Study on the prediction method of grasshopper occurrence risk in Inner Mongolia based on the maximum entropy model during the growing period

Fu Wen, Ronghao Liu, Axel Garcia y Garcia, Huichun Ye, Longhui Lu, Eerdeng Qimuge, Zhongxiang Sun, Chaojia Nie, Xuemei Han, Yue Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

Grasshoppers represent a significant biological challenge in Inner Mongolia’s grasslands, severely affecting the region’s animal husbandry. Thus, dynamic monitoring of grasshopper infestation risk is crucial for sustainable livestock farming. This study employed the Maxent model, along with remote sensing data, to forecast Oedaleus decorus asiaticus occurrence during the growing season, using grasshopper suitability habitats as a base. The Maxent model’s predictive accuracy was high, with an AUC of 0.966. The most influential environmental variables for grasshopper distribution were suitable habitat data (34.27%), the temperature-vegetation dryness index during the spawning period (18.81%), and various other meteorological and vegetation factors. The risk index model was applied to calculate the grasshopper distribution across different risk levels for the years 2019–2022. The data indicated that the level 1 risk area primarily spans central, eastern, and southwestern Inner Mongolia. By examining the variable weights, the primary drivers of risk level fluctuation from 2019 to 2022 were identified as accumulated precipitation and land surface temperature anomalies during the overwintering period. This study offers valuable insights for future O. decorus asiaticus monitoring in Inner Mongolia.

Original languageEnglish (US)
Pages (from-to)843-857
Number of pages15
JournalJournal of economic entomology
Volume117
Issue number3
DOIs
StatePublished - Jun 1 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved.

Keywords

  • influencing factor
  • insect dynamics
  • Maxent
  • predictive modeling
  • remote sensing

PubMed: MeSH publication types

  • Journal Article

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