Abstract

Global anthropogenic change threatens the health and productivity of forest ecosystems. Assisted migration and reforestation are tools to help mitigate these impacts. However, questions remain about how to approach sourcing seeds to ensure high establishment and future adaptability. Using exome-capture sequencing, we demonstrate a computational approach to finding the best n-sets from a candidate list of seed sources that collectively achieve high genetic diversity (GD) and minimal genetic load (GL), while also increasing evolvability in quantitative traits. The benefits of this three-part strategy (diversity-load-evolvability) are to increase near-term establishment success while also boosting evolutionary potential to respond to future stressors. Members of The Nature Conservancy and the Central Appalachian Spruce Restoration Initiative planted 58,000 seedlings across 255 acres. A subset of seedlings was monitored for establishment success and variation in growth. The results show gains in GD relative to GL and increases in quantitative genetic variation in seedling growth for pooled vs. single-source restoration. No single "super source" was observed across planting sites; rather, monitoring results demonstrate that pooling of multiple sources helps achieve higher GD:GL and evolvability. Our study shows the potential for integrating genomics into local-scale restoration and the importance of building partnerships between academic researchers and applied conservation managers.

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