Detecting Key Factors of Grasshopper Occurrence in Typical Steppe and Meadow Steppe by Integrating Machine Learning Model and Remote Sensing Data

Abstract

Grasshoppers mainly threaten natural grassland vegetation and crops. Therefore, it is of great significance to understand the relationship between environmental factors and grasshopper occurrence. This paper studies the spatial distribution and key factors of grasshopper occurrence in two grass types by integrating a machine learning model (Maxent) and remote sensing data within the major grasshopper occurrence areas of Inner Mongolia, China. The modelling results demonstrate that the typical steppe has larger suitable area and more proportion for grasshopper living than meadow steppe. The soil type, above biomass, altitude and temperature mainly determine the grasshopper occurrence in typical steppe and meadow steppe. However, the contribution of these factors in the two grass types is significantly different. In addition, related vegetation and meteorological factors affect the different growing stages of grasshoppers between the two grass types. This study clearly defines the different effects of key environmental factors (meteorology, vegetation, soil and topography) for grasshopper occurrence in typical steppe and meadow steppe. It also provides a methodology to guide early warning and precautions for grasshopper pest prevention. The findings of this study will be helpful for future management measures, to ensure grass ecological environment security and the sustainable development of grassland.

Analysis of Spatiotemporal Variation in Habitat Suitability for Oedaleus decorus asiaticus Bei-Bienko on the Mongolian Plateau Using Maxent and Multi-Source Remote Sensing Data

“…During the overwintering period, extremely low temperatures reduced the survival of grasshopper eggs [ 44 ]. In the hatching period, aside from low temperatures, which could induce the death or diapause of grasshopper eggs [ 55 ], the soil type and precipitation could affect the hatching success rate of grasshopper eggs [ 14 ]. In the nymph and emergence periods, the food and growth environment determined whether grasshoppers could grow normally [ 14 ].…”

“…In this study, the suitable threshold of the Maxent model was set to 0.5. Based on the literature and expert experience [ 8 , 14 , 60 , 61 ], the suitability of each habitat factor was divided into low suitability (<0.5), medium suitability (0.5–0.6), and high suitability (>0.6). In calculations, areas with low suitability were assigned values of 1, areas with medium suitability were assigned values of 2, and areas with high suitability were assigned values of 3.…”

“…The distributions of grasshoppers cannot be characterized using satellite remote sensing images because of their small size [ 14 ]. Recent studies have shown that the growth and development of grasshoppers are closely related to their habitat [ 15 ], including meteorological, topographical, soil, and vegetation factors [ 16 , 17 , 18 , 19 , 20 ].…”

“…Figure3shows the response curve, which indicates the relationships between grasshopper suitability and key habitat factors on the Mongolian Plateau. The classification threshold of each habitat factor was determined based on the default setting of the Maxent model (suitability threshold of 0.5), the literature, and expert experience[14,62]. The suitability of each habitat factor was divided into three levels: low (<0.5), medium (0.5-0.6), and high (>0.6).…”

Innovative approach to predict soil moisture using the backpropagation‐Elman neural network

“…The inter‐monthly variability of precipitation is significant, with the main concentration from June to September, accounting for approximately 74.4% of the annual precipitation. The dominant soil type in the area is Chestnut Soil, and the most widespread plant communities are Leymus chinensis (Trinius ex Bunge) Tzvelev and Stipa grandis P. Smirn communities (Kolås et al., 2014; Liu et al., 2021; Lu et al., 2022).…”