Dataset for: Predicted climate and rangeland vegetation changes: impacts on pastoral systems from eleven Mediterranean case studies

This dataset supports the study “Modelling climate change impacts on Mediterranean rangelands and pastoral systems using WorldClim and MaxEnt”, developed within the PRIMA project “Innovative Models for Sustainable Future of Mediterranean Pastoral Systems” (PASTINNOVA). The dataset contains all the input data required to reproduce the modelling workflow applied across eleven Mediterranean case studies. Specifically, it includes: (i) occurrence points derived from classified spectral vegetation indices (NDVI or SAVI), representing proxies of vegetation productivity and forage resource suitability; (ii) original Landsat-derived vegetation index rasters; and (iii) a set of 33 environmental raster variables, including 19 bioclimatic variables from WorldClim, along with soil and topographic variables. Climate data are provided as both baseline (1990) conditions, directly obtained from WorldClim, and future projections under SSP245 and SSP585 scenarios. Future climate layers are derived from the mean ensemble of three Global Circulation Models (CMCC-ESM2, EC-Earth3-Veg, and HadGEM3-GC31-LL) for multiple time slices (2030, 2050, 2070, 2090). The dataset is organised by case study and scenario to facilitate reproducibility of the MaxEnt modelling procedure. Refer to 'README.txt' for brief istructions, however a detailed description of the methodological framework, including climate trend analysis, environmental variable preprocessing, vegetation index derivation, and model configuration, is provided in the associated manuscript and supplementary materials. This dataset is intended to support reproducible research and to enable further ecological modelling and comparative analyses of Mediterranean pastoral systems under climate change. The dataset integrates case study data provided by partners of the PRIMA PASTINNOVA project, who contributed local expertise and knowledge of the analysed pastoral systems.