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阳宗海湖滨湿地沉积物磷形态及影响因子

Sediment phosphorus fraction in sediments and environmental factors in Yangzonghai lakeside wetland
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摘要 以云南阳宗海南岸湖滨湿地表层沉积物磷形态为研究对象,分析沉积物磷形态含量(磷酸二钙型Ca_2-P、磷酸八钙型Ca_8-P、磷酸铝盐Al-P、磷酸铁盐Fe-P、闭蓄态磷酸盐O-P、磷石灰型Ca_(10)-P)随时间推移的变化特征,探究13项环境因子与磷形态之间的关系,用线性回归分析方法分析环境因子对磷形态的影响.结果表明:湖滨湿地沉积物6种磷形态在分布上无明显季节性规律且各磷形态含量呈湖岸至湖心递减趋势,以Ca_(10)-P含量为主(占全磷的85%),环境因子沉积物全磷、沉积物总砷、沉积物pH、溶解氧、电导率对磷形态影响较大;线性回归分析能较好地预测惰性磷的时空分布规律(平均相对误差为14.77%),而活性磷相对误差较大,达到28%,可能与环境因子变化对活性磷分布影响显著有关. Sediments and lake water were sampled from Yangzonghai lakeside wetland every 3 months from July 2015 to April 2016. The contents of 6 types of phosphorus(P)compounds(Ca2-P, Ca8-P, Al-P, Fe-P, O-P, Ca10-P)were measured. The relationship between 13 environmental factors and P speciation was interpreted using linear regression analysis. Results showed that Ca10-P was the main P form in the sediments, occupying 85% of total P. There was no obvious pattern for P speciation. The contents of all P fractions generally decreased from lakeshore to lake center. Among all environmental factors, total P and total arsenic in the sediments, sediment pH, dissolved oxygen, and electrical conductivity had relatively high influence on P speciation. The accuracy of predicted inert P content based on linear regression analysis was relatively high, with average relative error being 14.77%. While the relative error for active P was high, reaching 28%, which was very likely to be attributed to its susceptibility to environmental factors.
作者 刘云根 王妍 齐丹卉 李梦莹 徐晓军 LIU Yungen;WANG Yan;QI Danhui;LI Mengying;XU Xiaojun(Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan 650504, China;College of Ecology and Soil and Water Conservation, Southwest Forestry University, Kunming, Yunnan 650224, China)
出处 《福建农林大学学报(自然科学版)》 CSCD 北大核心 2019年第2期244-251,共8页 Journal of Fujian Agriculture and Forestry University:Natural Science Edition
基金 国家自然科学基金项目(41761098 21767027 31560147)
关键词 湖滨湿地 沉积物 磷形态 线性回归分析 Yangzonghai lakeside wetland sediments speciation of inorganic phosphorus linear-regression analysis
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