Nonparametric approaches for estimating regional lake nutrient thresholds |
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| Affiliation: | 1. School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China;2. School of Environment, Nanjing University, Nanjing 210023, China;1. Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Soil Ecology, Center for Agricultural Resources Research, Institute of Genetic and Developmental Biology, The Chinese Academy of Sciences, 286 Huaizhong Road, Shijiazhuang 050021, Hebei, China;2. Water Systems and Global Change Group, Wageningen University and Research, Droevendaalsesteeg 4, Wageningen 6780 PB, the Netherlands;3. Netherlands Institute of Ecology (NIOO-KNAW), Department of Aquatic Ecology, P.O. Box 50, Wageningen 6700 AB, the Netherlands |
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| Abstract: | Nonparametric approaches including a classification and regression tree (CART), a nonparametric changepoint analysis (nCPA) and a Bayesian hierarchical modeling (BHM) method were developed to determine ecoregional nutrient response thresholds. A CART analysis revealed that hierarchical structure was important for predicting Chl a concentrations from total nitrogen (TN) and total phosphorus (TP). The nCPA and BHM methods confirmed the CART results for each node in the tree, and the 90% confidence interval for each threshold was calculated to quantify uncertainty. The CART, nCPA, and BHM methods suggested that the nutrient criteria differed significantly within certain nutrient ecoregions and that numerical nutrient criteria of 0.0150–0.222 mg/L TP and 0.300–1.766 mg/L TN may control Chl a concentrations in the various lake ecoregions. The results of this analysis suggest that the integration of CART, nCPA and BHM might be useful for determining nutrient thresholds. |
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| Keywords: | Nutrient threshold Classification and regression tree Nonparametric changepoint analysis Bayesian hierarchical modeling Lake ecoregion |
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