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Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on integrated assessment and farming systems analysis, and account for adaptation at different levels. With a case study for Flevoland, the Netherlands, we illustrate that (1) crop models cannot account for all relevant climate change impacts and adaptation options, and (2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semiquantitative and participatory method assessing impacts of extreme events shows that there are nevertheless several climate risks. A range of adaptation measures are, however, available to reduce possible negative effects at crop level. In addition, at farm level farmers can change cropping patterns, and adjust inputs and outputs. Also farm structural change will influence impacts and adaptation. While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at crop and farm level, impacts may be less negative in some regions and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world.

Agriculture is vulnerable to climate change in multiple ways. Here, we use the northern region of the Netherlands as a case study to explore how risk assessments for climate change impacts on crop production can address multiple vulnerabilities. We present a methodology, which we call agro climate calendar (ACC) that (i) includes potential yield losses, as well as loss of product quality, and (ii) assesses the risks of a variety of climate factors including weather extremes and the emergence and abundance of pests and diseases. Climate factors are defined for two time slices: 1990 (1976-2005) and 2040 (2026-2055); the frequency of occurrence of the factors is compared for the two periods, and the resulting frequency shifts are presented in a crop calendar on a monthly basis. This yields an indication of the magnitude and direction of changes in climatic conditions that can lead to damage by extreme events and pests and diseases. We present results for the two most important crops in the region, seed potato, and winter wheat. The results provide a good overview of risks from climate factors, and the most important threats and opportunities are identified. This semi-quantitative approach is firmly rooted in farm management, which is the level where operational and strategic decisions are made. Thus, the approach is well suited to assist local stakeholders such as farmers and policy makers to explore farm-level adaptation. This work is complementary to previous modeling work that focused mainly on the relation between mean climate change factors (i.e., temperature) and crop yield.

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