|Title||Recent advances in integrated assessments of climate change impacts on European agriculture|
|Author(s)||Webber, Heidi; Reidsma, P.; Ewert, Frank|
|Source||In: Book of abstracts. - - p. 38 - 38.|
|Event||MACSUR Science Conference 2017, Berlin, 2017-05-22/2017-05-24|
Plant Production Systems
|Publication type||Abstract in scientific journal or proceedings|
|Abstract||The broad EU public expects agriculture to improve global food security, protect the environment and sustain rural communities and landscapes. Agricultural policy makers must additionally consider resource scarcity and degradation, loss of biodiversity, climate change adaptation and, increasingly, mitigation. Integrated assessment modelling (IAM) can simultaneously consider key
agricultural drivers and the main economic and environmental outcomes in identifying opportunities and balancing trade-offs for EU agriculture in the future. In this review of recent and on-going European scale IAM studies, results are synthesized to quantify the range of uncertainty for key impact variables. Explicit attention is given to the drivers (climate change, socio-economic scenarios, technological) and adaptations considered, their relative importance
across impact variables, feedbacks and cross-scale linkages. Crop management adaptations, widely demonstrated in regional studies, were found to have a large effect on crop yields as simulated with crop models, with relatively less influence on simulated economic variables. The few studies to simultaneously consider climate change and technological development, found yield trends offset yield losses due to climate change and be more important than adaptation.
The MACSUR Coordinate Global and Regional Assessment (CGRA) seeks to explicitly model yields trends with crop models, partnering with the Global Yield Gap Atlas (GYGA) to understand the relative contribution of management and breeding to past trends. Examples of heat and drought risk analysis with crop models are presented, though their consideration in economic studies
remains limited. Finally, opportunities are identified for cross-scale analysis and assessment within MACSUR.