Dataset of Functional Traits and Genomic Data for Scots Pine Progenies (for paper entitled: Adaptive Capacity of Scots Pine Progenies Under Severe Drought Revealed Through High-Throughput Phenotyping and Genetic Analysis)

Scots pine (<i>Pinus sylvestris</i> L.) is widely distributed and harbors broad adaptive amplitude toward adverse environmental factors. Its adaptability is key for forestry, promising resilience against Europe’s climate-driven droughts. In this study, we investigated the physiological and genetic responses to drought stress in three provenances of pedigreed Scots pine seedlings from distinct upland and lowland habitats in the Czech Republic. A water deficit was induced in two-year-old, potted seedlings at the beginning of the growing season, followed by a recovery period during new shoot development. (1) We analyzed various physiological attributes and Photosystem II (PSII) parameters to detect treatment-level responses using a high-throughput phenotyping unit, including steady-state quantum yield of PSII (QY Lss), maximum quantum efficiency of PSII (QY max), non-photochemical quenching (NPQ Lss), needle chlorophyll fluorescence ratio (SFR_R), and needle temperature normalized to ambient temperature (∆T). The clear divergence in QY max, QY Lss, NPQ Lss, and ΔT suggests that drought stress significantly impacts photosynthetic efficiency and heat dissipation, with recovery occurring after rewatering. (2) To explore genetic variation in needle functional traits over time, we applied a single nucleotide polymorphism genotyping array and linear mixed models integrating estimated genomic relationships. Heritability (h²) varied widely among traits—QY max and QY Lss showed the greatest variability (0–0.37), NPQ Lss exhibited a narrower range aside from two outlier peaks, and SFR_R and ∆T displayed lower variability and lower h² values (0–0.24). Our findings provide insights into Scots pine’s adaptive capacity and address practical problems in forest management, particularly in light of changing weather patterns and climate variability. To support further research, we share the associated functional (growth-related and optically assessed) and genomic datasets used in this study in the accompanying repository, contributing to advanced optically-based early-age phenotyping to enhance forest resilience. The explanatory readme file is provided.