Tracing the intruders: a global appraisal of marine invasive species detection through DNA-based approaches

Early detection and monitoring of non-indigenous species (NIS) is crucial to prevent their establishment and to reduce ecological and economic impacts in coastal ecosystems. Traditional monitoring approaches, which rely largely on morphological identification of collected organisms, are often time-consuming and may fail to detect species that occur at low abundance, are morphologically cryptic, or are present in the form of inconspicuous life stages. DNA-based approaches, particularly those resorting to environmental DNA, have demonstrated high aptitude for biodiversity monitoring and biosecurity surveillance. By examining the genetic material from bulk community samples or released into the environment, DNA-based approaches enable the detection of species without the need for direct observation, thereby increasing detection sensitivity and expanding the scope of monitoring programs. Despite the rapid growth of its employment in marine monitoring, a global synthesis of the status and trends of DNA-based approaches for detecting NIS in this environment has been lacking. Here, we present such synthesis, based on 146 published studies employing DNA for NIS detections in coastal environments. Two main methodological approaches were used across the reviewed studies, namely DNA metabarcoding which was applied in 49% of studies, closely followed by targeted single-species PCR assays, used in 42% of the studies. A smaller proportion of studies (10%) combined both approaches, integrating broad community screening with targeted detection to improve surveillance efficiency. Globally, 752 NIS were detected across disparate taxonomic groups, with metazoans representing the largest proportion of detections (464 species), followed by Chromista (210 species) and Plantae (77 species). Among these, the most frequently detected taxonomic groups included Dinophyceae (Dinoflagellata), Teleostei (Chordata), Florideophyceae (Rodophyta), Polychaeta (Annelida), Copepoda and Malacostraca (Arthropoda), and Ascidiacea (Chordata). At the species level, several well-known marine invaders were recurrently reported, including Bugula neritina (Linnaeus, 1758), Styela plicata (Lesueur, 1823), Acartia (Acanthacartia) tonsa Dana, 1849-1852, and Botryllus schlosseri (Pallas, 1766), highlighting the ability of DNA approaches to detect widespread and established invaders across different regions. The mitochondrial cytochrome c oxidase subunit I (COI) gene was the most widely used genetic marker, reflecting its broad taxonomic coverage and extensive representation in reference databases, particularly for targeting Metazoa. Ribosomal RNA genes, particularly 18S and 16S rRNA gene markers, were also frequently employed to target a wider range of eukaryotic taxa. Regarding sampled substrates, water was by far the most analyzed substrate, followed by zooplankton and biofouling communities collected from man-made structures. Notably, approximately 31% of all NIS detections reported in the reviewed studies constituted new regional records. These results highlight the potential of eDNA for coastal monitoring but also underline important limitations. Persistent geographical, taxonomic, and methodological biases can affect detection outcomes, and reliance on single sample types or markers may increase false negatives - particularly critical for NIS early detection. Therefore, multi-marker and multi-substrate approaches are essential to improve detection reliability and support effective biosecurity strategies. As reference databases continue to expand and methodological protocols become increasingly standardized, DNA-based monitoring is likely to play a central role in future management and surveillance of biological invasions in coastal ecosystems. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/722998v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@17948b1org.highwire.dtl.DTLVardef@193832dorg.highwire.dtl.DTLVardef@189033dorg.highwire.dtl.DTLVardef@33cddf_HPS_FORMAT_FIGEXP M_FIG C_FIG