Structural evolution of international crop trade networks

Abstract

Food security is a critical issue closely linked to human being. With the increasing demand for food, international trade has become the main access to supplementing domestic food shortages, which not only alleviates local food shocks, but also exposes economies to global food crises. In this paper, we construct four temporal international crop trade networks (iCTNs) based on trade values of maize, rice, soybean and wheat, and describe the structural evolution of different iCTNs from 1993 to 2018. We find that the size of all the four iCTNs expanded from 1993 to 2018 with more participants and larger trade values. Our results show that the iCTNs not only become tighter according to the increasing in network density and clustering coefficient, but also get more similar. We also find that the iCTNs are not always disassortative, unlike the world cereal trade networks and other international commodity trade networks. The degree assortative coefficients depend on degree directions and crop types. The analysis about assortativity also indicates that economies with high out-degree tend to connect with economies with low in-degree and low out-degree. Additionally, we compare the structure of the four iCTNs to enhance our understanding of the international food trade system. Although the overall evolutionary patterns of different iCTNs are similar, some crops exhibit idiosyncratic trade patterns. It highlights the need to consider different crop networks’ idiosyncratic features while making food policies. Our findings about the dynamics of the iCTNs play an important role in understanding vulnerabilities in the global food system.

Structural Evolution of Global Soybean Trade Network and the Implications to China

“…The complex network method is an important tool to study the characteristics and dynamics of international trade systems using topological features, which was widely applied in public transportation [ 5 , 6 ], air quality [ 7 ], disease transmission [ 8 , 9 ], and natural resource flow [ 10 , 11 , 12 ]. In terms of grain trade [ 13 , 14 ], Srishti et al [ 15 ] analyzed the impact of extreme weather on wheat trade by the complex network; Zhou et al [ 16 ] built the global rice network and studied its evolution characteristics. Lu et al [ 17 ] constructed different weighted and unweighted trade networks and analyzed the trade networks of soybean, soybean oil, and soybean meal using complex network analysis.…”

Unraveling the key drivers of community composition in the agri-food trade network

“…Significant findings have been reported across various context. For instance, research has delved into the characteristics and evolution of the trade network concerning both the entire spectrum of agricultural products 11 , 12 , 13 14 and specific commodities 15 – 18 . Additionally, studies have explored the virtual water network associated with agricultural products 19 – 23 and the detection of community structures.…”