Ensuring the supply of aquatic products, strengthening food security, and preparing for supply crises under extreme conditions are crucial. Therefore, understanding the systemic impacts and transmission paths caused by different sources is of great value for preventing supply crises. To explore this issue, this article selects relevant data from 2019 to 2022, applies a cascade failure model to simulate potential supply chain avalanche effects, and conducts a detailed analysis of the structural characteristics of crisis transmission. The results show as bellows. (1) When the ratio r=8, the avalanche processes caused by different economies as crisis sources exhibit significant differences. (2) The trend of snowball changes of important crisis sources from 2019 to 2022 shows diverse characteristics. (3) Out-degree, out-intensity, and centrality of intermediaries have a significant impact on the dynamic transmission of aquatic product supply crises, while in-degree, in-intensity, and eigenvector centrality are not significant. (4) Under the condition of r=8, only the aquatic product supply crisis in Ecuador can spread to China. (5) Spatial proximity has a significant impact on the successive diffusion of crises, and indirect infection is the main route for transmitting cascade crises, which has an important impact on the avalanche process. By optimizing import configurations at critical nodes, implementing dynamic risk monitoring mechanisms, and fostering multilateral trade collaboration, this approach addresses cascading supply risks stemming from climate change and geopolitical conflicts, thereby enhancing the resilience and sustainability of the global aquatic product trade network.
Key words
aquatic products trade /
complex network /
supply crisis /
cascade failure
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References
[1] Bellmann C,Tipping A,Sumaila U R.Global trade in fish and fishery products: An overview[J].Marine Policy,2016(69): 181-188.
[2] FAO.The state of world fisheries and aquaculture.2020 sustainability in action [R].Rome:FAO,2020.
[3] McClanahan T,Allison E H,Cinner J E.Managing fisheries for human and food security[J].Fish and Fisheries, 2015,16(1):78-103.
[4] Gephart J A,Pace M L.Structure and evolution of the global seafood trade network[J].Environmental Research Letters,2015,10(12):125014.
[5] 王泽宇,郭婷,王焱熙.复杂网络视角下全球水产品贸易格局演化及影响因素[J].地域研究与开发,2022,41(2):1-6,13.
[6] 彭飞,胡锦琳,伏捷等.“21世纪海上丝绸之路”沿线国家水产品贸易网络分析[J].热带地理,2021,41(6):1188-1198.
[7] 王文宇,贺灿飞.关系经济地理学与贸易网络研究进展[J].地理科学进展,2022,41(3):461-476.
[8] Lee K M,Yang J S, Kim G,et al.Impact of the topology of global macroeconomic network on the spreading of economic crises[J].PloS one,2011,6(3):e18443.
[9] Chen Z,An H,An F,et al.Structural risk evaluation of global gas trade by a network-based dynamics simulation model[J].Energy,2018(159):457-471.
[10] Wang X,Li H,Yao H,et al.Simulation analysis of the spread of a supply crisis based on the global natural graphite trade network[J].Resources Policy,2018(59):200-209.
[11] Tian X,Geng Y,Sarkis J,et al.Features of critical resource trade networks of lithium-ion batteries[J].Resources Policy,2021(73):102177.
[12] Sun X,Shi Q,Hao X.Supply crisis propagation in the global cobalt trade network[J].Resources,Conservation and Recycling,2022(179):106035.
[13] 王星星,钟维琼,朱德朋.全球镍矿贸易网络的供应风险传播研究[J].地球学报,2023,44(2):361-368.
[14] Bridge G.Mapping the terrain of time-space compression:Power networks in everyday life[J].Environment and planning D:Society and Space,1997,15(5):611-626.
[15] Dobson I,Carreras B A,Lynch V E,et al.Complex systems analysis of series of blackouts:Cascading failure, critical points,and self-organization[J].Chaos: An Interdisciplinary Journal of Nonlinear Science,2007,17(2):026103.
[16] Bakshy E,Hofman J M,Mason W A,et al.Everyone's an influencer: quantifying influence on twitter[A].Irwin King. Proceedings of the fourth ACM international conference on Web search and data mining[C].New York: Association
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