Network and Modeling Activities within the GRA Croplands Research Group: MAGGnet and GRAMP.

Concurrent efforts to mitigate agricultural greenhouse gases (GHGs) while adapting production practices to projected hardships of climate change will be essential to ensure long-term sustainability and food security. Relevant and timely agricultural research must focus on how to best respond to climate change by utilizing a balance of thoroughly tested and novel management practices and technologies. Mitigation research in agriculture should provide a mechanistic understanding of the underlying processes affecting natural resources, be scalable to provide useful predictions for a range of management scenarios, and be translated in such a way that it effectively supports both adoption of best practices/systems by producers and informed decision making for regional and national policies. In response to these challenges, the Global Research Alliance on Agricultural Greenhouse Gases (GRA) was formed in 2009 to develop trans-national strategies for reducing GHG intensity of agricultural production. To facilitate focused efforts, the GRA is organized in four research groups (Cropland, Livestock, Paddy Rice, Integrative) each of which developed work plans to enable successful collaborations, as well as to share knowledge and best practices, build capacity and capability among participants, and move towards transformative solutions to reduce agricultural GHG emissions. This presentation will review two activities within the GRA Croplands Research Group: MAGGnet and GRAMP. MAGGnet (Managing Agricultural Greenhouse Gases Network) was established to provide a platform for the inventory and analysis of agricultural GHG mitigation research throughout the world. GRAMP (Global Research Alliance Modelling Platform) serves as a web-based modelling platform to link researchers with appropriate datasets, models and training material. Together, MAGGnet and GRAMP have the potential to leverage limited-resource investments by any one country to produce an inclusive, globally-shared meta-database and modelling platform focused on the science of GHG mitigation.