Document of bibliographic reference 405803

BibliographicReference record

Type

Bibliographic resource

Type of document

Journal article

BibLvlCode

AS

Title

Bridging the gap between the public’s knowledge and detection of marine non-indigenous species through developing automated image classification applications for marine species

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.

Abstract in other language

non-indigenous species, biological invasions, public support, artificial intelligence, automated image classification

Bibliographic citation

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. https://dx.doi.org/10.3389/fmars.2025.1508851

Topic

Marine

Is peer reviewed

true

Access rights

open access

Is accessible for free

true