One of the biggest dilemmas for contemporary agriculture is rooted in nutrient management. A large amount of synthetic fertiliser 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 fertiliser 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 characterise nutrient cycling in both livestock and cropping systems at the farm scale.
IdenWays adopts and tests a group of these models and applies them to a representative group of farms to explore to what degree the environmental impacts of farming can be minimised by maximising nutrient recycling at the farm scale.
The IdenWays project developed simulation modeling to improve nutrient management in farm animal-plant-soil systems. Representative farms were selected as test cases from the collaborative partner countries – United States, Canada, United Kingdom, and Germany.
The project focused on the ManureDNDC model, which simulates farm carbon, nitrogen and water cycling, including livestock and manure facility components, livestock and manure management facilities, and a range of farm management activities.
A new version of ManureDNDC was created through this project, distributed to the team for evaluation, and tested against data from the representative farms. The project ended before the model was fully tested and ready for distribution through the Global Research Alliance (GRA). Work on ManureDNDC is ongoing, supported by the California Air Resources Board, to develop a process-based dairy farm emission model for making refined estimations of C and N emissions from California dairy farms.
The Global Research Alliance (GRA) continues to support model intercomparison activies. The GRAMP (GRA Modeling Platform) website that this project contributed to was transfered afterwards to the partner in the United Kingdom (J. Yeluripati, the James Hutton Institute and the University of Aberdeen).
*At the time of the proposal. Please consider this data as an accurate estimate; it may vary during the project’s lifespan.
Total costs include in kind contribution by grant holders and can therefore be higher than the total requested funding.