Identification and classification of risk zones for Calliptamus italicus based on remote sensing and ensemble modeling: considering population density and habitat suitability

Abstract

Locust outbreaks remain a major challenge to global ecological and environmental security. Calliptamus italicus is the most common migratory locust in the China-Kazakhstan border region. Although relevant countries are actively carrying out control, the excessively large control area has become an important burden. Previous studies have mapped its potential suitable areas, but most studies used only a single model and focused only on suitability changes. Limited attention has been paid to the effect of density on population distribution. This study identifies risk zones by integrating potential suitable areas with population density. It aims to enhance suitable habitat prediction and is of great significance for improving locust control. Based on five categories of Earth observation data and field-surveyed occurrence and density data, this study constructed a regional risk zoning framework using nine models, geographical detector, and path analysis. The ensemble model yielded an AUC value of 0.98, outperforming previous studies in this region. The suitable areas of Calliptamus italicus showed a radial spatial pattern expanding outward from highly suitable areas. Seasonal temperature and precipitation, vegetation condition, and soil texture had the highest explanatory power for regional locust density, and formed multiple impact pathways. Risk zones were distributed in the northern part of the study area and the transboundary continuous grassland belt, and gradually extended toward the central region, showing an overall banded or mosaic spatial pattern. A spatial mismatch existed between suitable areas and risk zones, highlighting the complementary value of field-measured density data in locust risk assessment. This framework helps provide a new perspective for pest management and control under climate change.