Structure of the Global Virtual Meat Protein Trade Network

Given the uneven global distribution of livestock resources leading to a mismatch in protein supply and demand, and the current lack of clarity regarding the mechanisms and evolution of virtual protein flows embedded within meat trade, this study constructs a global virtual meat protein trade network for the period 1995~2022. Our aim is to deeply analyze its structural evolution, geographical patterns, and inherent inequalities. We converted global meat trade data into virtual protein flows and employed complex network analysis to comprehensively examine the network's topological indicators, including average degree, graph density, clustering coefficient, path length, number of communities, and modularity. Additionally, the Gini coefficient was introduced to quantify import and export inequalities. Results reveal a significant increase in the total volume of global virtual meat protein trade, with poultry experiencing particularly rapid growth. The trade pattern is highly concentrated, with China, the United States, and Germany accounting for 25.3% of global virtual protein imports. Trade relations have evolved from regional to global, with emerging economies playing an increasingly pivotal role. Network structure analysis indicates enhanced connectivity, dynamic changes in efficiency and clustering, and clearer community delineation. The Gini coefficient confirms a significant inequality in global virtual meat protein trade, especially pronounced in exports. This research is the first to construct a global virtual protein trade network for meat and reveals the mechanisms of trade concentration and inequality from the perspective of the coupling of nutritional value flow and network structure.