Abstract: The European Union (EU) has recently reformed its Common Agricultural Policy (CAP) and, in parallel, has completely abolished the production quotas for milk. These changes will have important consequences for the use of land, of inputs (i.e., water and chemicals) and on the economic performance of rural areas. It is of interest to evaluate the integrated impact of these modifications and of climate change (CC), since the latter could neutralize or reverse some desired effects of the former. For this purpose, this paper evaluates the potential impact of the abolition of milk quotas, as well as of the reform of the first pillar of CAP in two different climate scenarios (present and near future). A bio-economic model simulates the possible adaptation of various farm types in an agricultural area of Southern Italy to these changes, given the available technological options and current market conditions. The main results show that the considered policy changes have small positive impacts on economic and environmental factors of the study area. However, some farm types are more affected. CC can effectively attenuate or reverse several of those effects, especially in some farm types. These results can inform the planning of future changes to the CAP, which will have to act in the context of deeper climate alteration.

Abstract: In this study, we compare the relative importance of climate change to technological, management, price and policy changes on European arable farming systems. This required linking four models: the SIMPLACE crop growth modelling framework to calculate future yields under climate change for arable crops; the CAPRI model to estimate impacts on global agricultural markets, specifically product prices; the bio-economic farm model FSSIM to calculate the future changes in cropping patterns and farm net income at the farm and regional level; and the environmental model INTEGRATOR to calculate nitrogen (N) uptake and losses to air and water. First, the four linked models were applied to analyse the effect of climate change only or a most likely baseline (i.e. B1) scenario for 2050 as well as for two alternative scenarios with, respectively, strong (i.e. A1-b1) and weak economic growth (B2) for five regions/countries across Europe (i.e. Denmark, Flevoland, Midi Pyrenees, Zachodniopomorsld and Andalucia). These analyses Were repeated but assuming in addition to climate change impacts, also the effects of changes in technology and management on crop yields, the effects of changes in prices and policies in 2050, and the effects of all factors together. The outcomes show that the effects of climate change to 2050 result in higher farm net incomes in the Northern and Northern-Central EU regions, in practically unchanged farm net incomes in the Central and Central-Southern EU regions, and in much lower farm net incomes in Southern EU regions compared to those in the base year. Climate change in combination with improved technology and farm management and/or with price changes towards 2050 results in a higher to much higher farm net incomes. Increases in farm net income for the B1 and A1-b1 scenarios are moderately stronger than those for the B2 scenario, due to the smaller increases in product prices and/or yields for the B2 scenario. Farm labour demand slightly to moderately increases towards 2050 as related to changes in cropping patterns. Changes in N2O emissions and N leaching compared to the base year are mainly caused by changes in total N inputs from the applied fertilizers and animal manure, which in turn are influenced by changes in crop yields and cropping patterns, whereas NH3 emissions are mainly determined by assumed improvements in manure application techniques. N emissions and N leaching strongly increase in Denmark and Zachodniopomorski, slightly decrease to moderately increase in Flevoland and Midi-Pyrenees, and strongly decrease in Andalucia, except for NH3 emissions which zero to moderately decrease in Flevoland and Denmark. (C) 2015 Elsevier Ltd. All tights reserved.

Abstract: Impacts of climate change on European agricultural production, land use and the environment depend on its impact on crop yields. However, many impact studies assume that crop management remains unchanged in future scenarios, while farmers may adapt their sowing dates and cultivar thermal time requirements to minimize yield losses or realize yield gains. The main objective of this study was to investigate the sensitivity of climate change impacts on European crop yields, land use, production and environmental variables to adaptations in crops sowing dates and varieties’ thermal time requirements. A crop, economic and environmental model were coupled in an integrated assessment modelling approach for six important crops, for 27 countries of the European Union (EU27) to assess results of three SRES climate change scenarios to 2050. Crop yields under climate change were simulated considering three different management cases; (i) no change in crop management from baseline conditions (NoAd), (ii) adaptation of sowing date and thermal time requirements to give highest yields to 2050 (Opt) and (iii) a more conservative adaptation of sowing date and thermal time requirements (Act). Averaged across EU27, relative changes in water-limited crop yields due to climate change and increased CO2 varied between -6 and + 21% considering NoAd management, whereas impacts with Opt management varied between + 12 and + 53%, and those under Act management between 2 and + 27%. However, relative yield increases under climate change increased to + 17 and + 51% when technology progress was also considered. Importantly, the sensitivity to crop management assumptions of land use, production and environmental impacts were less pronounced than for crop yields due to the influence of corresponding market, farm resource and land allocation adjustments along the model chain acting via economic optimization of yields. We conclude that assumptions about crop sowing dates and thermal time requirements affect impact variables but to a different extent and generally decreasing for variables affected by economic drivers.