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What is the robustness of early warning signals to temporal aggregation?

By Victor Frossard, Bruno Saussereau, Antoine Perasso and François Gillet


International audienceA number of methods have recently been developed to identify early warning signals (EWSs) within time-series structure typically characteristic of the rise of critical transitions. Inherent technical constraints often limit the possibility to obtain from sediment both regular and high-resolution time series rather most palaeoecological time series obtained from sediment records represent time-aggregated ecological signals. In this study, therobustness of EWS detection to temporal aggregation was addressed using simulated time series mimicking ecological dynamics. Using a stochastic differential equation based on a deterministic model exhibiting a critical transition between two stable equilibria, two different scenarios were simulated using different combinations of forcing and noise intensities (critical slowing-down and driver-mediated flickering scenarios). Thetemporal resolution of each simulated time series was progressively decreased by averaging the data from 1t = 1 up to 1t = 10 time-unit intervals. EWSs [standard deviation, autocorrelation at lag-1 (AR(1)), skewness and kurtosis] were applied to all time series. Robustness of EWSs to data aggregation was assessed through a block-based approach using Kendall rank correlation Tau. Standard deviation appeared to be robustto data aggregation up to 1t = 10 for the slowing-down scenario and up to 1t = 5 for the driver-mediated flickering scenario while autocorrelation remained robust up to 1t = 2 for the slowing-down scenario and did not support data aggregation for the driver-mediated scenario. Skewness and kurtosis performed poorly for the two scenarios and were not considered as robust EWSs even for the original simulated time series using the block-based approach. Our results suggest that high-resolution palaeoecological time series could be in a large extent suitable to support EWS analyses

Topics: early warning signal, time series, temporal aggregation, resilience, stability, lakes, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Publisher: 'Frontiers Media SA'
Year: 2015
DOI identifier: 10.3389/fevo.2015.00112
OAI identifier: oai:HAL:hal-01211252v1
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