Abstract: Climate change is among the major drivers of agricultural land use change and demands autonomous farm adaptation as well as public mitigation and adaptation policies. In this article, we present an integrated land use model (ILM) mainly combining a bio-physical model and a bio-economic farm model at field, farm and landscape levels. The ILM is applied to a cropland dominated landscape in Austria to analyze impacts of climate change and mitigation and adaptation policy scenarios on farm production as well as on the abiotic environment and biotic environment. Changes in aggregated total farm gross margins from three climate change scenarios for 2040 range between + 1% and + 5% without policy intervention” and compared to a reference situation under the current climate. Changes in aggregated gross margins are even higher if adaptation policies are in place. However, increasing productivity from climate change leads to deteriorating environmental conditions such as declining plant species richness and landscape appearance. It has to be balanced by mitigation and adaptation policies taking into account effects from the considerable spatial heterogeneity such as revealed by the ILM. (C) 2016 Elsevier Ltd. All rights reserved.

Abstract: • Evidence use in EU Impact Assessment reports is limited. • Many scientific studies used farm models for assessment of policies in the EU. • Scientific challenges include understanding farmer decision-making and interactions. • Model codes and data should be published, including evaluation. • Stronger science-policy interaction is required. Farm models are potentially relevant tools for policy impact assessment. Governments and international organizations use impact assessment (IA) as an ex-ante policy process and procedure to evaluate impacts of policy options as part of the introduction of new policies. IA is increasingly used. This paper reviews both the use of farm models in such policy IAs in the European Commission, and the development and use of farm models for policy IA by the scientific community over the past decade. A systematic review was performed, based on 202 studies from the period 2007–2015 and results were discussed in a science-policy workshop. Based on the literature review and the workshop, this paper describes progress in the development of farm models, challenges in their use in policy processes and a research and cooperation agenda. We conclude that main issues for a research agenda include: 1) better understanding of farmer decision-making and effects of the social milieu, with increased focus on the interactions between farmers and other actors, the link to the value chain, and farm structural change; 2) thorough and consistent model evaluation and model comparison, with increased attention for model sensitivity and uncertainty, and 3) the organization of a network of farm modellers. In addition, the agenda for science-policy cooperation emphasizes the need for: 4) synthesizing research evidence into systematic reviews as an institutional element in the existing science-policy-interfaces for agricultural systems, 5) improved and timely data collection, allowing to assess heterogeneity in farm objectives, management and indicators, and 6) stronger science-policy interaction, moving from a research-driven to a user-driven approach.

Abstract: • This study combines crop, livestock and economic models.
• Models interaction is through use of relevant input and output variables.
• Future climate change will result in increased grass and wheat dry matter yields.
• Changes in grass, wheat and milk yields in future reduce farm emissions intensity.
• Changes in future dry matter yields and emissions lead to increased profitability.
There is a scientific consensus that the future climate change will affect grass and crop dry matter (DM) yields. Such yield changes may entail alterations to farm management practices to fulfill the feed requirements and reduce the farm greenhouse gas (GHG) emissions from dairy farms. While a large number of studies have focused on the impacts of projected climate change on a single farm output (e.g. GHG emissions or economic performance), several attempts have been made to combine bio-economic systems models with GHG accounting frameworks. In this study, we aimed to determine the physical impacts of future climate scenarios on grass and wheat DM yields, and demonstrate the effects such changes in future feed supply may have on farm GHG emissions and decision-making processes. For this purpose, we combined four models: BASGRA and CSM-CERES-Wheat models for simulating forage grass DM and wheat DM grain yields respectively; HolosNor for estimating the farm GHG emissions; and JORDMOD for calculating the impacts of changes in the climate and management on land use and farm economics. Four locations, with varying climate and soil conditions were included in the study: south-east Norway, south-west Norway, central Norway and northern Norway. Simulations were carried out for baseline (1961–1990) and future (2046–2065) climate conditions (projections based on two global climate models and the Special Report on Emissions Scenarios (SRES) A1B GHG emission scenario), and for production conditions with and without a milk quota. The GHG emissions intensities (kilogram carbon dioxide equivalent: kgCO2e emissions per kg fat and protein corrected milk: FPCM) varied between 0.8 kg and 1.23 kg CO2e (kg FPCM)− 1, with the lowest and highest emissions found in central Norway and south-east Norway, respectively. Emission intensities were generally lower under future compared to baseline conditions due mainly to higher future milk yields and to some extent to higher crop yields. The median seasonal above-ground timothy grass yield varied between 11,000 kg and 16,000 kg DM ha− 1 and was higher in all projected future climate conditions than in the baseline. The spring wheat grain DM yields simulated for the same weather conditions within each climate projection varied between 2200 kg and 6800 kg DM ha− 1. Similarly, the farm profitability as expressed by total national land rents varied between 1900 million Norwegian krone (NOK) for median yields under baseline climate conditions up to 3900 million NOK for median yield under future projected climate conditions.