Abstract
The deep ocean is the largest biome on Earth and faces increasing anthropogenic pressures from climate change and commercial fisheries. Our ability to sustainably manage this expansive habitat is impeded by our poor understanding of its inhabitants and by the difficulties in surveying and monitoring these areas. Environmental DNA (eDNA) metabarcoding has great potential to improve our understanding of this region and to facilitate monitoring across a broad range of taxa. Here, we evaluate two eDNA sampling protocols and seven primer sets for elucidating fish diversity from deep sea water samples. We found that deep sea water samples (> 1400 m depth) had significantly lower DNA concentrations than surface or mid-depth samples necessitating a refined protocol with a larger sampling volume. We recovered significantly more DNA in large volume water samples (1.5 L) filtered at sea compared to small volume samples (250 mL) held for lab filtration. Furthermore, the number of unique sequences (exact sequence variants; ESVs) recovered per sample was higher in large volume samples. Since the number of ESVs recovered from large volume samples was less variable and consistently high, we recommend the larger volumes when sampling water from the deep ocean. We also identified three primer sets which detected the most fish taxa but recommend using multiple markers due the variability in detection probabilities and taxonomic resolution among fishes for each primer set. Overall, fish diversity results obtained from metabarcoding were comparable to conventional survey methods. While eDNA sampling and processing need be optimized for this unique environment, the results of this study demonstrate that eDNA metabarcoding can facilitate biodiversity surveys in the deep ocean, require less dedicated survey effort per unit identification, and are capable of simultaneously providing valuable information on other taxonomic groups.
Highlights
The deep ocean is the largest biome on Earth by volume and one of the planet’s most understudied environments [1]
The fish species detected included several deep-water and demersal specialists, such as Bigelow’s Ray (Rajella bigelowi), Agassiz’ Slickhead (Alepocephalus agassizii), Greenland Dwarf Snailfish (Psednos groenlandicus), along with the Roundnose Grenadier (Coryphaenoides rupestris) and the Northern Wolffish (Anarhichas denticulatus), which are listed as Critically Endangered and Endangered, respectively on the IUCN Red List [39, 40]
We demonstrated a successful protocol for the detection of deep-sea fishes using Environmental DNA (eDNA) from seawater samples collected at depths down to 2500 m
Summary
The deep ocean is the largest biome on Earth by volume and one of the planet’s most understudied environments [1]. Monitoring and managing the impacts of commercial fishing and climate change in this environment is difficult due to logistic constraints and the high cost of sampling such challenging environments [7]. Despite these impediments, documenting the biodiversity of this region is integral to sustainable management and ecosystem monitoring. Small nets and filtration systems can target small zooplankton and phytoplankton and autonomous video camera systems can capture a range of macrofauna [8] Each of these methods have limitations in their ability to capture a community based on morphological and behavioral selectivity as well as taxonomic resolution. The need to employ multiple sampling methods to assess the biodiversity of the deep sea increases the sampling effort required, complicates the interpretation of data, and thereby adds to the challenges of surveying this environment
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