Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2 , and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative land uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.

Ecosystems are important and dynamic components of the global carbon cycle, and terrestrial biospheric models (TBMs) are crucial tools in further understanding of how terrestrial carbon is stored and exchanged with the atmosphere across a variety of spatial and temporal scales. Improving TBM skills, and quantifying and reducing their estimation uncertainties, pose significant challenges. The Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal multi-scale and multi-model intercomparison effort set up to tackle these challenges. The MsTMIP protocol prescribes standardized environmental driver data that are shared among model teams to facilitate model–model and model–observation comparisons. This paper describes the global and North American environmental driver data sets prepared for the MsTMIP activity to both support their use in MsTMIP and make these data, along with the processes used in selecting/processing these data, accessible to a broader audience. Based on project needs and lessons learned from past model intercomparison activities, we compiled climate, atmospheric CO2 concentrations, nitrogen deposition, land use and land cover change (LULCC), C3 / C4 grasses fractions, major crops, phenology and soil data into a standard format for global (0.5° × 0.5° resolution) and regional (North American: 0.25° × 0.25° resolution) simulations. In order to meet the needs of MsTMIP, improvements were made to several of the original environmental data sets, by improving the quality, and/or changing their spatial and temporal coverage, and resolution. The resulting standardized model driver data sets are being used by over 20 different models participating in MsTMIP. The data are archived at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov) to provide long-term data management and distribution.

Abstract. Methane (CH4) and nitrous oxide (N2O) are two most important greenhouse gases after carbon dioxide, but their regional and global budgets are far from certain, which is largely owing to uncertainties in scaling up field measurements as well as the poor model representation of processes and factors governing CH4 and N2O exchange between the terrestrial biosphere and atmosphere. In this study, we applied a process-based, coupled biogeochemical model (DLEM – the Dynamic Land Ecosystem Model) to estimate the magnitudes, spatial and temporal patterns of CH4 and N2O fluxes as driven by multiple environmental changes including climate variability, rising atmospheric CO2, increasing nitrogen deposition, tropospheric ozone pollution, land use change and nitrogen fertilizer use. The estimated CH4 and N2O emissions from global land ecosystems were 169.43 ± 32.92 Tg C yr−1 and 12.52 ± 1.52 Tg N yr−1, respectively. Our simulations have indicated a significant (P < 0.01) increasing trend for CH4 (0.75 ± 0.08 Tg C yr−1) and N2O (0.14 ± 0.02 Tg N yr−1) during 1981–2010. CH4 and N2O emissions increased significantly in most climatic zones and continents, especially in tropical region and Asia. The most rapid increase in CH4 emission was found in wetlands (including rice fields and natural wetlands) owing to increased rice field area and climate change; N2O emission increased substantially for all the biome types and the largest increase occurred in upland crops owing to increasing air temperature and nitrogen fertilizer use. Given large increase in CH4 and N2O emission at global scale, we suggest that these two gases together with CO2 have to be simultaneously considered when evaluating if a policy is effective or efficient to reduce global warming in the future.

Terrestrial biosphere models (TBMs) have become an integral tool for extrapolating local observations and understanding of land-atmosphere carbon exchange to larger regions. The North American Carbon Program (NACP) Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP) is a formal model intercomparison and evaluation effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. MsTMIP builds upon current and past synthesis activities, and has a unique framework designed to isolate, interpret, and inform understanding of how model structural differences impact estimates of carbon uptake and release. Here we provide an overview of the MsTMIP effort and describe how the MsTMIP experimental design enables the assessment and quantification of TBM structural uncertainty. Model structure refers to the types of processes considered (e.g., nutrient cycling, disturbance, lateral transport of carbon), and how these processes are represented (e.g., photosynthetic formulation, temperature sensitivity, respiration) in the models. By prescribing a common experimental protocol with standard spin-up procedures and driver data sets, we isolate any biases and variability in TBM estimates of regional and global carbon budgets resulting from differences in the models themselves (i.e., model structure) and model-specific parameter values. An initial intercomparison of model structural differences is represented using hierarchical cluster diagrams (a.k.a. dendrograms), which highlight similarities and differences in how models account for carbon cycle, vegetation, energy, and nitrogen cycle dynamics. We show that, despite the standardized protocol used to derive initial conditions, models show a high degree of variation for GPP, total living biomass, and total soil carbon, underscoring the influence of differences in model structure and parameterization on model estimates.

Abstract. A process-based ecosystem model, the Dynamic Land Ecosystem Model (DLEM), was applied to evaluate the effects of cropland expansion on terrestrial carbon fluxes and pools in South and Southeast Asia in the 20th century. The results indicated that cropland expansion in both regions has resulted in a release of 18.26 Pg C into the atmosphere in the study period. Of this amount, approximately 23 % (4.19 Pg C) was released from South Asia and 77 % (14.07 Pg C) from Southeast Asia. More land area was converted to cropland but less carbon was emitted in South Asia than in Southeast Asia, where forest biomass and soil carbon are significantly higher. Carbon losses in vegetation, soil organic matter, and litter carbon pools accounted for 15.09, 2.01, and 1.60 Pg C, respectively. Significant decreases in vegetation carbon occurred across most regions of Southeast Asia due to continuous cropland expansion and depletion of natural forests. Our study also indicated that it is important to take into account the land use legacy effect when evaluating the contemporary carbon balance in terrestrial ecosystems.

Continental-scale estimations of terrestrial methane (CH4) and nitrous oxide (N2O) fluxes over a long time period are crucial to accurately assess the global balance of greenhouse gases and enhance our understanding and prediction of global climate change and terrestrial ecosystem feedbacks. Using a process-based global biogeochemical model, the Dynamic Land Ecosystem Model (DLEM), we quantified simultaneously CH4 and N2O fluxes in North America's terrestrial ecosystems from 1979 to 2008. During the past 30 years, approximately 14.69 ± 1.64 T g C a−1 (1 T g = 1012 g) of CH4, and 1.94 ± 0.1 T g N a−1 of N2O were released from terrestrial ecosystems in North America. At the country level, both the US and Canada acted as CH4 sources to the atmosphere, but Mexico mainly oxidized and consumed CH4 from the atmosphere. Wetlands in North America contributed predominantly to the regional CH4 source, while all other ecosystems acted as sinks for atmospheric CH4, of which forests accounted for 36.8%. Regarding N2O emission in North America, the US, Canada, and Mexico contributed 56.19%, 18.23%, and 25.58%, respectively, to the continental source over the past 30 years. Forests and croplands were the two ecosystems that contributed most to continental N2O emission. The inter-annual variations of CH4 and N2O fluxes in North America were mainly attributed to year-to-year climatic variability. While only annual precipitation was found to have a significant effect on annual CH4 flux, both mean annual temperature and annual precipitation were significantly correlated to annual N2O flux. The regional estimates and spatiotemporal patterns of terrestrial ecosystem CH4 and N2O fluxes in North America generated in this study provide useful information for global change research and policy making.