Wildlife trade study based on the ANOVA method

Abstract

Today, 78% of new human infectious diseases originate from wild animals. A complete ban on wildlife trade would be effective in stopping the occurrence and spread of infectious diseases, but it is estimated that a ban on wild meat consumption could cost China's economy 50 billion RMB ($7.1 billion) and put millions of people out of work. Therefore, it is worth considering whether the wildlife trade should be banned in the long term. In this paper, we first collected data on wildlife trade for 20 years and performed steps such as integrating and classifying the data, testing statistics, data pre-processing, and eliminating outliers. The most traded species was the macaque. Then, a principal component analysis was conducted to analyze the contribution of each purpose of wildlife trade, and a multiple regression analysis was used to obtain the most important purposes of commercial, zoo, and circus or traveling exhibitions. Finally, through one-way ANOVA, it was found that wildlife trade import and export data did not vary much in different years, but in 2019, the number of imports decreased sharply and the number of exports surged.