Modelling is a way to gain insights into complex interactions and trade-offs in order to plan research activities that will achieve the most impact.
Challenge
There are trade-offs between productivity, food and nutrition security and environmental goals. For example, focusing on increased productivity can result in more food crops, but reduced nutrition and a degraded environment. On the other hand, focusing just on the environment, can negatively impact productivity.
Trade-offs may be immediate and local, for example, applying synthetic fertilizers to fields can boost yields, but increase nitrogen levels in water bodies, leading to decreased oxygen and death of fish. However, sometimes the impact of decisions made in one place and time have seemingly disconnected effects far away in the future or another location. For instance, a focus on feeding the world by cultivating starchy like wheat, rice and potatoes is having a global effect on nutrition as nutrient-dense fruit and vegetables are replaced in fields, markets and plates.
Also the needs and challenges of the future will be quite different from those we face today – for example climate change combined with growing population, especially in urban areas and in developing countries and their changing food needs and preferences require new solutions based on careful planning and detailed analysis of all these possible future trends, their interactions and effects on food systems.
Solution
Our scientists carry out modelling exercises before the intervention takes place (foresight modelling and ex ante analysis) which means they can try out different options to find those that have the fewest trade-offs or that actually create synergies – win-win situations in which positive outcomes reinforce each other. They can then work out which are likely to be the most impactful places to work in, crops to work on, practices to explore, and data sources to use (prioritizing modelling).
Our approach
We use models developed by other organizations and combine them in novel ways for new insights. For example, the IMPACT model developed by the International Food Policy Research Institute (IFPRI – a CGIAR Research Centre), projects regional and country-level aggregate food production, consumption and prices under different scenarios (including climate change, socio-economic developments or technological progress), with detailed breakdowns on major crops.
FarmDesign, developed by Wageningen University and used by several CGIAR Research Programs (e.g. Agriculture for Nutrition and Health), shows consequences of decisions at the field and farm level, like which like which crops to plant and whether to include animals on the farm. It explores relations among different productive, socio-economic, nutritional and environmental farm objectives. FarmDESIGN combines a bio-economic farm model with a multi-objective optimization algorithm based on yields and market prices of agricultural commodities among other things.
If you combine these two models, you can analyze how possibly future global trends might affect a farm, through markets, trade and yield developments, and what strategies a farm household can adopt to achieve certain goals and the tradeoffs resulting from using these strategies.