C and N Models Intercomparison and Improvement to assess management options for GHG mitigation in agrosystems worldwide – CN-MIP

The “C and N Models Inter-comparison and Improvement to assess management options for
GHG mitigation in agrosystems worldwide” (CN-MIP) addresses theme 1, topic 1 of the FACCE-JPI
2013 call. Our project will coordinate international development, evaluation and inter-comparison of
agricultural process-based models to reduce uncertainty in estimating greenhouse gas emissions from
crops, grassland and livestock systems. The project will focus on improving the simulation of
management options to enable evaluation of credible mitigation strategies adapted to diverse
agrosystems under different climatic conditions. CN-MIP responds to the priority of the core theme 5
"Mitigation of Climate Change" of the FACCE-JPI strategic research agenda, to improve the greenhouse
gas (GHG) inventory methods, particularly the "certified" modellingTIER3 modelling approach for
quantifying emissions and the effects of mitigation options. The project also supports initiatives outlined
in the Global Research Alliance (GRA) on Agricultural Greenhouse Gases, which aim to improve
measurement methodology and modelling, as well as inventory of GHG emissions and C sequestration in
soils. The consortium comprises eleven partners: INRA (France), University of Aberdeen (UK),
Helmholt-Zentrum Postam (GER), University of Florence (IT), CRA-Consiglio per la Ricerca in Agricoltura
(IT), University of Milan (It), University of Sassari (IT), New Zealand Institute for Plant and Food Research
(NZ), Colorado State University (USA), Woods Hole Research Center (USA), Queensland University of
Technology (AU). The proposing partners are experienced modelers and experimentalists, already
involved in internationally funded projects on measuring and modelling of greenhouse gas emissions,soil
carbon sequestration, and reactive nitrogen, for a variety of agricultural conditions (annual crops,
grasslands, tree crops) under temperate, Mediterranean and tropical conditions (GRA CN, Livestock and
Cropland groups, AgMIP, MACSUR, Reactive N RCN, NANORP, etc.). This network will provide connections
and sharing of models, modelling protocols and datasets, but also the necessary interactions with
stakeholders. The project will be undertaken from January 2014 to December 2016, in 4 work packages (i)
Definition of model data requirements, selection of process-based CN models (i.e. DNDC, DNDC mobile,
DSSAT, Roth C, DayCent, PaSim, STICS, APSIM, EPIC, CN-SIM), selection of appropriate databases; (ii)
development of common protocols for modelling and model inter-comparison; (iii) identification and
testing of mitigation options, improvement of models for coverage, predictive capability and reliability;
(iv) dissemination and training. Deliverables will be guidelines for the selection of database and the
simulation of mitigation options, evaluation of uncalibrated and calibrated model performances for an
array of GHG emission outputs, improved model tools, peer-reviewed research papers, communication
and reports to policy makers and stakeholders, and training sessions for students and scientists.