This workflow integrates genomic and climate data to optimize seed production areas, implying better biodiversity conservation.
Key Points
The research aims to develop a workflow that uses genomic and climate data to design effective seed production areas (SPAs) for enhancing genetic diversity.
Integrated genomic data with future climate projections to identify genetic neighbourhoods.
Utilized a climate-matching tool to find external genetic neighbourhoods with analogous climates.
Evaluated common allelic diversity under various sampling decisions.
Developed an optimisation method to maximize allele representation using site frequency spectra.
Implemented strategies: local, predictive, and climate-adjusted provenancing.
Multiple sampling strategies could capture over 90% of common alleles from local genetic neighbourhoods.
Including climate-matched sources nearly doubled allelic representation in SPAs.
The workflow proved adaptable to practical limitations like site inaccessibility.