Abstract
Ruminant production systems are important producers of food, support rural communities and culture, and help
to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these
systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensification
of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights
into the complexity underlying the relationships between climate change, management and policy choices, food
production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant
systemsmodeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate
change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant
growth, yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland
quality and the impact of management changes requires further development. Current livestock models provide
a good basis for predicting animal production; linking these with models of animal health and disease is a priority.
Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants
from livestock farms, and to support the management decisions of farmers from environmental and economic
standpoints. Other models focus on how policy and associated management changes affect a range of economic
and environmental variables at regional, national and European scales. Models at larger scales generally utilise
more empirical approaches than those applied at animal, field and farm-scales and include assumptions which
may not be valid under climate change conditions. It is therefore important to continue to develop more realistic
representations of processes in regional and global models, using the understanding gained from finer-scale
modeling. An iterative process of model development, in which lessons learnt from mechanistic models are applied
to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. Developing
the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer
links between modelers and experimental researchers, and also requires knowledge-sharing and increasing
technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model
development and application is vital for the creation of relevant models, and important in reducing problems related
to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and
other stakeholders under climate change will require collaboration within adequately-resourced, long-term
inter-disciplinary research networks.
Original language | English |
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Pages (from-to) | 24 - 37 |
Number of pages | 14 |
Journal | Agricultural Systems |
Volume | 147 |
Early online date | 25 May 2016 |
DOIs | |
Publication status | First published - 25 May 2016 |
Bibliographical note
1023324Keywords
- Food security
- Livestock systems
- Pastoral systems
- Policy support