Rothamsted Research, North Wyke, Okehampton, Devon, EX20 2SB, UK.
Sci Total Environ. 2011 Sep 1;409(19):3993-4009. doi: 10.1016/j.scitotenv.2011.05.050. Epub 2011 Jun 23.
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).
当今，农业系统面临着多重需求。社会、国家法规和市场力量都在从我们的农业系统中寻求看似相互冲突的结果，例如食品质量、可承受的价格、健康的环境、对动物福利、生物多样性等的关注。这些需求或理想结果中的许多都是相互关联的，因此实现一个目标往往会影响另一个目标，而且重要的是，这会对农场的经济可行性构成风险。SIMS（奶牛场）是一个农场规模模型，用于探索奶牛场系统的这种复杂性。SIMS（奶牛场）集成了现有的方法来模拟农场管理、气候和土壤特征之间的相互作用对氮、磷和碳损失的影响。它还包括对农场盈利能力和生物多样性、牛奶质量、土壤质量和动物福利属性的影响。SIMS（奶牛场）也可用于优化肥料氮。本文讨论了与其他建模方法相比，使用 SIMS（奶牛场）的一些局限性和优势，并提出了一些潜在的改进方法。使用该模型，我们评估了在非优化和优化肥料氮使用条件下，有机奶牛系统与常规奶牛场的可持续性。模型输出表明，例如，与基于草地/玉米的常规系统相比，基于草-三叶草草地和玉米青贮的有机奶牛系统每升牛奶的温室气体总排放量和硝酸盐淋失及氮氧化物排放量都要小得多。这些差异主要是因为常规系统依赖间接能源来“固定”氮，而有机系统则依赖生物固氮。SIMS（奶牛场）的运行结果还表明，与常规系统相比，有机系统在财务绩效、土壤质量和生物多样性评分方面具有一些潜在的优势。优化肥料氮的时间和速度表明，有很大的空间可以减少（每升牛奶的温室气体排放量）。
