Baseline and Future (Shared Socio-economic Pathways 1-2.6 and 3-7.0 for the 2050s) Climate Suitability Atlas for 290 Useful Tree Species for Rwanda

Climate suitability scores were calculated for 290 useful tree species included in the Know Some Useful Trees and Shrubs for Agricultural and Pastoral Communities of Rwanda or in the list of native useful tree species obtained from the GlobalUsefulNativeTrees database (Kindt et al. 2023). After compiling the list of species, we checked for afterwards for the availability of globally observed environmental ranges for these species from the TreeGOER database (Kindt 2023). Species with fewer than 10 observations in TreeGOER were excluded. The climate scoring system is the same that is used in the GlobalUsefulNativeTrees database: Score = 3 means that in 'environmental space' the planting site occurs within the 25% - 75% species's range (as documented in the TreeGOER) for all variables Score = 2 corresponds to the 5% - 95% species's range for all variables Score = 1 corresponds to the 0% - 100% species's range for all variables Score = 0.5 means that the planting site occurs outside the 0% - 100% species's range for some of the variables, but for heat-related bioclimatic variables (used to produce the maps shown here: BIO01, monthCountByTemp10, growingDegDays5, BIO05 and BIO06) to be below the minimum (‘too cold but not too hot’) and for water-related bioclimatic variables (used here: BIO12, climaticMoistureIndex, BIO16, BIO17 and MCWD) to be above the maximum (‘too wet but not too dry’) Score = 0 means that the planting site occurs outside the 0% - 100% species's range for some of the variables Score = -1 means that the species is not documented by TreeGOER Bioclimatic conditions for future climates (2050s: 2041-2060) correspond to the median values from 24 Global Climate Models (GCMs) for Shared Socio-Economic Pathway (SSP) 1-2.6 and from 22 GCMs for SSP 3-7.0. Future and baseline bioclimatic layers were processed from raster layers obtained from WorldClim 2.1 at resolutions of 2.5 arc-minutes. Similar methods were used to obtain median values for the ClimateForecasts and CitiesGOER databases. Calculations of climate scores were made with similar scripting pipelines in the R statistical environment as documented here: https://rpubs.com/Roeland-KINDT/1168650. These scripts use similar calculations methods as those used for the global case studies of the TreeGOER manuscript (Kindt 2023), and used internally in the GlobalUsefulNativeTrees online database. Interested readers should especially refer to the manuscript for further details on methods used and their justification. The maps include a red polygon showing the country outline of Rwanda obtained from the GADM database. References Nduwayezu, J.B., Ruffo, C.K., Minani, V., Munyaneza, E. and Nshutiyayesu, S. 2009. Know Some Useful Trees and Shrubs for Agricultural and Pastoral Communities of Rwanda. Institute of Scientific and Technological Research, Butare, Rwanda. Kindt, R. (2023). TreeGOER: A database with globally observed environmental ranges for 48,129 tree species. Global Change Biology, 00, 1–16. https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914. Kindt, R. (2024). TreeGOER: Tree Globally Observed Environmental Ranges (2024.07) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.13132613 Kindt, R., Graudal, L., Lillesø, JP.B. et al. (2023). GlobalUsefulNativeTrees, a database documenting 14,014 tree species, supports synergies between biodiversity recovery and local livelihoods in landscape restoration. Sci Rep 13, 12640. https://doi.org/10.1038/s41598-023-39552-1 Kindt, R. (2023). CitiesGOER: Globally Observed Environmental Data for 52,602 Cities with a Population ≥ 5000 (2023.10) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10004594 Kindt, R. (2024). ClimateForecasts: Globally Observed Environmental Data for 15,504 Weather Station Locations (2024.07) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.12679832 Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1‐km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302–4315. https://doi.org/10.1002/joc.5086 Title, P. O., & Bemmels, J. B. (2018). ENVIREM: An expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography, 41(2), 291–307. https://doi.org/10.1111/ecog.02880 Funding The development of this climate change atlas for Rwanda was supported by the Green Climate Fund through the IUCN-led Transforming the Eastern Province of Rwanda through Adaptation project, by the Bezos Earth Fund to the Quality Tree Seed for Africa in Kenya and Rwanda project and by the German International Climate Initiative (IKI) to the regional tree seed programme on The Right Tree for the Right Place for the Right Purpose in Africa.