Effective biomonitoring is critical for driving management outcomes that ensure long‐term sustainability of the marine environment. In recent years, environmental DNA (eDNA), coupled with metabarcoding methodologies, has emerged as a promising tool for generating biotic surveys of marine ecosystems, including those under anthropogenic pressure. However, more empirical data are needed on how to best implement eDNA field sampling approaches to maximize their utility for each specific application. The effect of the substrate chosen for eDNA sampling on the diversity of marine taxa detected by DNA metabarcoding has not yet been systematically analysed, despite aquatic systems being those most commonly targeted for eDNA studies. We investigated the effect of four commonly used eDNA substrates to explore taxonomic diversity: (a) surface water, (b) marine sediment, (c) settlement plates and (d) planktonic tows. With a focus on coastal ports, 332 eDNA samples from Australia (Indian and Southern oceans) and Kazakhstan (Caspian Sea) were collected and analysed by multi‐assay DNA metabarcoding. Across study locations, between 30% and 52% of eukaryotic families detected were unique to a particular substrate and <6% of families were found in all four substrates. Taxonomic composition varied significantly depending on the substrate sampled implying that the suitability (and bias) of an eDNA substrate will depend on the focal taxa. These findings demonstrate that single substrate eDNA metabarcoding likely underestimates the total eukaryotic diversity. Future eDNA experimental design should consider incorporating multiple substrates or select substrate(s) best suited to the specific detection of target taxa.

Fish biodiversity management relies on an accurate understanding of species identity. Biomonitoring of marine fishes conventionally involves observational identification and counts of species using an assortment of techniques including fishing, trapping, baited or unbaited remote underwater video, diver-operated stereo-video, or underwater visual census. Each biomonitoring technique has strengths and weaknesses, but all rely on expertise in fish taxonomy or, at a minimum, observers skilled in fish identification (Harvey

Environmental DNA (eDNA) metabarcoding is a sensitive and widely used approach for species detection and biodiversity assessment. The most common eDNA collection method in aquatic systems is actively filtering water through a membrane, which is time consuming and requires specialized equipment. Ecological studies investigating species abundance or distribution often require more samples than can be practically collected with current filtration methods. Here we demonstrate how eDNA can be passively collected in both tropical and temperate marine systems by directly submerging filter membranes (positively charged nylon and non-charged cellulose ester) in the water column. Using a universal fish metabarcoding assay, we show that passive eDNA collection can detect fish as effectively as active eDNA filtration methods in temperate systems and can also provide similar estimates of total fish biodiversity. Furthermore, passive eDNA collection enables greater levels of biological sampling, which increases the range of ecological questions that eDNA metabarcoding can address.

Metabarcoding of environmental DNA (eDNA) when coupled with high throughput sequencing is revolutionising the way biodiversity can be monitored across a wide range of applications. However, the large number of tools deployed in downstream bioinformatic analyses often places a challenge in configuration and maintenance of a workflow, and consequently limits the research reproducibility. Furthermore, scalability needs to be considered to handle the growing amount of data due to increase in sequence output and the scale of project. Here, we describe eDNAFlow, a fully automated workflow that employs a number of state-of-the-art applications to process eDNA data from raw sequences (single-end or paired-end) to generation of curated and noncurated zero-radius operational taxonomic units (ZOTUs) and their abundance tables. This pipeline is based on Nextflow and Singularity which enable a scalable, portable and reproducible workflow using software containers on a local computer, clouds and high-performance computing (HPC) clusters. Finally, we present an in-house Python script to assign taxonomy to ZOTUs based on user specified thresholds for assigning lowest common ancestor (LCA). We demonstrate the utility and efficiency of the pipeline using an example of a published coral diversity biomonitoring study. Our results were congruent with the aforementioned study. The scalability of the pipeline is also demonstrated through analysis of a large data set containing 154 samples. To our knowledge, this is the first automated bioinformatic pipeline for eDNA analysis using two powerful tools: Nextflow and Singularity. This pipeline addresses two major challenges in the analysis of eDNA data; scalability and reproducibility.

Advances in high-throughput sequencing (HTS) are revolutionizing monitoring in marine environments by enabling rapid, accurate and holistic detection of species within complex biological samples. Research institutions worldwide increasingly employ HTS methods for biodiversity assessments. However, variance in laboratory procedures, analytical workflows and bioinformatic pipelines impede the transferability and comparability of results across research groups. An international experiment was conducted to assess the consistency of metabarcoding results derived from identical samples and primer sets using varying laboratory procedures. Homogenized biofouling samples collected from four coastal locations (