Assessing Phytoplankton Primary Productivity Variability in the Changjiang Estuary, East China Sea From Coupled Fast Repetition Rate (FRR) Fluorometry and Chlorophyll‐a Measurements

Author:

Zhu Yuanli12ORCID,Hughes David J.3ORCID,Feng Yuanyuan4,Browning Thomas J.5ORCID,Du Ping126ORCID,Meng Qicheng67ORCID,Wang Shengqiang8ORCID,Wang Bing126,Li Dewang126ORCID,Jiang Zhibing126ORCID,Zeng Jiangning126ORCID

Affiliation:

1. Key Laboratory of Marine Ecosystem Dynamics Ministry of Natural Resources Second Institute of Oceanography Hangzhou PR China

2. Key Laboratory of Nearshore Engineering Environment and Ecological Security of Zhejiang Province Hangzhou PR China

3. Australian Institute of Marine Science Townsville QLD Australia

4. School of Oceanography Shanghai Jiao Tong University Shanghai PR China

5. Marine Biogeochemistry Division GEOMAR Helmholtz Centre for Ocean Research Kiel Germany

6. Observation and Research Station of Marine Ecosystem in the Yangtze River Delta Ministry of Natural Resources Hangzhou PR China

7. State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography Ministry of Natural Resources Hangzhou PR China

8. School of Marine Sciences Nanjing University of Information Science and Technology Nanjing PR China

Abstract

AbstractPhytoplankton primary productivity (PP) varies significantly over environmental gradients, particularly in physically‐dynamic systems such as estuaries and coastal seas. During summer, runoff peaks in the Changjiang River driving large environmental gradients in both the Changjiang estuary and adjacent East China Sea (ECS), likely driving significant variability in PP. As satellite models of PP often underperform in coastal waters, we aimed to develop a novel approach for assessing net PP variability in such a dynamic environment. Parallel in situ measurements of Fast Repetition Rate (FRR) fluorometry and carbon (C) uptake rates were conducted for the first time in this region during two summer cruises in 2019 and 2021. A series of 13C‐incubations (n = 31) were performed, with measured PP ranging from ∼6 to 1,700 mgC m−3 d−1. Net PP values were significantly correlated with salinity (r = 0.45), phytoplankton chlorophyll a (Chl‐a, r = 0.88), Photosystem II (PSII) functional absorption cross‐section (σPSII, r = −0.76) and maximum PSII quantum yield (Fv/Fm, r = 0.59). Stepwise regression analysis showed that Chl‐a and σPSII were the strongest predictors of net PP. A generalized additive model (GAM) was also used to estimate net PP considering nonlinear effects of Chl‐a and σPSII. We demonstrate that GAM outperforms linear modeling approaches in estimating net PP in this study, as evidenced by a lower root mean square error (∼140 vs. 250 mgC m−3 d−1). Our novel approach provides a valuable tool to examine carbon cycling dynamics in this important region.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Paleontology,Atmospheric Science,Soil Science,Water Science and Technology,Ecology,Aquatic Science,Forestry

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