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    Estimating Nutrients and Chlorophyll a Relationships in Finnish Lakes
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    Finnish Environment Institute, Helsinki, Finland
    Duke University, Nicholas School of the Environment and Earth Sciences, Durham, North Carolina
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    Environmental Science & Technology

    Cite this: Environ. Sci. Technol. 2006, 40, 24, 7848–7853
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    https://doi.org/10.1021/es061359b
    Published October 24, 2006
    Copyright © 2006 American Chemical Society
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    Abstract

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    We model the response of chlorophyll aa surrogate for the phytoplankton community volumeto variations in lake total phosphorus (TP) and total nitrogen (TN) concentrations. The model is fitted to a large cross-sectional data set from the Finnish Lake monitoring network. The objective is to support the Finnish Government in identifying management actions to achieve compliance of the chlorophyll a concentration standard with a given confidence level and to provide tools for the estimation of critical (target) loads for nutrients in monitored lakes. We develop a Bayesian hierarchical linear model which combines advantages of both the currently preferred non-hierarchical lake-type-specific linear model and lake-specific linear model fitted separately using data from a single lake. The hierarchical model is less biased at lake-level compared to the lake type model. In contrast to the lake model, it predicts the lake specific chlorophyll a response to nutrients outside the lake specific observational range. The hierarchical model is used to calculate probabilities of chlorophyll a concentration exceeding the standard under different nitrogen and phosphorus concentration combinations. These probabilities can be used to estimate acceptable nitrogen−phosphorus concentration combinations by a lake manager. We discuss how our study can be useful in implementing the European Water Framework Directive.

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     Corresponding author phone:  358 19 40300 359; fax:  358 19 40300 391; e-mail:  [email protected].

    Supporting Information Available

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    Table 1:  Observed log(TP), log(TN), log(Chla), and TN/TP-ratio within Lake types. Table 2:  Correlation between log (TP), log(TN), and log(Chla) within Lake types. Table 3:  The number of observations per year from 1988 to 2004. Table 4:  Number of observations within the lake types. Figure 1:  Conditioning plot that illustrates the log(Chla) to log(TP) relationship conditioned on log(TN) concentrations and depth. Figure 2:  Conditioning plot that illustrates the log(Chla) to log(TN) relationship conditioned on log(TP) concentrations and depth. Figure 3:  Fit plot that shows 10, 50, and 90th percentiles of predicted chlorophyll a concentration as a function of observed value for shallow, very humic lakes, type 9. This material is available free of charge via the Internet at http://pubs.acs.org.

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    Cite this: Environ. Sci. Technol. 2006, 40, 24, 7848–7853
    Click to copy citationCitation copied!
    https://doi.org/10.1021/es061359b
    Published October 24, 2006
    Copyright © 2006 American Chemical Society
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