Analysis reveals that incorporating droughts and heatwaves improves forest pest predictions in China, indicating a need for better management strategies.
Key Points
Main finding shows that including compound drought and heatwave events enhances forest pest incident predictions.
Key evidence indicates a 10.6% improvement in predictive performance when including compound events over basic models.
The approach utilized machine learning to assess pest incidence data across several cities in China from 2003 to 2018.
Significance lies in providing insights into climate change effects on forest health and aiding in pest management strategies.