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关于生态系统动态建模的历史:定性模型的兴起和承诺
Maximilien Cosme1,2, Colin Thomas3, Cédric Gaucherel3
1UMR AMAP, INRAE, University of Montpellier (Faculté des Sciences), IRD, CIRAD, CNRS, 34398 Montpellier, France.
Entropy (Basel, Switzerland)
|November 24, 2023
概括
生态系统建模使用定性离散事件网络 (EDEN) 来解决数据局限性并提高对环境变化的理解. 这种方法增强了生态洞察力,以更好地管理生态系统.
科学领域:
- 生态生态学 生态生态学
- 环境科学 环境科学
- 计算科学 计算科学
背景情况:
- 生态系统建模,起源于20世纪50年代,使用诸如微分方程之类的定量方法来研究生态动力学和人类影响.
- 传统的定量模型面临着局限性,特别是在数据较差的环境中.
- 质量动态建模方法已经出现,以解决这些局限性,为生态系统动态提供替代抽象.
研究的目的:
- 解决复杂,多学科的环境问题建模的挑战,特别是在数据有限的场景.
- 根据目标评估现有的建模方法,如掌握定性动态,最小化参数假设,并实现解释和预测能力.
- 提出一种适用于环境科学中的生态系统建模的新型建模框架.
主要方法:
- 讨论现有的定性动态建模方法及其属性 (例如确定性,随机性,更新同步性).
- 对建模框架的评估与四个关键目标相比:定性动态,最小参数假设,解释能力和预测能力.
- 生态离散事件网络 (EDEN) 建模框架的介绍和描述.
主要成果:
- EDEN框架提供了对生态系统动态的定性,离散事件,部分同步和可能性视角.
- 通过生态实例和现有技术分析EDEN属性,证明了它们对环境科学的相关性.
- EDEN模型为研究生态系统动态提供了有价值的替代方案,特别是当定量数据稀缺时.
结论:
- 拟议的EDEN建模框架非常适合解决生态系统建模中的复杂和多学科挑战.
- EDEN的定性和离散事件性质为生态研究和环境管理提供了灵活和稳健的方法.
- 这一框架提高了研究生态系统动态和人为影响的能力,特别是在数据较差的情况下.
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