The backbone of benthic marine monitoring programs is the biological component, traditionally the macrofauna inventory. Such macrofauna-based environmental impact assessments (EIA), however, are very time consuming and expensive. To overcome these shortcomings, we used environmental metabarcoding to test the potential of protists as bioindicators in EIAs.
We evaluated benthic bacterial communities as bioindicators in environmental impact assessments of salmon aquaculture, a rapidly growing sector of seafood industry. Sediment samples (n=72) were collected from below salmon cages towards distant reference sites. Bacterial community profiles inferred from DNA metabarcodes were compared to reference data from standard macrofauna biomonitoring surveys of the same samples.
Mercury (Hg) is a highly toxic element for living organisms and is known to bioaccumulate and biomagnify. Here, we analyze the response of benthic foraminifera communities cultured in mesocosm and exposed to different concentrations of Hg. Standard morphological analyses and environmental DNA metabarcoding show evidence that Hg pollution has detrimental effects on benthic foraminifera.
At present, environmental impacts from offshore oil and gas activities are partly determined by measuring changes in macrofauna diversity. Morphological identification of macrofauna is time-consuming, expensive and dependent on taxonomic expertise. In this study, we evaluated the applicability of using foraminiferal-specific metabarcoding for routine monitoring.
The rapid growth of the salmon industry necessitates the development of fast and accurate tools to assess its environmental impact. Macrobenthic monitoring is commonly used to measure the impact of organic enrichment associated with salmon farm activities. However, classical benthic monitoring can hardly answer the rapidly growing demand because the morphological identification of macro-invertebrates is time-consuming, expensive and requires taxonomic expertise.
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.
Environmental diversity surveys are crucial for the bioassessment of anthropogenic impacts on marine ecosystems. Traditional benthic monitoring relying on morphotaxonomic inventories of macrofaunal communities is expensive, time-consuming and expertise-demanding. High-throughput sequencing of environmental DNA barcodes (metabarcoding) offers an alternative to describe biological communities.
Although protists are critical components of marine ecosystems, they are still poorly characterized. Here we analysed the taxonomic diversity of planktonic and benthic protist communities collected in six distant European coastal sites. Environmental deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) from three size fractions (pico-, nano- and micro/mesoplankton), as well as from dissolved DNA and surface sediments were used as templates for tag pyrosequencing of the V4 region of the 18S ribosomal DNA.
Recent developments in DNA barcoding and environmental genomics based on next-generation sequencing technologies offer a new avenue for exploring the diversity of life in the oceans. These techniques can be applied to any type of marine sample (water, sediment, stomach contents) and can focus on a specific group of organisms or provide data on global biodiversity. They can be used to detect only metabolically active organisms (RNA) or to follow long-term changes by analysing DNA preserved in the environment.
The measurement of species diversity represents a powerful tool for assessing the impacts of human activities on marine ecosystems. Traditionally, the impact of fish farming on the coastal environment is evaluated by monitoring the dynamics of macrobenthic infaunal populations. However, taxonomic sorting and morphology-based identification of the macrobenthos demand highly trained specialists and are extremely time-consuming and costly, making it unsuitable for large-scale biomonitoring efforts involving numerous samples.