数字农科院2.0

Spatial and Temporal Variability of Grassland Grasshopper Habitat Suitability and Its Main Influencing Factors

文献类型: 外文期刊

作者: Du, Bobo;Wei, Jun;Lin, Kejian;Lu, Longhui;Ding, Xiaolong;Ye, Huichun;Huang, Wenjiang;Wang, Ning

作者机构:

关键词: grasshopper;Maxent;remote sensing;influencing factors;suitable area

期刊名称: REMOTE SENSING

ISSN:

年卷期: 2022 年 14.0 卷 16 期

页码:

摘要: Grasshoppers are highly destructive pests, and their outbreak can directly damage livestock development. Grasshopper outbreaks can be monitored and forecasted through dynamic analysis of their potential geographic distribution and main influencing factors. By integrating vegetation, edaphic, meteorological, topography, and other geospatial data, this study simulated the grasshopper suitability index in Hulunbuir grassland using maximum entropy species distribution modeling (Maxent). The Maxent model showed high accuracy, with the training area under the curve (AUC) value ranging from 0.897 to 0.973 and the testing AUC ranging from 0.853 to 0.971 for the past 13 years. The results showed that suitable areas, including the most suitable area and moderately suitable area, accounted for a small proportion and were mainly located in the eastern and southern parts of the study area. According to model analysis based on 51 environmental factors, not all factors played a significant role in the grasshopper cycle. Moreover, differences in environmental factors drive the spatial variability of suitable areas for grasshoppers. The monitoring and prediction of potential outbreak areas can be improved by identifying major environmental factors having large variability between suitable and unsuitable areas. Future trends in grasshopper suitability indices are likely to contradict past trends in most of the study area, with only approximately 33% of the study area continuing the past trend. The results are expected to guide future monitoring and prediction of grasshoppers in Hulunbuir grassland.

分类号:

  • 相关文献

[1]Assessment on Potential Suitable Habitats of the Grasshopper Oedaleus decorus asiaticus in North China based on MaxEnt Modeling and Remote Sensing Data. Zhongxiang Sun,Huichun Ye,Wenjiang Huang,Erden Qimuge,Huiqing Bai,Chaojia Nie,Longhui Lu,Binxiang Qian,Bo Wu. 2023

[2]Assessing the establishment risk for parthenogenetic populations of Lissorhoptrus oryzophilus in global rice-growing areas and potential economic impact in China. Li, Luoyuan,Jin, Zhenan,Li, Ming,Xue, Yantao,Guo, Jianyang,Jia, Dong,Ma, Ruiyan,Lue, Zhichuang,Xian, Xiaoqing,Liu, Wanxue. 2025

[3]基于MaxEnt模型的小麦印度腥黑穗病在中国的适生性分析. 周益林,赵遵田,段霞瑜. 2010

[4]香蕉细菌性枯萎病菌在中国的潜在适生区域. 陈林,许景生,张争,张昊,冯洁. 2008

[5]基于MaxEnt的麦瘟病在全球及中国的潜在分布区预测. 陈林,周益林,段霞瑜. 2011

[6]基于MaxEnt的麦田恶性杂草节节麦的潜在分布区预测. 张朝贤,黄红娟,李燕,陈景超,杨龙,魏守辉. 2013

[7]潜在外来入侵甜菜孢囊线虫在中国的适生阵风险分析. 彭德良,刘淑艳. 2008

[8]危险性外来入侵香蕉穿孔线虫在我国的适生性风险分析. 彭德良. 2008

[9]基于MaxErrt模型的小麦印度腥黑穗病在中国的适生性分析. 周益林,赵遵田,段霞瑜. 2010

[10]潜在外来入侵香蕉穿孔线虫在我国的适生性风险分析. 彭德良. 2008

[11]潜在外来入侵甜菜孢囊线虫在中国的适生性风险分析. 彭德良,刘淑艳. 2008

[12]利用MAXENT预测玉米霜霉病在中国的适生区. 陈林,丁克坚,段霞瑜,周益林. 2009

[13]多种生物潜在分布预测分析软件功能对比分析. 程登发,田喆,张云慧,孙京瑞. 2007

[14]相似穿孔线虫在中国的适生区预测. 谢丙炎,万方浩,肖启明,戴良英. 2007

[15]基于优化的MaxEnt模型预测海灰翅夜蛾潜在地理分布区. 赵浩翔,冼晓青,郭建洋,张桂芬,王瑞,刘万学,万方浩. 2022

[16]沙漠蝗在中国的潜在地理分布. 张源,秦誉嘉,赵紫华,涂雄兵,张泽华,李志红. 2021

[17]基于MaxEnt模型的银胶菊及其天敌银胶菊叶甲的适生区预测. 陈地宝,张玉,杨鸣,林蓉,刘万学,Weyl Philip,冼晓青. 2025

[18]Quantitative Analysis of Plant Consumption and Preference by Oedaleus asiaticus (Acrididae: Oedipodinae) in Changed Plant Communities Consisting of Three Grass Species. Zhang, Z.,McNeill, M..

[19]Diets structure of a common lizard Eremias argus and their effects on grasshoppers: Implications for a potential biological agent. Wu, Huihui,Tu, Xiongbing,Wang, Guangjun,Cao, Guangchun,Nong, Xiangqun,Zhang, Zehua,Zhang, Zhuoran,Su, Hongtian,Shi, Yongming. 2016

[20]Dietary Stress From Plant Secondary M.etabolites Contributes To Grasshopper ( Oedaleus Asiaticus) Migration Or Plague By Regulating Insect Insulin-Like Signaling Pathway. Huang, Xunbing,Liu, Wen,Huang, Xunbing,Li, Shuang,Tu, Xiongbing,Zhang, Zehua,Zhang, Zehua,McNeill, Mark Richard,Lv, Shenjin,Ma, Jingchuan,Ma, Jingchuan,Tu, Xiongbing. 2019

作者其他论文 更多>>