Acknowledging the spatial heterogeneity in modelling/reconstructing carbon dioxide exchange in a northern aapa mire

Chamber method is commonly used to measure the CO2 exchange from plant communities. Due to low time resolution, actual measurements reflect only momentary CO2 exchange rates. Therefore, a common way to derive seasonal or annual estimates is to establish models describing the response of CO2 exchange to environmental variables, and then to reconstruct the CO2 exchange over the desired time period. There are several alternative ways to obtain the CO2 balance for the entire mire: models can be parameterized by individual sample plots, plant communities or the entire site. Similarly, the CO2 balance can be reconstructed by plots, plant communities or the entire site. We tested how the choice of the modelling and reconstruction approach influences the CO2 exchange estimates for the entire mire and for individual sample plots and plant communities. We measured the CO2 exchange in a spatially heterogeneous sedge-dominated northern aapa mire for two growing seasons. We observed high spatial variation in CO2 balance between the plant communities. We noticed that when the CO2 balances of individual sample plots or plant communities are of interest, using a model appropriate for the entire site may result in biased estimates. In worst case the different modelling approaches may turn the CO2 balance of an individual sample plot from positive to negative. Further, while using the whole ecosystem approach in modelling, the superior ability of chamber method in acknowledging spatial variation is lost. While the modelled growing season CO2 balance of the mire ranged from 232 to 625 g CO2 m−2 depending on the chosen modelling and reconstruction approach, the average estimates still remained within the uncertainty range of one another. Acknowledgement of the spatial variation in plant community level makes the areal estimate more robust to varying weather conditions. Further, the reliability of estimates is improved by explicit formulation of the choices behind the modelling and reconstruction units reflecting the study objectives.