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Estimating Components of Lake Metabolism by the Free-Water Dissolved-Oxygen Method

James N. McNair
Annis Water Resources Institute


Project description

Importance of lake metabolism to the carbon cycle

Lake metabolism is a set of coupled physiological processes carried out by the living component of lake ecosystems. It includes production of oxygen (O2) by splitting water molecules in the light reactions of oxygenic photosynthesis, uptake of carbon dioxide (CO2) and synthesis of simple carbohydrates in the dark reactions of oxygenic photosynthesis, synthesis of photoautotroph biomass from these simple carbohydrates and additional nutrients (e.g., nitrogen and phosphorus), consumption of dissolved organic matter and existing biomass by heterotrophic organisms to produce new biomass, respiratory uptake of O2 and production of CO2 by aerobic organisms, and several additional processes that usually are less important.

The mass of carbon taken up by oxygenic photoautotrophs in a lake over a specified period of time (e.g., one day or one year) is called gross primary production (GPP). The mass of carbon released by all aerobic organisms in a lake over the same period of time is called total respiration (R). The difference between GPP and R is called net production (NP = GPP - R) and tells us whether the living component of the lake ecosystem takes up more carbon as CO2 than it releases (so the lake is a net carbon sink) or less carbon than it releases (so the lake is a net carbon source) over the specified period of time. The lake is a net carbon sink if GPP > R (NP > 0) and a net carbon source if GPP < R (NP < 0).

Because of the very large number of lakes around the world (especially small lakes, which are the most productive), collectively they play a significant role in the global carbon cycle and in determining atmospheric concentrations of CO2, a major greenhouse gas (Cole et al., 2007; Tranvik et al., 2009). This fact underscores the importance of obtaining accurate estimates of GPP and R in lakes around the world.

New statistical tools for estimating carbon uptake and release by lakes

My work on lake metabolism involved using data from the Muskegon Lake Observatory buoy to estimate GPP, R, and NP via the so-called free-water dissolved-oxygen method. This method requires (1) time series of measured dissolved oxygen (DO) concentrations and several other water-quality and weather variables, (2) a process-based model of DO dynamics in the lake, and (3) a statistical technique for estimating GPP, R, and NP using the measured time series and the model of DO dynamics.

I developed a new statistical estimation technique that is more efficient than previous methods (McNair et al., 2013, 2015). For this work, I used a standard and very simple type of model of DO dynamics in which it is assumed that the upper layer of water in a stratified lake is well mixed at all times and that there is no significant exchange between this layer and deeper water. Under these artificial assumptions, it suffices to measure DO concentrations at a single depth (in this mixed layer) as the basis for estimating GPP, R, and NP. The statistical method, however, can be applied to more-realistic models (McNair et al. 2015).

Numerical examples

Figure 1 shows several examples where I applied the new statistical estimation procedure to time series data for Muskegon Lake. I include examples where the mixed-layer model of DO dynamics accounts for observed dynamics very well, as well as examples where it accounts for them poorly. It turns out that days where the model of DO dynamics accounts for observed dynamics poorly are common in Muskegon Lake. Since the derived estimates of GPP, R, and NP cannot be trusted in such cases, it is important to determine why the model fails and to correct the problem(s). The two main issues probably are the fact that exchanges of DO between the upper few meters of the water column and deeper water are ignored and the fact that the complex and time-varying hydrodynamics of the lake also are ignored.

Examples

Figure 1. Examples of fitting four versions of the model of DO dynamics (rows) to Muskegon Lake time-series data for four different days (columns). Row 4 shows the PAR times series for reference.


Acknowledgement. This work was partially supported by a grant from U.S. EPA Great Lakes Restoration Initiative.

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Selected References

Cole J.J., Prairie, Y.T., Caraco, N.F., McDowell, W.H., Tranvik, L.J., Striegl, R.G., Duarte, C.M., Kortelainen, P., Downing, J.A., Middelburg, J.J., and Melack, J. 2007. Plumbing the global carbon cycle: integrating inland waters into the terrestrial carbon budget. Ecosystems 10: 171--184.

McNair, J.N., Gereaux, L.C., Weinke, A.D., Sesselmann, M.R., Kendall, S.T., and Biddanda, B.A. 2013. New methods for estimating components of lake metabolism based on free-water dissolved-oxygen dynamics. Ecological Modelling 263: 251--263.

McNair, J.N., Sesselmann, M.R., Gereaux, L.C., Weinke, A.D., Kendall, S.T., and Biddanda, B.A. 2015. Alternative methods for estimating components of lake metabolism using process-based models of dissolved-oxygen dynamics. Fundamental and Applied Limnology 186: 21--44.

Tranvik, L.J., and 30 others, 2009: Lakes and reservoirs as regulators of carbon cycling and climate. Limnology and Oceanography 54: 2298--2314.

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Page last modified: 24 December 2018