A 3‐year plankton DNA metabarcoding survey reveals marine biodiversity patterns in Australian coastal waters

Abstract

AbstractAimTo use a long‐term collection of bulk plankton samples to test the capacity of DNA metabarcoding to characterize the spatial and seasonal patterns found within a range of zooplankton communities, and investigate links with concurrent abiotic data collected as part of Australia's Integrated Marine Observing System (IMOS) programme.LocationSamples were sourced seasonally for 3 years from nine Pan‐Australian marine sites (n = 90).MethodsHere, we apply a multi‐assay metabarcoding approach to environmental DNA extracted from bulk plankton samples. Six assays (targeting 16SrRNA and COI genes) were used to target, amplify and sequence the zooplankton diversity found within each sample. The data generated from each assay were filtered and clustered into OTUs prior to analysis. Abiotic IMOS data collected contemporaneously enabled us to explore the physical and chemical drivers of community composition.ResultsFrom over 25 million sequences, we identified in excess of 500 distinct taxa and detected clear spatial differences. We found that site and sea surface temperature are the most consistent predictors of differences between zooplankton communities. We detected endangered and invasive species such as the bryozoan Membranipora membranacea and the mollusc Maoricolpus roseus, and seasonal occurrences of species such as humpback whales (Megaptera novaeangliae). We also estimated the number of samples required to detect any significant seasonal changes. For OTU richness, this was found to be assay dependent and for OTU assemblage, a minimum of nine samples per season would be required.Main ConclusionOur results demonstrate the ability of DNA to capture and map zooplankton community changes in response to seasonal and spatial stressors and provide vital evidence to environmental stakeholders. We confirm that a metabarcoding method offers a practical opportunity for an ecosystem‐wide approach to long‐term biomonitoring and understanding marine biomes where morphological analysis is not feasible.