Forage and more widely grassland systems are difficult to analyze in economic terms because a large proportion of what is produced is not marketed. Economic misestimation of these farm products may dramatically alter projected climate change impacts. This study estimates the economic value of grass and assesses the impact of climatic variations on grassland–livestock systems by taking various environmental and climatic factors into account. Accordingly, grass yield responses to nitrogen inputs (N-yield functions) have been simulated using the grassland biogeochemical PaSim model and then fed into the economic farm-type supply AROPAj model. We developed a computational method to estimate shadow prices of grass production, allowing us to better estimate the effects of climatic variability on grassland and crop systems. This approach has been used on a European scale under two Intergovernmental Panel on Climate Change climate scenarios (AR4 A2 and B1). Results show a significant change in land use over time. Accordingly, due to decreases in feed expenses, farmers may increase livestock, thereby increasing overall greenhouse gas emissions for all scenarios considered. As part of autonomous adaptation by farming systems, N-yield functions extending to pastures and fodders allow us to improve the model and to refine results when marketed and non-marketed crops are considered in a balanced way.