Articles producció científicaEnginyeria Química

Machine learning unveils large-scale impact of Posidonia oceanica on Mediterranean Sea water

  • Datos identificativos

    Identificador:  imarina:9446685
    Autores:  Trois; C; del Fabro; LD; Baulin; VA
    Resumen:
    Posidonia oceanica is a protected endemic seagrass of the Mediterranean Sea that fosters biodiversity, stores carbon, releases oxygen, and provides habitat to numerous sea organisms. Leveraging augmented research, we collected a comprehensive dataset of 174 features compiled from diverse data sources. Through machine learning analysis, we discovered the existence of a robust correlation between the location of P. oceanica and water biogeochemical properties. The model's feature importance showed that carbon-related variables such as net biomass production and carbon dioxide flux have their values altered in the areas with P. oceanica. The study provides evidence of the plant's ability to exert a global impact on the environment and underscores the crucial role of this plant in sea ecosystems, emphasizing the need for its conservation and management.
  • Otros:

    Enlace a la fuente original: https://www.sciencedirect.com/science/article/pii/S0048969725004371?via%3Dihub
    Referencia de l'ítem segons les normes APA: Trois; C; del Fabro; LD; Baulin; VA (2025). Machine learning unveils large-scale impact of Posidonia oceanica on Mediterranean Sea water. SCIENCE OF THE TOTAL ENVIRONMENT, 968(), 178802-. DOI: 10.1016/j.scitotenv.2025.178802
    Referencia al articulo segun fuente origial: SCIENCE OF THE TOTAL ENVIRONMENT. 968 178802-
    DOI del artículo: 10.1016/j.scitotenv.2025.178802
    Año de publicación de la revista: 2025-03-10
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Fecha de alta del registro: 2026-05-09
    Autor/es de la URV: Baulin, Vladimir
    Departamento: Enginyeria Química
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    Autor según el artículo: Trois; C; del Fabro; LD; Baulin; VA
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Waste management and disposal, Pollution, Environmental sciences, Environmental engineering, Environmental chemistry, Biotecnología, Biodiversidade, Administração pública e de empresas, ciências contábeis e turismo
    Direcció de correo del autor: vladimir.baulin@urv.cat
  • Palabras clave:

    Posidonia oceanica
    Marine ecosystem
    Machine learning
    Biogeochemical variables
    Environmental Chemistry
    Environmental Engineering
    Environmental Sciences
    Pollution
    Waste Management and Disposal
    Biotecnología
    Biodiversidade
    Administração pública e de empresas
    ciências contábeis e turismo
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