Foresight Research and Knowledge Management, Government Office for Science, 1 Victoria Street, London SW1H 0ET, UK.
Philos Trans R Soc Lond B Biol Sci. 2010 Sep 27;365(1554):3049-63. doi: 10.1098/rstb.2010.0141.
Complex socio-ecological systems like the food system are unpredictable, especially to long-term horizons such as 2050. In order to manage this uncertainty, scenario analysis has been used in conjunction with food system models to explore plausible future outcomes. Food system scenarios use a diversity of scenario types and modelling approaches determined by the purpose of the exercise and by technical, methodological and epistemological constraints. Our case studies do not suggest Malthusian futures for a projected global population of 9 billion in 2050; but international trade will be a crucial determinant of outcomes; and the concept of sustainability across the dimensions of the food system has been inadequately explored so far. The impact of scenario analysis at a global scale could be strengthened with participatory processes involving key actors at other geographical scales. Food system models are valuable in managing existing knowledge on system behaviour and ensuring the credibility of qualitative stories but they are limited by current datasets for global crop production and trade, land use and hydrology. Climate change is likely to challenge the adaptive capacity of agricultural production and there are important knowledge gaps for modelling research to address.
复杂的社会-生态系统，如食物系统，是不可预测的，尤其是对于 2050 年等长期的时间跨度。为了应对这种不确定性，情景分析已经与食物系统模型结合使用，以探索可能的未来结果。食物系统情景使用了多种情景类型和建模方法，具体取决于研究的目的以及技术、方法和认识论上的限制。我们的案例研究并没有为预计到 2050 年全球人口将达到 90 亿的情况预测马尔萨斯式的未来；但国际贸易将是结果的关键决定因素；而且到目前为止，食物系统各维度的可持续性概念还没有得到充分的探索。在全球范围内，通过参与其他地理尺度的关键行为者的参与性进程，可以增强情景分析的影响力。食物系统模型在管理系统行为的现有知识和确保定性故事的可信度方面具有价值，但它们受到全球作物生产和贸易、土地利用和水文学的当前数据集的限制。气候变化可能会挑战农业生产的适应能力，模型研究需要解决重要的知识空白。
