Integrating Copernicus Earth Observation and Artificial Intelligence for Habitat Suitability Modeling of Pinctada radiata in Semi-Enclosed Coastal Watersheds of Central Greece

Abstract

Semi-enclosed coastal systems are highly dynamic environments where benthic organisms are exposed to strong hydrographic gradients and increasing anthropogenic pressures. This study assessed the habitat suitability of the pearl oyster Pinctada radiata in two contrasting Mediterranean gulfs of Central Greece, the Maliakos and the South Evoikos, by integrating Copernicus Earth Observation (EO) products with an Artificial Intelligence (AI) modeling framework. Environmental variables, including sea surface temperature, salinity, chlorophyll-a concentration, current velocity, and dissolved oxygen, were derived from satellite and marine datasets and used to train a multi-algorithm ensemble combining Maximum Entropy (MaxEnt), Extreme Gradient Boosting (XGBoost), and a Convolutional Neural Network (CNN). The ensemble model showed strong predictive skill (AUC = 0.94; TSS = 0.80) and identified temperature, dissolved oxygen, and substrate type as the main drivers of habitat suitability. Spatial projections indicated that roughly two-thirds of the study area currently supports favorable conditions for P. radiata, particularly in shallow, low-energy, mesotrophic zones. Under a simulated +2 °C warming scenario, highly suitable habitats declined by about 20%, highlighting the species’ sensitivity to future thermal stress and subsequent oxygen depletion, demonstrating the value of EO-driven AI approaches for anticipating ecological change in vulnerable coastal systems.

Keywords

Copernicus / Artificial intelligence / Pinctada radiata / Habitat suitability / Semi-enclosed gulf / Mediterranean / Machine learning / Climate scenario

CRediT authorship contribution statement

Conceptualization, D.P. and D.K.; Methodology, D.P.; Software, D.P.; Validation, D.P., D.K., A.C., D.V. and G.K.; Formal Analysis, D.P.; Investigation, D.P.; Resources, D.K., A.C., D.V. and G.K.; Data Curation, D.P.; Writing-Original Draft Preparation, D.P.; Writing-Review & Editing, D.P., D.K., A.C., D.V. and G.K.; Visualization, D.P.; Supervision, D.K.; Project Administration, D.K.; Funding Acquisition, D.K. All authors have read and agreed to the published version of the manuscript.

Availability of data and materials

The data supporting the findings of this study are available from the corresponding author upon reasonable request. Environmental datasets used in this study were obtained from publicly accessible repositories, including the Copernicus Marine Environment Monitoring Service (CMEMS) and EMODnet. Processed datasets and model outputs generated during the study are available from the corresponding author upon reasonable request.

Funding

This research was funded by the Region of Central Greece, under the Regional Development Programme (PPA), Priority Axis 2.4 “Risk Prevention and Management”, Project Code: Π89-2.13.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This research was supported by the research program of the Region of Central Greece (Project Code: Π89-2.13), implemented under the “Regional Development Programme (PPA) of Central Greece”, Priority Axis 2.4 “Risk Prevention and Management”, entitled “Investigation of the Biology, Fisheries, Ecology, and Population Dynamics of the bivalve pearl oyster Pinctada imbricata radiata in the South Evoikos and Maliakos Gulfs”.

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