Dakos Vasilis, Glaser Sarah M, Hsieh Chih-Hao, Sugihara George
Institute of Integrative Biology, Center for Adaptation to a Changing Environment, ETH Zurich, Zurich, Switzerland
Korbel School of International Studies, University of Denver, Denver, USA.
J R Soc Interface. 2017 Mar;14(128). doi: 10.1098/rsif.2016.0845.
Populations occasionally experience abrupt changes, such as local extinctions, strong declines in abundance or transitions from stable dynamics to strongly irregular fluctuations. Although most of these changes have important ecological and at times economic implications, they remain notoriously difficult to detect in advance. Here, we study changes in the stability of populations under stress across a variety of transitions. Using a Ricker-type model, we simulate shifts from stable point equilibrium dynamics to cyclic and irregular boom-bust oscillations as well as abrupt shifts between alternative attractors. Our aim is to infer the loss of population stability before such shifts based on changes in nonlinearity of population dynamics. We measure nonlinearity by comparing forecast performance between linear and nonlinear models fitted on reconstructed attractors directly from observed time series. We compare nonlinearity to other suggested leading indicators of instability (variance and autocorrelation). We find that nonlinearity and variance increase in a similar way prior to the shifts. By contrast, autocorrelation is strongly affected by oscillations. Finally, we test these theoretical patterns in datasets of fisheries populations. Our results suggest that elevated nonlinearity could be used as an additional indicator to infer changes in the dynamics of populations under stress.
种群偶尔会经历突然变化，如局部灭绝、数量大幅下降或从稳定动态转变为剧烈的不规则波动。尽管这些变化大多具有重要的生态影响，有时还会产生经济影响，但它们仍然极难提前察觉。在此，我们研究了在各种转变过程中处于压力下的种群稳定性变化。我们使用里克型模型模拟从稳定的平衡点动态向周期性和不规则的繁荣-萧条振荡的转变，以及不同吸引子之间的突然转变。我们的目标是根据种群动态非线性的变化，在这些转变发生之前推断种群稳定性的丧失。我们通过比较直接从观测时间序列拟合到重构吸引子上的线性模型和非线性模型的预测性能来衡量非线性。我们将非线性与其他建议的不稳定领先指标（方差和自相关）进行比较。我们发现，在转变之前，非线性和方差以相似的方式增加。相比之下，自相关受到振荡的强烈影响。最后，我们在渔业种群数据集中检验了这些理论模式。我们的结果表明，升高的非线性可作为一个额外指标，用于推断处于压力下的种群动态变化。
