Interactions between carbon and nitrogen dynamics in estimating net primary productivity for potential vegetation in North America

We use the terrestrial ecosystem model (TEM), a process-based model, to investigate how interactions between carbon (C) and nitrogen (N) dynamics affect predictions of net primary productivity (NPP) for potential vegetation in North America. Data on pool sizes and fluxes of C and N from intensively studied field sites are used to calibrate the model for each of 17 non-wetland vegetation types. We use information on climate, soils, and vegetation to make estimates for each of 11,299 non-wetland, 0.5° latitude × 0.5° longitude, grid cells in North America. The potential annual NPP and net N mineralization (NETNMIN) of North America are estimated to be 7.032 × 1015 g C yr−1 and 104.6 × 1012 g N yr−1, respectively. Both NPP and NETNMIN increase along gradients of increasing temperature and moisture in northern and temperate regions of the continent, respectively. Nitrogen limitation of productivity is weak in tropical forests, increasingly stronger in temperate and boreal forests, and very strong in tundra ecosystems. The degree to which productivity is limited by the availability of N also varies within ecosystems. Thus spatial resolution in estimating exchanges of C between the atmosphere and the terrestrial biosphere is improved by modeling the linkage between C and N dynamics. We also perform a factorial experiment with TEM on temperate mixed forest in North America to evaluate the importance of considering interactions between C and N dynamics in the response of NPP to an elevated temperature of 2°C. With the C cycle uncoupled from the N cycle, NPP decreases primarily because of higher plant respiration. However, with the C and N cycles coupled, NPP increases because productivity that is due to increased N availability more than offsets the higher costs of plant respiration. Thus, to investigate how global change will affect biosphere-atmosphere interactions, process-based models need to consider linkages between the C and N cycles

The Chinese Impact on GDP Growth and Inflation in the Industrial Countries

The integration of China into the global economy is one of the most spectacular events in economic history. This paper investigates to what extent this process affects output growth and inflation in the advanced countries. A GVAR model is specified to explore interdependencies between business cycles in China and industrial countries, including the US, the euro area and Japan. For robustness, the results are compared to those obtained from leading structural models, such as NiGEM and OEF. Evidence is based on the responses to a Chinese demand shock arising from the recent fiscal stimulus program. The results show that the impact on output growth in the advanced economies can be quite substantial, especially for the Asian region. The expansionary effects in the US and the euro area responses are lower, as trade linkages are less intensive. The multipliers are also reduced by a sizeable effect on inflation, as Chinese firms participate in international production chains.GVAR, Chinese economy, shock transmission

Impacts of land use, restoration, and climate change on tropical peat carbon stocks in the 21st century: Implications for climate mitigation

The climate mitigation potential of tropical peatlands has gained increased attention as Southeast Asian peatlands are being deforested, drained and burned at very high rates, causing globally significant carbon dioxide (CO2) emissions to the atmosphere. We used a process-based dynamic tropical peatland model to explore peat carbon (C) dynamics of several management scenarios within the context of simulated twenty-first century climate change. Simulations of all scenarios with land use, including restoration, indicated net C losses over the twenty-first century ranging from 10 to 100 % of pre-disturbance values. Fire can be the dominant C-loss pathway, particularly in the drier climate scenario we tested. Simulated 100 years of oil palm (Elaeis guineensis) cultivation with an initial prescribed burn resulted in 2400–3000 Mg CO2 ha−1 total emissions. Simulated restoration following one 25-year oil palm rotation reduced total emissions to 440–1200 Mg CO2 ha−1, depending on climate. These results suggest that even under a very optimistic scenario of hydrological and forest restoration and the wettest climate regime, only about one third of the peat C lost to the atmosphere from 25 years of oil palm cultivation can be recovered in the following 75 years if the site is restored. Emissions from a simulated land degradation scenario were most sensitive to climate, with total emissions ranging from 230 to 10,600 Mg CO2 ha−1 over 100 years for the wettest and driest dry season scenarios, respectively. The large difference was driven by increased fire probability. Therefore, peat fire suppression is an effective management tool to maintain tropical peatland C stocks in the near term and should be a high priority for climate mitigation efforts. In total, we estimate emissions from current cleared peatlands and peatlands converted to oil palm in Southeast Asia to be 8.7 Gt CO2 over 100 years with a moderate twenty-first century climate. These emissions could be minimized by effective fire suppression and hydrological restoration

The Time-Series Properties of Aggregate Consumption: Implications for the Costs of Fluctuation

While this is typically ignored, the properties of the stochastic process followed by aggregate consumption affect the estimates of the costs of fluctuations. This paper pursues two approaches to modelling aggregate consumption dynamics and to measuring how much society dislikes fluctuations, one statistical and one economic. The statistical approach estimates the properties of consumption and calculates the cost of having consumption fluctuating around its mean growth. The paper finds that the persistence of consumption is a crucial determinant of these costs and that the high persistence in the data severely distorts conventional measures. It shows how to compute valid estimates and confidence intervals. The economic approach uses a calibrated model of optimal consumption and measures the costs of eliminating income shocks. This uncovers a further cost of uncertainty, through its impact on precautionary savings and investment. The two approaches lead to costs of fluctuations that are higher than the common wisdom, between 0.5% and 5% of per capita consumption.