Abstract: In the arable farming region Flevoland in The Netherlands climate change, including extreme events and pests and diseases, will likely pose risks to a variety of crops including high value crops such as seed potato, ware potato and seed onion. A well designed adaptation strategy at the farm level can reduce risks for farmers in Flevoland. Currently, most of the impact assessments rely heavily on (modelling) techniques that cannot take into account extreme events and pests and diseases and cannot address all crops, and are thus not suited as input for a comprehensive adaptation strategy at the farm level. To identify major climate risks and impacts and develop an adaptation measure portfolio for the most relevant risks we complemented crop growth modelling with a semi-quantitative and participatory approach, the Agro Climatic Calendar (ACC), A cost-benefit analysis and stakeholder workshops were used to identify robust adaptation measures and design an adaptation strategy for contrasting scenarios in 2050. For Flevoland, potential yields of main crops were projected to increase, but five main climate risks were identified, and these are likely to offset the positive impacts. Optimized adaptation strategies differ per scenario (frequency of occurrence of climate risks) and per farm (difference in economic loss). When impacts are high (in the +2 degrees C and A1 SRES scenario) drip irrigation was identified as the best adaptation measure against the main climate risk heat wave that causes second-growth in seed and ware potato. When impacts are smaller (the +1 degrees C and B2 SRES scenario), other options including no adaptation are more cost-effective. Our study shows that with relatively simple techniques such as the ACC combined with a stakeholder process, adaptation strategies can be designed for whole farming systems. Important benefits of this approach compared to modelling techniques are that all crops can be included, all climate factors can be addressed, and a large range of adaptation measures can be explored. This enhances that the identified adaptation strategies are recognizable and relevant for stakeholders. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: Global climate is changing and food production is very sensitive to weather and climate variations. Global assessments of climate change impacts on food production have been made since the early 1990s, initially with little attention to the uncertainties involved. Although there has been abundant analysis of uncertainties in future greenhouse gas emissions and their impacts on the climate system, uncertainties related to the way climate change projections are scaled down as appropriate for different analyses and in modelling crop responses to climate change, have been neglected. This review paper mainly addresses uncertainties in crop impact modelling and possibilities to reduce them. We specifically aim to (i) show ranges of projected climate change-induced impacts on crop yields, (ii) give recommendations on use of emission scenarios, climate models, regionalization and ensemble crop model simulations for different purposes and (iii) discuss improvements and a few known unknowns’ affecting crop impact projections.

Abstract: Process-based crop models that synthesise the latest scientific understanding of biophysical processes are currently the primary scientific tools available to assess potential impacts of climate change on crop production. Important obstacles are still present, however, and must be overcome for improving crop modelling application in integrated assessments of risk, of sustainability and of crop-production resilience in the face of climate change (e.g. uncertainty analysis, model integration, etc.). The research networks MACSUR and AGMIP organised the CropM International Symposium and Workshop in Oslo, on 10-12 February 2014, and present this CR Special, discussing the state-of-the-art-as well as future perspectives-of crop modelling applications in climate change risk assessment, including the challenges of integrated assessments for the agricultural sector.