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Quantitative analysis of the spread pattern of pine wilt disease from the Yangtze River Basin in China
Haochang Hu1, Hongwei Zhou1, Chengzhe Wang1
1College of Computer and Control Engineering, Northeast Forestry University, Harbin, China.
Background:
Pine wilt disease (PWD) poses a severe threat to the stability of China's ecosystems and their carbon sequestration capacity. However, the complex interactions between natural and anthropogenic spread pathways remain poorly quantified. By analyzing epidemic subcompartment records from 2014 to 2023, this study established quantitative thresholds to distinguish natural from anthropogenic spread, simulated the historical anthropogenic spread process, and identified the spatiotemporal drivers underlying both spread patterns.
Results:
The research findings indicate a maximum natural spread distance of 2.725 km per year. Distances beyond this threshold were attributed to anthropogenic spread. Across the decade, anthropogenic spread averaged 36.916 km year, peaking at 91.959 km in outbreak intensive years. A geodetector analysis revealed that natural spread was primarily influenced by normalized difference vegetation index (NDVI), wind speed, and temperature, whereas anthropogenic spread was influenced by road density. By integrating road hierarchy data, wood processing plant locations and wood transportation logistics, the study simulated the anthropogenic spread pattern and mapped cross-regional long-distance spread corridors.
Conclusion:
This study provides the distance-based quantitative criterion distinguishing natural and anthropogenic PWD spread, and demonstrates that long-distance dispersal is overwhelmingly driven by human activities. The integrated probability modeling and road network framework offers an operational tool for identifying high-risk pathways and supports targeted surveillance, quarantine design, and regional management strategies for PWD and other human-vectored forest pests. © 2026 Society of Chemical Industry.
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