2023

Food Supply Shock Explorer

Entry type: Single project

Country/area: Austria

Publishing organisation: Complexity Science Hub Vienna

Organisation size: Small

Publication date: 2022-09-29

Language: English

Authors: Moritz Laber, Peter Klimek, Martin Bruckner, Liuhuaying Yang, Stefan Thurner

Biography:

The Complexity Science Hub Vienna (CSH) is a Vienna-based research organization with the aim to bundle, coordinate and advance the research of complex systems, system analysis and big data science in Austria. In addition to scientific research, we create data visualizations and data stories for science dissemination.
This dashboard is part of scientific paper “Shock propagation in international multilayer food-production network determines global food availability”.

Project description:

The “Food Supply Shock Explorer” dashboard aims to show the impacts of sudden disruptions to global food supply chains. The default scenario shows the global effects if Ukraine can no longer produce maize. Our model combines information on the trade, production, and consumption of 125 food products in 192 countries. As products turn into other products along the supply chain, the shock to Ukrainian maize production does not only affect the availability of maize but also causes losses of other products, such as pig or poultry meat due to a lack of animal feed.

Impact reached:

The war in Ukraine called attention to the vulnerability of the global food supply system. This project utilizes a combination of data analysis, computer modeling, and simulations to investigate the effects of various potential scenarios such as natural disasters, economic crises, and pandemics on food production and distribution.

Due to dependencies in the global food-production network, the local loss of one crop can lead to shortages in other countries and affect other products made from it. Instead of treating products in isolation, our model reveals the losses of 125 food products after a localized shock to agricultural production in 192 countries using a multilayer network model of trade (direct) and conversion of food products (indirect).
This dashboard allows users to explore which food products are lost and which countries are affected most severely when a specific supplier stops producing a single food product. The goal is to facilitate policy makers,stakeholders, and the public to gain a better understanding of the vulnerabilities in the global food system and to identify potential strategies for mitigating the impacts of future food supply shocks.

Techniques/technologies used:

The resulting losses in the dashboard are visualized in a map view and a 2D-grid view. The map view provides an intuitive geographic story, while grid view has the advantage of seeing patterns efficiently across product types and regions.
The visual elements in the dashboard were custom developed using the D3.js library. All of them are responsive, adapting to the different device sizes including small mobile displays.

Context about the project:

The data and model used in the dashboard is the scientific work of researchers affiliated to Complexity Science Hub Vienna, Austria, Section for Science of Complex Systems CeMSIIS Medical University of Vienna,Vienna, Austria, Santa Fe Institute, Santa Fe,USA, and Institute for Ecological Economics, Vienna University of Economics and Buisness, Austria. The dashboard is created by researchers from Complexity Science Hub Vienna, Austria.

What can other journalists learn from this project?

Instead of treating products in isolation, our model reveals the losses of 125 food products after a localized shock to agricultural production in 192 countries using a multilayer network model of trade (direct) and conversion of food products (indirect). Therefore it provides a better understanding of the vulnerabilities in the global food system. By playing product type and country filters, journalists can investigate the issues under varied social scenarios, such as wars and pandemics.

Project links:

https://vis.csh.ac.at/food-supply-shocks/