Merging two eDNA metabarcoding approaches and citizen-science-based sampling to facilitate fish community monitoring along vast Sub-Saharan coastlines

Abstract

The coastline of Sub-Saharan Africa hosts highly diverse fish communities of great conservation value, which are also key resources for local livelihoods. However, many costal ecosystems are threatened by overexploitation and their conservation state is frequently unknown due to their vast spatial extent and limited monitoring budgets. Here, we evaluated the potential of citizen science-based eDNA surveys to alleviate such chronic data deficiencies and assessed fish communities in Mozambique using two 12S metabarcoding primer sets. Samples were either collected by scientific personnel or trained community members and results from the two metabarcoding primers were combined using a new data merging approach. Irrespective of the background of sampling personnel, a high average fish species richness was recorded (38 ± 20 OTUs per sample). Individual sections of the coastline largely differed in the occurrence of threatened and commercially important species, highlighting the need for regionally differentiated management strategies. A detailed comparison of the two applied primer sets revealed an important trade-off in primer choice with MiFish primers amplifying a higher number of species but Riaz primers performing better in the detection of threatened fish species. This trade-off could be partly resolved by applying our new data-merging approach, which was especially designed to increase the robustness of multiprimer assessments in regions with poor reference libraries. Overall, our study provides encouraging results but also highlights that eDNA-based monitoring will require further improvements of, for example, reference databases and local analytical infrastructure to facilitate routine applications in Sub-Saharan Africa.