You are here:
CLIMATIC EFFECTS ON TUNDRA CARBON STORAGE INFERRED FROM EXPERIMENTAL DATA AND A MODEL
Citation:
Mckane, R., E. B. Rastetter, G. R. Shaver, K. J. Nadelhoffer, A. E. Giblin, J. A. Laundre, AND F. S. Chapin,III. CLIMATIC EFFECTS ON TUNDRA CARBON STORAGE INFERRED FROM EXPERIMENTAL DATA AND A MODEL. Ecology 78(4):1170-1187, (1997).
Description:
We used a process-based model of ecosystem carbon (C) and nitrogen (N)dynamics, MBL-GEM (Marine Biological Laboratory General Ecosystem Model), to integrated and analyze the results of several experiments that examined the response of arctic tussock tundra to manipulations of CO2, temperature, light, and soil nutrients. The experiments manipulated these variables over 3- to 9-yr periods and were intended to simulate abticipated changes in the arctic environment. Our objective was to use the model to extend the analysis of the experimental data so that unmeasured changes in ecosystem C storage and the underlying mechanisms controlling those changes could be estimated and compared. Using an inverse calibration method, we derived a single parameter set for the model that closely simulated the measured responses of tussock tundra to all of the experimental treatments. This parameterization allowed us to infer confidence limits for ecosystem components and processes that were not directly measured in the experiments. Thus, we used the model to estimate changes in ecosystem C storage by inferring key soil processes within the constraints imposed by measured components of the ecosystem C budget. Because tussock tundra is strongly N limited, we hypothesized that changes in ecosystem C storage in response to the experimental treatments would be constrained by several key aspects of C-N interactions: (1) changes in the amount of N in the ecosystem, (2) changes in the C:N ratios of vegetation and soil, and (3) redistribution of N between soil (with a low C:N ratio)and vegetation (with a high C:N ratio). The model results reveal widely differing patterns of change in C-N interactions and constraints on change in ecosystem C storage among treatments. For example, after 9 yr the elevated CO2 (2 x ambient) treatment and the N fertilized (10 g N.m-2.yr-1) treatment increased ecosystem C stocks by 1.4 and 2.9%, respectively. Whereas the increase in the CO2 treatment was due solely to an increase in the C:N ratios of vegetation and soil, the increase in the fertilized treatment was due to increased ecosystem N content and a shift of N from soil to vegetation. In contrast, the greenhouse (3.5o above ambient) and shade (one-half ambient light) treatments decreased ecosystem C stocks by 1.9 and 2.7%, respectively. The primary reason for the net C losses in these treatments was an increase in respiration relative to photosynthesis, with a consequent decrease in the ecosystem C:N ratio. However, when we simulated the elevated temperatures in the greenhouse treatment without the confounding effects of decreased light intensity (an artifact of the greenhouse structures), there was a long-term increase in ecosystem C stocks because of increased photosynthetic respons to the temperature-induced shift of N from soil to vegetation. If our simulated changes in ecsystem C storage are extrapolated for the ~43 Pg C contained in arctic tundras globally, the maximum net gain or loss (~0.3% per yr) from tundra would be equivalent to 0.13 Pg C/yr. Although fluxes of this magnitude would have a relatively minor impact on current changes in atmospheric CO2, the long-term impact on tundra C stores could be significant. The synthesis and insights provided by the model should make it possible to extrapolate into the future with a better understanding of the processes governing long-term changes in tundra C storage.