Slower recovery in space before collapse of connected populations.
Slower recovery in space before collapse of connected populations.
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作者：
从临界点附近的扰动中较慢的恢复及其在波动模式中的间接特征被认为预示着各种各样的系统中的灾难。最近在实地和实验室对人口进行的研究利用时间序列数据证实了一些理论上预测的预警指标，如恢复时间或波动的大小和时间尺度的增加。然而，时间预警信号的预测能力受到长期观测需求的限制。大规模空间数据更容易获取，但空间扩展系统中的警报信号性能需要进行经验检验。在这里，我们使用空间扩展的酵母种群，这是一个显示折叠分叉的实验系统，基于时空波动来评估预警信号，并在空间中识别新的预警指标。我们发现，在相关种群崩溃之前，两个基于波动的领先指标有所增加；然而，增加的幅度小于在孤立种群中观察到的，这可能是因为分散减少了局部变异。此外，我们还提出了一个基于确定性空间模式的通用指标“恢复长度”。作为恢复时间的空间对应，恢复长度被定义为连通种群从空间扰动(例如，质量较差的区域)中恢复的距离。在我们的实验中，在种群崩溃之前，恢复长度显著增加，这表明在空间扩展的系统中，恢复的空间尺度可以在引爆点之前提供更好的警告信号。
Slower recovery from perturbations near a tipping point and its indirect signatures in fluctuation patterns have been suggested to foreshadow catastrophes in a wide variety of systems. Recent studies of populations in the field and in the laboratory have used time-series data to confirm some of the theoretically predicted early warning indicators, such as an increase in recovery time or in the size and timescale of fluctuations. However, the predictive power of temporal warning signals is limited by the demand for long-term observations. Large-scale spatial data are more accessible, but the performance of warning signals in spatially extended systems needs to be examined empirically. Here we use spatially extended yeast populations, an experimental system displaying a fold bifurcation, to evaluate early warning signals based on spatio-temporal fluctuations and to identify a novel warning indicator in space. We found that two leading indicators based on fluctuations increased before collapse of connected populations; however, the magnitude of increase was smaller than that observed in isolated populations, possibly because local variation is reduced by dispersal. Furthermore, we propose a generic indicator based on deterministic spatial patterns, “recovery length”. As the spatial counterpart of recovery time, recovery length is defined as the distance for connected populations to recover from perturbations in space (e.g. a region of poor quality). In our experiments, recovery length increased substantially before population collapse, suggesting that the spatial scale of recovery can provide a superior warning signal before tipping points in spatially extended systems.
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影响因子：
64.8
作者：
Kéfi, Sonia;Rietkerk, Max;de Ruiter, Peter C.
通讯作者：
de Ruiter, Peter C.
影响因子：
64.8
作者：
Drake, John M.;Griffen, Blaine D.
通讯作者：
Griffen, Blaine D.
影响因子：
6.3
作者：
Harper, KA;Macdonald, SE;Esseen, PA
通讯作者：
Esseen, PA
DOI：
10.1098/rspb.2012.2085
发表时间：
2012-12-07
影响因子：
4.7
作者：
Boettiger, Carl;Hastings, Alan
通讯作者：
Hastings, Alan
影响因子：
2.9
作者：
Dakos, Vasilis;Kefi, Sonia;Scheffer, Marten
通讯作者：
Scheffer, Marten