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Moving forest tree species beyond their current range (assisted gene flow, AGF), could become a necessity to mitigate the adverse effects of climate change. Monitoring the rate of hybridization and the spread of adaptive genetic variants upon AGF using genetic evaluation is impractical and expensive. Here we develop a cost-effective remote sensing tool based on optical spectroscopy to map the genetic and phenotypic clines between European and oriental beech, and to develop a protocol based on machine learning to uncover the relationship between the two. We will use the natural hybrid zone between the two species in Bulgaria to sample training populations and collect genomic and remote sensing data. Our approach will be evaluated on four existing >100-year-old oriental beech plantations in Switzerland and France that are living laboratories of of AGF. Our approach is a proof-of-principle which could be developed to monitor hybridization in other species upon AGF.

This project is co-lead by Prof. Dr. Meredith Schumann at ther University of Zurich.

 

Tracing hybridization of oriental beech following assisted gene flow: an approach combining high-throughput genomics, remote sensing and machine learning