Development and preliminary validation of a multi-trophic metabarcoding biotic index for monitoring benthic organic enrichment

Abstract

Sea-based fish farms are associated with strong, benthic enrichment gradients and routine monitoring is usually required by regulation. This has traditionally been based on benthic macrofaunal communities, which is reliant on taxonomic expertise, and turn-around times can be slow, limiting opportunities for adaptive management. Environmental metabarcoding is a powerful high-throughput sequencing-based technique that can identify and quantify benthic assemblages. Previous studies have demonstrated relationships between specific taxonomic groups (e.g., bacteria, foraminifera) and anthropogenic effects. However, the absence of fixed categorical scales makes the use of data challenging for routine biomonitoring. In this study, we analysed 105 sediment samples collected over three years from three salmon farms spanning two separate bioregions. Environmental DNA and RNA (eDNA/eRNA) metabarcoding of three taxonomic groups (foraminifera, bacteria, and general eukaryotes) was undertaken in parallel with traditional macrofaunal and biochemical analyses, which were used to calculate an Enrichment Stage index for each sample. The most abundant 200–250 Operational Taxonomic Units in each taxonomic group were assessed and assigned to Eco-Groups. These bioindicator taxa were then used to develop a Metabarcoding Biotic Index for each taxonomic group individually and in combination (multi-trophic Metabarcoding Biotic Index). The weakest relationship was between the foraminiferal Metabarcoding Biotic Index and Enrichment Stage (eDNA/eRNA, R2 = 0.731–0.850), whereas strong correspondence was obtained between the multi-trophic Metabarcoding Biotic Index and Enrichment Stage, or when just bacteria and eukaryotes data were combined (eDNA/RNA, R2 > 0.900). The strong relationships obtained between the multi-trophic Metabarcoding Biotic Index and Enrichment Stage confirms that this method has the potential to complement or even replace current fish farm biomonitoring techniques in the near future.