Bridging the gap between the public’s knowledge and detection of marine non-indigenous species through developing automated image classification applications for marine species
Zhou, P.; He, X.-Q.; Tu, Z.-Y.; Sun, D.; Wang, C.-S.; Shen, H.-B.; Pan, X. (2025). Bridging the gap between the public’s knowledge and detection of marine non-indigenous species through developing automated image classification applications for marine species. Front. Mar. Sci. 12: 1508851. https://dx.doi.org/10.3389/fmars.2025.1508851
In: Frontiers in Marine Science. Frontiers Media: Lausanne. ISSN 2296-7745; e-ISSN 2296-7745, meer
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| Auteurs | | Top |
- Zhou, P.
- He, X.-Q.
- Tu, Z.-Y.
- Sun, D.
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- Wang, C.-S.
- Shen, H.-B.
- Pan, X.
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| Abstract |
Biological invasions are impacting biodiversity, ecosystem, and socio-economics globally. Marine non-indigenous species (mNIS) can be introduced through human activities, such as maritime shipping and careless discarding of aquarium species. Despite significant efforts to prevent the introduction of mNIS, occurrences continue to arise, including fishes, crustaceans, ascidians, anthozoans, bryozoans, sponges, macroalgae, seagrasses and mangroves (Alidoost Salimi et al., 2021). Once mNIS establish in recipient regions, controlling and eradicating them becomes a challenging task. Early awareness of mNIS could enhance the effectiveness of early response, particularly during the introduction phase, which is critical to reduce the impacts of mNIS in the future. Therefore, it is imperative to develop reliable and cost-effective strategies for the early detection of mNIS before they successfully establish themselves in new habitats and pose threats to local biodiversity. |
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