Modeling and prediction of phase shifts in noisy two-cycle oscillations
Modeling and prediction of phase shifts in noisy two-cycle oscillations
复制标题
噪声二周期振荡中相移的建模和预测
DOI：
10.1007/s00285-023-01960-2
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发表时间：
2023
影响因子：
1.9
通讯作者：
Hastings, Alan
中科院分区：
文献类型：
--
作者：
Nareddy, Vahini Reddy;Machta, Jonathan;Abbott, Karen;Esmaeili, Shadisadat;Hastings, Alan
理解和预测噪声存在下的生态动力学仍然是一个重大而重要的挑战。鉴于许多生态数据质量差，许多生态模型不精确，情况尤其如此。作为这个问题的第一种方法，我们在这里集中在一个简单的系统表示为一个离散时间模型与2周期的行为，反映交替的高和低人口规模。这种动态自然出现在生态系统与过度补偿密度依赖。我们要问的是，人口估计中包含的细节数量如何影响预测振荡阶段变化可能性的能力，这意味着高人口数是发生在奇数年还是偶数年。我们通过将连续的人口水平转换为简单的，粗粒度的描述，使用两个状态和四个状态的模型来调整细节的水平。我们还考虑了三个参数的三次噪声过补偿模型。对相位变化的关注是我们所问的问题和我们使用的方法与更标准的时间序列方法的区别。显然，添加观测状态提高了预测相移的能力。特别地，四态模型和立方模型优于两态模型，因为它们包括过渡状态，动力学通常在相变期间通过该过渡状态。尽管如此，在高噪音水平的预测技能的改善是相对温和的。此外，相位变化的频率强烈地依赖于噪声水平，并且受总体模型中确定幅度的参数的影响要小得多，因此相移频率可能用于推断噪声水平。
Understanding and predicting ecological dynamics in the presence of noise remains a substantial and important challenge. This is particularly true in light of the poor quality of much ecological data and the imprecision of many ecological models. As a first approach to this problem, we focus here on a simple system expressed as a discrete time model with 2-cycle behavior, reflecting alternating high and low population sizes. Such dynamics naturally arise in ecological systems with overcompensatory density dependence. We ask how the amount of detail included in the population estimates affects the ability to forecast the likelihood of changes in the phase of oscillation, meaning whether high populations occur in odd or in even years. We adjust the level of detail by converting continuous population levels to simple, coarse-grained descriptions using two-state and four-state models. We also consider a cubic noisy over-compensatory model with three parameters. The focus on phase changes is what distinguishes the question we are asking and the methods we use from more standard time series approaches. Obviously, adding observation states improves the ability to forecast phase shifts. In particular, the four-state model and cubic model outperform the two-state model because they include a transition state, through which the dynamics typically pass during a phase change. Nonetheless, at high noise levels the improvement in forecast skill is relatively modest. Additionally, the frequency of phase changes depends strongly on the noise level, and is much less affected by the parameter determining amplitude in the population model, so phase shift frequencies could possibly be used to infer noise levels.
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DOI：
--
发表时间：
1981
期刊：
影响因子：
--
作者：
R. May
通讯作者：
R. May
生态学的季节性：理论进展与展望
DOI：
--
发表时间：
2018
期刊：
Ecological Complexity : An International Journal on Biocomplexity in the Environment and Theoretical Ecology
影响因子：
--
作者：
E. White;A. Hastings
通讯作者：
A. Hastings
果树的交替结果。
影响因子：
56.9
作者：
H. Tukey
通讯作者：
H. Tukey
影响因子：
4.8
作者：
Ives, Anthony R.;Abbott, Karen C.;Ziebarth, Nicolas L.
通讯作者：
Ziebarth, Nicolas L.
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DOI：
--
发表时间：
2005
期刊：
影响因子：
--
作者：
K. Gross;A. Ives;E. Nordheim
通讯作者：
E. Nordheim