The Global Research Alliance Modeling Platform: Predicting Changes in Soil Carbon and Nitrogen

The Global Research Alliance Modeling Platform (GRAMP) is a tool to aid in cost-effectively measuring changes in soil chemistry – specifically, carbon and nitrogen – that can lead to the release of greenhouse gases (GHG).  As an online resource, GRAMP provides ecological models and training materials to support researchers in the biogeochemical modeling community and project developers in carbon markets and ecosystem service markets.  The platform also functions as a virtual community where researchers and others working on biogeochemical models can exchange ideas and improve their understanding of these models, thereby improving their accuracy and performance. 

GRAMP seeks to improve biogeochemical model predictions of soil carbon and nitrogen cycling in the context of climate change to better inform decisions that impact land use changes, to improve accuracy of measurements for use in carbon and ecosystem service markets, and to improve knowledge on which to base policy and program development.  The site only includes information and data on the DeNitrification-DeComposition (DNDC) and ECOSSE models at present, but with additional time and resources, GRAMP intends to increase the number of models profiled by the site.   

C-AGG GRAMP Initiative

To further the research community’s understanding of nitrous oxide (N2O) emissions fluxes from agriculture, and to enhance science-based carbon and ecosystem service market development, C-AGG is supporting the development of a new web-based database and query system to store, analyze and distribute existing field data on N2O emissions, and to add additional peer-reviewed data and datasets as they become available.  Currently, these datasets are not located or accessible in any one location.  This project will create a central repository at the GRAMP website.  In its current form, the GRAMP website has a tool to query meta-data about field measurements and studies on N2O emissions. While this feature is useful and shows where data are potentially available on a geographic basis, the new initiative will expand the feature to enable users to search both meta-data and measurement data for studies of interest - e.g., by geography, by crop, by management system (tillage, form of applied N, etc.).

The new database also links the research community and GHG offset practitioners with appropriate datasets, models and training material related to N2O calculations, adding utility to the database in order to bolster ecosystem service market needs and capabilities.  In addition to uploading and housing all publicly available data on N2O emissions from U.S. agriculture, a key feature of the database will be allowing researchers to directly upload new published, peer-reviewed data to the site as it becomes available -- pending peer review by GRAMP technical experts -- to facilitate wider applicability of models and use of data in more geographic areas where market methodologies for N2O emissions reductions are applicable. 

Furthering Market Development

The new database will enable users to easily access field data on N2O emissions and associated information on crop management, soils and site location needed for independent validation of the biogeochemical models, like the DNDC model.  The DNDC model is a critical science-based, cost-effective underpinning to carbon market methodologies for cropping systems in the US.  The American Carbon Registry (ACR) in November 2010 published a validated, peer-reviewed Methodology for N2O Emissions Reductions from Changes in Fertilizer Management, one of the first market-based methodologies available for this particular project category.  The ACR methodology utilizes the process-based DNDC model to estimate direct N2O emissions for project baseline and emissions reduction scenarios.  For projects to be eligible under the ACR Methodology, the DNDC model must be calibrated for a given region and cropping system through access to data for that region.  Model uncertainty must also be calculated using independent field measurements. The enhancements to the model that are provided by this new work address a previous lack of access to field measurement data that has impeded use of the methodology in most areas.

The new database will overcome a significant barrier to project development by providing project developers and modelers with a comprehensive source of data to validate process models, such as DNDC, in order to cost-effectively and accurately quantify greenhouse gas emissions for market-based nutrient management protocols.

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