预测生物控制中的自然敌人的有效性,使用事先分析
Andrew Paul Gutierrez1,2, Luigi Ponti3,4, Peter Neuenschwander5
1Center for the Analysis of Sustainable Agroecological Systems, Kensington, CA, 94707-1035, USA. CASAS.global@berkeley.edu.
Scientific reports
|December 29, 2025
概括
预测自然敌人对入侵物种控制的有效性至关重要. 机械模型可以预测预释成功,改善生物控制和全球粮食安全.
科学领域:
- 生态生态学 生态生态学
- 农业科学 农业科学
- 生物控制 生物控制
背景情况:
- 侵入性物种对农业和自然系统造成重大全球损失.
- 引入自然敌人用于生物控制的成功率很低,这是由于无法预测的有效性.
- 现有的对生物控制工作的审查缺乏预测释放前有效性的方法.
研究的目的:
- 开发和演示一种方法来预测生物控制中自然敌人的释放前有效性.
- 分析引入的自然敌人和特有病原体对控制非洲入侵害虫的贡献.
- 评估生物控制对不同非洲生态区木产量恢复的影响.
主要方法:
- 利用了天气驱动的三倍增长性生理学基础的人口模型 (PBDM).
- 在非洲解构了麻豆虫 (CM) 和麻豆绿虫 (CGM) 的生物控制.
- 对模拟结果进行生物经济分析,以分析控制贡献和收益回收.
主要成果:
- 使用PBDM的预先释放前分析准确地预测了CM和CGM的生物控制.
- PBDM分析解释了其他历史生物控制计划的成功和/或失败.
- 该研究确定了自然敌人和真菌病原体对害虫控制的具体贡献.
结论:
- 精确参数化的机械模型,如PBDMs,可以可靠地预测释放前自然敌人的有效性.
- 这种预测能力可以显著提高生物控制计划的成功率.
- 通过有效管理入侵物种,实施此类模型对于改善全球粮食安全至关重要.
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