Structure and Evolution of the International Pesticide Trade Networks

Abstract

To meet the increasing demand for food around the world, pesticides are widely used and will continue to be widely used in agricultural production to reduce yield losses and maintain product quality. International pesticide trade serves to reallocate the distribution of pesticides around the world. We investigate the statistical properties of the international trade networks of five categories of pesticides from the view angle of temporal directed and weighted networks. We observed an overall increasing trend in network size, network density, average in- and out-degrees, average in- and out-strengths, temporal similarity, and link reciprocity, indicating that the rising globalization of pesticides trade is driving the networks denser. However, the distributions of link weights remain unchanged along time for the five categories of pesticides. In addition, all the networks are disassortatively mixed because large importers or exporters are more likely to trade with small exporters or importers. We also observed positive correlations between in-degree and out-degree, in-strength and out-strength, link reciprocity and in-degree, out-degree, in-strength, and out-strength, while node’s local clustering coefficient is negatively related to in-degree, out-degree, in-strength, and out-strength. We show that some structural and dynamic properties of the international pesticide trade networks are different from those of the international trade networks, highlighting the presence of idiosyncratic features of different goods and products in the international trade.

Structural evolution of international crop trade networks

“…Over the last 26 years, the density rose with some fluctuations, and it indicates that the global food trade is becoming more and more frequent and close. The increasing densities of the iCTNs are consistent with some other international trade networks [38], but are much smaller [25,39] than the total world trade networks. The density curves for rice, maize and wheat showed a linear upward trend, where the density of the rice network had the largest slope of increase and has become the largest since 1998.…”

“…There are much more importing economies than exporting economies, and many economies both export and import the same crops, which is also observed for the international pesticide trade networks [25].…”

“…Figures 3A,B show the yearly evolution of the average indegree and in-strength from 1993 to 2018. The average node indegree represents the average number of exporting partners owned to an economy [30], which is equal to the average node our-degree [25]. Figure 3A shows that the evolution of the average in-degree has an excellent linear growth with respect to time t:…”

“…The degrees and the strengths measure the importance of a node, and we used the average degrees and the average strengths to evaluate the overall structure of the networks. It is easy to get that the average in-degree of nodes 〈k in 〉 V is equal to the average out-degree of nodes 〈k out 〉 V [25]. The average in-strength 〈s in 〉 V and the average out-strength 〈s out 〉 V respectively measure the average values of imports and exports, which are also equal to each other.…”

“…Node similarity has been widely studied for simple networks [44,45] and multi-layer networks [43,46]. This paper adopts a simple indicator to measure the similarity coefficient between two successive networks [25], since the links in iCTNs might look similar or change significantly. Considering two successive networks G(t − 1) and G(t), let E (t−1)∪t E(t − 1) ∪ E(t) be the union set of directed links and E (t−1)∩t E(t − 1) ∩ E(t) be the intersection of directed links.…”