title: SIMS(DAIRY): a modelling framework to identify sustainable dairy farms in the UK. Framework description and test for organic systems and N fertiliser optimisation.
abstract: Multiple demands are placed on farming systems today. Society, national legislation and market forces seek what could be seen as conflicting outcomes from our agricultural systems, e.g. food quality, affordable prices, a healthy environmental, consideration of animal welfare, biodiversity etc., Many of these demands, or desirable outcomes, are interrelated, so reaching one goal may often compromise another and, importantly, pose a risk to the economic viability of the farm. SIMS(DAIRY), a farm-scale model, was used to explore this complexity for dairy farm systems. SIMS(DAIRY) integrates existing approaches to simulate the effect of interactions between farm management, climate and soil characteristics on losses of nitrogen, phosphorus and carbon. The effects on farm profitability and attributes of biodiversity, milk quality, soil quality and animal welfare are also included. SIMS(DAIRY) can also be used to optimise fertiliser N. In this paper we discuss some limitations and strengths of using SIMS(DAIRY) compared to other modelling approaches and propose some potential improvements. Using the model we evaluated the sustainability of organic dairy systems compared with conventional dairy farms under non-optimised and optimised fertiliser N use. Model outputs showed for example, that organic dairy systems based on grass-clover swards and maize silage resulted in much smaller total GHG emissions per l of milk and slightly smaller losses of NO(3) leaching and NO(x) emissions per l of milk compared with the grassland/maize-based conventional systems. These differences were essentially because the conventional systems rely on indirect energy use for 'fixing' N compared with biological N fixation for the organic systems. SIMS(DAIRY) runs also showed some other potential benefits from the organic systems compared with conventional systems in terms of financial performance and soil quality and biodiversity scores. Optimisation of fertiliser N timings and rates showed a considerable scope to reduce the (GHG emissions per l milk too).
authors.affiliation: Rothamsted Research, North Wyke, Okehampton, Devon, EX20 2SB, UK. agustin.delprado@bc3research.org
authors.forename: A
authors.initials: A
authors.lastname: Del Prado
authors.forename: T
authors.initials: T
authors.lastname: Misselbrook
authors.forename: D
authors.initials: D
authors.lastname: Chadwick
authors.forename: A
authors.initials: A
authors.lastname: Hopkins
authors.forename: R J
authors.initials: RJ
authors.lastname: Dewhurst
authors.forename: P
authors.initials: P
authors.lastname: Davison
authors.forename: A
authors.initials: A
authors.lastname: Butler
authors.forename: J
authors.initials: J
authors.lastname: Schröder
authors.forename: D
authors.initials: D
authors.lastname: Scholefield
mesh_terms: D058572:Carbon Footprint; D003612:Dairying; D005308:Fertilizers; D008962:Models, Theoretical; D009584:Nitrogen; D058871:Organic Agriculture / Q000379:methods*; D012987:Soil / Q000737:chemistry; D006113:United Kingdom
chemical_list: D005308:Fertilizers; D012987:Soil; D009584:Nitrogen