geoSABINA: Species distribution models (SDMs): Tree species

This dataset provides information on the current and future potential distribution of trees in peninsular Spain, predicted using species distribution models (SDMs). For each species, the SDMs were projected under current (1990-2010) and four future (2071-2100) climate scenarios. Models were generated with the R package sabinaNSDM using a spatially-nested hierarchical (NSDM) and ensemble approach combining two scales (global and regional) and three statistical algorithms: generalized linear models, gradient boosted machine, and random forests. Model training utilized tree species occurrence data alongside environmental variables from the geoSABINA dataset. The SDMs employed two spatially-nested hierarchical modeling (NSDM) strategies: the covariate strategy and multiply strategy. This dataset includes both continuous suitability maps and binary presence-absence maps [derived from the suitability maps using thresholds based on True Skill Statistic (bin.TSS.tif files) and the Receiver Operating Characteristic (bin.ROC.tif) curve]. Additionally, uncertainty maps  (EMcv.tif files) are provided. This dataset comprises a total of 2,835 raster layers in TIFF format, with a spatial resolution of 250 x 250 meter. Model thresholds and accuracy values are provided in the directory “values”. A detailed list of available layers is provided in data_table_sdms_trees.csv, which includes information on the category, dataset, description, resolution, time period, and path.

Raster information

• Resolution: 250 m
• Extent: -75888.32, 1031611.68, 3977269.52, 4870519.52 (xmin, xmax, ymin, ymax)
• CRS: WGS 84 / UTM Zone 30N (EPSG:32630)

References: The references in this list should be added to any publication using these data:

• Goicolea, T., Morales-Barbero, J., García-Viñas, J.I, Gastón, A., Aroca-Fernández, M.J., Calleja, J.A., Moren, J.C. , Ramos-Gutiérrez, I., Rodríguez, M.A., Lima, H., Broennimann, O., Guisan, A, Adde, A., Pérez-Latorre, A.V., G. Mateo, R. (2025) Scientific Data.
• Goicolea, T., Adde, A., Broennimann, O., García-Viñas, J.I., Gastón, A., Aroca-Fernández, M.J. et al. (2024). Spatially-Nested Hierarchical Species Distribution Models to Overcome Niche Truncation in National-Scale Studies. Ecography. https://doi.org/10.1111/ecog.07328