High resolution maps resulting from a trend analysis conducted for the period 2000–2020 on the probability of occurrence maps prepared by Bonannella et al. (2022). For this analysis we selected the realized distribution time series layers at 30m spatial resolution for 6 out of 16 species described in the mentioned publication: Silver fir (Abies alba Mill.) European beech (Fagus sylvatica L.) Norway spruce (Picea abies L.) Black pine (Pinus nigra J. F. Arnold) Scots pine (Pinus sylvestris L.) Common oak (Quercus robur L.) The trend analysis was conducted per pixel on each of these species individually. We fitted simple OLS regression models with the probability of occurrence as the dependent variable and time as the independent variable. After the model fitting, we also calculated the t-test statistics to determine the presence of an increasing (positive) or decreasing (negative) trend or no trend at all. By combining the regression slope coefficient (β) and the p-value from the t-test statistics we assigned each pixel to one of three classes: positive: β > 0.25 AND p-value < 0.05 negative: β < −0.25 AND p-value < 0.05 no trend / stable: −0.25 ≤ β ≥ 0.25 OR p-value > 0.05 We then aggregated the resulting classes at 1km resolution maps to capture the prevalent trend in probability of occurrence over a certain area. Files are named according to the following naming convention, e.g.: veg_abies.alba_slope_30m_0..0cm_epsg3035_v1.0 with the following fields: theme: e.g. veg, species code: e.g. abies.alba, variable name: e.g. slope, resolution in meters e.g. 30m, reference depths (vertical dimension): e.g. 0..0cm, coordinate system: e.g. epsg3035, data set version: e.g. v1.0. For each species here we provide the following layers: veg_abies.alba_slope: slope coefficient (scaling factor: 10000) veg_abies.alba_pvalue: p-value (scaling factor: 1000) veg_abies.alba_pos.trends_30m: pixels classified as positive on the original maps at 30m resolution (boolean layer with range 0–100, only the two extremes values are present) veg_abies.alba_pos.trends_1km: proportion of pixels of the positive class over a 1×1 km area (range 0–100) veg_abies.alba_neg.trends_30m: pixels classified as negative on the original maps at 30m resolution (boolean layer with range 0–100, only the two extremes values are present) veg_abies.alba_neg.trends_1km: proportion of pixels of the negative class over a 1×1 km area (range 0–100) veg_abies.alba_no.trends_30m: (pixels classified as no trend / stable on the original maps at 30m resolution (boolean layer with range 0–100, only the two extremes values are present) veg_abies.alba_no.trends_1km: proportion of pixels of the no trend / stable class over a 1×1 km area (range 0–100) Files are provided as GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files are provided in QML format A publication describing, in detail, all processing steps is currently in review. See at: Bonannella, C., Parente, L., de Bruin, S. and Herold, M. (2023). Multi-decadal trend analysis and forest disturbance assessment of European tree species: concerning signs of a subtle shift, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-3288937/v1]