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United States Department of Agriculture

Agricultural Research Service

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Research Project: USDA AGRI AND FORSTRY GREENHOUSE GAS INVENT. AND EVALUATE THE POTENTIAL OF DIFF. CROPPING SYSTEMS, INCL. BIOFUELS, TO MITIGATE GHG EMISSIONS

Location: Soil Plant Nutrient Research (SPNR)

2013 Annual Report


1a.Objectives (from AD-416):
To assist ARS in producing the U.S. Agriculture and Forestry Greenhouse Gas Inventory and assess the impacts of different crop management practices at the national scale. These efforts will facilitate collaborative efforts between ARS and CSU to continue simulation model development, testing, and refinement of input data to predict the impacts of changing climate and management on greenhouse gas (GHG) emissions, crop yields and soil carbon content.


1b.Approach (from AD-416):
Major products so far include the 2nd edition of the USDA GHG inventory published in 2008 and development of the GRACEnet data entry template. Major improvements in the 2nd edition of the inventory include more refined partitioning of GHG sinks and sources, better quantification of uncertainty and more accurate emission estimates, and quantification of mitigation potentials. Model improvements, tests, and applications used to generate data for the inventory have been reported in 12 journal and several presentations at meetings and symposia. The DAYCENT model was used to perform life cycle analysis for different biofuel cropping systems and initial tests were conducted to implement high resolution NRI data for future GHG inventory simulations.

In addition to producing and improving future editions of the USDA GHG Inventory, general goals for the next 5 years include evaluating biofuel cropping systems and investigating how changes in land use and climate impact crop yields and GHG fluxes. Production and improvement of the U.S. Agriculture and Forestry Greenhouse Gas Inventory requires applying and improving the models used to calculate emissions and their associated uncertainty ranges. Use of more refined model input data, further comparison of model outputs with field measurements, and increased computing capacity lead to more accurate national scale estimates and better characterization of the regional and temporal patterns of emissions. ARS will interact with CSU to incorporate programming expertise, high capacity computing clusters, and data collection into the inventory analyses. CSU will assist ARS in evaluating the impacts and feasibility of different cropping systems, including biofuels by implementing and testing the ability of models to represent the impacts of improved N management technologies and perform regional analysis to identify local best management practices.


3.Progress Report:

ARS and Colorado State University have incorporated database, programming, and computer systems and improved methodologies into GHG inventory and mitigation analyses. These improved methodologies resulted in more reliable emission estimates and are described in the 2013 EPA Inventory of U.S. Greenhouse Gas Emissions and Sinks and in the 4th edition of the U.S. Agriculture and Forestry Greenhouse Gas Inventory to be published by USDA in 2014. The DayCent and CENTURY models were used to help develop Technical Guidelines for Quantifying Greenhouse Gas Sources and Sinks in the Forest and Agriculture Sectors mandated in the 2008 Farm Bill and will be published in 2013. The DayCent model was used to project the impacts of converting pasture to energy can production in Florida. The model has also been used to assess the impacts of winter season biofuel crops on plant production, greenhouse gas emissions, and nitrate leaching in selected counties in the US and regionally for the Chesapeake Bay watershed. Major model improvements have recently been implemented including a methane production submodel and a more sophisticated forest model. ADODR monitoring was conducted via phone calls, e-mails, and on-site meetings. Accomplishments: Inventory of US Greenhouse Gas Emissions and Sinks: 1990-2011 published by EPA: Compared to other economic sectors, estimates of greenhouse gas emissions from agriculture are highly uncertain. Thus, more accurate methods to quantify greenhouse gas emissions from the agricultural sector are required. The recently published Inventory of US Greenhouse Gas Emissions and Sinks: 1990-2011 published by EPA features emissions calculated from model simulations of over 300,000 cropped and grazed areas across the US. Simulating US agricultural lands at finer spatial resolution resulted in narrower uncertainty ranges for nitrous oxide emissions (the major soil GHG gas) compared to previous inventories. The report partitions emissions spatially and by source category so policy makers can identify where mitigation efforts should be targeted. Results from this inventory are reported to The United Nations Framework Convention on Climate Change (UNFCCC). Development of Technical Guidelines for Quantifying Greenhouse Gas Sources and Sinks in the Forest and Agriculture Sectors: Development of these guidelines was mandated in the 2008 Farm Bill. During a series of in person and teleconference meetings the working group decided that the CENTURY model would be used to quantify changes in soil carbon stocks in response to different land management options. For nitrous oxide emissions, the working group decided to use the DayCent model to estimate emissions from cropped and grazed systems under typical land management and then developed adjustment factors to quantify how emissions would change in response to different mitigation practices. Model simulations were completed in 2013, the document describing the guidelines underwent expert review in early 2013, and will be released for public review in July, 2013. Environmental Impacts of Biofuel Feedstock Production Systems: The Energy Independence and Security Act of 2007 mandates the production of 36 billion gallons of biofuel by 2022 and that the greenhouse gas emissions associated with producing this fuel are 20 to 60% lower than petroleum based fuel. Field data from energy cane plots in Florida were used to verify the ability of the DayCent ecosystem model to represent the feedstock yields. The model was then used to quantify yields and greenhouse gas emissions for lands currently used pasture and to project yields and emissions if this land was converted to cellulosic ethanol production using perennial crops. Conversion from pasture to energy cane created a sink for GHGs on Spodosols and reduced the size of the GHG source on Histosols. Recent Model Improvements: A methane (CH4) production submodel was developed and tested using data from rice paddies in China. Field measurements from 25 sites were used for parameterization and 72 sites were used for model evaluation. DayCent accounted for 83% of the variation in methane emissions from the 72 independent sites used for model validation. This new modeling capability will lead to better estimates of GHG emissions from flooded rice systems in the US to be reported in future GHG inventories. The forest version of DayCent (ForCent) was also recently improved and tested. ForCent includes a more sophisticated photosynthesis submodel, a more detailed fine root growth submodel, and a more resolved representation of surface organic matter dynamics. The model was tested using measurements of carbon stock, carbon flux, and isotope data from field studies at the Harvard forest in Massachusetts. ForCent was able to represent decadal-scale measurements in soil C stocks, mean residence times, fluxes, and responses to warming and N addition experiments. This will lead to improved projections of the ability of forests to provide biofuel feedstocks under different climate change scenarios. The CENTURY model was also modified for simulating environmental impacts of woody biomass harvesting and a global sensitivity analysis was performed to better quantify uncertainty ranges for model outputs. Lastly, the model was extended to simulate GHG emissions form turf grass systems. This has the potential to improve GHG emissions estimates from urban soils reported in national GHG inventories.

Peer-reviewed journal articles: Bonan, G. B., Hartman, M. D., Parton, W. J. and Wieder, W. R. 2013. Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4). Global Change Biology, 19: 957–974. doi: 10.1111/gcb.12031. Cheng, K., Ogle, S. M., Parton, W. J., & Pan, G. 2013. Predicting methanogenesis from rice paddies using the DAYCENT ecosystem model. Ecological Modelling, 261, 19-31. Fugui W., D.J. Mladenoff, J.A. Forrester, C. Keough,W.J. Parton. 2013. Global sensitivity analysis of a modified CENTURY model for simulating impacts of harvesting fine woody biomass for bioenergy. Ecological Modelling, 259: 16–23. Duval, B. D., Davis, S. C., Anderson-Teixeira, K. J., Keogh, C., Parton, W. J., Long, S. P., & DeLucia, E. H. Conversion of pasture to energy cane For Bioenergy is predicted to alter greenhouse gas exchange and soil carbon. PLoS ONE, in press. Savage, K. E., Parton, W. J., Davidson, E. A., Trumbore, S. E. and Frey, S. D. 2013. Long-term changes in forest carbon under temperature and nitrogen amendments in a temperate northern hardwood forest. Global Change Biology. doi: 10.1111/gcb.12224. Zhang, Y., Qian, Y., Mecham, B., & Parton, W. J. 2013. Development of Best Turfgrass Management Practices Using the DAYCENT Model. Agronomy Journal, doi: 10.2134/agronj2012.0487. Peer-reviewed book chapter: Parton, W.J., M.P. Gutmann, M.D. Hartman, E.R. Merchant, S.M. Lutz, S.J. DelGrosso. 2013. Simulating biogeochemical impacts of historical land-use changes in the U.S. Great Plains from 1870 to 2003, Chapter 11, pp 287-304. In: Land use and the carbon cycle: Advances in Integrated Science, Management, and Policy. Eds.: D.G. Brown, D.T. Robinson, N.H.F. French, B.C. Reed, Cambridge University Press Peer-reviewed government report: EPA. Inventory of US greenhouse gas emissions and sinks: 1990-2011. 2013. Environmental Protection Agency, Office of Atmospheric Programs. Washington, D.C.


Last Modified: 11/27/2014
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