Phenotypic drought stress prediction of European beech (Fagus sylvatica) by genomic prediction and remote sensing

Markus Pfenninger^1,2*Liam Jude Langan¹Barbara Feldmeyer¹Barbara Fussi³Janik Hoffmann¹Jessica Hetzer¹Muhidin Šeho³Karl-Heinz Mellert³Thomas Hickler^1,4

• ¹Senckenberg Biodiversity and Climate Research Centre, Frankfurt (Main), Germany
• ²Johannes Gutenberg Universitat Mainz Institut fur Organismische und Molekulare Evolutionsbiologie, Mainz, Germany
• ³Bayerischen Amts fur Waldgenetik, Teisendorf, Germany
• ⁴Goethe-Universitat Frankfurt am Main, Frankfurt, Germany

Current climate change species response models usually do not include evolution. We integrated remote sensing with population genomics to improve phenotypic response prediction to drought stress in the key forest tree species European beech (Fagus sylvatica L.). We used whole-genome sequencing of pooled DNA from natural stands along an ecological gradient from humid-cold to warm-dry climate. We phenotyped stands for leaf area index (LAI) and moisture stress index (MSI) for the period 2016-2022. We predicted this data with matching meteorological data and a newly developed genomic population prediction score in a Generalised Linear Model. Model selection showed that the addition of genomic prediction decisively increased the explanatory power. We then predicted the response of beech to future climate change under evolutionary adaptation scenarios. A moderate climate change scenario would allow persistence of adapted beech forests, but not worst-case scenarios. Our approach can thus guide mitigation measures, such as allowing natural selection or proactive evolutionary management.