A Comparison of Genomic Forecasts Based on Genotypes versus Allele Frequencies

Area of Science:

• Ecology
• Genetics
• Conservation Biology

Background:

• Climate and land use change disrupt species' adaptive variation and environmental optima.
• Identifying nonlocal genetic sources is crucial for effective species restoration.
• Genomic offset methods show promise for predicting adaptive potential, but require refinement.

Purpose of the Study:

• To compare the predictive accuracy of genotype- and allele frequency-based genomic offset models.
• To evaluate model performance using both individual and population-level fitness metrics.
• To assess the impact of the number of loci on model accuracy.

Main Methods:

• Utilized simulation data for extensive model evaluations (>810,000).
• Compared genotype-based and allele frequency-based models.
• Factorially evaluated models using individual and population mean fitness.

Main Results:

• Model performance was minimally impacted by the number of loci.
• Population-level fitness evaluation provided optimistic predictions for both model types.
• Genotype-based models improved predictions in non-cline environments by utilizing more loci.

Conclusions:

• Genotype-based models enhance genomic offset predictions in complex, discontinuous landscapes.
• Individual fitness evaluation provides a more realistic assessment of predictive performance.
• Recommendations are provided for the future application and evaluation of genomic offset tools.