| 引用本文: | 黄立成,周远洋,周起超,王玮璐,董云仙,李凯迪,常军军.云南程海浮游植物初级生产力的时空变化及其影响因子.湖泊科学,2019,31(5):1424-1436. DOI:10.18307/2019.0508 |
| HUANG Licheng,ZHOU Yuanyang,ZHOU Qichao,WANG Weilu,DONG Yunxian,LI Kaidi,CHANG Junjun.Temporal-spatial variation in phytoplankton primary production and its influencing factors in Lake Chenghai on the Yunnan Plateau, China. J. Lake Sci.2019,31(5):1424-1436. DOI:10.18307/2019.0508 |
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| 云南程海浮游植物初级生产力的时空变化及其影响因子 |
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黄立成1, 周远洋1,2, 周起超1,3, 王玮璐1, 董云仙1, 李凯迪1,2, 常军军2
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1.云南省环境科学研究院云南省高原湖泊流域污染过程与管理重点实验室, 昆明 650034;2.云南大学生态学与环境学院, 昆明 650500;3.云南大学资源环境与地球科学学院/高原湖泊生态与污染治理研究院, 昆明 650500
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| 摘要: |
| 2016年4月-2017年2月，采用黑白瓶法研究了云南程海单点（码头点位）浮游植物初级生产力的垂直分布及其季节变化，同时基于全湖9个点位的现场调查和生产力垂向归纳模型（VGPM）估算并探讨了程海浮游植物初级生产力的时空变化及其主要影响因子.结果显示，码头点位的年均（均值±标准误）水柱（0~3 m）总初级生产力（GPPC）、净初级生产力（NPPC）和呼吸消耗量（RC）分别为5.40×103±0.64×103、2.36×103±0.63×103和3.06×103±0.82×103 mg O2/（m2·d）；不论春夏季（4-8月）、秋冬季（9月-次年2月）还是全年，码头点位的单位生物量GPP（GPP/Chl.a）和单位生物量NPP（NPP/Chl.a）的最大值和最小值均分别出现在水下0.5 m和3.0 m处.经VPGM估算，程海全湖的初级生产力（PPeu）年均值为6.54×103±0.30×103 mg C/（m2·d）（2.74×103~18.62×103 mg C/（m2·d））.PPeu的时空变化方面，春夏季是PPeu快速上升的时节，秋冬季PPeu的月变化则呈波动状态，春夏季与秋冬季PPeu无显著性差异；PPeu整体空间异质性较弱，仅在降水最为充沛的7、8月表现出南北向的异质性，这与降水条件和流域营养盐输入的空间异质性有关.回归分析发现，虽然程海PPeu的主要影响因子具有季节异质性，但不论春夏季、秋冬季还是全年，浮游植物生物量均是重要的影响因子，水温亦是春夏季的重要影响因子. |
| 关键词: 浮游植物初级生产力 黑白瓶法 生产力垂向归纳模型 时空分布 程海 |
| DOI：10.18307/2019.0508 |
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| 基金项目:国家自然科学基金项目（41601208，41621002）、国家重点研发计划项目（2017YFA0605202）、云南省环保专项项目和云南省环境科学研究院创新团队计划项目联合资助. |
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| Temporal-spatial variation in phytoplankton primary production and its influencing factors in Lake Chenghai on the Yunnan Plateau, China |
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HUANG Licheng1, ZHOU Yuanyang1,2, ZHOU Qichao1,3, WANG Weilu1, DONG Yunxian1, LI Kaidi1,2, CHANG Junjun2
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1.Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Yunnan Institute of Environmental Science, Kunming 650034, P. R. China;2.School of Ecology and Environmental Science, Yunnan University, Kunming 650500, P. R. China;3.Institute of Plateau Lake Ecology and Pollution Management, School of Resource Environment and Earth Science, Yunnan University, Kunming 650500, P. R. China
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| Abstract: |
| From April 2016 to February 2017, the temporal-spatial distribution of phytoplankton primary production in Lake Chenghai at Yunnan, China was investigated monthly via light-dark bottle method (at a dock site) and vertically generalized production model (VGPM) (across nine sampling sites), and the potential influencing factors were also analyzed. The results showed that the annual mean values (mean±SE) of gross primary production (GPPC), net primary production (NPPC) and respiration (RC) of water column (0-3 m) at dock site were 5.40×103±0.64×103, 2.36×103±0.63×103 and 3.06×103±0.82×103 mg O2/(m2·d), respectively. Meanwhile, the maximal and minimal values of the GPP and NPP per biomass (GPP/Chl.a and NPP/Chl.a) in vertical profile were both present at the depth of 0.5 m and 3.0 m respectively, whether during spring and summer (from April to August, 2016), autumn and winter (from September 2016 to February 2017) or the entire experimental period at dock site. Moreover, the annual mean value and range of the phytoplankton primary production (PPeu) estimated by VGPM were 6.54×103±0.30×103 and 2.74×103-18.62×103 mg C/(m2·d), respectively. PPeu increased rapidly during spring and summer, and fluctuated during autumn and winter. No significant difference for PPeu was detected between spring-summer and autumn-winter. The spatial heterogeneity of PPeu was weak in general despite the significant difference in the north-south direction in July and August with plentiful rainfall which might be related to the rainfall and spatial heterogeneity of nutrients input from the basin. Furthermore, although the major influencing factors for PPeu and their relative importance were changed with season, the phytoplankton biomass was the most important factor impacting PPeu during the entire period, and the water temperature was also an important factor during spring and summer. |
| Key words: Phytoplankton primary production light-dark bottle method vertically generalized production model (VGPM) temporal-spatial distribution Lake Chenghai |
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