Determining ecoregional numeric nutrient criteria by stressor-response models in Yungui ecoregion lakes, China.
The importance of developing numeric nutrient criteria has been recognized to protect the designated uses of water bodies from nutrient enrichment that is associated with broadly occurring levels of nitrogen/phosphorus pollution. The identification and estimation of stressor-response models in aquatic ecosystems has been shown to be useful in the determination of nutrient criteria. In this study, three methods based on stressor-response relationships were applied to determine nutrient criteria for Yungui ecoregion lakes with respect to total phosphorus (TP), total nitrogen (TN), and planktonic chlorophyll a (Chl a). Simple linear regression (SLR) models were established to provide an estimate of the relationship between a response variable and a stressor. Multiple linear regressions were used to simultaneously estimate the effect of TP and TN on Chl a. A morphoedaphic index (MEI) was applied to derive nutrient criteria using data from Yungui ecoregion lakes, which were considered as areas with less anthropogenic influences. Nutrient criteria, as determined by these three methods, showed broad agreement for all parameters. The ranges of numeric nutrient criteria for Yungui ecoregion lakes were determined as follows: TP 0.008-0.010 mg/L and TN 0.140-0.178 mg/L. The stressor-response analysis described will be of benefit to support countries in their numeric criteria development programs and to further the goal of reducing nitrogen/phosphorus pollution in China.
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Science, Beijing, 100012, China, huoshouliang@126.com.
Shouliang
S
Huo
Chunzi
C
Ma
Beidou
B
Xi
Zhonghua
Z
Tong
Zhuoshi
Z
He
Jing
J
Su
Fengchang
F
Wu
D002681:China; D002734:Chlorophyll / Q000032:analysis*; D000077194:Chlorophyll A; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods; D005068:Eutrophication; D060106:Lakes; D016014:Linear Models; D008962:Models, Theoretical; D009584:Nitrogen / Q000032:analysis*; D010758:Phosphorus / Q000032:analysis*; D012044:Regression Analysis; D014874:Water Pollutants, Chemical / Q000032:analysis
D014874:Water Pollutants, Chemical; D002734:Chlorophyll; D010758:Phosphorus; D009584:Nitrogen; D000077194:Chlorophyll A