Raw data and code for Semizer‑Cuming et al. (2026): Combining niche modelling, soil properties and genomics to investigate adaptive potential of silver fir

The raw data and associated code support an investigation into the adaptive potential of native silver fir in mixed mountainous forests of southern Germany. The SSR genotype dataset for 12 stands was generated using nine microsatellite markers and used to calculate population genetic parameters. SNP genotyping of six selected stands along an environmental gradient was performed using the SPET method to identify gene loci potentially under selection. The environmental dataset comprises 33 variables characterizing site conditions, including predictors relevant to tree distribution, vitality, and growth that were used for genotype–environment association analyses. The code includes scripts for variant filtering, outlier detection, and associated simulations. Microsatellite analyses revealed relatively high genetic diversity and identified three major spatial–genetic clusters along an east–west gradient. Shared outlier loci were linked to stress related pathways involved in growth regulation. Twenty five environmentally associated outliers were located in genes encoding proteins involved in diverse metabolic functions, including drought response mechanisms. These results contribute to understanding spatial–genetic structuring and the adaptive potential of silver fir, providing insights that support conservation and sustainable management of the species’ genetic resources in Germany.本研究的原始数据与配套代码可支撑针对德国南部山地混交林中原生银冷杉（silver fir）适应潜力的相关探究。研究采用9对微卫星标记，生成了覆盖12个林分的简单序列重复（Simple Sequence Repeat, SSR）基因型数据集，并以此计算种群遗传参数。本研究还针对沿环境梯度选取的6个林分，采用SPET技术开展单核苷酸多态性（Single Nucleotide Polymorphism, SNP）基因分型，以筛选潜在受选择的基因位点。环境数据集包含33项表征立地条件的变量，其中包括与林木分布、活力及生长相关的预测因子，这些变量被用于基因型-环境关联分析。配套代码涵盖变异过滤、异常位点检测及相关模拟分析的脚本文件。微卫星标记分析结果显示，该物种具有较高的遗传多样性，并沿东西梯度划分出3个主要的空间遗传聚类群。共有的异常位点与参与生长调控的胁迫相关通路存在关联。另有25个与环境相关的异常位点位于编码多种代谢功能蛋白的基因中，其中包含干旱响应机制相关基因。本研究结果有助于解析银冷杉的空间遗传结构及其适应潜力，为德国境内该物种遗传资源的保护与可持续管理提供了科学参考。