The Sub-Saharan alpine freshwater biodiversity is currently impacted by human settlements, climate change, agriculture, and mining activities. Because of the limited biodiversity studies in the region, a better understanding is needed of the important environmental variables affecting macroinvertebrate assemblages. In this paper, macroinvertebrate diversity responses to 18 environmental variables were studied at 30 sites along unique Rwenzori rivers at the equator in Uganda. We hypothesized that anthropogenic disturbance and local environmental variables affect macroinvertebrate diversity, irrespective of altitudinal gradients. Based on altitude and climate, the sites were subdivided into three altitude groups consisting of 10 sites each: upstream (US) 1400–1600 m.a.s.l.; midstream (MS) 1091–1399 m.a.s.l., and downstream (DS) 900–1090 m.a.s.l. A total of 44 macroinvertebrate families and 1623 individuals were identified. The macroinvertebrate diversity patterns were influenced by temperature, altitude, and latitude. Regression analysis revealed that temperature and nickel, were negative predictors of taxa richness. Nickel, which is released by mining activity, is detrimental to aquatic communities in Sub-Saharan alpine ecosystems. Significant longitudinal variation in macroinvertebrate diversity was observed between the sites, which were also affected by mineral and temperature gradients. Our study highlights the need for long-term monitoring in this region to detect and reduce the threats to river biodiversity from anthropogenic activity.

The Rwenzori region in Uganda, a global biodiversity hotspot, is currently undergoing exponential economic and population growth, which puts continuous stress on its freshwater ecosystems. In Sub-Saharan Africa, biomonitoring campaigns using region-specific biotic indices is limited, particularly in Uganda. In this research, we present the Rwenzori Score (RS), a new macroinvertebrate-based biotic index developed to specifically assess the aquatic health of Rwenzori streams and rivers. We collected and measured both biological and physicochemical variables and identified 34,202 macroinvertebrates, belonging to 64 different taxa. The RS was developed in two steps. First, using canonical ordination, we identified chemical variables that correlated significantly with gradients in macroinvertebrate assemblage distribution and diversity. Second, based on selected variables and weighted averages, we determined specific family indicator values and assigned pollution tolerance values (varying from 1: tolerant; to 10: sensitive) to a family. Finally, we established four water quality classes: poor, fair, good, and excellent. The RS is highly correlated with the Average Score Per Taxon System (p < 0.05), a well-known and widely used biotic index. The RS has 5 unique taxa that are not included in other regional indices. In this regard, the development of the RS is a beneficial tool for tailor-made biomonitoring that can contribute to the sustainable development of the Rwenzori stream and river basins.