The scenario narratives for the Shared Socio-economic Pathways (SSPs) 1 ‘Sustainability’, 2 ‘Middle of the Road’ and 3 ‘Regional Rivalry’, were modeled using the spatially explicit land-system model CLUMondo (v5.1). This generated projected land-use outcomes under each of these future pathways for the year 2050. The SSP2 scenario was modeled following assumptions about technologically induced yield increases over time, as well as without these assumptions, leading to a total of four potential land-use outcomes across three different socio-economic scenarios. The projected demands for arable crops, permanent crops, livestock, and wood production, were provided by GLOBIOM. For SSP1, additional demands were included for wetland restoration in agricultural areas, and for the number of trees planted (please see documentation for full explanation and data sources). Additional modifications were made to SSP1 to better reflect sustainability values and environmental policies, such as capping wood production at 2030 levels. The basemap which was used across all scenarios was developed using different inputs to reflect sixteen different land classes (see: Sandström et al. 2023 ( https://doi.org/10.34894/THARMK)). The average amount of each of the goods and services supplied by each land system class was calculated for each region. The model then functioned to balance supply against demand, simulating land-use changes in response to changes in demand, but while also respecting the spatial probability of each land system's occurrence. This repository therefore contains the following: - Final land use maps (asci) for each of the four future pathways (SSP1, SSP2-no technology increases, SSP2-technology increases, SSP3). - Final land use maps (PNG) for each of the four future pathways - Documentation for each of the three scenarios - Excel containing the technological coefficients for SSP2 - Legend that can be used to visualize results in QGIS

CLUMondo, 5.1

This land system map of Europe was used as the basemap for timestep 0 in all of the scenarios.