Testing source elevation versus genotype as predictors of sugar pine performance in a post-fire restoration planting

Area of Science:

• Ecology
• Genetics
• Forestry

Background:

• Climate change necessitates reassessment of seed sourcing for reforestation to prevent local maladaptation in trees.
• Genetic association studies and historical climate data are potential tools for identifying suitable planting stock but require validation in operational programs.

Purpose of the Study:

• To compare the effectiveness of genotype-environment association (GEA) with traditional source elevation in predicting sugar pine seedling performance in a post-fire restoration experiment.
• To evaluate the utility of genomic data versus climate matching for guiding seed selection in reforestation under changing environmental conditions.

Main Methods:

• Conducted genotype-environment association (GEA) analysis on sugar pine (P. lambertiana) to identify SNPs linked to climate gradients, particularly April snowpack.
• Established a post-fire seedling planting experiment, testing the predictive power of source elevation and GEA-derived genotype indices on seedling survival and growth.
• Utilized Bayesian models to analyze seedling performance data from three sites within the King Fire scar over three years.

Main Results:

• Identified 829 SNPs significantly associated with climate gradients, with 323 showing potential functional importance.
• Source elevation was generally a better predictor of seedling performance than genotype indices derived from GEA.
• Seedlings from lower elevations (500-1800 ft) and one seed zone south performed comparably or better than local sources.

Conclusions:

• Climate matching using historical climate data for seed sourcing units provides a practical starting point for selecting climate-adapted seedlings.
• While GEA shows potential, further research with more extensive genomic and performance data is needed to enhance its utility in operational seed selection for reforestation.