By Brett Glencross, Technical Director, IFFO, UK
A recent paper titled ‘From farm to food systems: Developing aquaculture models to explore their role in food systems’ provides a novel approach to how we can better assess the future of sustainable animal protein production. Through the development of a series of integrated Dynamic Energy Budget (DEB) models for species like Atlantic salmon, European seabass and common carp, the authors managed to connect production of these key aquaculture species into broader food system frameworks. Notably, the work allows us to move beyond the simplistic “fish-in, fish-out” debates to a more nuanced, systemic understanding of aquaculture’s potential as an important protein production system.
Historically, aquaculture has been the “neglected youngest child” in global food system modelling, garnering most attention for all the wrong reasons and often on misapplied understandings. While we have robust, decades-old data for cattle, poultry and pig production systems, aquaculture has often been reduced to a few data points or ignored entirely. This oversight is problematic because aquatic foods are among the most resource-efficient proteins available. Not only that, but they are among the fastest growing animal production sectors in the world, accounting for over 20 percent of global animal protein consumption. The authors argue that without the use of sophisticated, bioenergetic-based models that account for different species and management practices, it becomes difficult to plan for a food system that remains within planetary boundaries.
One of the most impressive aspects of the research was the use of DEB models to bridge the gap where empirical farm data is scarce. By simulating life-cycle growth performance and nutrient requirements across various temperature clusters in Europe, the study provides a “digital twin” of sorts for different aquaculture systems. This allows us to ask “what if” questions: such as how does water temperature affect the efficiency of seabass in a changing climate?
The finding that these models accurately predict performance across a range of species is not a major new finding, similar such models have been around in aquaculture since the 1990s. However, it is a significant step-forward for improving our “circularity” assessment. If we can predict exactly what a fish needs to grow—and when it will be ready—we can better align aquaculture with other industries, such as using agricultural and/or fishery by-products as feed, thereby closing the nutrient supply loop.
However, the real challenge for the application of such work remains its implementation into broader policy. Data-driven models are usually only as good as the policy (or industry) that they inform. While we have increasing numbers of such models to show that aquaculture belongs at the centre of the circular food economy; the question is whether regulators, policy makers and the industry are ready to move beyond the green base of old thinking paradigms and embrace the new options available in blue food systems.
