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Spati-Temporal Dynamics of Bio-Production Systems by Chaos Time Series Analysis

混沌时间序列分析生物生产系统的时空动力学

基本信息

批准号：
14360148
负责人：
SAKAI Kenshi
金额：
$ 9.41万
依托单位：
Tokyo University of Agriculture and Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2002
资助国家：
日本
起止时间：
2002 至 2005
项目状态：
已结题

项目摘要

The concept of deterministic chaos is attractive for ecologists, because it implies an underlying order behind the complexity of ecological systems. Nonlinear time series analysis (NTSA) is used to investigate deterministic chaos. However, most ecological time series are too short to perform NTSA, which requires a time series whose size is in the thousands. On the application of NTSA on ecological dynamics., we need to develop appropriate way to reconstruct ecological dynamics with limited data, and observation. Here we propose "ensemble reconstruction" of the dynamics from a very short ecological time series whose size is smaller than ten. In most tree crops such as citrus, nuts and acorns, the yield alternates between high and low yielding years. Isagi, et al. proposed a theoretical model that describes masting as chaos that can be applied to alternate bearing. We used an ensemble dataset consisting of the yields of 48 individual trees over 7 years to test our proposed method and successfully validated this method by one-year forward prediction three times in 2002, 2003 and 2004. We also show that conventional tools such as Lyapunov spectrum and correlation dimension can be applied with the ensemble reconstruction method. This method offers an essential tool to realize an ecosystem approach towards and/or adaptive control of real world ecosystems and their biodiversity. We also conducted remote sensing to estimate the spatio-temporal dynamics.

确定性混沌的概念对生态学家来说很有吸引力，因为它暗示了生态系统复杂性背后的潜在秩序。非线性时间序列分析 (NTSA) 用于研究确定性混沌。然而，大多数生态时间序列都太短，无法执行 NTSA，而 NTSA 需要大小为数千的时间序列。在NTSA在生态动力学中的应用上，我们需要开发适当的方法来利用有限的数据和观测来重建生态动力学。在这里，我们提出从规模小于 10 的非常短的生态时间序列中进行动态的“整体重建”。大多数木本作物，如柑橘、坚果和橡子，产量在高产年份和低产年份之间交替。伊佐吉等人。提出了一种理论模型，将桅杆描述为可应用于备用方位的混沌。我们使用由 48 棵单树 7 年产量组成的集成数据集来测试我们提出的方法，并通过 2002 年、2003 年和 2004 年三次的一年前向预测成功验证了该方法。我们还表明，Lyapunov 谱和相关维数等常规工具可以应用于集成重建方法。该方法提供了一个重要的工具来实现对现实世界生态系统及其生物多样性的生态系统方法和/或适应性控制。我们还进行了遥感来估计时空动态。