Exploring sustainable farming scenarios at a regional scale: an application to dairy farms in Brittany

The objective of this study was to model land use configuration for a sustainable dairy sector in Brittany, France, using results from Life Cycle Assessment (LCA) in Multiple-Goal Linear Programming (MGLP). To generate future land-use configurations that met environmental targets, the approach required (1) defining a set of current and alternative land-use types, (2) defining a set of characteristics of these land-use types, (3) quantifying these characteristics for all land-use types, (4) calculating the regional sum of each indicator for current land-use types to establish the baseline scenario, and (5) defining scenarios consisting of a set of goals to meet (maximize milk production or farm profit) and environmental constraints not to violate (per-ha limits on nitrate leaching, non-renewable energy use, and greenhouse gas emissions). Existing dairy farms were classified into 5 groups (from organic to intensive) according to their mode of production, quantity of milk production, and fodder-crop and grass area. Alternative land uses, namely 100%-grass-based dairy systems or forest, were characterized to explore the potential effects of replacing current dairy farmland with them. The MGLP model was unable to find a combination of current land-use types that could meet the three environmental constraints while using all of the land available. With alternative land-use types allowed, however, the model maximized milk production while meeting environmental constraints by allocating 55–60, 21–44, and 1–19% of the area to grass-based dairy systems, intensive farms, and forest, respectively, which decreased regional milk production by 8–30%. The trade-offs shown in MGLP results predict consequences of applying environmental constraints on agricultural production, revealing challenges that agricultural policies may face. The major benefits of coupling MGLP and LCA results include (1) taking into account social and economic indicators while considering environmental concerns, (2) quantification of potential environmental impacts to optimize agricultural production from an LCA perspective, (3) consideration of a variety of complementary production modes in a region, and (4) generation of scenarios that can be discussed with stakeholders as support information for environmentally-conscious decision making regarding land use.