Designing Environmental DNA Biotic Surveys for the Deep Seafloor

Olivier Laroche1,2, Oliver Kersten3, Craig R Smith4 and Erica Goetze4, (1)Cawthron Institute, Nelson, New Zealand, (2)Institute of Marine Research, Benthic Habitats and Shellfish, Tromso, Norway, (3)University of Oslo, Centre for Ecological and Evolutionary Synthesis, Oslo, Norway, (4)University of Hawai'i at Mānoa, Department of Oceanography, Honolulu, United States
Abstract:
Diverse and remote deep-sea communities are critically under-sampled and increasingly threatened by anthropogenic impacts. Environmental DNA (eDNA) metabarcoding could facilitate rapid and comprehensive biotic surveys in the deep ocean, yet many aspects of the sources, transport and residence times of eDNA in the deep sea are still poorly understood. In order to examine the influence of the water column on benthic eDNA surveys, we investigated the occurrence of pelagic eDNA across: (1) deep-sea habitat types, including abyssal plains and seamounts, (2) benthic sample types, including polymetallic nodules, sediment, and seawater within the benthic boundary layer (BBL), and (3) sediment depth horizons. Pelagic eDNA, both in terms of reads and amplicon sequence variants (ASVs), was minimal within sediment and nodule samples (< 2%), and is unlikely to affect benthic surveys that monitor resident organisms at the deep seafloor. However, pelagic eDNA was substantial within the BBL (up to 38 % ASVs, 91% reads), deriving from both deep pelagic residents as well as legacy eDNA that is sourced from the high biomass upper ocean and sinks as detrital particulate organic matter (POM) into the abyss. eDNA retention in the benthos appeared to be influenced by current-topography interactions, with pelagic eDNA comprising a larger fraction of seafloor eDNA in abyssal plain than in seamount habitats. Study-wide, our estimated metazoan sampling coverage ranged from 40% to 74%, despite relatively large sample size. Future deep-sea eDNA surveys should aim to understand oceanographic influences on eDNA residence times and observed community diversity, consider habitat heterogeneity at a range of spatial scales, and process large amounts of material per sample.