{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Lu L"],"funding":["Director Fund of the International Research Center of Big Data for Sustainable Development Goals","Inner Mongolia Autonomous Region science and technology planning project","Strategic Priority Research Program of Chinese Academy of Sciences","Central Public-interest Scientific Institution Basal Research Fund"],"pagination":["894"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9603866"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["13(10)"],"pubmed_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 si"],"journal":["Insects"],"pubmed_title":["Detecting Key Factors of Grasshopper Occurrence in Typical Steppe and Meadow Steppe by Integrating Machine Learning Model and Remote Sensing Data."],"pmcid":["PMC9603866"],"funding_grant_id":["2021GG0069","Y2021XK24","CBAS2022DF001","XDA26010304"],"pubmed_authors":["Lu L","Wang N","Du B","Huang W","Eerdengqimuge","Zhou Y","Ye H","Sun Z","Weijun","Kong W"],"additional_accession":[]},"is_claimable":false,"name":"Detecting Key Factors of Grasshopper Occurrence in Typical Steppe and Meadow Steppe by Integrating Machine Learning Model and Remote Sensing Data.","description":"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 si","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Sep","modification":"2025-04-04T11:29:27.959Z","creation":"2025-04-04T11:29:27.959Z"},"accession":"S-EPMC9603866","cross_references":{"pubmed":["36292842"],"doi":["10.3390/insects13100894"]}}