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Shock propagation from the Russia–Ukraine conflict on international multilayer food production network determines global food availability

Nature Food volume 4, pages 508–517 (2023)Cite this article

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Abstract

Dependencies in the global food production network can lead to shortages in numerous regions, as demonstrated by the impacts of the Russia–Ukraine conflict on global food supplies. Here we reveal the losses of 125 food products after a localized shock to agricultural production in 192 countries and territories using a multilayer network model of trade (direct) and conversion of food products (indirect), thereby quantifying 108 shock transmissions. We find that a complete agricultural production loss in Ukraine has heterogeneous impacts on other countries, causing relative losses of up to 89% in sunflower oil and 85% in maize via direct effects and up to 25% in poultry meat via indirect impacts. Whereas previous studies often treated products in isolation and did not account for product conversion during production, the present model considers the global propagation of local supply shocks along both production and trade relations, allowing for a comparison of different response strategies.

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Fig. 1: Schematic representation of trade and production as a multilayer network for three countries and two products.
Fig. 2: A toy example that illustrates different shock propagation channels that can contribute to losses in our model.
Fig. 3: Time evolution of the available amount in a baseline case and after a shock next to the resulting relative loss.
Fig. 4: A simultaneous shock to the production of all food products in Ukraine affects different world regions and products.
Fig. 5: Comparison of losses within one layer (trade) and across layers (production).

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Data availability

The data used in this study as input for simulations are available on GitHub at https://github.com/L-MoNi/shock-propagation-food-supply.

Code availability

Python was used to perform the simulations and data analysis. Simulation and analysis code for this study is available in a repository at https://github.com/L-MoNi/shock-propagation-food-supply.

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Acknowledgements

We are grateful to C. Diem, T. Reisch, A. Pichler, J. Hurt and F. Neffke for illuminating discussions. This work was supported by the Austrian Science Promotion Agency FFG under 882184 (S.T.) and 886360 (S.T.) and by the Austrian Science Fund FWF under P 31598-G31 (M.B.).

Author information

Authors and Affiliations

  1. Complexity Science Hub Vienna, Vienna, Austria

    Moritz Laber, Peter Klimek, Liuhuaying Yang & Stefan Thurner

  2. Network Science Institute, Northeastern University, Boston, MA, USA

    Moritz Laber

  3. Center for Medical Data Science CeDAS, Medical University of Vienna, Vienna, Austria

    Peter Klimek & Stefan Thurner

  4. Supply Chain Intelligence Institute Austria, Vienna, Austria

    Peter Klimek & Stefan Thurner

  5. Institute for Ecological Economics, Vienna University of Economics and Business, Vienna, Austria

    Martin Bruckner

  6. Institute of Environmental Engineering, ETH Zurich, Zurich, Switzerland

    Martin Bruckner

  7. Santa Fe Institute, Santa Fe, NM, USA

    Stefan Thurner

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Contributions

P.K., M.L. and S.T. contributed to study conception and design. Data were collected by M.B. Analysis was carried out by M.L. Results were interpreted by P.K., M.L. and S.T. The artwork was conceived by L.Y. and M.L. The first draft of the manuscript was written by M.L., and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Stefan Thurner.

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Nature Food thanks Megan Konar, Antoine Bernard de Raymond and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information

Supplementary Tables 1–14, Figs. 1–3, Algorithm 1 and Analysis.

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Laber, M., Klimek, P., Bruckner, M. et al. Shock propagation from the Russia–Ukraine conflict on international multilayer food production network determines global food availability. Nat Food 4, 508–517 (2023). https://doi.org/10.1038/s43016-023-00771-4

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