Introduction
Environmental DNA (eDNA) metabarcoding is emerging as a scalable, cost-effective tool for monitoring environmental impacts in salmon farming. While it offers advantages over traditional macrofaunal assessments, such as faster processing and broader biodiversity detection, uncertainty around protocol standardization, limits its operational use. Equally important is understanding how much variation naturally occurs between replicate sediment samples. To confidently implement eDNA in routine monitoring, we need to distinguish between biological variability and methodological noise, and ensure that protocol choices do not overshadow meaningful ecological signals.
Materials and Methods
Sediment samples were collected from coastal salmon farms in western Scotland. Replicates were taken to assess within-site biological variability. Two different PCR protocols (primarily differing in DNA polymerase) were applied to the same DNA extracts to evaluate the effects of methodological variation on diversity metrics and community composition. Microbial communities were characterized via 16S rRNA gene sequencing. The results were compared against traditional macrofaunal assessments to evaluate eDNA’s stability and suitability for environmental monitoring.
Results
The two PCR protocols used in this study yielded statistically significant differences in bacterial community composition, indicating that protocol choice can influence eDNA-based assessments. Furthermore, the comparison of replicate samples showed that within-site variability in bacterial eDNA communities was comparable to that of macrofaunal assemblages collected according to compliance monitoring protocol (~25% variability in both cases), supporting the reliability of eDNA for detecting spatial patterns in benthic environments.
Conclusion
Despite some sensitivity to laboratory protocols, eDNA-based biomonitoring offers reliable results with variability levels comparable to traditional methods. With protocol harmonization, eDNA has strong potential to serve as a scalable, cost-effective tool for routine environmental monitoring in the salmon aquaculture industry.