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

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.