Long-Term Spatiotemporal Pattern and Temporal Dynamic Simulation of Pine Wilt Disease

As a prominent forest pest on international quarantine lists, pine wilt disease (PWD) is characterized by its ease of transmission, rapid onset, high mortality rate, and the complexity of its prevention and control. The disease inflicts devastating damage on pine forest ecosystems and biodiversity in affected regions, resulting in substantial losses of ecological and economic value. This study uses 40 years of county-level data on PWD occurrences in China to investigate the historical spatiotemporal distribution patterns, the spreading process, and the impact of PWD on forest ecosystems. We divided the spread of PWD in China into three stages based on the changes in the number of affected areas. We used SaTScan spatial scanning to analyze the spatiotemporal distribution patterns and regional characteristics of the disease in each stage. Based on the spatial relationships of the affected areas, we identified two types of spread, namely continuous spread and leapfrogging spread, and conducted ecological models of the two spreading processes to describe the spread of PWD over the past 40 years. The results indicate that PWD has two major expansion periods in China. They show a diffusion pattern spreading from points to areas, ultimately forming four clusters with regional characteristics. Driving factors were selected for model construction based on the biological characteristics and spatiotemporal distribution patterns of PWD. The Susceptible (SIS) model and Random Forest (RF) model achieve good results in simulating continuous and leapfrog spread. By integrating the models of the two spreading processes, we can clearly quantify the 40-year spread of PWD in China. The long-term dynamic ecological modeling of PWD, based on historical dissemination characteristics, facilitates the development of disaster prediction models and the maintenance of forest ecosystems while also providing case studies for the invasion and spread of forest pests and pathogens.