从一种局部描述型到一种通用的预测模型,通过捕食者调节谷物虫的调节
Eric Stell1,2, Riccardo Bommarco3, Amanda N Laubmeier4
1LAE, Université de Lorraine, INRAE, Colmar, France.
The Journal of animal ecology
|May 27, 2024
概括
预测自然捕食者对昆虫害虫的控制是可持续农业的关键. 这项研究改进了食物网模型,整合了更多的生物因素,但发现普遍性增加降低了可靠性,突出了需要更好的数据和特征理解的需要.
科学领域:
- 农业生态学 农业生态学
- 生态生态学 生态生态学
- 数学建模的数学建模
背景情况:
- 农业生态系统中的昆虫害虫种群动态是复杂的,受到生物和非生物因素的影响.
- 预测捕食者和寄生虫的自然调节可以减少对化学农药的依赖.
- 之前的一种食物网模型使用了一种全度假设来模拟在谷物田中的虫动态上的掠食者影响.
研究的目的:
- 扩展和测试现有的食物网模型的适用性和预测能力.
- 将额外的生物功能 (寄生,承载能力,温度影响) 整合到模型中.
- 开发和评估一个多领域校准方法,以提高模型的通用性.
主要方法:
- 参数化了原始模型,使用来自法国54个领域的动态节肢动物社区数据.
- 综合寄生,虫承载能力和温度依赖的生长速度功能.
- 采用多场校准策略来估计通用的全米参数.
主要成果:
- 特定领域的参数化为观察到的虫动态的59% (原始) 和53% (修订) 提供了很好的匹配 (伪R2高达0.99).
- 多场校准提高了模型的通用性,但降低了适合性,表明了权衡.
- 修订后的模型的预测能力需要进一步改进.
结论:
- 改善食物网模型需要更深入地了解身体大小和其他特征如何影响食物互动.
- 获得高分辨率的生态数据对于有效应用这些建模方法至关重要.
- 未来的改进应该整合额外的生物功能和功能特征超越身体大小.
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