关于使用共存结果进行入侵预测的极限
Jie Deng1, Washington Taylor2, Simon A Levin3
1Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
Journal of theoretical biology
|November 26, 2023
概括
生态社区的动态往往涉及入侵过程. 这项研究揭示,虽然个人在共存中的生存预测了入侵者殖民,但社区层面的预测对入侵动态不那么可靠.
科学领域:
- 生态生态学 生态生态学
- 理论生态学理论生态学
- 数学生物学 数学生物学
背景情况:
- 生态社区表现出由概率过程驱动的复杂动态,特别是入侵.
- 理论和实验研究主要侧重于共存动态,因为研究入侵的技术挑战.
- 了解共存和入侵结果之间的关系对于预测自然生态系统至关重要.
研究的目的:
- 从共存动态来研究入侵动态的可预测性.
- 确定共存和入侵结果之间的可翻译性限制.
- 为了解环境不确定性下的这些动态提供一个理论框架.
主要方法:
- 使用了几何和概率的Lotka-Volterra框架.
- 在共存和入侵场景中分析了不同生态结果 (生存,持久性,排除) 之间的概率转换.
- 研究了环境不确定性对这些动态的影响.
主要成果:
- 在共存动态中的个人生存概率与入侵者殖民概率密切相关.
- 社区坚持到社区增强的翻译不那么精确.
- 将排除概率转换为替换概率的翻译是最不准确的.
结论:
- 共存动态提供了部分但不完美的入侵动态预测器.
- 环境不确定性下的Lotka-Volterra框架强调了从共存数据中预测入侵成功的具体局限性.
- 这些发现为生态入侵研究提供了可测试的理论基础.
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