Abstract: The paper addresses future climate and policy uncertainty for agricultural production and food security in Norway. The two crop simulation models, CSM-CERES-Wheat and, the LINGRA model, were used to determine the impact of climate change on grain yield of spring wheat, and harvest security and biomass yield of timothy, an important forage grass in Northern Europe, respectively. Harvestable yield distributions from the crop models were fed into a stochastic version of the economic sector model Jordmod. Distributions of the rates of agricultural subsidies rates were assessed based on past policy changes and prospective reforms. The model was used to assess the effects of both climate and policy uncertainty on agricultural production, land use, and national food security. Jordmod is comprised of a supply module in which stochastic profits for more than 300 regional farms are maximized and a deterministic market module which maximizes social welfare in the agricultural sector. Socio-economic scenarios were developed around the level of ambition of Norwegian agricultural policy makers. The model results were contrasted with the deterministic results based on average yield and payment rates. The innovation of this paper lays in assessing the combined effects of future climate and policy uncertainty for the agricultural sector in Norway. It also highlights the potential errors made by neglecting these types of uncertainty in economic modelling. No Label

Abstract: The primary objective of this study was to assess the status and priorities for future development in modelling of the impacts of animal health on greenhouse gas (GHG) emissions. It also aimed to facilitate communication between experimental researchers and modellers by defining a list of parameters that are needed to model livestock health and disease, and the impact of health conditions on GHG emissions. The summary presented here provides a brief overview of ongoing work, which the L2.1/L2.2 partners, with support from the Global Research Alliance Animal Health Network (GRA AHN), is currently developing into a paper for publication in a peer reviewed journal.

Abstract: The purpose of this report is to propose a general procedure for sensitivity analysis when used to evaluate system sensitivity to climate change, including uncertainty information. While sensitivity analysis has been largely used to evaluate how uncertainties in inputs or parameters propagate through the model and manifest themselves in uncertainties in model outputs, there is much less experience with sensitivity analysis as a tool for studying how sensitive a system is to changes in inputs. This report should help make clear the differences between these two uses of sensitivity analysis, and provide guidance as to the procedure for using sensitivity analysis for evaluating system sensitivity to climate change. No Label