Accurate assessment of the impact of salmon farming on benthic sediment enrichment using foraminiferal metabarcoding

• Published in: Marine pollution bulletin 2015-11, Vol.100 (1), p.370-382
• Main Authors: Pochon, X., Wood, S.A., Keeley, N.B., Lejzerowicz, F., Esling, P., Drew, J., Pawlowski, J.
• Format: Article
• Language: English
• Subjects: Animals; Aquaculture; Benthic ecology; Biodiversity; Biomonitoring; Ecology, environment; Ecosystem; Environmental Monitoring - methods; Environmental Sciences; Foraminifera; Foraminifera - classification; Foraminifera - genetics; Geologic Sediments - chemistry; High-Throughput Nucleotide Sequencing; High-throughput sequencing; Life Sciences; Marine; Metabarcoding; Multivariate Analysis; New Zealand; Oncorhynchus tshawytscha; Salmon
• ISSN: 0025-326X; 1879-3363
• DOI: 10.1016/j.marpolbul.2015.08.022

Assessing the environmental impact of salmon farms on benthic systems is traditionally undertaken using biotic indices derived from microscopic analyses of macrobenthic infaunal (MI) communities. In this study, we tested the applicability of using foraminiferal-specific high-throughput sequencing (HTS) metabarcoding for monitoring these habitats. Sediment samples and physico-chemical data were collected along an enrichment gradient radiating out from three Chinook salmon (Oncorhynchus tshawytscha) farms in New Zealand. HTS of environmental DNA and RNA (eDNA/eRNA) resulted in 1,875,300 sequences that clustered into 349 Operational Taxonomic Units. Strong correlations were observed among various biotic indices calculated from MI data and normalized fourth-root transformed HTS data. Correlations were stronger using eRNA compared to eDNA data. Quantile regression spline analyses identified 12 key foraminiferal taxa that have potential to be used as bioindicator species. This study demonstrates the huge potential for using this method for biomonitoring of fish-farming and other marine industrial activities. •Foraminiferal metabarcoding is a cost-effective tool for monitoring environmental impacts of fish farming.•Metabarcoding data correlate strongly with traditional biotic indices derived from macrobenthic infaunal community data.•Correlations are stronger using eRNA compared to eDNA data.•Quantile regression spline analysis identifies 12 key foraminiferal taxa that have potential to be used as bioindicator species.