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Identifying ways to reduce agricultural GHG emissions: A multinational modeling approach to optimize C and N cycles between livestock and cropping systems

Edwin Haas from KIT, Germany (Karlsruhe Institute of Technology)

IdenWays

One of the biggest dilemmas for contemporary agriculture is rooted in nutrient management. A large amount of synthetic fertilizer is produced to support production of food and forage, while a large amount of nutrients contained in livestock manure is discarded as waste. The nutrient losses due to both fertilizer application and manure disposal have severely polluted the environment at local to global scales. People have long been being aware of the problem. However, the efforts to improve the nutrient-use efficiency of the agricultural sector have been hampered by a lack of validated tools to track nutrient cycling across animal-plant-soil systems. A number of process-based, biogeochemical models have been developed that provide capabilities to quantify cycles of carbon (C), nitrogen (N) and other nutrients in agro-ecosystems. However only recently do models characterize nutrient cycling in both livestock and cropping systems at the farm scale. This proposed study will adopt and test a group of these models and apply them to a representative group of farms to explore to what degree the environmental impacts of farming can be minimized by maximizing nutrient recycling at the farm scale.
Six farms will be selected from the collaborative partner countries – the U.S., Canada, the U.K., Germany, New Zealand and Australia. The criteria for selection include (1) representativeness in farm nutrient management for the country, (2) accessibility of local climate/soil/management and crop yield data for driving and evaluating model runs, and (3) availability of measured greenhouse gas (GHG) emission data and, where available, nitrate leaching and NH3 volatilization for model validation.
The six partner groups participating in the project have been working in collaboration during the past 10-20 years with a focus on model development. A soil chemistry-cored model, Denitrification-Decomposition or DNDC, has been adopted and developed into new versions by the partner groups. By integrating these models onto a unified platform and characterizing differences in process descriptions, we will develop a tool to serve GHG mitigation across livestock and cropping systems at the farm or regional scale in a way that has already been done for climate models (model ensemble). All of these models represent a large collection of scientific knowledge and experience about structure, function and behaviour of agro-ecosystems. This proposed study will characterize the approaches employed by a range of models and thus contribute to the development of more comprehensive ecosystem theory.
The project will complete four tasks: (1) Evaluating the DNDC family models and possibly unifying some approaches by establishing a common database to supply input information and benchmark cases for model validation; the six farms will provide a foundation for benchmark tests; (2) Testing and modifying these models against observations in the six farms; conduct model comparisons to identify the strengths and weaknesses of the models; collectively improve the models through validation, sensitivity, and comparison tests; (3) Evaluating best management practices for GHG mitigation at the farm scale by running the model array with alternative management scenarios for the six farms; and (4) Disseminating the model array for broader use through the GRA and GRAMP networks.