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. 2022 Nov 16;12(1):19641.
doi: 10.1038/s41598-022-21777-1.

Robustness and efficiency of international pesticide trade networks subject to link removal strategies

Wen-Jie Xie  1   2 , Jian-An Li  1 , Na Wei  1 , Li Wang  3 , Wei-Xing Zhou  4   5   6
Affiliations

Robustness and efficiency of international pesticide trade networks subject to link removal strategies

Wen-Jie Xie et al. Sci Rep. .

Abstract

The international pesticide trade network (iPTN) is a key factor affecting global food production and food security. The trade relationship is a key component in iPTNs. In a complex international trade environment, we model the impacts of uncertain factors such as trade wars, economic blockades and local wars, as removing vital relationships in the trade network. There are many complex network studies on node centrality, but few on link centrality or link importance. We propose a new method for computing network link centrality. The main innovation of the method is in converting the original network into a dual graph, the nodes in the dual graph corresponding to the links of the original network. Through the dual graph, the node centrality indicators can measure the centrality of the links in the original network. We verify the effectiveness of the network link centrality indicator based on the dual graph in the iPTN, analyze the relationship between the existing network link centrality indicators and the indicator proposed in this paper, and compare their differences. It is found that the trade relationships with larger indicators (hub, outcloseness, outdegree) based on the dual graph have a greater impact on network efficiency than those based on the original pesticide trade networks.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
An example of the topology of the international pesticide trade network (iPTN) with part of links in 2018. The six plots correspond to the trade networks of pesticide products, including (a) aggregated, (b) insecticides, (c) fungicides, (d) herbicides, (e) disinfectants, and (f) rodenticides and other similar products.
Figure 2
Figure 2
Example of building a dual graph. (a) Original graph. (b) Dual graph.
Figure 3
Figure 3
Spearman’s rank correlation coefficients between link centrality indicators in international pesticide trade networks in 2018. The six plots correspond to the trade networks of pesticide products, including (a) aggregated, (b) insecticides, (c) fungicides, (d) herbicides, (e) disinfectants, and (f) rodenticides and other similar products.
Figure 4
Figure 4
The relation between the proportion p of the deleted links and the proportion γI of the number of economies in the largest component formed by the remaining network links after deleting the links according to the indicator I. In the legends, descend, ascend and random correspond to the cases of preferentially deleting the largest, smallest and random links with indicator I, respectively. Each plot corresponds to a link importance or centrality indicator.
Figure 5
Figure 5
Comparison of the influence of different indicators on network robustness. In the legends, descend, ascend and random correspond to the cases of preferentially deleting the largest, smallest and random links of the indicator I, respectively. The six plots correspond to the trade networks of pesticide products, that is, (a) aggregated, (b) insecticides, (c) fungicides, (d) herbicides, (e) disinfectants, and (f) rodenticides and other similar products.
Figure 6
Figure 6
Comparison of the influence of different indicators on network robustness. In the legends, descend, ascend and random correspond to the cases of preferentially deleting the largest, smallest and random links of the indicator I, respectively. Each plot corresponds to an link importance or centrality indicator.
Figure 7
Figure 7
The relation between the proportion p of the deleted links and the network efficiency βI of the remaining network links after deleting the links according to the indicator I. In the legends, descend, ascend and random correspond to the cases of preferentially deleting the largest, smallest and random links with indicator I, respectively. Each plot corresponds to a link importance or centrality indicator.
Figure 8
Figure 8
Comparison of the influence of different indicators on network efficiency. In the legends, descend, ascend and random correspond to the cases of preferentially deleting the largest, smallest and random links of the indicator I, respectively. The six plots correspond to the trade networks of pesticide products are (a) aggregated, (b) insecticides, (c) fungicides, (d) herbicides, (e) disinfectants, and (f) rodenticides and other similar products.
Figure 9
Figure 9
Comparison of the influence of different indicators on network efficiency. In the legends, descend, ascend and random correspond to the cases of preferentially deleting the largest, smallest and random links of the indicator I, respectively. Each plot corresponds to an link importance or centrality indicator.
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