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Large‐scale eDNA metabarcoding survey reveals marine biogeographic break and transitions over tropical north‐western Australia

Citation

West, Katrina et al. (2021), Large‐scale eDNA metabarcoding survey reveals marine biogeographic break and transitions over tropical north‐western Australia, Dryad, Dataset, https://doi.org/10.5061/dryad.8kprr4xmm

Abstract

Aim: Environmental DNA (eDNA) metabarcoding has demonstrated its applicability as a highly sensitive biomonitoring tool across small spatial and temporal scales in marine ecosystems. However, it has rarely been tested across large spatial scales, or biogeographical barriers. Here, we scale up marine eDNA metabarcoding, test its ability to detect a major marine biogeographic break, and evaluate its use as a regional biomonitoring tool in Australia.

Location: North-western Australia (NWA)

Methods: We applied metabarcoding assays targeting the mitochondrial 16S rRNA and CO1 genes to 284 surface seawater eDNA samples collected from 71 mid-shelf, inshore, coastal and nearshore estuarine sites over 700 km of the NWA coastline.

Results: Metabarcoding detected a wide range of bony fish (404 taxa), elasmobranchs (44) and aquatic reptiles (5). We detected bioregional and depth differentiation within inshore bony fish communities. These findings support the presence of a marine biogeographic break, which is purported to occur in the vicinity of Cape Leveque, demarcating the border between the Kimberley and Canning bioregions. Inshore bony fish and elasmobranch communities, as well as coastal bony assemblages, were additionally found to differ between the South and North Kimberley regions suggesting previously unrecognised subregional differentiation among these taxa. The overall compositional data has been used to update distribution information for a number of endangered, elusive and data-deficient taxa, including sawfish (family: Pristidae), northern river shark (Glyphis garricki) and wedgefish (genus: Rhynchobatus).

Main conclusions: eDNA metabarcoding demonstrated a high level of sensitivity that was able to discern fine-scale patterns across the large-scale, remote and oceanographically complex region of North-western Australia. Importantly, this study highlights the potential of integrating broad-scale eDNA metabarcoding alongside other baseline surveys and long-term monitoring approaches, which are crucial for the sustainable management and conservation of marine biodiversity in this unique marine region.

Methods

Four one-litre water replicates were sampled from 71 sites across the Canning/Kimberley bioregions in September 2017 and July/September 2018, totaling 284 samples over 700 km of coastline. Samples were taken on a transect line traversing a purported biogeographic break and more widely across the Kimberley region in mid-shelf, inshore, coastal and nearshore estuarine habitats. Samples were immediately stored on ice and were individually filtered across Pall 0.45mm Supor® polyethersulfone membranes using a Pall Sentino® Microbiology pump (Pall Corporation, Port Washington, USA) within five hours of collection.

DNA was extracted from half of the filter membranes using a DNeasy Blood and Tissue Kit (Qiagen; Venlo, Netherlands) with modifications. DNA was amplified using three previously published PCR assays (16S and COI) to target bony fish, elasmobranchs and aquatic reptiles from our mixed seawater samples (see Diversity and Distributions publication for more information). 

Libraries were sequenced on 300 cycle (for unidirectional sequencing of the 16S & COI amplicons) MiSeq® V2 Standard Flow Cells on an Illumina MiSeq platform (Illumina, San Diego, USA), housed in the TrEnD Laboratory at Curtin University, Western Australia. Sequencing reads were demultiplexed and quality filtered in OBITools (v1.2.9; Boyer et al., 2014) and in R (v3.5.3; RStudio Team, 2015) using the DADA2 (v1.10.1) bioinformatics package (Callahan et al., 2016).

Usage Notes

We have uploaded demultiplexed (unfiltered) data for public use. This is in a fastq format and corresponds to sample IDs (see Diversity and Distributions publication for more information). We have also uploaded a taxonomic (read abundance) matrix that has gone through our quality filtering (DADA2) pipeline and has been blasted against NCBI's GenBank (2019). This can be directly used for multivariate statistical analyses.

Funding

Australian Research Council, Award: LP160100839