Spatiotemporal distribution characteristics of phytoplankton communities in Baiyangdian Lake and their driving factors

DENG Lijiao; ZHANG Yi; LI Hao; ZENG Jun; LAI Junxiang

doi:10.13205/j.hjgc.202605011

Volume 44 Issue 5

May 2026

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2026 > 44(5): 112-121

DENG Lijiao, ZHANG Yi, LI Hao, ZENG Jun, LAI Junxiang. Spatiotemporal distribution characteristics of phytoplankton communities in Baiyangdian Lake and their driving factors[J]. ENVIRONMENTAL ENGINEERING , 2026, 44(5): 112-121. doi: 10.13205/j.hjgc.202605011

Citation:

DENG Lijiao, ZHANG Yi, LI Hao, ZENG Jun, LAI Junxiang. Spatiotemporal distribution characteristics of phytoplankton communities in Baiyangdian Lake and their driving factors[J]. ENVIRONMENTAL ENGINEERING , 2026, 44(5): 112-121. doi: 10.13205/j.hjgc.202605011

Citation:

DENG Lijiao, ZHANG Yi, LI Hao, ZENG Jun, LAI Junxiang. Spatiotemporal distribution characteristics of phytoplankton communities in Baiyangdian Lake and their driving factors[J]. ENVIRONMENTAL ENGINEERING , 2026, 44(5): 112-121. doi: 10.13205/j.hjgc.202605011

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Spatiotemporal distribution characteristics of phytoplankton communities in Baiyangdian Lake and their driving factors

doi: 10.13205/j.hjgc.202605011

DENG Lijiao^1,3,
ZHANG Yi²,
LI Hao^{1
,
,},
ZENG Jun¹,
LAI Junxiang¹

1. Guangxi Key Laboratory of Marine Environmental Science, Guangxi Academy of Marine Sciences, Guangxi Academy of Sciences, Nanning 530007, China;
2. School of Environment, Beijing Normal University, Beijing 100875, China;
3. Beijing Zhong Di Hong Ke Environmental Science and Technology Company Limited, Beijing 100020, China

Received Date: 2026-01-22
Available Online: 2026-06-06

Abstract

Abstract

Phytoplankton are highly sensitive to environmental changes and respond rapidly. Their community dynamics serve as important early warning indicators of lake ecosystem conditions. Previous studies have focused on qualitatively analyzing the combined effects of multiple physicochemical water quality factors on phytoplankton communities； however， few have quantitatively distinguished between the direct and indirect effects of different physicochemical water quality factors on these communities. This study used correlation analysis， redundancy analysis， and structural equation modeling to explore the spatial distribution characteristics of phytoplankton communities in Baiyangdian Lake and their driving factors. A total of 113 species belonging to 57 genera and 7 phyla were recorded. Phytoplankton density showed significant seasonal and spatial variability， reaching its maximum in summer. Diatoms and green algae dominated in spring， transitioning to cyanobacterial dominance in summer and autumn， and then reverting to green algae dominance in winter. Structural equation modeling revealed that water temperature had a total positive effect on phytoplankton biomass （β = 0.96）， consisting of a direct positive effect （β = 0.94， P < 0.05） and an indirect positive effect via increased abundance （β = 0.02）. Total nitrogen had a negative total effect on phytoplankton biomass （β = -0.96）， consisting of a direct negative effect （β = -0.95， P < 0.05） and an indirect negative effect via reduced abundance （β = -0.01）. Total nitrogen exerted a negative effect on abundance （β = -0.15， P < 0.05）. This study provides a scientific basis for ecosystem health assessment， eutrophication control strategies， and biodiversity protection in Baiyangdian Lake.
- phytoplankton,
- community,
- physicochemical water quality factors,
- structural equation modelling,
- direct and indirect effects

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References(45)

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