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Abstract:
Permanent grasslands constitute the most widespread land use type for agriculturally managed peatlands in Europe. They are typically significant sources of CO2 to the atmosphere as a result of drainage-induced peat decomposition, but quantitative data are still scarce. This study presents an in-depth analysis of CO2 flux variability at the site (n=3) and plot scale (n=9) for different Danish permanent grasslands on peat. Net ecosystem exchange (NEE) of CO2 and ecosystem respiration were monitored over one year with closed dynamic chambers. The first part of the data analysis consisted of a detailed evaluation of the flux dataset to gain insight into the potential effects of fast fluctuations in the wind and light intensity on the plot scale CO2 flux. In the second part of the analysis, gross photosynthesis and ecosystem respiration were modeled on the field and plot scale with candidate sets of simple light and temperature response models commonly applied in ecological studies. The detailed flux dataset analysis revealed that upward concave flux curves, which are not explainable by diffusion theory, can either be the result of a fan-induced increase in headspace turbulence, or of a photosynthesis overshoot into shaded or darkened chamber measurement periods. Instead of discarding such measurements from the dataset, this study proposes the use of linear flux calculation as a way to obtain less biased flux rate estimates. For the carbon balance modeling, it could be shown that annual NEE estimates for a site differ (0.2–0.3kgCO2m−2) between different models available for gap-filling CO2 flux time series even when the models were equally suitable according to statistical evaluation. Overall, all plots showed significant carbon losses over the course of a year (1.5–5.6kgCO2m−2, including harvested aboveground biomass); however, it was not possible to relate spatial differences in the CO2 flux dynamics between and within the study sites to certain peat properties or management types due to high uncertainties in the annual estimates.
