About

CN-MIP is an international study coordinated together with the Integrative Research Group (IRG) of the Global Research Alliance on Agricultural Greenhouse Gases (GRA), which aims at benchmarking simulation models of yield, N₂O and C fluxes, for a wide range of grassland and cropland situations, and testing agricultural mitigation options. The objective is to improve national greenhouse gases (GHG) inventories through Tier 3 method. The Intergovernmental Panel on Climate Change (IPCC) classifies the methodological approaches in three different Tiers, according to the quantity of information required, and the degree of analytical complexity.

The objectives of CN-MIP are:

• Examining whether the use of modeling can provide a credible and generalisable estimation method for the large variability in GHG emissions within and across sites. This variability makes difficult the evaluation of the intensity of emissions at annual and regional scales.
• Developing Tier 3 approach for the wide diversity of cropping systems and climate, worldwide.
• Investigating the effect of agricultural mitigation options on GHG emissions under various climates and systems.

CN-MIP joined the IRG group of the GRA with 10 teams and 9 models to achieve these objectives.

Results

None of the 24 models tested has superior performance in all circumstances. Median prediction of models is a plausible estimator of yields, N₂O emissions and C storage and provides a more robust estimator than individual models. A set of models (ensemble approach) allows unbiased estimate for main crops (maize, wheat, rice and grassland).

CN-MIP has several implications at local, regional and global levels, including the improvement of national inventories from Intergovernmental Panel on Climate Change (IPCC) Tier 1 or 2 methods to Tier 3 methods:

• Ability of modelling approach to provide credible and generalisable estimation method for GHG emissions.
• A set of models uncalibrated for specific conditions which provide an unbiased estimate using the range of experimental errors for the main three crops (maize, wheat, rice).
• The possibility to develop Tier 3 methodology for assessing N₂O regional emissions through the construction of a meta-model, that could be used to assess effectiveness of management options for mitigation.

This project contributes to the international research program 4 per 1000, by evaluating the performance of soil C models to predict evolution of soil C stocks in response to agricultural practices.