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Quantifying Greenhouse Gas Mitigation Effectiveness through the GRA (Global Research Alliance) Croplands Greenhouse Gas Network (MAGGnet)
Project
Project code: TI-AK-08-PID1534
Contract period: 01.01.2014
- 01.12.2016
Purpose of research: Inventory & Assessment
Agricultural soils are relevant sources of greenhouse gases. The international research network MAGGnet aims at improving models to predict greenhouse gas emissions from agricultural soils and to assess mitigation measures. The project MAGGnet will quantify greenhouse gas (GHG) mitigation potential of cropland management practices based on a recently developed database coordinated by the GRA Croplands Research Group. Specific objectives of the project include: 1. Quantification of the effectiveness of specific mitigation practices (e.g., fertilizer type/rate, tillage, crop rotation, residue management, cover crop, livestock integration, etc.) for arable crops throughout the world using meta-analyses, 2. Quantification of potential tradeoffs in GHG mitigation and crop yield, 3. Identification of critical data gaps 4. Facilitation of communication and cooperation among member countries in GRA Research Groups to improve predictive capabilities of process-based models. A comprehensive database containing land use induced GHG emissions and relevant environmental conditions will be build up within the project. This data base will be based on a data collection within the Global Research Alliance on Agricultural Greenhouse Gases containing metadata of experiments on the effects of mitigation measures on greenhousegas emissions. Validated data will be used in meta-analyses approaches to quantify the effectiveness of mitigation practices through appropiate statistical models.Examined cropland practices may include fertilizer rate/type, tillage, crop rotation, crop type, cover crop use, residue management, livestock integration and other management options depending on the data available. Within regionalisation studies developed statistcal models will help to quantify the mitigation effects of specific management options. The expanded database will be made available to other GRA research groups all of which are involved in improving predictive capabilities of process based models used to predict carbon dioxide, nitrous oxide and methane emissions from land use.
Section overview
Subjects
- Crop Production
- Climate Change
- Computer science
