Time dynamics and invariant subnetwork structures in the world cereals trade network

被引:35
作者
Dupas, Marie-Cecile [1 ]
Halloy, Jose [1 ]
Chatzimpiros, Petros [1 ]
机构
[1] Univ Paris Diderot, LIED, Paris, France
关键词
D O I
10.1371/journal.pone.0216318
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The development of industrial agriculture has enabled a sharp increase in food trade at the global scale. Worldwide trade underpins food security by distributing food surpluses to food deficient countries. The study of agricultural product flows can provide insights on the complex interactions between exporting and importing countries and the resulting network structures. Commercial partnerships between countries can be modelled using a complex network approach. Based on the detailed trade matrices from FAO covering the period from 1986 to 2013, we present an analysis of the world cereal trade in terms of weighted and directed networks. The network nodes are the countries and the links are the trades of agricultural products in mass. We reveal the changing topology and degree distribution of the world network during the studied period. We distinguish three entangled subnetwork structures when considering the temporal stability of the trades. The three subnetworks display distinct properties and a differential contribution in total trade. Trades of uninterrupted activity over the 28-year study period compose the backbone network which accounts for two thirds of all traded mass and is scale-free. Inversely, two thirds of the trades only have one or two consecutive years of activity and define the transient subnetwork which displays random growth and accounts for very little traded mass. The trades of intermediate duration display an exponential growth both in numbers and in traded mass and define the intermediate subnetwork. The topology of each subnetwork is a time invariant. The identification of invariant structures is a useful basis for developing prospective agri-food network modelling to assess their resilience to perturbations and shocks.
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页数:21
相关论文
共 52 条
[1]   powerlaw: A Python']Python Package for Analysis of Heavy-Tailed Distributions [J].
Alstott, Jeff ;
Bullmore, Edward T. ;
Plenz, Dietmar .
PLOS ONE, 2014, 9 (01)
[2]   Classes of small-world networks [J].
Amaral, LAN ;
Scala, A ;
Barthélémy, M ;
Stanley, HE .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2000, 97 (21) :11149-11152
[3]  
[Anonymous], 2003, LINKED NEW SCI NETWO
[4]  
[Anonymous], 2016, Network Science
[5]  
[Anonymous], 2018, [No title captured], P44
[6]  
[Anonymous], 2009, CHINESE PHYS LETT, DOI [10.1088/0256-307X/26/11/118901, DOI 10.1088/0256-307X/26/11/118901]
[7]   Emergence of scaling in random networks [J].
Barabási, AL ;
Albert, R .
SCIENCE, 1999, 286 (5439) :509-512
[8]   On the temporal variability of the virtual water network [J].
Carr, Joel A. ;
D'Odorico, Paolo ;
Laio, Francesco ;
Ridolfi, Luca .
GEOPHYSICAL RESEARCH LETTERS, 2012, 39
[9]  
Chapagain A.K., 2003, Virtual water flows between nations in relation to trade in livestock and livestock products
[10]   Teleconnected food supply shocks [J].
d'Amour, Christopher Bren ;
Wenz, Leonie ;
Kalkuhl, Matthias ;
Steckel, Jan Christoph ;
Creutzig, Felix .
ENVIRONMENTAL RESEARCH LETTERS, 2016, 11 (03)