Identification and Spatiotemporal Dynamics of Suitable Habitats for Dasyhippus barbipes (Fischer-Waldheim, 1846) (Orthoptera: Acrididae: Gomphocerinae) Using a Coupled Random Forest and MaxEnt Approach

Grasshopper outbreaks severely threaten pastoral agriculture and grassland ecosystems in Inner Mongolia, China. Identifying suitable habitats and understanding their monthly dynamics are critical for early warning and targeted control. This study integrated multi-source remote sensing data (Moderate Resolution Imaging Spectroradiometer land surface temperature (MODIS LST), normalized difference vegetation index (NDVI), and enhanced vegetation index (EVI)), meteorological data (precipitation and temperature), soil and topographic variables, and field survey data (May–July 2023) to construct a coupled Random Forest (RF) and Maximum Entropy (MaxEnt) model for the dominant grasshopper species Dasyhippus barbipes. Key objectives were to identify environmental variables at different developmental stages, map monthly suitable habitats, quantify inter-monthly spatiotemporal-shift patterns of suitable habitats using a suitability class transition matrix, and analyze association patterns of NDVI, precipitation, and LST with suitability transitions. The results showed the following: (1) Key drivers varied monthly—vegetation/soil types, precipitation, and FVC dominated in May; FVC, SOC, slope, and NDVI increased in June; and soil, vegetation, aspect, and Max. The temperature of Warmest Month (Bio5) dominated in July. (2) Highly suitable areas expanded eastward from central Xilingol League and Chifeng City, following west-to-east and center-to-north-and-south diffusion patterns. (3) Vegetation green-up, precipitation (as a limiting moisture driver), and LST (threshold effects on development rates) jointly formed a vegetation–water–heat synergistic system. (4) The coupled Random Forest (RF) and Maximum Entropy (MaxEnt) model achieved high accuracy (AUC > 0.91), with variable importance matching observed spatiotemporal patterns. This study elucidates the monthly scale evolution of D. barbipes-suitable habitats and multi-factor associations between environmental predictors and habitat suitability, providing a scientific basis for refined monitoring, early warning, and green control in Inner Mongolia’s typical steppes.