The increased occurrence of shocks is making it more and more difficult to provide food and nutrition security for everyone at all times . This is where resilience comes into play. Resilience, roughly understood as the ability of a system to absorb disturbances and reorganize after disturbances, has understandably become a very prominent and dominant concept for food systems. At the same time, however, resilience is an amoeba-like concept that is hard to define, harder to measure and even harder to build. For starters, a system such as a food system, cannot be resilient. Some of its functions can be resilient to certain disturbances. But not all functions. And not to all types of disturbances.
I have been fortunate to collaborate in the „Enhancing Resilience in Food Systems“ project at ETH Zurich for a while now. The project develops guidelines that propose a suite of methods, techniques and tools to assess and build resilience in food systems.
These methods, techniques and tools are based on the following understanding of resilience that we describe on page 20 in an article in Global Food Security.
“The food system resilience concept acknowledges the dynamic nature of food systems: it aims to maximize the functional goal of food security over time, despite disturbances, but does not require the assumption of a single optimal, indefinitely sustainable, steady state. Rather, it entails a long-term, continuous action and learning cycle that iteratively builds resilience over time, and enhances performance of the food system. Disturbances are seen as an opportunity for change and improvement, with learning occurring after each successive shock.”
In a special issue of the magazine Sight and Life, we summarize one of the first applications of the guidelines to the case of Tef, a key food security crop, in Ethiopia. The case study illustrates the impossibility of using a single procedure with fixed methods. Instead, it emphasizes the need for flexibility in the application of the resilience assessment guidelines to allow for differences in context, availability of data and expertise, as well as engagement of stakeholders. The case study also highlights how consulting directly with relevant stakeholders leads to contrasting conclusions compared to what scientists and governmental actors may think are suitable interventions for building resilience. Finally, the case study shows that interventions for building resilience need to be tailored to particular stages of the value chain.
How does system dynamics fit into all of this? One of my PhD students, Hugo Herrera, is studying this question in quite some detail and he is accumulating an impressive number of presentations and publications about this. Here, I focus on the one dimension of his research that I have been most actively involved, namely the identification of resilience measures. Calculating these measures from a system dynamics model demonstrates that there is not only the risk of a trade-off between resilience and other food system outcomes but also within resilience, e.g. between elasticity and robustness.