Long-term joint effect of nutrients and temperature increase on algal growth in Lake Taihu,China

作     者：Chun Ye Zhemin Shen Tao Zhang Maohong Fan Yangming Lei Jianda Zhang 

作者机构：School of Environmental Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China Chinese Research Academy of Environmental Sciences Beijing 100012 China School of Civil and Environmental Engineering Georgia Institute of Technology Atlanta GA 30332 USA School of Energy Resources and Department of Chemical & Petroleum Engineering University of Wyoming Laramie WY 82071 USA Jiangsu Environmental Monitoring Center 241Fenghuangxijie Road Nanjiang 210036 China 

出 版 物：《Journal of Environmental Sciences》 (环境科学学报（英文版）)

年 卷 期：2011年第23卷第2期

页      面：222-227页

核心收录：

学科分类：07[理学] 070601[理学-气象学] 08[工学] 0815[工学-水利工程] 0706[理学-大气科学] 

基　　金：supported by the State Technology Major Special Project on Water Pollution Control(No.2008ZX07101-009,2009ZX07101-015) the National Natural Science Foundation of China(No. 90510009) 

主　　题：lake eutrophication algal bloom global warming 

摘      要：To study how global warming and eutrophication affect water ecosystems, a multiplicative growth Monod model, modified by incorporating the Arrhenius equation, was applied to Lake Taihu to quantitatively study the relationships between algal biomass and both nutrients and temperature using long-term data. To qualitatively assess which factor was a limitation of the improved model, temperature variables were calculated using annual mean air temperature （AT）, water temperature （WT）, and their average temperature （ST）, while substrate variables were calculated using annual mean total nitrogen （TN）, total phosphorus （TP）, and their weighted aggregate （R）, respectively. The nine fitted curves showed that TN and AT were two important factors influencing algal growth; AT limited growth as algal photosynthesis is mainly carried out near the water surface; N leakage of phytoplankton and internal phosphorus load from sediment explains why TN was the best predictor of peak biomass using the Monod model. The fitted results suggest that annual mean algal biomass increased by 0.145 times when annual mean AT increased by 1.0℃. Results also showed that the more eutrophic the lake, the greater the effect AT had on algal growth. Subsequently, the long-term joint effect of annual temperature increase and eutrophication to water ecosystems can be quantitatively assessed and predicted.