Spatiotemporal Changes of Pine Caterpillar Infestation Risk and the Driving Effect of Habitat Factors in Northeast China - Jingzheng Zhao; Mingchang Wang; Dong Cai; Linlin Wu; Xue Ji; Qing Ding; Fengyan Wang; Minshui Wang (Remote Sensing)
Pine caterpillar (Dendrolimus) infestations threaten pine forests, causing severe ecological and economic impacts. Identifying the driving factors behind these infestations is essential for effective forest management. This study uses the APCIRD framework combined with an improved random forest model to analyze spatiotemporal changes in infestation risk and the driving effects of habitat factors in Northeast China. From 2019 to 2024, we applied SHapley Additive exPlanations (SHAP), frequency analysis, fitting functions, and GeoDetector to quantify the impact of key drivers, such as snow cover and soil, on infestation risk. The findings include (1) the APCIRD framework with the MLP-random forest model (MRF) accurately assesses infestation risks. MRF is composed of MLP and random forest. Between 2019 and 2024, areas with high infestation risk declined, shifting from higher to lower levels, with Eastern Heilongjiang and Southwest Liaoning remaining as key concern areas; (2) snow cover and soil factors are critical to infestation risk, with eight key habitat factors significantly affecting the risk. Their relationships with infestation risk follow complex, non-monotonic quartic and cubic patterns; (3) factors triggering high infestation risks are mostly at low to moderate levels. High-risk areas tend to have low to moderate elevation (<800 m), moderate to high solar radiation and temperature, gentle slopes (<30°), low to moderate evaporation, shallow snow depth (<0.02), moderate snow temperature (266.73–275), low to moderate soil moisture (0.2–0.3), moderate to high soil temperature (276.73–286.92), low to moderate rainfall, moderate wind speed, low leaf area index, high vegetation type, low vegetation cover, low population density, and low surface runoff. Interactions between factors provide a stronger explanation of infestation risk than individual factors. The APCIRD framework, combined with MRF, offers valuable insights for understanding the drivers of pine caterpillar infestations.