Economy importance and structural robustness of the international pesticide trade networks

TL;DR

This paper analyzes the importance and robustness of the international pesticide trade network, revealing how different economies contribute and how the network withstands various shocks over time.

Contribution

It introduces a comprehensive evaluation of economic importance using nine node metrics and examines the network's structural robustness under different shock scenarios.

Findings

Clustering coefficient negatively correlates with other node metrics.

The network is robust under certain shocks but fragile under others.

Robustness evolves over time with an inverse U-shape pattern.

Abstract

Pesticides are a kind of agricultural input, whose use can greatly reduce yield loss, regulate plant growth, effectively liberate agricultural productivity, and improve food security. The availability of pesticides in economies all over the world is ensured by pesticide redistribution through international trade and economies play different roles in this process. In this work, we measure and rank the importance of economies using nine node metrics in an evolutionary way. It is found that the clustering coefficient is correlated negatively with the other eight node metrics, while the other eight node metrics are positively correlated with each other and can be grouped into three communities (betweenness; in-degree, PageRank, authority, and in-closeness; out-degree, hub, and out-closeness). We further investigate the structural robustness of the international pesticide trade networks proxied by the giant component size under three types of shocks to economies (node removal in descending order, randomly, and in ascending order). The results show that, except for the clustering coefficient, the international pesticide trade networks are relatively robust under shocks to economies in ascending orders and randomly, but fragile under shocks to economies in descending order. In contrast, removing nodes with the clustering coefficient in ascending and descending orders gives similar robustness curves. Moreover, the structural robustness related to the giant component size evolves over time and exhibits an inverse U-shaped pattern.