 |
| Titel |
CO2 flux determination by closed-chamber methods can be seriously biased by inappropriate application of linear regression |
| VerfasserIn |
L. Kutzbach, J. Schneider, T. Sachs, M. Giebels, H. Nykänen, N. J. Shurpali, P. J. Martikainen, J. Alm, M. Wilmking |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1726-4170
|
| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 4, no. 6 ; Nr. 4, no. 6 (2007-11-20), S.1005-1025 |
| Datensatznummer |
250001995
|
| Publikation (Nr.) |
 copernicus.org/bg-4-1005-2007.pdf |
|
|
|
|
|
| Zusammenfassung |
| Closed (non-steady state) chambers are widely used for quantifying carbon
dioxide (CO2) fluxes between soils or low-stature canopies and the
atmosphere. It is well recognised that covering a soil or vegetation by a
closed chamber inherently disturbs the natural CO2 fluxes by altering
the concentration gradients between the soil, the vegetation and the
overlying air. Thus, the driving factors of CO2 fluxes are not constant
during the closed chamber experiment, and no linear increase or decrease of
CO2 concentration over time within the chamber headspace can be
expected. Nevertheless, linear regression has been applied for calculating
CO2 fluxes in many recent, partly influential, studies. This approach
has been justified by keeping the closure time short and assuming the
concentration change over time to be in the linear range. Here, we test if
the application of linear regression is really appropriate for estimating
CO2 fluxes using closed chambers over short closure times and if the
application of nonlinear regression is necessary. We developed a nonlinear
exponential regression model from diffusion and photosynthesis theory. This
exponential model was tested with four different datasets of CO2 flux
measurements (total number: 1764) conducted at three peatlands sites in
Finland and a tundra site in Siberia. Thorough analyses of residuals
demonstrated that linear regression was frequently not appropriate for the
determination of CO2 fluxes by closed-chamber methods, even if closure
times were kept short. The developed exponential model was well suited for
nonlinear regression of the concentration over time c(t) evolution in the
chamber headspace and estimation of the initial CO2 fluxes at closure
time for the majority of experiments. However, a rather large percentage of
the exponential regression functions showed curvatures not consistent with
the theoretical model which is considered to be caused by violations of the
underlying model assumptions. Especially the effects of turbulence and
pressure disturbances by the chamber deployment are suspected to have caused
unexplainable curvatures. CO2 flux estimates by linear regression can
be as low as 40% of the flux estimates of exponential regression for
closure times of only two minutes. The degree of underestimation increased
with increasing CO2 flux strength and was dependent on soil and
vegetation conditions which can disturb not only the quantitative but also
the qualitative evaluation of CO2 flux dynamics. The underestimation
effect by linear regression was observed to be different for CO2 uptake
and release situations which can lead to stronger bias in the daily,
seasonal and annual CO2 balances than in the individual fluxes. To
avoid serious bias of CO2 flux estimates based on closed chamber
experiments, we suggest further tests using published datasets and recommend
the use of nonlinear regression models for future closed chamber studies. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|