Improved modeling of soil nitrogen loss. Nitrogen losses via advection and gaseous emissions show improvement in the new Equilibrium Chemistry Approximation (ECA) approach that represents multi-substrate, multi-consumer environment. Zhu and Riley (2016), doi:10.1038/nclimate2696.
Quantifying impacts of spatial scaling on environmental controls and spatial heterogeneity of soil carbon stocks. Spatial scaling of soil organic carbon stocks studied to improve representation of heterogeneity in biogeochemicaal land surface models. Mishra and Riley (2015) doi:10.5194/bg-12-3993-2015.
BGC Feedbacks Researchers Report the Latest Global Biogeochemistry Science and Host the ILAMB Town Hall Meeting at the American Geophysical Union (AGU) Fall Meeting in San Francisco in December.
Radiocarbon constraints imply reduced carbon uptake by soils during the 21st century. He et al. (2016), doi:10.1126/science.aad4273.
Climate change impacts on ocean net primary production and export production are regulated by increasing stratification and phytoplankton community structure in CMIP5 models. Fu et al. (2016), doi:10.5194/bg-13-5151-2016.
Drought severity mediated by plant responses to increasing atmospheric carbon dioxide. Swann et al. (2016), doi:10.1073/pnas.1604581113.
Strategies for improving predictions of heterotrophic respiration. Decomposition Functional Types (DFTs) proposed for improving the representation of heterotrophic respiration at large scales in Earth system models. Bond-Lamberty et al. (2016), doi:10.1002/ecs2.1380.
Human-induced greening of the northern extratropical land surface. Researchers demonstrate first evidence of discernible human fingerprint on physiological vegetation changes. Mao et al. (2016), doi:10.1038/nclimate3056
How does phosphorus cycling affect carbon uptake in the Amazon? Researchers use nwe model simulations to show that considering P dynamics reduced the simulated historical terrestrial carbon sink by about 26%. Yang et al. (2016), doi:10.1002/2016GL069241.
ILAMB Benchmarking System (v2) Released: New software framework released for systematically assessing land model fidelity through comparison of 24 variables with 60 observational datasets. Collier et al. (2016), doi:10.18139/ILAMB.v002.00/1251621.
Spatial representation of high latitude soil properties in CMIP5 Earth system models. Observations, spatial analysis, undertainty analysis used for data-model comparison of permafrost affected regions. Mishra et al. (2016), doi:10.1016/j.geoderma.2016.04.017.
Greening of the Earth and responsible driving mechanisms. International team of researchers finds a persistent and widespread increase of growing season integrated leaf area index (GSILAI) over 25-50% of the global vegetated area.
Researchers study temperature influence on phytoplankton community growth rates. Sherman et al. (2016), doi:10.1002/2015GB005272.
Can representing leaf and root traits improve model predictions? We developed a new mechanistic model that links leaf nitrogen and plant productivity and represents root-scale uptake kinetics. Ghimire et al. (2016), doi:10.1002/2015MS000538.
Modeling the Carbon Cycle as a Nonautonomous System: We developed a theory for transit times and mean ages for the terrestrial carbon cycle as a nonautonomous compartmental system. Rasumussen et al. (2016), doi:10.1007/s00285-016-0990-8.
Predicting biomass of hyperdiverse and structurally complex central Amazonian forests. Comparison of 12 tree estimation models for six forest scenarios shows generic global or pantrompical biomass estimation models can lead to strong biomass biases. Magnabosco Marra et al. (2016), doi:105194/bg-13-1553-2016.
Attribution of changes in global wetland methane emissions from pre-industrial to present. A methane model, integreated into a land model, was used to examine the sensitivity of emissions to climate, carbon dioxide, nitrogen deposition, inundation, and land use. Paudel et al. (2016), doi:10.1088/1748-9326/11/3/034020.
Responses of two nonlinear microbial models to warming and increased carbon input. International group interrogates responses of proposed nonlinear microbial models to understand behavior of carbon dioxide efflux and carbon storage. Wang et al. (2016), doi:10.5194/bg-13-887-2016.
Multiple soil nutrient competition between plants, microbes, and mineral surfaces. A new multi-nutrient competition model that accounts for competition among plant roots, decomposing microbes, nitrifiers, denitrifiers, and mineral surfaces tested and calibrated at tropical forest sites. Zhu et al. (2016), doi:10.5194/bg-13-341-2016.
Improving model structures for analyzing priming. Researchers used a multi-pool soil carbon model to show that the traditional one-pool approach is not adequate to infer priming. Georgiou et al. (2015), doi:10.1111/gcb.13039.
How can we most directly combine datasets to estimate the magnitude of the permafrost carbon-climate feedback? New synthesis of syntheses is used to quantify the permafrost carbon-climate feedback. Koven et al. (2015), doi:10.1098/rsta.2014.0423
Marine systems model used to estimate the global distributions and surface activities of organic macromolecules. Offline simulations of a mechanistic marine biogeochemistry model were used to calculate concentration distributions of organic macromolecules as well as fractional surfactant coveraages and surface excess concentrations. Ogunro et al. (2015), doi:10.1007/s10533-015-0136-x
Incorporating phosphorus cycling into global scale modeling efforts: A worthwhile tractable endeavor. Researchers developed a road map for including phosphorus cycling in Earth system models. Reed et al. (2015), doi:101111/nph.13521
Disentangling climatic and anthropogenic controls on terrestrial evapotranspiration (ET) trends. Changing climate found to be dominant control on ET spatiotemporal variations in ET with atmospheric carbon dioxide being second most important. Mao et al. (2015), doi:10.1088/1748-9326/10/9/094008
What processes most strongly govern terrestrial carbon cycle feedbacks in Earth System Models? New research identifies the key carbon cycle processes responsible for model uncertainty and highlights interaction between productivity and soil decomposition. Koven et al. (2015), doi:10.5194/bg-12-5211-2015
UCI and NASA researchers uncover link between Amazon fire risk and devastating hurricanes. Scientists find that warmer-than-usual waters in the North Atlantic contribute to both high wildfire risk in the Amazon basin and strong hurricanes along North Atlantic shorelines. Chen et al. (2015). doi:10.1002/2015GL064505

Welcome to the RUBISCO Science Focus Area Website

Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO)

As Earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model predictions. To advance our understanding of biogeochemical processes and their interactions with climate under conditions of increasing atmospheric carbon dioxide (CO2), we need to develop new ways to use observations to constrain model results and inform model development. Better representation of biogeochemistry–climate feedbacks and ecosystem processes in ESMs is essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

In an effort sponsored by the U.S. Department of Energy’s Office of Science through the Regional and Global Model Analysis (RGMA) Program Area, a diverse team from Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory, the University of California at Irvine, the National Center for Atmospheric Research, the University of Michigan, Los Alamos National Laboratory, Sandia National Laboratories, and Northern Arizona University is developing new diagnostic approaches for evaluating ESM biogeochemical process representations. This research effort supports the International Land Model Benchmarking (ILAMB) Project by creating an open source benchmarking system that leverages a growing collection of laboratory, field, and remote sensing data. This benchmarking system, which will be extended to include ocean biogeochemistry, is expected to contribute model analysis and evaluation capabilities to phase 6 of the Coupled Model Intercomparison Project (CMIP6) and future modeling experiments. In addition, the researchers will use this system to engage experimentalists, including those in DOE’s Terrestrial Ecosystem Science Program, in identifying model weaknesses and needed measurements and field experiments.