基于生长期间最大模型的内蒙古虫发生风险预测方法的研究
Fu Wen1,2, Ronghao Liu2, Axel Garcia Y Garcia3,4
1International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.
Journal of economic entomology
|March 17, 2024
概括
在内蒙古,对 (Oedaleus decorus asiaticus) 感染风险的动态监测对于可持续的畜牧业至关重要. 一个Maxent模型准确地预测了子息地,确定了风险评估的关键环境驱动因素.
科学领域:
- 生态建模 生态建模
- 害虫管理 害虫管理 害虫管理
- 遥感应用 遥感应用
背景情况:
- 虫侵袭对内蒙古的草原和畜牧业构成重大威胁.
- 有效监测风险对于可持续的畜牧业至关重要.
研究的目的:
- 使用Maxent模型和遥感数据预测Oedaleus decorus asiaticus的发生情况.
- 确定影响分布和风险水平的关键环境变量.
主要方法:
- 利用马克森特模型来预测Oedaleus decorus asiaticus的息地适宜性.
- 集成的遥感数据与环境变量.
- 应用风险指数模型来评估 2019-2022 年的虫分布.
主要成果:
- 马克森特模型表现出高预测精度 (AUC = 0.966).
- 适合息地数据,温度-植被干燥指数和气象因素是虫分布的关键驱动因素.
- 一级风险区域集中在内蒙古的中部,东部和西南部.
- 在过冬期间积累的降水和陆地表面温度异常显著影响了风险波动.
结论:
- 这项研究为在内蒙古监测Oedaleus decorus asiaticus提供了一个强大的框架.
- 环境因素,特别是息地适宜性和气候异常,对于预测风险至关重要.
- 结果支持草原生态系统中的害虫管理的知情决策.
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