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Free keywords:
North-american grasslands; carbon-dioxide; model; climate;
fluxes; soils; CO2
Abstract:
We used a daily time step ecosystem model (DAYCENT) to simulate ecosystem processes at a daily, biweekly, monthly, and annual time step. The model effectively represented variability of ecosystem processes at each of these timescales. Evolution of CO2 and N2O, NPP, and net N mineralization were more responsive to variation in precipitation than temperature, while a combined temperature-moisture decomposition factor (DEFAC) was a better predictor than either component alone. Having established the efficacy of CENTURY at representing ecosystem processes at multiple timescales, we used the model to explore interannual variability over the period 1949-1996 using actual daily climate data. Precipitation was more variable than temperature over this period, and our most variable responses were in CO2 flux and NEP. Net ecosystem production averaged 6 g C m(-2) yr and varied by 100% over the simulation period. We found no reliable predictors of NEP when compared directly, but when we considered NEP to be lagged by 1 year, predictive power improved. It is clear from our study that NEP is highly variable and difficult to predict. The emerging availability of system-level C balance data from a network of flux towers will not only be an invaluable source of information for assessments of global carbon balance but also a rigorous test for ecosystem models.
