| Summary: | AbstractThe cycling of carbon in its gaseous, solid and dissolved forms is of central importance to ecosystem science, particularly, when the natural carbon cycle has been perturbed by human activity. Mathematical models are commonly used to asses and predict global and regional patterns of terrestrial carbon exchange. At the same time, processes operating on smaller (sub-grid) scales are usually outside the scope of the large-scale models exploring climate?biosphere interactions. However, if a sub-grid feature is found repeatedly in a large number of particular realizations, we may expect that its characteristic dynamics are likely to be important even at larger scales. This work examines some of these phenomena. First, a boreal landscape differentiated into forests and peatlands is investigated. Second, the export of dissolved organic carbon (DOC) in peatland streams is assessed.The work described herein mainly addresses methodology, i.e. how approaches to hydrology and ecosystem modelling can be combined. Specifically, the general ecosystem model GUESS was modified and supplied with new modules to be used for peatland simulations. The model was also designed to reproduce soil moisture and related ecosystem properties along a topographical catena. In addition, a completely new model of DOC production, transport and transformation in peat was developed. The data for model development and validation came from boreal catchments in the Vindelns Forest Research Parks, The Swedish University of Agricultural Sciences, Northern Sweden. A relatively good fit between the modelled and measured NEE at the Degerö Stormyr peatland was demonstrated for 2001-2003. Further, the model was used to demonstrate that the NEE was quite insensitive to changes in water table level within the ranges typical for the dominant mire plant community. The newly constructed model was able to reproduce DOC concentrations measured at the outlet of the Kallkälsmyren peatland for 1993-2001. The model suggested that the main drivers for ...
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