Eco- and Bioregions of Uganda

This repository contains data, statistics and maps on the hierarchical ecological zonation of Uganda using machine learning algorithms and global environmental datasets. The framework employs a systematic five-step approach integrating GIS analysis, statistical processing, and unsupervised hierarchical clustering to delineate ecological boundaries based on climate, topography, and vegetation patterns. Methodology:The eco-zonation process utilised 16 environmental parameters derived from global datasets, including WorldClim bioclimatic variables (1970-2000), SRTM elevation data, and surface water extent maps. Zonal statistics were calculated for micro-watersheds based on HydroSHEDS level-10 basins intersected with 1 km elevation contours. Hierarchical clustering analysis using Euclidean distance and agglomerative clustering identified optimal cluster numbers through silhouette analysis. Random forest models determined key environmental drivers at each hierarchical level. Validation:The framework was validated against 104 Potential Natural Vegetation (PNV) types using supervised random forest classification. Cross-validation achieved accuracies exceeding 61.1% across all hierarchical levels, with the highest performance (87.7%) at the ecoregion level. Indicator species analysis identified statistically significant vegetation associations within each ecological zone. Results:Uganda's 241,147 km² terrestrial area was stratified into five ecoregions: Central-Northern Plains (CNP), Southern Savanna-Woodland Landscapes (SSWL), Karamoja Dry Steppe (KDS), Lake Victoria-Kyoga Wetland-Woodlands (VKWW), and Montane-Alpine Ranges (MAR). These were further subdivided into 8, 12, and 20 bioregions at three successive hierarchical levels. Monthly precipitation patterns and wetland distribution emerged as primary drivers across all spatial scales. Repository Contents:The database includes processed spatial datasets in Excel and vector formats for spatial preprocessing and hierarchical clustering, ecological validation algorithms, and Excel spreadsheets summarising zonal statistics and final classifications. All materials enable full reproduction of the eco-zonation procedure for Uganda's river landscapes.