Modeling Posidonia oceanica shoot density and rhizome primary production.

ABSTRACT: Posidonia oceanica meadows rank among the most important and most productive ecosystems in the Mediterranean basin, due to their ecological role and to the goods and services they provide. Estimations of crucial ecological process such as meadows productivity could play a major role in an environmental management perspective and in the assessment of P. oceanica ecosystem services. In this study, a Machine Learning approach, i.e. Random Forest, was aimed at modeling P. oceanica shoot density and rhizome primary production using as predictive variables only environmental factors retrieved from indirect measurements, such as maps. Our predictive models showed a good level of accuracy in modeling both shoot density and rhizome productivity (R² = 0.761 and R² = 0.736, resp

SUBMITTER: Catucci E 

PROVIDER: S-EPMC7550612 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature