

FOLLOWUS
1.Jiangxi Key Laboratory of Hydrology-Water Resources and Water Environment, Nanchang Institute of Technology, Nanchang330099, China
2.Key Laboratory of Poyang Lake Environment and Resource Utilization, Ministry of Education, and School of Resources, Environmental & Chemical Engineering, Nanchang University, Nanchang330031, China
3.Lushan Botanical Garden, Jiangxi Province and Chinese Academy of Sciences, Jiujiang332900, China
4.China Railway Water Conservancy & Hydropower Planning and Design Group Co., Ltd., Nanchang330029, China
5.Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang330022, China
6.Institute of Watershed Ecology, Jiangxi Academy of Sciences, Nanchang330096, China
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收稿:2024-03-09,
纸质出版:2024-11-01
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Phytoplankton functional groups in Poyang Lake: succession and driving factors[J]. 海洋湖沼学报(英文), 2024,42(6):1764-1776.
LIU Jinfu,ZOU Haoyue,DENG Feng,et al.Phytoplankton functional groups in Poyang Lake: succession and driving factors[J].Journal of Oceanology and Limnology,2024,42(06):1764-1776.
Phytoplankton functional groups in Poyang Lake: succession and driving factors[J]. 海洋湖沼学报(英文), 2024,42(6):1764-1776. DOI: 10.1007/s00343-024-4074-0.
LIU Jinfu,ZOU Haoyue,DENG Feng,et al.Phytoplankton functional groups in Poyang Lake: succession and driving factors[J].Journal of Oceanology and Limnology,2024,42(06):1764-1776. DOI: 10.1007/s00343-024-4074-0.
Phytoplankton functional groups have gained increasing attention in recent years. To understand the composition of phytoplankton functional groups in Poyang Lake and their drivers
field investigations were conducted over three years: 2013
2014
and 2016. Phytoplankton were dominated by diatoms
contributing from 20.19% to 57.57% of the total biomass
followed by cyanobacteria
9.81%–39.98%.
Microcystis
sp. and
Anabaena
sp. were the dominant species among cyanobacteria. Twenty-six functional groups were identified among 72 genera or species
and fiver groups (P
B
MP
H1
and G) were categorized dominant. All of dominant groups except H1 were tolerate highly fluctuating mixing intensities and showed a typical monthly succession variation. Water temperature
water level
and nutrients are key drivers for the variation of phytoplankton communities at taxonomic and functional levels. Both of redundancy and variation partitioning analyses showed that environmental variables might explain functional groups better
than taxonomic communities
implying that the functional groups were more advantageous in showing the effects of environmental conditions than taxonomic compositions. Hydrological conditions have a crucial influence on phytoplankton assemblage dynamics in highly variable water regime lakes
but not in the largest ones. The functional groups method is suitable for identifying the spatial and seasonal characteristics of aquatic environments that significantly affected by water regimes.
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