ArticleScientific reports2023
Harnessing environmental DNA to reveal biogeographical patterns of non-indigenous species for improved co-governance of the marine environment in Aotearoa New Zealand.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Article
- Navigating uncertainty in environmental DNA detection of a nuisance marine macroalga.PloS one · 2025Article
- Article
- No pump, no problem: evaluating passive eDNA sampling for marine biomonitoring of a nuisance macroalga.PeerJ · 2025Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aotearoa New Zealand's Northern region is a major gateway for the incursion and establishment of non-indigenous species (NIS) populations due to high numbers of recreational and commercial vessels. This region also holds a unique marine ecosystem, home to many taonga (treasured) species of cultural and economic importance. Regular surveillance, eradication plans and public information sharing are undertaken by local communities and governmental organizations to protect these ecosystems from the impact of NIS. Recently, considerable investments went into environmental DNA (eDNA) research, a promising approach for the early detection of NIS for complementing existing biosecurity systems. We applied eDNA metabarcoding for elucidating bioregional patterns of NIS distributions across a gradient from harbors (NIS hotspots) to open seas (spreading areas). Samples were collected during a research cruise sailing across three Aotearoa New Zealand harbors, Waitematā, Whangārei and Pēwhairangi (Bay of Islands), and their adjacent coastal waters. The small-ribosomal subunit (18S rRNA) and mitochondrial cytochrome c oxidase I (COI) genes were screened using the online Pest Alert Tool for automated detection of putative NIS sequences. Using a probabilistic modelling approach, location-dependent occupancies of NIS were investigated and related to the current information on species distribution from biosecurity surveillance programs. This study was collaboratively designed with Māori partners to initiate a model of co-governance within the existing science system.
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