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