Phytoplankton functional types in the Black Sea. A regionalized algorithm for improving ecosystem monitoring by integrating In-Situ HPLC pigment analysis and satellite observations.

Phytoplankton in the Black Sea plays a key role in regional biogeochemical cycles, but its complex optical environment pose significant challenges for the remote sensing-based monitoring. This study develops a regionalized algorithm for phytoplankton functional types (PFTs) and size classes (PSCs) specifically tailored for the Black Sea. Using high-performance liquid chromatography (HPLC) pigment data from 690 stations collected over 12 bio-optical campaigns (2006-2019), we applied hierarchical clustering, principal component analysis, and network-based community detection to identify dominant phytoplankton groups and characterize their spatial and temporal variability. We derived region-specific coefficients for estimating PFT abundances from pigment signatures and developed algorithms linking chlorophyll-a to PFT distributions. Applying these algorithms to a satellite-derived chlorophyll-a dataset from 1998 to 2024, we generated long-term climatologies revealing clear spatial patterns: microplankton dominated the nutrient-rich northwestern shelf, comprising up to 70-80 % of total chlorophyll-a; nanoplankton exhibited a relatively uniform distribution across the basin (∼30-40 %), while picoplankton prevailed offshore, particularly in oligotrophic central and southern regions, contributing over 60 % of chlorophyll-a there. Our model outperformed existing global algorithms by reducing estimation errors and bias, particularly for cryptophytes and haptophytes-key functional groups in the Black Sea. Comparison with long-term microscopy data confirmed the model's robustness in capturing seasonal dynamics and ecological gradients. This work provides an improved framework for monitoring phytoplankton functional diversity in optically complex coastal basins like the Black Sea.