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对湖泊进行分类以量化湖上层叶绿素a与缺氧之间的关系。

Classifying lakes to quantify relationships between epilimnetic chlorophyll a and hypoxia.

作者信息

Yuan Lester L, Pollard Amina I

机构信息

Office of Science and Technology, Office of Water, U.S. Environmental Protection Agency, 1200 Pennsylvania Ave NW, Washington, DC, 20460, USA,

出版信息

Environ Manage. 2015 Mar;55(3):578-87. doi: 10.1007/s00267-014-0412-x. Epub 2014 Dec 4.

Abstract

Excess nutrient loading increases algal abundance which can cause hypoxia in many lakes and reservoirs. We used a divisive partitioning approach to analyze dissolved oxygen profile data collected across the continental United States to increase the precision of estimated relationships between chlorophyll a (chl a) concentrations and the extent of hypoxia in the water column. Chl a concentrations predicted the extent of hypoxia most accurately in lakes that were stratified at the time of sampling with a maximum temperature gradient of at least 1.2 °C/m. Lake elevation, Secchi depth, and lake geometry ratio further refined the specification of groups of lakes with different relationships between chl a and the extent of hypoxia. The statistical relationships between chl a and the extent of hypoxia that were estimated can be used directly for setting management thresholds for chl a in particular types of lakes.

摘要

过量的营养物质负荷会增加藻类数量,这可能导致许多湖泊和水库出现缺氧情况。我们采用了一种分裂分区方法来分析在美国大陆收集的溶解氧剖面数据,以提高叶绿素a(chl a)浓度与水柱缺氧程度之间估计关系的精度。在采样时分层且最大温度梯度至少为1.2°C/m的湖泊中,chl a浓度最准确地预测了缺氧程度。湖泊海拔、塞氏深度和湖泊几何比进一步细化了chl a与缺氧程度之间具有不同关系的湖泊组的分类。所估计的chl a与缺氧程度之间的统计关系可直接用于设定特定类型湖泊中chl a的管理阈值。

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