Submitted:
28 November 2025
Posted:
28 November 2025
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Abstract
Chlorophyll-a (Chl-a) concentration is a key indicator of coastal ecosystem health. Its spatio-temporal variability not only reflects primary productivity but also represents the ecosystem’s integrated response to climate change and human activities. To quantify long-term Chl-a trends in the Yellow and Bohai Seas and to identify regional differences across concentration levels, this study used a multi-source remote sensing reconstruction dataset generated with deep learning algorithms. By applying quantile regression, we characterized long-term Chl-a changes across different concentration percentiles. We also examined how environmental drivers—including sea surface temperature, mixed layer depth, wind speed, and sea surface height anomalies—shape long-term variability in representative marginal-sea environments such as eutrophic estuaries, aquaculture zones, and deep-water regions. Our results show that from 2005 to 2024, Chl-a concentrations in the Yellow and Bohai Seas decreased consistently across the 75th, 50th, and 25th percentiles, with decline rates of –4.82×10-3, –4.50×10-3, and –4.09×10-3 mg/(m³·a), respectively. The rate of change also displayed strong seasonal differences: the summer decline (–0.0638 mg/(m³·a)) was substantially greater than that in winter (–0.04 mg/(m³·a)). Spatially, reductions were more pronounced in high-concentration nearshore waters than in offshore regions. Analysis of underlying mechanisms indicates that mixed-layer depth and wind speed are the primary physical controls on Chl-a variability, though their impacts differ regionally. In nearshore areas such as Qinhuangdao, strong wind-wave disturbance and deepening of the mixed layer enhanced vertical mixing, leading to light limitation and sediment resuspension, ultimately suppressing phytoplankton growth and driving the observed Chl-a decline. In contrast, offshore waters were more strongly influenced by mesoscale processes such as fronts and eddies, with local physical forcing exerting comparatively weaker direct effects on phytoplankton dynamics. Overall, this study provides new insights for improving the modelling and management of coastal ecosystems under the combined pressures of climate change and anthropogenic activities.
