Rwenzori Score (RS): A Benthic Macroinvertebrate Index for Biomonitoring Rivers and Streams in the Rwenzori Region, Uganda

Abstract

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.

Towards a global river health assessment framework

“…The robustness and ease of use of these systems led to the creation of multiple similar systems in other regions, such as the Spanish Biological Monitoring Water Quality (BMWQ) (Camargo, 1993), Wisconsin Biotic Index (BI) and Family Biotic Index (FBI) (Hilsenhoff, 1987;Hilsenhoff et al, 1988), Australian Stream Invertebrate Grade Number Average Level (SIGNAL) scoring system (Chessman, 1995(Chessman, , 2003, New Zealand's Macroinvertebrate Community Index (MCI) (Stark, 1985(Stark, , 1998, and South African Scoring System (SASS) (Dickens and Graham, 2002). The later was since adapted to various other African countries as the Namibian Scoring System (NARS) (Palmer and Taylor, 2004), Tanzanian River Scoring System (TARISS) (Kaaya, Day and Dallas, 2015), Zambian Invertebrate Scoring System (ZISS) (Dallas et al, 2018), and Rwenzori Score (RI) (Musonge et al, 2020). Also common are Periphyton (Diatom)-based Specific Pollution sensitivity Indices, SPI (e.g., Karthick et al, 2010) that claim to provide high-resolution indication of sources and types of pollution.…”

Chemical pollution as a driver of biodiversity loss and potential deterioration of ecosystem services in Eastern Africa: A critical review

“…A batch of studies has addressed the impact of chemical pollution in this area, especially in freshwater ecosystems. In 2019/2020, Musonge et al 38,39 developed macro-invertebrate-based indexes to investigate the chemical pollution patterns in a biodiversity hotspot in Uganda, the Rwenzori region. Their studies found evidence of pollution according to the different abundances of the macro-invertebrates compared to reference sites.…”

Bioassessment of multiple stressors in Afrotropical rivers: Evaluating the performance of a macroinvertebrate-based index of biotic integrity, diversity, and regional biotic indices

“…Although limited in comparison to other continents (e.g., Herman and Nejadhashemi, 2015;Ruaro et al, 2020;Feio et al, 2021;Vadas et al, 2022), several studies have used biological communities to study the condition of streams and rivers in Africa. These studies use heterogeneity (richness) and diversity indices (Odume and Muller, 2011;Olawusi-Peters and Ajibare, 2014;Soko and Gyedu-Ababio, 2015;Arimoro and Keke, 2017;Masese et al, 2020), regional or countryspecific biotic indices (Dickens and Graham, 2002;Aschalew and Moog, 2015;Kaaya et al, 2015;Dallas et al, 2018;Musonge et al, 2020) and multimetric indices (Odume et al, 2012;Mereta et al, 2013;Lakew and Moog, 2015;Edegbene 2021;Edegbene et al, 2019;Tampo et al, 2020;Edegbene et al, 2022;Kaboré et al, 2022). Diversity indices provide a numerical measure of species diversity in a community based on composition and structure other than the number of species, while richness or heterogeneity indices are an indicator of the relative diversity of species in a community (Mouchet et al, 2010;Magurran, 2013).…”

“…Similarly, while some MMIs have been tested and validated for monitoring of some of the African aquatic ecosystems (e.g., Raburu and Masese, 2012;Moges et al, 2016;Tampo et al, 2020;Achieng et al, 2021;Kaboré et al, 2022), some have been used without validation, including Toham and Teugels (1999), Masese et al (2009a), Aura et al (2010), Alemu et al (2018) and Aura et al (2021). This means that these biotic indices and MMIs must be tested for performance and validated before being used widely to assess the ecological conditions of streams and rivers across the African continent (e.g., Bere and Nyamupingidza, 2014;Musonge et al, 2020).…”