| 本文已被：浏览 137次 下载 24次 |
|
|
|
| 鄱阳湖浮游植物时空变化特征及其对极端洪枯事件的响应 |
|
李文轩1, 蒋名亮2, 徐力刚3, 胡颂平4, 游海林5, 周权平6, 陈 孜6
|
|
1.江西农业大学生物科学与工程学院，中国科学院南京地理与湖泊研究所;2.中国科学院南京地理与湖泊研究所,中国科学院南京地理与湖泊研究所鄱阳湖湖泊湿地综合研究站;3.中国科学院南京地理与湖泊研究所,中国科学院南京地理与湖泊研究所鄱阳湖湖泊湿地综合研究站，中国科学院大学南京学院;4.江西农业大学生物科学与工程学院;5.中国科学院南京地理与湖泊研究所鄱阳湖湖泊湿地综合研究站，江西省科学院流域生态研究所;6.中国地质调查局南京地质调查中心，自然资源部流域生态地质过程重点实验室
|
|
| 摘要: |
| 鄱阳湖作为中国最大的淡水湖泊，其水生态健康状态始终是人们关注的热点。近些年，鄱阳湖极端洪旱灾害频发，浮游植物生长受极端洪旱的影响发生了明显变化。为了分析浮游植物时空分布特征、探究环境因子对鄱阳湖浮游植物影响机制以及极端洪枯事件对浮游植物的影响，利用结构方程模型（SEM）构建浮游植物与环境因子的影响路径模型，定量分析环境因子对浮游植物的影响程度。结果表明，鄱阳湖浮游植物以蓝藻、绿藻为主且有明显的季节特征，在7月丰水期浮游植物丰度达到最高；由结构方程模型(SEM)可知，影响浮游植物最关键的因子为物理因子（WT>pH>SD>DO），其次为营养物质（TN>NO3--N>TP>NO2--N>PO43--P），浮游植物对高温、高营养和高pH较偏好。2020年极端洪水和2022年极端高温干旱，浮游植物主要受WT、DO、SD等物理因子的影响；在影响较小的营养物质中，主要的限制性因素分别为磷和氮。与正常年份相比，极端洪水年鄱阳湖受入湖来水及降雨的增多，湖区水量急剧增加，“稀释”作用超过WT、DO和SD对浮游植物生长的促进作用造成浮游植物丰度和生物量有所下降；在营养物质中，磷成为主要限制性因素。而极端高温干旱年受入湖来水的减少及湖水的快速蒸发，“浓缩”作用超过WT和SD对浮游植物生长的抑制作用造成浮游植物丰度和生物量显著增加，同时，营养物质对浮游植物的作用更加凸显。研究结果表明极端洪枯事件导致鄱阳湖浮游植物变化明显，确定其对浮游植物的影响机制，可以为极端洪枯事件下浮游植物监测、管理提供一定的理论基础。 |
| 关键词: 鄱阳湖 浮游植物 结构方程模型(SEM) 环境因子 极端洪枯 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目），江西省科技计划项目 ，江西省青年人才培养项目，中国地质调查局地质调查项目, |
|
| Spatial and temporal characteristics of phytoplankton in Poyang Lake and its response to extreme flood and drying events |
|
LI Wenxuan,JIANG Mingliang,XU Ligang,HU Songping,YOU Hailin,ZHOU Quanping,CHEN Zi
|
|
Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences/Poyang Lake Laboratory for Wetland Ecosystem Research, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences/University of Chinese Academy of Sciences
|
| Abstract: |
| As the largest freshwater lake in China, the water ecological health status of Poyang Lake has always been a hot spot of concern. In recent years, extreme floods and droughts have occurred frequently in Poyang Lake, and phytoplankton growth has changed significantly under the influence of extreme floods and droughts. In order to analyze the spatial and temporal distribution characteristics of phytoplankton, explore the influence mechanism of environmental factors on phytoplankton in Poyang Lake and the influence of extreme flood and drought events on phytoplankton, structural equation modeling (SEM) was used to construct the influence path model between phytoplankton and environmental factors, and to quantitatively analyze the extent of the influence of environmental factors on phytoplankton. The results showed that the phytoplankton in Poyang Lake was dominated by cyanobacteria and green algae with obvious seasonal characteristics. The most critical factors affecting the abundance of phytoplankton were physical factors (WT>pH>SD>DO), followed by nutrients (TN>NO3--N>TP>NO2--N>PO43--P), and phytoplankton preferred high temperature, high nutrients and high pH. In the extreme flood in 2020 and the extreme high temperature and drought in 2022, the abundance of phytoplankton were mainly affected by physical factors such as WT, DO and SD. impacts. Among the less affected nutrients, the main limiting factors were phosphorus and nitrogen, respectively. Compared with normal years, in the extreme flood year, Poyang Lake suffered from the increase of incoming water and rainfall, the water volume in the lake area increased sharply, and the "dilution" effect exceeded the promotion of phytoplankton growth by WT, DO and SD, resulting in the decrease of phytoplankton abundance and biomass; among the nutrients, phosphorus became the main limiting factor. In extreme high temperature and drought years, due to the reduction of incoming water and the rapid evaporation of lake water, the "concentration" effect exceeded the inhibitory effect of WT and SD on phytoplankton growth, resulting in a significant increase in phytoplankton abundance and biomass, and at the same time, the effects of nutrients on phytoplankton were more pronounced. The results of the study show that extreme flood and drought events lead to significant changes in phytoplankton in Poyang Lake, and determining the mechanism of its impact on phytoplankton can provide a certain theoretical basis for phytoplankton monitoring and management under extreme meteorological events. |
| Key words: Poyang Lake Phytoplankton Structural Equation Modeling (SEM) Environmental factors Extreme flood and drought |
