Periodic Reporting for period 1 - CIFTRESS (Climatic Impact on Food Trade RESilience and Security)
Okres sprawozdawczy: 2019-05-15 do 2021-05-14
Under climate change, crop yields will decrease because the increases in global temperature negatively affect plant growth, water availability, soil fertility, and plant pest control In addition, climate change may disrupt the availability of staple foods for import and export. Under climate change, agricultural commodity trade is predicted to increase in value, and production to shift to regions in the mid to high latitudes, while in low-latitude regions production and export potential would be reduced. Hence, climate change undermines food security and resilience not only by exacerbating the challenges of meeting the demands of a larger and more affluent population but also by propagating regional shocks and disruptions within increasingly interconnected food trade networks. While previous research has focused on the former, the opportunities from and risks for trade networks across regions have remained relatively less explored. More specifically, previous research has mainly considered bilateral ‘direct’ trade relationships, while ‘in-direct’ trade relationships described by ‘network topologies’ have been taken into account only marginally. A network topology defines, in this case, trade relations, as the systems-level architecture composed of nodes and their ‘weighted’, i.e. the strength and intensity, of their connecting flow links. Accordingly, my research objective is to examine the joint climate, agro-environmental, and economic induced changes to the trade network topologies of five staple foods, i.e. wheat, corn, soy, barley, and rice up to the year 2080.
Using the Global Agro-Ecological Zones (GAEZ), machine learning, and agent-based modeling approaches, this research simulated the trade network topologies of four major global staple food, i.e. wheat, corn, soy, and rice, for the years 2020 (the average of 2010-2040), 2050 (the average of 2040-2060), and 2080 (the average of 2070-2090) under multiple climatic and economic scenarios (see Methods). This entails utilizing the Global Agro-Ecological Zones (GAEZ) framework to simulate the production, machine learning to project the consumption, and an agent-based model to generate the trade networks of the aforementioned staple food commodities. For each of the four major staple food commodities, we constructed 60 trade networks which include 1) three years, i.e. 2020 2050, and 2080; 2) four representative concentration pathways (RCPs) scenarios, i.e. RCP 2.6 RCP 4.5 RCP 6.0 and RCP 8.5; and 3) five shared social-economic pathways (SSPs) scenarios, i.e. SSP1, SSP2, SSP3, SSP4, and SSP5. Each of the networks encompasses 179 world major countries, and the links of the network are the physical trade value measured in tones among these countries. The trade network topologies under each scenario is examined through the Ecological Network Analysis (ENA) approach (see Methods) to evaluate the agro-economic implications of the resilience and security of staple foods under future climate change scenarios. These future networks are also compared with historical network topologies from 1986 to 2019.
As changes in both the food production and consumption are affected by the aforementioned climate change scenarios, to meet the food demand of each country, the food trade network needs to be adjusted. Our results reveal that in comparison to 2019 the network resilience of all four staple foods in all scenarios are increasing for wheat (1.9%~4.2%), corn (0.4%~3.2%) and soy (27.3%~27.5%), while spanning a wide range for rice (4.7%~-6.9%). Contrary to other SSP scenarios, the SSP4 scenario will see an increase in the trade network resilience. These results indicate that under the extreme RCP scenarios, the food trade network needs to be more resilient to meet the food demand of all countries. Compared with wheat and corn, the current soy trade network needs to be adjusted the most to improve its resilience, while the future trade network for rice is still quite uncertain. These findings can enable new strategies inspired by network science for public policies relevant to the security and resilience of staple foods under future climate change.
As changes in both the food production and consumption are affected by the aforementioned climate change scenarios, to meet the food demand of each country, the food trade network needs to be adjusted. Our results reveal that in comparison to 2019 the network resilience of all four staple foods in all scenarios are increasing for wheat (1.9%~4.2%), corn (0.4%~3.2%) and soy (27.3%~27.5%), while spanning a wide range for rice (4.7%~-6.9%). Contrary to other SSP scenarios, the SSP4 scenario will see an increase in the trade network resilience. These results indicate that under the extreme RCP scenarios, the food trade network needs to be more resilient to meet the food demand of all countries. Compared with wheat and corn, the current soy trade network needs to be adjusted the most to improve its resilience, while the future trade network for rice is still quite uncertain. These findings can enable new strategies inspired by network science for public policies relevant to the security and resilience of staple foods under future climate change.
Among all climate change scenarios, the network resilience of wheat trade needs to be improved the most (6.5%) in the rcp4.5-ssp3 scenario and the least (1.2%) in the rcp2.6-ssp2 scenario for the year 2080, compared with that in the year 2019. For rice, the rcp45-ssp3 scenario in the year 2020 and the rcp26-ssp5 scenario in the year 2080 will respectively see the most (6.5%) and least changes (-20.4%) in the network resilience. For corn, the rcp85-ssp3 scenario in the year 2080 and the rcp45-ssp5 scenario in the year 2020 will respectively see the most (4.7%) and the least (-0.1%) change in the network resilience. For soy, the rcp26-ssp3 scenario in the year 2080 and the rcp85-ssp5 scenario in the year 2080 will respectively see the most (27.6%) and the least (26.7%) change in network resilience. This indicates that the changes in network resilience differ greatly for wheat, rice, corn, and soy under the same climate change scenario and the network topology does not change the most under extreme climate change scenarios, such as RCP 8.5 and ssp5.
Resilience is not only collectively determined but it is arguably a public good, whereby its benefits are non-excludable, non-rivalrous, and lead to positive externalities and the emergence of network mutualism. The benefits of a resilient trade system to shocks and disturbances are inherently non-excludable, e.g. a resilient food commodity trade network maintains a constant supply of food and is of benet to everyone that partakes in the trade system. In the same vein, it can be seen that the benefits of a resilient trade system are non-rivalrous. Any particular group of people benefiting from the trade system's ability to return to a previous equilibrium or adapt to a new equilibrium after a shock or disturbance would not necessarily deprive other groups of people of benefiting from the same attribute of the trade system. In addition, a resilient trade system provides several positive externalities. Even if all participants did not invest adequately in resilience-building measures, the benet of a resilient trade system can be enjoyed by all actors participating in the trade system. This promotes trust in the global trade system and allows countries to produce goods and services reflecting their comparative advantage, while concurrently depending on their trade partners to meet their own consumption and production demands. Hence, applying the lens of provisioning a public good can help in understanding the reasons for the under-supply of resilience within critical human systems such as trade networks and design policy responses.
Resilience is not only collectively determined but it is arguably a public good, whereby its benefits are non-excludable, non-rivalrous, and lead to positive externalities and the emergence of network mutualism. The benefits of a resilient trade system to shocks and disturbances are inherently non-excludable, e.g. a resilient food commodity trade network maintains a constant supply of food and is of benet to everyone that partakes in the trade system. In the same vein, it can be seen that the benefits of a resilient trade system are non-rivalrous. Any particular group of people benefiting from the trade system's ability to return to a previous equilibrium or adapt to a new equilibrium after a shock or disturbance would not necessarily deprive other groups of people of benefiting from the same attribute of the trade system. In addition, a resilient trade system provides several positive externalities. Even if all participants did not invest adequately in resilience-building measures, the benet of a resilient trade system can be enjoyed by all actors participating in the trade system. This promotes trust in the global trade system and allows countries to produce goods and services reflecting their comparative advantage, while concurrently depending on their trade partners to meet their own consumption and production demands. Hence, applying the lens of provisioning a public good can help in understanding the reasons for the under-supply of resilience within critical human systems such as trade networks and design policy responses.