1. Elucidating phytoplankton limiting factors in lakes and reservoirs of the Chinese Eastern Plains ecoregion
- Author
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Zou, Wei, Zhu, Guangwei, Xu, Hai, Zhu, Mengyuan, Qin, Boqiang, Zhang, Yunlin, Bi, Yonghong, Liu, Miao, and Wu, Tianhao
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Strategic planning (Business) -- Analysis ,Reservoirs -- Analysis ,Eutrophication -- Analysis ,Chlorophyll -- Analysis ,Environmental issues - Abstract
Keywords Eutrophication; Cyanobacterial blooms; Quantile regression; Water depth; Chlorophyll a Highlights * Site-specific algal limiting factors were identified for the studied 54 freshwaters. * Algae in 16% and 84% sites were limited by nutrient and non-nutrient factors, respectively. * Algae in the studied freshwaters would be potentially P-limited with depths of >5.2 m. * Alleviating lake blooms by nutrient reduction requires different strategies depending on depths. Abstract Knowledge of phytoplankton limiting factors is essential for cost-efficient lake eutrophication management. Herein, we propose a statistical framework to explore site-specific phytoplankton limiting factors and their dependence on water depth (WD) in 54 lakes in the Chinese Eastern Plains ecoregion. First, the maximal chlorophyll a (Chla) response to total N (TN) or P (TP), representing a region-specific 'standard' model where phytoplankton were primarily N- or P-limited, was quantified using a 95% quantile regression. Second, site-specific limiting factors were identified using analogical residual analysis. N- or P-limitation was inferred if Fraction.sub.TN (i.e. fraction of Chla observed and predicted by the 'standard' model for a given TN) > 0.95 or Fraction.sub.TP >0.95; if both Fraction.sub.TN and Fraction.sub.TP 5.2 m can entail control of N, N+P, and P, respectively. This study provides essential information for formulating context-dependent bloom control for lakes in our study area and serves as a valuable reference for developing a cost-efficient eutrophication management framework for other regions. Author Affiliation: (a) Taihu Laboratory for Lake Ecosystem Research, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, PR China (b) Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, PR China (c) Jiangsu Provincial Key Laboratory of Environmental Engineering, Jiangsu Provincial Academy of Environmental Science, Nanjing, 210036, PR China (d) National Engineering Laboratory for Lake Pollution Control and Ecological Restoration, Chinese Research Academy of Environmental Sciences, Beijing, 100012, PR China * Corresponding author. Taihu Laboratory for Lake Ecosystem Research, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing, 210008, PR China. Article History: Received 3 April 2022; Revised 7 June 2022; Accepted 14 June 2022 Byline: Wei Zou (a), Guangwei Zhu [gwzhu@niglas.ac.cn] (a,*), Hai Xu (a), Mengyuan Zhu (a), Boqiang Qin (a), Yunlin Zhang (a), Yonghong Bi (b), Miao Liu (c), Tianhao Wu (d)
- Published
- 2022
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