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Chlorophyll–nutrient relationships of different lake types using a large European dataset

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Abstract

In Europe there is a renewed focus on relationships between chemical determinands and ecological impact as a result of the Water Framework Directive (WFD). In this paper we use regression analysis to examine the relationship of growing season mean chlorophyll a concentration with total phosphorus and total nitrogen using summary data from over 1,000 European lakes. For analysis, lakes were grouped into types with three categories of mean depth, alkalinity and humic content. The lakes were also divided into broad geographic regions covering Atlantic, Northern, Central/Baltic and for some types the Mediterranean areas of Europe. Chlorophyll a was found to be significantly related to both total phosphorus and total nitrogen, although total phosphorus was almost always found to be the best predictor of chlorophyll. Different nutrient chlorophyll relationships were found for lakes according to mean depth and alkalinity, although no significant effect of geographic region or humic content was found for the majority of lake types. We identified three groups of lakes with significantly different responses. Deep lakes had the lowest yield of chlorophyll per unit of nutrient, low and moderate alkalinity shallow lakes the highest and high alkalinity lakes were intermediate. We recommend that the regression models provided for these three lake groups should be used for lake management in Europe and discuss the limitations of such models.

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Authors and Affiliations

  1. Environment Agency (EA), Reading, UK

    G. Phillips

  2. Finnish Environment Institute (SYKE), Helsinki, Finland

    O.-P. Pietiläinen

  3. Centre for Ecology and Hydrology (CEH), Edinburgh, UK

    L. Carvalho

  4. Joint Research Centre (JRC), Ispra, Italy

    A. Solimini, A. Lyche Solheim & A. C. Cardoso

  5. Norwegian Institute for Water Research (NIVA), Oslo, Norway

    A. Lyche Solheim

Authors
  1. G. Phillips
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  2. O.-P. Pietiläinen
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  3. L. Carvalho
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  4. A. Solimini
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  5. A. Lyche Solheim
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  6. A. C. Cardoso
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Corresponding author

Correspondence to G. Phillips.

Appendices

Appendices

Appendix 1. Relationship between summer mean total phosphorus (μg l−1) and chlorophyll a (μg l−1) in lakes grouped by alkalinity and mean depth. Solid lines show modelled regressions, upper and lower 90% confidence intervals. Dotted lines show modelled regressions ±95th percentile of regression residuals.

Appendix 2. Equations to calculate expected chlorophyll a from total phosphorus. The upper and lower boundary values are very similar to the 90% confidence limit of the regression and are determined by adding the 95th and 5th percentiles of the regression residuals. For any particular TP value approximately 90% of lakes will have a chlorophyll concentration below the upper boundary and above the lower boundary.

 

Model 5 Low and moderate alkalinity, shallow and very shallow lakes

Upper boundary

Log10[Chl] = −0.528 + 1.108 Log10[TP] + 0.278

Regression

Log10[Chl] = −0.528 + 1.108 Log10[TP]

Lower boundary

Log10[Chl] = −0.528 + 1.108 Log10[TP] − 0.346

Model 6 High alkalinity shallow and very shallow lakes

Upper boundary

Log10[Chl] = −0.306 + 0.868 Log10[TP] + 0.352

Regression

Log10[Chl] = −0.306 + 0.868 Log10[TP]

Lower boundary

Log10[Chl] = −0.306 + 0.868 Log10[TP] + −0.500

Model 7 All deep lakes

Upper boundary

Log10[Chl] = −0.286 + 0.776 Log10[TP] + 0.306

Regression

Log10[Chl] = −0.286 + 0.776 Log10[TP]

Lower boundary

Log10[Chl] = −0.286 + 0.776 Log10[TP] + 0.305

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Phillips, G., Pietiläinen, OP., Carvalho, L. et al. Chlorophyll–nutrient relationships of different lake types using a large European dataset. Aquat Ecol 42, 213–226 (2008). https://doi.org/10.1007/s10452-008-9180-0

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