Carbon Dynamics and Land-Use Choices: Building a Regional-Scale Multidisciplinary Model

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over fifty years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.carbon, sequestration, climate change, land use, modelling

Carbon Dynamics and Land-use Choices: Building a Regional-scale Multidisciplinary Model

Policy enabling tropical forests to approach their potential contribution to global-climate-change mitigation requires forecasts of land use and carbon storage on a large scale over long periods. In this paper, we present an integrated modeling methodology that addresses these needs. We model the dynamics of the human land-use system and of C pools contained in each ecosystem, as well as their interactions. The model is national scale, and is currently applied in a preliminary way to Costa Rica using data spanning a period of over fifty years. It combines an ecological process model, parameterized using field and other data, with an economic model, estimated using historical data to ensure a close link to actual behavior. These two models are linked so that ecological conditions affect land-use choices and vice versa. The integrated model predicts land use and its consequences for C storage for policy scenarios. These predictions can be used to create baselines, reward sequestration, and estimate the value in both environmental and economic terms of including C sequestration in tropical forests as part of the efforts to mitigate global climate change. The model can also be used to assess the benefits from costly activities to increase accuracy and thus reduce errors and their societal costs.carbon, sequestration, climate change, land use, modelling

Simulation of nitrous oxide and nitric oxide emissions from tropical primary forests in the Costa Rican Atlantic Zone

Nitrous oxide (N2O) and nitric oxide (NO) are important atmospheric trace gases participating in the regulation of global climate and environment. Predictive models on the emissions of N2O and NO emissions from soil into the atmosphere are required. We modified the CENTURY model (Soil Sui. Sec. Am. J., 51 (1987) 1173) to simulate the emissions of N2O and NO from tropical primary forests in the Atlantic Zone of Costa Rica at a monthly time step. Combined fluxes of N2O and NO were simulated as a function of gross N mineralization and water- filled pore space (WFPS). The coefficients for partitioning N2O from NO were derived from field measurements (Global Biogeochem. Cycles, 8 (1994) 399). The modified CENTURY was calibrated against observations of carbon stocks in various pools of forest ecosystems of the region, and measured WFPS and emission rates of N2O and NO from soil to the atmosphere. WFPS is an important factor regulating nutrient cycling and emissions of N2O and NO from soils making the accuracy of the WFPS prediction central to the modeling process. To do this, we modified the hydrologic submodel and developed a new method for the prediction of WFPS at the monthly scale from daily rainfall information. The new method is based on: (1) the relationship between monthly rainfall and the number of rainfall events, and (2) the relative cumulative frequency distribution of ranked daily rainfall events. The method is generic and should be applicable to other areas. Simulated monthly average WFPS was 0.68+/-0.02 - identical with the field measurement average of 0.68+/-0.02 from the annual cycle observed by Keller and Reiners (Global Biogeochem. Cycles, 8 (1994) 399). Simulated fluxes of N2O and NO were 52.0+/-9.4 mg-N m(-2) month (1) and 6.5+/-0.7 mg-N m(-2) month(-1), respectively, compared with measured averages of 48.2+/-11.0 mg-N m(-2) month(-1) and 7.1+/-1.1 mg-N m(-2) month (1). The simulated N2O/NO ratio was 11.2+/-1.9 compared with the measured value of 10.9+/-4.7. WFPS is the dominant determinant of the fraction of gross N mineralization that is emitted from the soil as N2O and NO. If WFPS were not limiting during part of the year, this fraction would be 4.2%. With some periods of lower WFPS, the realized fraction is 2.2%. Because of the strong relationships between N2O and NO emission rates and rainfall and its derivative, WFPS, these moisture variables can be used to scale up nitrogen trace gas fluxes from sites to larger spatial scales. (C) 2000 Elsevier Science Ltd. All rights reserved