FACCE-JPI Knowledge Hub co-ordination of livestock/grasslands (LIVEM) component of MACSUR

"There are limited data concerning the adaptation of livestock production systems in Europe to climate change. This means that estimates of baseline impacts are few and therefore analyses of the advantages and disadvantages of particular adaptation strategies difficult to assess. Similarly, risk thresholds and the likelihood of severe events are not well understood. This means that the need for and capacity of both autonomous and planned adaptations is unclear and represents a major gap in the provision of scientific evidence to policymakers and other stakeholders. Major challenges for the Livestock Sub-Theme are: (i) Identify, evaluate and increase the accessibility of relevant datasets for grasslands, livestock production and climate change (ii) Compare models at a variety of spatial scales such as grass growth, grasslands and livestock production systems (including infectious disease) and assess model robustness and uncertainty in their estimates (iii) Integrate models across scales with a central focus on adaptation but consideration also of mitigation measures and potential trade-offs (iv) Disseminate outcomes to inform policymakers , stakeholders and end-users (v) Undertake cross-cutting activities with other themes and integrate whenever possible livestock models with crop and socio-economic models in case studies and integrated pilot studies."

FACCE MACSUR focuses on modelling European agriculture with climate change for food security. The work is organized in three themes on crop, livestock and trade modelling. The partnership consists of 73 partners from 16 countries all over Europe. The overarching challenge is to develop a pan-European capability in the development, use and interpretation of models to perform risk assessments of the impacts of climate change on European agriculture. To address this the following challenges must be met: 1. Identify and address a range of issues between models in different themes to enable their closer integration including issues of scale and data processing. 2. Train a new generation of scientists to work across models which contribute to greater integration of models. This challenge can be described as focusing on the creation of integrated modellers as opposed to integrated models. 3. Determine the contribution that can be made to reducing uncertainty over the impacts of climate change on European food security by adopting integrated models of crop production, animal production and trade.