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Updated: Aug 31, 2026
Visualizing Oceanographic Data to Depict Long-term Changes in Phytoplankton
Published on: July 28, 2023
A spatio-correlation-based reconstruction of 40-year nutrient and diatom-dinoflagellate community dynamics in Laizhou
Guangshen Tan1, Kan Chen2, Ruobing Na1
1Frontiers Science Center for Deep Ocean Multispheres and Earth System, and Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, Ocean University of China, Qingdao, 266100, China; College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao, 266100, China.
Abstract:
Coastal environmental changes are restructuring diatom and dinoflagellate communities. However, the mechanisms linking long-term nutrient dynamics to diatom- and dinoflagellate-dominated states remain unclear, primarily due to the scarcity of consistent, long-term nutrient and biological records. In this study, we compiled multi-source observations spanning nearly four decades from Laizhou Bay, China. Using a newly developed spatial-correlation-based reconstruction framework, we generated a coherent spatio-temporal dataset of nutrients and diatom-dinoflagellate community structure. A common classification scheme comprising six characteristic spatial distribution types was established for DIN, DIP, and the Diatom-Dinoflagellate Community Index (RDino), defined as the ratio of dinoflagellate abundance to the combined abundance of dinoflagellates and diatoms. Five of these six types were represented in the available RDino records. We further detected non-monotonic, step-like changes in nutrient concentrations (DIN, DIP, SiO₃), stoichiometric ratios (N/P, Si/N), RDino, sea-surface salinity (SSS), and sea-surface temperature (SST). Mechanistically, elevated N/P ratios, regional warming, salinity gradients, and inherently weak hydrodynamics jointly promoted a shift toward dinoflagellate dominance. Notably, recent reductions coinciding with policy implementation in nutrient inputs have begun to moderate this trend. This study establishes a long-term dataset of nutrients and RDino for Laizhou Bay and clarifies the links between environmental change and phytoplankton community restructuring. Subject to the availability of high-quality reference periods and relatively stable hydrodynamic and geomorphic controls that allow recurrent spatial patterns to be identified, the proposed framework offers a transferable methodological pathway for reconstructing sparse historical data in semi-enclosed bays and estuarine coastal systems.
