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MODelling vegetation response to EXTREMe Events

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Better models help ensure food security in the face of climate change

Agricultural production and hence food security is increasingly under threat from climate change due to an increase in extreme weather events. Accurate estimations of agricultural production by combining crop-country-forecasting events based on models and agro-climatic indicators allow governments in Europe and around the world to take effective mitigating actions.

Climate Change and Environment icon Climate Change and Environment
Food and Natural Resources icon Food and Natural Resources
Security icon Security

Model-based estimates of agricultural production are key elements for ensuring food security in a world confronted with climate change. Projected climate change calculations can reveal more than just mean temperature rise, by indicating the frequency and severity of floods, droughts, and severe heat and cold. The EU-funded project MODEXTREME (Modelling vegetation response to extreme events) helps agriculture to face extreme climatic events by improving the capability of biophysical models to simulate the responses of vegetation to climate variability and extremes. The two key targets were the production of novel (reusable) libraries of models and the improvement of yield monitoring and forecasting systems. Researchers identified and integrated the responses of main crops, grassland and tree systems to extreme weather events. Yield monitoring and forecasting systems were improved and integrated into process-based models across different climate conditions. Agricultural productivity over the short to medium term was also estimated. Project partners also developed generically usable software units for implementing libraries of models. This extended the multi-model platform BioMA (Biophysical Model Applications) for the simulation of plant growth and development, thus providing direct support to the European Commission Joint Research Centre’s MARS: Monitoring Agricultural ResourceS – Agri4Cast action. Project partners also engaged with local stakeholders to improve yield forecasts. The simulation model used can be extended to virtually any other simulation model of plant growth and development. Agro-climatic indicators were also developed and used to identify extreme weather events during plant growing seasons to determine their impact on agricultural production. MODEXTREME highlighted the potential for modelling tools to show the impact of extreme weather on agricultural systems, thereby reducing uncertainties in the estimates of agricultural production. The developments will also strengthen the role of the EU forecasting system in agriculture.

Keywords

Food security, climate change, extreme weather events, agricultural production, MODEXTREME

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