) against multiple fitness traits measured in four long-term (>40 yr) common gardens. Within common gardens, we found that genomic offset predictions were largely unaffected by the model choice, the number or type of markers used for model training, with the strongest discrepancies observed for LFMM climate-associated markers. Model performance remained relatively stable when the number or size of populations in the training set was reduced, suggesting that these models can reliably project genomic offsets for new populations. However, model performances varied among common gardens, with highly accurate fitness predictions in some gardens but contradictory results in others. Model performance was influenced by the choice of climate predictors, their relationships with fitness traits, and the genetic cluster in which the models were evaluated. Overall, our results highlight the challenges of projecting genomic offsets across large spatial scales in genetically structured species, due to spatial variation in environmental drivers of adaptation and complex interactions among them. By capitalizing on our comprehensive validation, we identified the most robust models for projecting fitness declines in black spruce under future climate scenarios.

evolutionary biology↗

bioRxiv2025

The genomic basis of local adaptation in the white x Engelmann spruce hybrid zone

Hybridization between species can occur along repeated zones of contact, providing a natural laboratory for studying the interplay between migration and selection, and identifying loci involved in adaptation and reproductive isolation. However, interpreting how evolutionary processes shape genomic patterns can be challenging: repeatability of genotype-environment association alone is not strong evidence for selection, as hybrid zones derived from the same parental species are not evolutionarily independent. Conversely, processes that operate within the middle of each hybrid zone, such as selection driving directional introgression, may be more evolutionarily independent, and therefore provide stronger evidence of selection. Here we compared hybridization and local adaptation patterns between two replicated regions within the western Canada interior spruce hybrid zone: a broad latitudinal transect with gradual environmental variation and a narrow elevational transect with substantial topographical and environmental variation. We discovered a complex pattern of introgression, with strong differences in ancestry maintained even across small spatial scales at several locations along the elevational transect. Despite differences in their spatial scales, the elevational and latitudinal transects revealed strikingly similar genome-wide patterns of differentiation and adaptation, and consistent patterns of directional introgression. We explore the extent to which the evolutionary non-independence of these hybrid zones allows inferences about the role of natural selection and drift in shaping these patterns. Consistent with theory, we found longer genomic tracts in the elevational transect, likely because the steeper environmental gradients over shorter distances limit the rate of mixing by migration and recombination relative to drift and selection.

evolutionary biology↗