利用非参数内在可预测性检验检测种群时间序列中的随机性

IF 6.3 2区 环境科学与生态学 Q1 ECOLOGY
Bilgecan Şen, Christian Che-Castaldo, Heather J. Lynch, Francesco Ventura, Michelle A. LaRue, Stéphanie Jenouvrier
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引用次数: 0

摘要

许多以随机动态为主的生态系统会产生复杂的时间序列,从本质上限制了预测的准确性。这些系统的 "内在可预测性 "可以用一种称为加权排列熵(WPE)的时间序列复杂度指标来近似表示。虽然 WPE 是在建立模型前衡量预测性能的有用指标,但它对噪声很敏感,而且可能因时间序列的长度而产生偏差。在此,我们引入了一种简单的随机排列测试(rWPE),以评估时间序列的内在可预测性是否高于白噪声。我们将 rWPE 应用于模拟数据和经验数据,以评估其性能和实用性。为此,我们模拟了各种情况下的种群动态,包括线性趋势、混沌、周期和平衡动态。我们还利用全球种群动态数据库(Global Population Dynamics Database)中 4 个动物纲 932 个物种的观测丰度时间序列对这一方法进行了进一步测试。最后,我们使用阿德利企鹅(Pygoscelis adeliae)和帝企鹅(Aptenodytes forsteri)的时间序列作为案例研究,展示了 rWPE 在单一物种多个种群中的应用。我们的研究表明,rWPE 可以确定一个系统的可预测性是否明显高于白噪声,即使是短至 10 年的时间序列,在生物现实随机性水平下也能显示出明显的趋势。此外,当时间序列至少有 30 个时间步长并显示出混沌或周期性动态时,rWPE 的统计功率接近 100%。在平衡动力学条件下,无论时间序列长短,统计能力都会下降到 10%左右。在四类动物分类群中,哺乳动物的时间序列相对频率最高(28%),它们的时间序列长度超过 30 个时间步长,而且在复杂性方面与白噪声无异,其次是昆虫(16%)、鸟类(16%)和多骨鱼类(11%)。通过告知预测者系统可预测性的内在限制,它可以指导建模者对预测性能的预期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Detecting stochasticity in population time series using a non-parametric test of intrinsic predictability

Detecting stochasticity in population time series using a non-parametric test of intrinsic predictability

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来源期刊
CiteScore
11.60
自引率
3.00%
发文量
236
审稿时长
4-8 weeks
期刊介绍: A British Ecological Society journal, Methods in Ecology and Evolution (MEE) promotes the development of new methods in ecology and evolution, and facilitates their dissemination and uptake by the research community. MEE brings together papers from previously disparate sub-disciplines to provide a single forum for tracking methodological developments in all areas. MEE publishes methodological papers in any area of ecology and evolution, including: -Phylogenetic analysis -Statistical methods -Conservation & management -Theoretical methods -Practical methods, including lab and field -This list is not exhaustive, and we welcome enquiries about possible submissions. Methods are defined in the widest terms and may be analytical, practical or conceptual. A primary aim of the journal is to maximise the uptake of techniques by the community. We recognise that a major stumbling block in the uptake and application of new methods is the accessibility of methods. For example, users may need computer code, example applications or demonstrations of methods.
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