DOI: 10.5061/dryad.2jm63xsvq
title: Data from: Phenotypic drought stress prediction of European beech (Fagus sylvatica) by genomic prediction and remote sensing

description: 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.
description: The sites selected for this
 study were in many regards typical for German beech
 forests. They comprised a
 large ecological amplitude with regard to long-term conditions. Within the
 range from humid-cold to warm-dry climatic conditions, important
 demographic and genetic processes in beech forests are taking
 place. Therefore, the aim
 of selection and stratification was to cover the climatic spectrum of
 forested areas in central and southern Germany to a large extent. For the
 characterisation of the climatic niche, we used the climatic marginality
 towards the rear edge,
 i.e. the dry and warm border of species distributions. 
 <strong>Construction of
 population pools, sequencing, population structure and genetic
 diversity</strong> From each tree, 1-2 buds or 3-4 leaf discs of
 0.5 mm diameter (approx. 50 mg of fresh plant material) were dried in
 Silicagel prior to homogenization. DNA was extracted using an in-house
 protocol. We constructed DNA pools per population using the same DNA
 quantity per individual beech. DNA concentration was measured using a
 Quantus fluorometer (Promega). Library preparation and 150bp paired-end
 sequencing with 450bp insert was conducted at
 Novogene. Reads were trimmed using Trimmomatic
 v.0.39 and quality
 controlled with FastQC v.0.11.9. We used BWA mem v.0.7.17 to map the reads onto the newest version of the
 beech reference genome and
 Samtools v.1.10 to
 convert, sort and pile up the bam files. Duplicates were marked and
 removed with Picard v.2.20.8 (https://github.com/broadinstitute/picard).
 PoPoolation2 v.2.201 pipeline was used to remove indels, and
 calculated allele frequencies for every position and pairwise FSTs in
 non-overlapping 1kb windows. Genetic variation (ϴ) and nucleotide
 diversity (π) were estimated in the same windows with
 PoPoolation1
 v.1.2.2.
 We considered only sites
 within a coverage range of 15-50X.