Abstract: Adaptation of agriculture to climate change will be driven at the farm level in first place. The MONICA model was employed in four different modelling exercises for demonstration and testing different management options for farmers in Germany to adjust their production system. 30-Year simulations were run for the periods 1996-2025 and 2056-2085 using future climate data generated by a statistical method on the basis of measured data from 1961 to 2000 and the A1B scenario of the IPCC (2007a). Crop rotation designs that are expected to become possible in the future due to a prolonged vegetation period and at the same time shortened cereal growth period were tested for their likely success. The model suggested that a spring barley succeeding a winter barley may be successfully grown in the second half of the century, allowing for a larger yields by intensification of the cropping cycle. Growing a winter wheat after a sugar beet may lead to future problems as late sowing makes the winter wheat grow into periods prone to drought. Irrigation is projected to considerably improve and stabilise the yields of late cereals and of shallow rooting crops (maize and pea) on sandy soils in the continental climate part of Germany, but not in the humid West. Nitrogen fertiliser management needs to be adjusted to increasing or decreasing yield expectations and for decreasing soil moisture. On soils containing sufficient amounts of Moisture and soil organic matter, enhanced mineralisation is expected to compensate for a greater N demand. (C) 2012 Elsevier B.V. All rights reserved.

Abstract: The Mediterranean region has always shown a marked inter-annual variability in seasonal weather, creating uncertainty in decisional processes of cultivation and livestock breeding that should not be neglected when modeling farmers’ adaptive responses. This is especially relevant when assessing the impact of climate change (CC), which modifies the atmospheric variability and generates new uncertainty conditions, and the possibility of adaptation of agriculture. Our analysis examines this aspect reconstructing the effects of inter-annual climate variability in a diversified farming district that well represents a wide range of rainfed and irrigated agricultural systems in the Mediterranean area. We used a Regional Atmospheric Modelling System and a weather generator to generate 150 stochastic years of the present and near future climate. Then, we implemented calibrated crop and livestock models to estimate the corresponding productive responses in the form of probability distribution functions (PDFs) under the two climatic conditions. We assumed these PDFs able to represent the expectations of farmers in a discrete stochastic programming (DSP) model that reproduced their economic behaviour under uncertainty conditions. The comparison of the results in the two scenarios provided an assessment of the impact of CC, also taking into account the possibility of adjustment allowed by present technologies and price regimes. The DSP model is built in blocks that represent the farm typologies operating in the study area, each one with its own resource endowment, decisional constraints and economic response. Under this latter aspect, major differences emerged among farm typologies and sub-zones of the study area. A crucial element of differentiation was water availability, since only irrigated C3 crops took full advantage from the fertilization effect of increasing atmospheric CO2 concentration. Rainfed crop production was depressed by the expected reduction of spring rainfall associated to the higher temperatures. So, a dualism emerges between the smaller impact on crop production in the irrigated plain sub-zone, equipped with collective water networks and abundant irrigation resources, and the major negative impact in the hilly area, where these facilities and resources are absent. However intensive dairy farming was also negatively affected in terms of milk production and quality, and cattle mortality because of the increasing summer temperatures. This provides explicit guidance for addressing strategic adaptation policies and for framing farmers’ perception of CC, in order to help them to develop an awareness of the phenomena that are already in progress, which is a prerequisite for effective adaptation responses.

Abstract: Agricultural vulnerability to climate change is likely to vary considerably between agro-environmental regions. Exemplified on Austrian cropland, we aim at (i) quantifying climate change impacts on agricultural vulnerability which is approximated by the indicators crop yields and gross margins, (ii) developing robust crop production portfolios for adaptation, and (iii) analyzing the effect of agricultural policies and risk aversion on the choice of crop production portfolios. We have employed a spatially explicit, integrated framework to assess agricultural vulnerability and adaptation. It combines a statistical climate change model for Austria and the period 2010-2040, a crop rotation model, the bio-physical process model EPIC (Environmental Policy Integrated Climate), and a portfolio optimization model. We find that under climate change, crop production portfolios include higher shares of intensive crop management practices, increasing average crop yields by 2-15% and expected gross margins by 3-18%, respectively. The results depend on the choice of adaptation measures and on the level of risk aversion and vary by region. In the semi-arid eastern parts of Austria, average dry matter crop yields are lower but gross margins are higher than in western Austria due to bio-physical and agronomic heterogeneities. An abolishment of decoupled farm payments and a threefold increase in agri-environmental premiums would reduce nitrogen inputs by 23-33%, but also crop yields and gross margins by 18-37%, on average. From a policy perspective, a twofold increase in agri-environmental premiums could effectively reduce the trade-offs between crop production and environmental impacts. (C) 2015 Elsevier Ltd. All rights reserved.