Grasshoppers, as pernicious pests, pose a formidable threat to the advancement of agriculture and animal husbandry. Their presence can elicit a cascade of environmental challenges, underscoring the pressing need for effective control measures. However, grasshopper development is an intricate process influenced by diverse environmental factors with varying weights across regions, making it difficult to prevent and control. Therefore, this study focused on the prevalent infestation region, Xilingol, and selected Dasyhippus barbipes as the research subject because of its highest density and largest damaged area. Initially, according to the development mechanisms of D. barbipes, 31 habitat factors from five categories (meteorology, vegetation, soil, topography, and ecology) were selected; then, difference tests, correlation analysis, importance tests, and principal component analysis were applied to construct representative indicators for monitoring the habitat of D. barbipes (HDB). Subsequently, employing the occurrence data of D. barbipes from 2018 to 2023, a spatial pattern analysis was conducted to explore the hotspot aggregation area (HAA) and spatiotemporal characteristics of D. barbipes. Finally, considering landscape and spatial heterogeneity, the Landscape-based Geographically Weighted Logistic Regression (L-GWLR) model for HDB was constructed to achieve adaptive changes in factor weights across regions. The indicators included minimum temperature during the egg stage, precipitation, and soil temperature during the spawning stage, slope, fractional vegetation coverage in the nymph stage, soil moisture in the 1st to 3rd nymph instar, patch area, and gyration radius. The spatial pattern analysis revealed a significant spatial autocorrelation in the distribution of D. barbipes at a 90 % confidence interval (z > 1.65 and p < 0.1), and HAAs were concentrated in West Ujimqin, XilinHot, and ZhengLan. The habitat monitoring results demonstrated the superior performance of the L-GWLR model over models neglecting landscape or spatial heterogeneity. These findings provide essential support for the environmentally friendly scientific control of grasshoppers, contributing significantly to the sustainable development of agriculture and animal husbandry.

Since the 1970s, the ongoing retreat of the global cryosphere has been affecting human societies and causing a series of snow- and ice-related disasters (SIRDs). Based on existing research results, this paper focuses on searching for the formation mechanism of SIRDs, classifies their types and spatiotemporal scales, and reveals the integrated impacts of the SIRD and its future situation on global high-hazard areas. On land, SIRDs mainly occur in the high mountainous areas of middle-low latitude and the permafrost regions of high latitude, in the behaviors of increasing frequency of glacier/snow/glacier lake outburst flood-related disasters and an expanding range of freeze-thaw disasters. The recorded frost events show a decreasing trend but the hail hazard distributions are greatly heterogenous. Overall, the frequency of rain-on-snow events is projected to increase on land in the future. In the ocean, SIRDs are mainly distributed in the Arctic coastal areas and global low-lying islands or areas, with great potential risk. Among them, coastal freeze-thaw, icebergs, and sea-level rise and its impacts are likely or expected to continue increasing in the next few decades.