Integrating functional trait diversity and machine learning for ecological status assessment of Turkish coastal waters under the EU Water Framework Directive
Baytut, Ö.; Çetin, T. (2026). Integrating functional trait diversity and machine learning for ecological status assessment of Turkish coastal waters under the EU Water Framework Directive. Est., Coast. and Shelf Sci. 341: 110107. https://dx.doi.org/10.1016/j.ecss.2026.110107
In: Estuarine, Coastal and Shelf Science. Academic Press: London; New York. ISSN 0272-7714; e-ISSN 1096-0015, meer
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| Author keywords |
Trait-based ecology; Phytoplankton community structure; Ecological status assessment; Biomonitoring; ANFIS; Biodiversity indices |
| Abstract |
Understanding the functional attributes of phytoplankton communities is critical for improving ecological status assessments in coastal waters. This study presents the first comprehensive assessment of phytoplankton functional diversity (FD) alongside taxonomic biodiversity across Turkish coastal waters using an integrated analytical approach that combines ordination techniques, trait-based metrics, and machine learning (ML) algorithms. Phytoplankton biomass and trait data collected from 78 coastal stations (2016–2020) were used to compute Functional Richness (FRic), Functional Evenness (FEve), Functional Divergence (FDiv), Shannon diversity, Menhinick's richness, and Pielou's evenness. Community composition was characterised using Principal Coordinate Analysis (PCoA) based on (Bray–Curtis) dissimilarities, while major environmental gradients were identified through Principal Component Analysis (PCA). FDiv was the most predictable index, with SVR achieving the highest accuracy (R2 = 0.847), closely followed by Random Forest (R2 = 0.843) and Gradient Boosting (R2 = 0.827). The hybrid framework introduced here provides a transferable, early-warning tool for ecological diagnostics and establishes a robust foundation for next-generation coastal biomonitoring.The findings of this study have direct implications for policymakers and environmental managers, particularly within the implementation framework of the European Union Water Framework Directive (EU WFD). |
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