ARBEC III · 23–27 Nov 2026 · Nairobi

eDNA METABARCODING FOR FISH IN LAKE MALAWI

TRK6_025Oral presentationTrack 6 · Climate Resilience & Ecosystem Health

Sullamithe Mercy Manduwa, Heals Kabowa, Dalitso Kafumbata, Bosco Rusuwa, Joel Elkin, Bettina Fischer, Moritz Blumer, Richard Durbin

University of Malawi · Malawi

In the programme

Abstract

The fish species of Lake Malawi, one of the most diverse freshwater ecosystems globally with over 800 endemic cichlid species, are under ecological threat and require active monitoring and management. Traditional trawling-based monitoring methods provide limited taxonomic resolution and spatial coverage for nearshore and depth-restricted taxa, in addition to being time-consuming, invasive, and expensive. Environmental DNA (eDNA) metabarcoding offers a cost-effective, reliable, and non-invasive approach for African Great Lakes biomonitoring. To develop eDNA protocols for Lake Malawi I assessed the performance and taxonomic resolution of a universal mitochondrial primer pair (MiFish, 12S rRNA) and three cichlid-specific nuclear primer pairs; Deep-Shallow Utaka (DSU), Diplotaxodon (Di), and Mbuna-Rhamphochromis (MR) designed using whole-genome datasets from 1,375 Lake Malawi cichlids. Given the rapid radiation of cichlids, I collected 143 water samples across 45 lake sites. MiFish successfully recovered broad fish community profiles and detected both pelagic and littoral taxa, including rare and endemic species not always seen in the BIOMASS survey. While it reliably distinguished cichlids from non-cichlid taxa, Lake Malawi cichlid species lack sufficient mitochondrial variation to resolve using the MiFish amplicon. In contrast, the cichlid-specific nuclear primers exhibited low and inconsistent amplification. MR and DSU produced sparse and variable reads, and Di failed to yield consistent signals across replicates. While providing promise for the future, these results leave room for improved marker design and standardized protocols across laboratories to enhance taxon-level discrimination. Overall, this study advances the development of sustainable and scalable molecular monitoring frameworks for freshwater ecosystems.

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