RemoteHybridMonitoring

Summary

Moving forest tree provenances or closely related species beyond their current range (assisted gene flow, AGF), could become a necessity for foundational and economically important species to mitigate the adverse effects of climate change. Monitoring the rate of hybridization and the spread of adaptive genetic variants upon AGF using field sampling and genetic evaluation is impractical and expensive. In this study, we propose the development and evaluation of a cost-effective remote sensing tool. We will use state-of-the art genomics, terrestrial laser scanning, UAV-based imaging, and 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. In these sites, hybridization has been ongoing since several generations; a situation that we expect to encounter in future as a result of AGF in Central and Western Europe. Then, our approach will be evaluated on four existing >100-year-old oriental beech plantations in Switzerland and France that are living laboratories of AGF. Our approach is a proof-of-principle which could be developed to monitor hybridization in other species upon AGF and could provide a basis for the development of satellite-based monitoring as well.