Salmon farming is one of the most widespread activities in marine aquaculture. Salmonids fishes, along with carp, are the two most important fish groups in aquaculture. The aquaculture of salmonids is likely worth more than US$11 billion. However, the farming has considerable impact on the environment through factors such as nutrient enrichment due to the accumulation of waste food and faecal matter, as well as the ecotoxic effects of discharged medicines and antifouling compounds.
The impact of such farms on the coastal environment is traditionally assessed by monitoring some of the smaller species found in marine sediment samples collected at specific distances from farming sites. Visual identification of these animals under a microscope is time consuming and very expensive. It also requires highly-trained taxonomists, which renders this method unsuitable for any large-scale use.
A team led by Jan Pawlowski of the Faculty of Science of the University of Geneva in Switzerland, analysed this type of sediment using DNA Barcoding. Their target organisms are foraminifera because they provide well-established biomarkers of pollutions in the marine environment. Moreover, they possess the attributes of a reliable bioindicator, namely ubiquity, short life and reproductive cycles, and sensitivity to local abiotic conditions, making them highly responsive to environmental perturbations such as organic matter enrichment and physical disturbance. Previous studies showed that foraminiferal communities rapidly change under organic pollution exposures associated with fish farming . They also represent good indicators of the impact of offshore drilling activities and heavy metal pollution, as well as are sensitive to anoxia . However, all these studies have been restricted to the morphological identification and counting of hard-shelled foraminiferal species in dried sediment samples.
The researchers analysed both eDNA and RNA sequences from samples collected at various distances from two sets of salmon cages in the heart of the Scottish fjords. The goal was to estimate the foraminiferal diversity based on ribosomal sequences generated by the next generation sequencing technology which is perhaps better known as metabarcoding.
Our study revealed high variations between foraminiferal communities collected in the vicinity of fish farms and at distant locations. We found evidence for species richness decrease in impacted sites, especially visible in the RNA data. We also detected some candidate bioindicator foraminiferal species. Based on this proof-of-concept study, we conclude that NGS metabarcoding using foraminifera and other protists has potential to become a new tool for surveying the impact of aquaculture and other industrial activities in the marine environment.
This study is further proof that metabarcoding can be used for a wide range of micro- and meiofaunal taxa, some of which may turn to be much better ecological indicators than the macrofaunal species we are currently using for most assessments.