Robust models for assessing the effectiveness of technologies and managements to reduce N2O emissions from grazed pastures – Models4Pastures

Models4Pastures will test, improve, and then use, simulation models to provide robust assessments
of the impact of N2O mitigation options in grassland systems across a large geographic and climatic
range. Our models and assessments will take into account the effects of the mitigation option, and
its follow-on consequences (e.g. changes in grazing intensity) for other gases to understand the net
ecosystem effect, food production and variability of production, and the effects on the ability of the
soil to sustain production. This work will be done in the company of current and proposed
FACCE-JPI projects and other international activities,
We will use model inter-comparisons and development to provide improved tools for climate
change research. In our case we will concentrate on exploring N2O mitigation options for grassland
systems and the flow-on impacts of those mitigations on the ability of the soil to sustain production
and on the needs for changed inputs or management of the grasslands. The inclusion of New
Zealand and European teams provides a wide range of datasets, including a new dataset collected
at high temporal resolution and covering different climatic conditions and management practices,
and a range of models that have different formulation (assumptions and parameters) and
approaches. This is the ideal situation to explore the most effective model features and develop
models that are robust across a range of situations that is as wide as possible.
The suite of diverse models also forms an ideal ensemble with which to approach the study of
mitigation options. We expect that this combined approach (challenging/improving existing models
and ensemble modelling) will result in modelling tools that can be used with confidence by
scientists and mitigation assessments that policymakers can be assured are robust. Because many
of the scientists in our project are also involved in other modelling inter-comparison initiatives we
expect our findings will be rapidly and effectively disseminated to end users who will initially be
other scientists wishing to explore potential mitigation options and their consequences.