{"title":"Quantifying the temporal stability of international fertilizer trade networks","authors":"Mu-Yao Li, Li Wang, Wen-Jie Xie, Wei-Xing Zhou","doi":"10.1093/comnet/cnad037","DOIUrl":null,"url":null,"abstract":"Abstract The importance of fertilizers to agricultural production is undeniable, and most economies rely on international trade for fertilizer use. The stability of fertilizer trade networks is fundamental to food security. However, quantifying the temporal stability of a fast-growing system, such as the international fertilizer trade, requires a multi-dimensional perception. Therefore, we propose a new method, namely the structural inheritance index, to distinguish the stability of the existing structure from the influence of the growing process. The well-known mutual information and Jaccard index are calculated for comparison. We use the three methods to measure the temporal stability of the overall network and different functional sub-networks of the three fertilizer nutrients N, P and K from 1990 to 2018. The international N, P and K trade systems all have a trend of increasing stability with the process of globalization. The existing structure in the fertilizer trading system has shown high stability since 1990, implying that the instability calculated by the Jaccard index in the early stage comes from the emergence of new trade. The stability of the K trade network is concentrated in large sub-networks, meaning that it is vulnerable to extreme events. The stable medium sub-network helps the N trade become the most stable nutrient trade. The P trade is clearly in the role of a catch-up player. Based on the analysis of the comparisons of three indicators, we concluded that all three nutrient trade networks enter a steady state.","PeriodicalId":15442,"journal":{"name":"Journal of complex networks","volume":"66 1","pages":"0"},"PeriodicalIF":2.2000,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of complex networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/comnet/cnad037","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The importance of fertilizers to agricultural production is undeniable, and most economies rely on international trade for fertilizer use. The stability of fertilizer trade networks is fundamental to food security. However, quantifying the temporal stability of a fast-growing system, such as the international fertilizer trade, requires a multi-dimensional perception. Therefore, we propose a new method, namely the structural inheritance index, to distinguish the stability of the existing structure from the influence of the growing process. The well-known mutual information and Jaccard index are calculated for comparison. We use the three methods to measure the temporal stability of the overall network and different functional sub-networks of the three fertilizer nutrients N, P and K from 1990 to 2018. The international N, P and K trade systems all have a trend of increasing stability with the process of globalization. The existing structure in the fertilizer trading system has shown high stability since 1990, implying that the instability calculated by the Jaccard index in the early stage comes from the emergence of new trade. The stability of the K trade network is concentrated in large sub-networks, meaning that it is vulnerable to extreme events. The stable medium sub-network helps the N trade become the most stable nutrient trade. The P trade is clearly in the role of a catch-up player. Based on the analysis of the comparisons of three indicators, we concluded that all three nutrient trade networks enter a steady state.
期刊介绍:
Journal of Complex Networks publishes original articles and reviews with a significant contribution to the analysis and understanding of complex networks and its applications in diverse fields. Complex networks are loosely defined as networks with nontrivial topology and dynamics, which appear as the skeletons of complex systems in the real-world. The journal covers everything from the basic mathematical, physical and computational principles needed for studying complex networks to their applications leading to predictive models in molecular, biological, ecological, informational, engineering, social, technological and other systems. It includes, but is not limited to, the following topics: - Mathematical and numerical analysis of networks - Network theory and computer sciences - Structural analysis of networks - Dynamics on networks - Physical models on networks - Networks and epidemiology - Social, socio-economic and political networks - Ecological networks - Technological and infrastructural networks - Brain and tissue networks - Biological and molecular networks - Spatial networks - Techno-social networks i.e. online social networks, social networking sites, social media - Other applications of networks - Evolving networks - Multilayer networks - Game theory on networks - Biomedicine related networks - Animal social networks - Climate networks - Cognitive, language and informational network