The full dataset includes needle functional traits and spectra measured on needle and canopy levels. The same ramets and clones sampled for needle level reflectance measurements were used for NFTs assessment. Current-year shoots were sampled and transported to the laboratory. Two complimentary needle samples were collected from each shoot. The first needle set was used for content assessment of photosynthetic pigments (chlorophyll a (chl a) and chlorophyll b (chl b); total chlorophylls (chl T); total carotenoids (car)). Needles were cut into 2-3 mm segments, and pigments were extracted in the dark at 4 °C for seven days using N-dimethylformamide (Porra et al., 1989). The content of photosynthetic pigments was determined spectrophotometrically using a Spectrophotometer (Evolution 201, Thermo Fisher Scientific, Waltham, MA, USA). According to Wellburn (1994), pigment concentrations were calculated and related to dry weight (mg of pigment per g of dry mass). The second needle set was used to assess fresh and dry weight and calculate water content as equivalent to weight reduction after drying the needles (60 °C to constant weight). Before drying, fresh needles were scanned (EPSON Perfection V600 Photo scanner with upper lamp, resolution 800 dpi, grayscale), and needle projection area and needle length were determined on binary images in ImageJ (National Institutes of Health, Bethesda, Maryland, USA). Leaf mass per area (LMA) was calculated as the dry weight of the needle sample related to the needle sample projection area (g/cm2). Leaf mass per area was used as one of the needle traits and for recalculating other needle traits (pigment and water content) to area-based values, a standard in remote sensing and spectroscopic applications. Photosynthetic pigment contents were measured in relation to dry needle mass in mg/g (e.g., chl aM for chlorophyll a per dry mass) and relation to needle area in µg/cm2 (e.g., chl aA for chlorophyll a per needle area). Water content was expressed as needle water content (NWC) in percentage and equivalent water thickness (EWT) in g/cm2, i.e., related to the needle area. In addition, the clones were genotyped on the recent 50K SNP array. The UAV-based reflectance data are in the last columns.

The full dataset includes needle functional traits and spectra measured on needle and canopy levels. The same ramets and clones sampled for needle level reflectance measurements were used for NFTs assessment. Current-year shoots were sampled and transported to the laboratory. Two complimentary needle samples were collected from each shoot. The first needle set was used for content assessment of photosynthetic pigments (chlorophyll a (chl a) and chlorophyll b (chl b); total chlorophylls (chl T); total carotenoids (car)). Needles were cut into 2-3 mm segments, and pigments were extracted in the dark at 4 °C for seven days using N-dimethylformamide (Porra et al., 1989). The content of photosynthetic pigments was determined spectrophotometrically using a Spectrophotometer (Evolution 201, Thermo Fisher Scientific, Waltham, MA, USA). According to Wellburn (1994), pigment concentrations were calculated and related to dry weight (mg of pigment per g of dry mass). The second needle set was used to assess fresh and dry weight and calculate water content as equivalent to weight reduction after drying the needles (60 °C to constant weight). Before drying, fresh needles were scanned (EPSON Perfection V600 Photo scanner with upper lamp, resolution 800 dpi, grayscale), and needle projection area and needle length were determined on binary images in ImageJ (National Institutes of Health, Bethesda, Maryland, USA). Leaf mass per area (LMA) was calculated as the dry weight of the needle sample related to the needle sample projection area (g/cm2). Leaf mass per area was used as one of the needle traits and for recalculating other needle traits (pigment and water content) to area-based values, a standard in remote sensing and spectroscopic applications. Photosynthetic pigment contents were measured in relation to dry needle mass in mg/g (e.g., chl aM for chlorophyll a per dry mass) and relation to needle area in µg/cm2 (e.g., chl aA for chlorophyll a per needle area). Water content was expressed as needle water content (NWC) in percentage and equivalent water thickness (EWT) in g/cm2, i.e., related to the needle area. In addition, the clones were genotyped on the recent 50K SNP array. The UAV-based reflectance data are in the last columns.

The filtered dataset from 50K Norway spruce SNPchip (filtration parameters: only PolyHighResolution, NoMi-norHom, MonoHighResolution categories of markers were kept, DQC: ≥ 0.82, QC call rate: ≥ 90). Genomic data of resistant individuals, referred to as the "Last Trees Standing" (LTS) and randomly selected individuals from natural regeneration within concerned sites (seedlings, young trees) and in adjacent unaffected stands (mature trees).

The filtered dataset from 50K Norway spruce SNPchip (filtration parameters: only PolyHighResolution, NoMi-norHom, MonoHighResolution categories of markers were kept, DQC: ≥ 0.82, QC call rate: ≥ 90). Genomic data of resistant individuals, referred to as the "Last Trees Standing" (LTS) and randomly selected individuals from natural regeneration within concerned sites (seedlings, young trees) and in adjacent unaffected stands (mature trees).

Half-sib progenies reflectance, pigment content and growth data.

Half-sib progenies reflectance, pigment content and growth data.

Seven complete mitochondrial genomes from Harley et al. (2016)

Seven complete mitochondrial genomes from Harley et al. (2016)

MS Excel file of supplementary tables

MS Excel file of supplementary tables