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Predicting participate pools of nitrogen, phosphorus and organic carbon in lakes

机译：预测湖泊中氮，磷和有机碳的参与量

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摘要

The variation between lakes with respect to concentrations of particulate nutrient pools was studied in 126 Norwegian lakes covering a wide range in lake-specific properties. Particulate phosphorus (P) always constituted close to 60% of total P (TP) concentrations. Particulate nitrogen (N) and organic carbon (C) concentrations, on the other hand, were sensitive to several lake characteristics, particularly to TP concentrations. Through optimisation procedures and multivariate regression, the present study presents general empirical models for predicting particulate nutrient concentrations. Furthermore, significant trend shifts in the relationships between TP vs. particulate N and TP vs. particulate organic C were observed at TP = 6 μg l~(-1) and TP = 80 μg l~(-1), suggesting non-linearities in these relationships along the TP gradient. A trend shift in the TP vs. chlorophyll relationship was observed at TP = 90. Taking such non-linearities into account may decrease the uncertainty in predicting particulate N, particulate organic C and chlorophyll.
机译：在126个挪威湖泊中研究了湖泊之间相对于颗粒养分池浓度的变化，这些湖泊涵盖了范围广泛的湖泊特定特性。磷（P）始终占总磷（TP）浓度的近60％。另一方面，颗粒氮（N）和有机碳（C）的浓度对几种湖泊特征特别是TP浓度敏感。通过优化程序和多元回归，本研究提出了用于预测颗粒养分浓度的一般经验模型。此外，在TP = 6μgl〜（-1）和TP = 80μgl〜（-1）时，观察到TP与颗粒N之间的关系以及TP与颗粒有机C之间的关系出现了显着的趋势变化，这表明存在非线性这些关系沿TP梯度变化。在TP = 90时，观察到TP与叶绿素之间的关系发生了趋势变化。考虑到此类非线性因素，可以减少预测颗粒氮，颗粒有机碳和叶绿素的不确定性。

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