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• W4376601716 abstract "为探究长江中下游富营养化浅水湖泊的浮游植物初级生产力季节性演替特征及其驱动因子，本研究于2020年4月（春）、8月（夏）、10月（秋）及2021年1月（冬）对湖北长湖浮游植物进行采样调查，同时运用黑白瓶测氧法及VGPM模型估算法分别估算了其浮游植物生产力水平，并探究驱动初级生产力季节性变化的主要环境因子。结果显示，4个季节共鉴定出浮游植物194种，其中绿藻门（95种，49%）和硅藻门（40种，21%）居绝对优势地位；黑白瓶法测得浮游植物水柱总生产力（P_t）季节变化为：夏季（（1841.24±345.93） mg C/（m²·d））>秋季（（1324.14±208.34） mg C/（m²·d））>春季（（847.50±247.72） mg C/（m²·d））>冬季（（711.43±133.52） mg C/（m²·d）），其中M2站位在夏季采样时（2424.66 mg C/（m²·d））水柱总生产力最高；在垂直空间上，浮游植物总生产力（GPP）及净生产力（NPP）随水深增加而逐渐变小。基于VGPM法估算的初级生产力（PP_eu）季节性分布为夏季（（3713.18±900.30） mg C/（m²·d））>秋季（（2643.62±1062.48） mg C/（m²·d））>春季（（2477.13±669.75） mg C/（m²·d））>冬季（（708.07±390.40） mg C/（m²·d）），空间分布特征呈现海子湖区>马洪台湖区>圆心湖区的趋势。相关性分析结果显示：长湖浮游植物初级生产力（P_t和PP_eu）相关系数为88.2%，具有极显著相关性，它们与浮游植物密度以及叶绿素a（Chl.a）浓度均具有显著相关性。多元逐步回归分析显示，PP_eu主要受Chl.a、水温、pH、总悬浮物和硝态氮的影响，而P_t则可以通过电导率、水温和溶解氧来进行预测。该结果可为长江中下游湖泊水体富营养化以及渔业生产潜力评估奠定基础。;In order to explore the spatiotemporal variation and driving factors of phytoplankton primary productivity in eutrophic lakes in the middle and lower reaches of Yangtze River, field work and bottling experiments were conducted in April 2020 (spring), August 2020 (summer), October 2020 (autumn) and January 2021 (winter) in Lake Changhu, Hubei Province, while VGPM model was used to estimate the phytoplankton primary productivity (PP_eu). The main environmental factors driving the seasonal change of phytoplankton primary productivity were also explored. According to the results, 194 species of phytoplankton were identified and phyla Chlorophyta (95 species, 49%) and Bacillariophyta (40 species, 21%) were dominant. The total productivity (P_t) value of water column changed as follows:summer ((1841.24±345.93) mg C/(m²·d)) > autumn ((1324.14±208.34) mg C/(m²·d)) > spring ((847.50±247.72) mg C/(m²·d)) >winter ((711.43±133.52) mg C/(m²·d)). The highest value of which was (2424.66 mg C/(m²·d)) at site M2 in summer, while the value of total productivity (GPP) and net productivity (NPP) of phytoplankton gradually decreased with the increase of water depth. The seasonal distribution of PP_eu estimated by VGPM model was autumn ((3713.18±900.30) mg C/(m²·d))>summer ((2643.62±1062.48) mg C/(m²·d))>spring ((2477.13±669.75) mg C/(m²·d))>winter ((708.07±390.4) mg C/(m²·d)), and the trend characteristics of spatial distribution showed Haizihu district>Mahongtai district>Yuanxinhu district. The Spearman correlation between primary productivity measured by bottling experiments and VGPM model (P_t and PP_eu) was significant with a coefficient of 88.2%. They both were highly correlated with phytoplankton density and chlorophyll-a (Chl.a). Multiple stepwise regression analysis showed that PP_eu was mainly influenced by Chl.a, water temperature (WT), pH, total suspended solid and nitrite while Pt can be predicted by conductivity, WT and dissolved oxygen. These data would lay a foundation for the assessment of lake eutrophication and fishery production potential in the middle and lower reaches of the Yangtze River." @default.
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• W4376601716 date "2023-01-01" @default.
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• W4376601716 title "Seasonal variation and driving factors of primary productivity of phytoplankton in Lake Changhu, Jianghan Plain" @default.
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• W4376601716 doi "https://doi.org/10.18307/2023.0307" @default.
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