No abstract

Targeted species‐specific and community‐wide molecular diagnostics tools are being used with increasing frequency to detect invasive or rare species. Few studies have compared the sensitivity and specificity of these approaches. In the present study environmental DNA from 90 filtered seawater and 120 biofouling samples was analyzed with quantitative PCR (qPCR), droplet digital PCR (ddPCR) and metabarcoding targeting the cytochrome c oxidase I (COI) and 18S rRNA genes for the Mediterranean fanworm Sabella spallanzanii. The qPCR analyses detected S. spallanzanii in 53% of water and 85% of biofouling samples. Using ddPCR S. spallanzanii was detected in 61% of water of water and 95% of biofouling samples. There were strong relationships between COI copy numbers determined via qPCR and ddPCR (water R2 = 0.81, p < .001, biofouling R2 = 0.68, p < .001); however, qPCR copy numbers were on average 125‐fold lower than those measured using ddPCR. Using metabarcoding there was higher detection in water samples when targeting the COI (40%) compared to 18S rRNA (5.4%). The difference was less pronounced in biofouling samples (25% COI, 29% 18S rRNA). Occupancy modelling showed that although the occupancy estimate was higher for biofouling samples (ψ = 1.0), higher probabilities of detection were derived for water samples. Detection probabilities of ddPCR (1.0) and qPCR (0.93) were nearly double metabarcoding (0.57 to 0.27 marker dependent). Studies that aim to detect specific invasive or rare species in environmental samples should consider using targeted approaches until a detailed understanding of how community and matrix complexity, and primer biases affect metabarcoding data.

Marine infrastructure can favor the spread of non-indigenous marine biofouling species by providing a suitable habitat for them to proliferate. Cryptic organisms or those in early life stages can be difficult to distinguish by conventional morphological taxonomy. Molecular tools, such as metabarcoding, may improve their detection. In this study, the ability of morpho-taxonomy and metabarcoding (18S rRNA and COI) using three reference databases (PR2, BOLD and NCBI) to characterize biodiversity and detect non-indigenous species (NIS) in biofouling was compared on 60 passive samplers deployed over summer and winter in a New Zealand marina. Highest resolution of metazoan taxa was identified using 18S rRNA assigned to PR2. There were higher assignment rates to NCBI reference sequences, but poorer taxonomic identification. Using all methods, 48 potential NIS were identified. Metabarcoding detected the largest proportion of those NIS: 77% via 18S rRNA/PR2 and NCBI and 35% via COI/BOLD and NCBI. Morpho-taxonomy detected an additional 14% of all identified NIS comprising mainly of bryozoan taxa. The data highlight several on-going challenges, including: differential marker resolution, primer biases, incomplete sequence reference databases, and variations in bioinformatic pipelines. Combining morpho-taxonomy and molecular analysis methods will likely enhance the detection of NIS from complex biofouling.