Study of Illegal Wildlife Trade based on ARIMA and Linear Regression Modeling

Abstract

Illegal wildlife trade has been on the rise in recent years, posing a threat to endangered species and ecosystems. In response to this problem, this study aims to identify the most suitable clients to implement anti-illegal trade projects and assess their capacity. Using a client assessment model, we identified the World Customs Organization as the most suitable to undertake a five-year project, predicted trade trends through an ARIMA model, and demonstrated project effectiveness. Intervention analysis showed that the project could reduce the number of illegal transactions. However, the project required more resources and authority. Linear regression modeling reveals that the client needs to be upgraded in many areas. This study provides important guidance for reducing illegal wildlife trade and calls for increased cooperation and resource allocation to protect wildlife ecosystems.