Detection of regime shifts in the environment: testing “STARS” using synthetic and observed time series

Abstract

While marine populations change all the time, sometimes regime shifts involve an entire ecosystem, resulting in crucial and sometimes permanent alterations in the ecosystem trophic web and services. A commonly used method to detect shifts in marine systems is the Sequential t-test Analysis of Regime Shifts (STARS). In this work, we chose to analyse the limits and performance of STARS because of its free open-source software and wide use. For the first time, we tested the STARS algorithm using synthetic time series and autoregressive integrated moving average time series, designed to resemble natural observations. We then applied the information obtained from these tests to investigate the STARS detections on an observed time series, that of Calanus finmarchicus in the North Sea. Our tests indicated that in no experiments did STARS detect 100% of the artificial change points at the exact time of the shift. In most cases, STARS tended to anticipate the shift by a few time units. Overall, we determined STARS to be a good method to detect shifts in observed natural time series, so long as the exact time of the shift is not necessary and the possibility of false positives is taken into account.

Reference state, structure, regime shifts, and regulatory drivers in a coastal sea over the last century: The Central Baltic Sea case

“…Furthermore, given that the regime shift detection method STARS often does not detect the exact year of a shift (Stirnimann et al 2019), we interpreted the set of breakpoints identified by STARS and bcp at different probability levels with caution as the approximate time of major ecosystem changes.…”

Evidence of climate‐driven regime shifts in the Aegean Sea’s demersal resources: A study spanning six decades

“…The three states in PC1sys (1966–1991, 1992–2002, 2003–2015) were very distinct and did not overlap, contrary to the states detected in PC1str (Figure 6). We cannot be conclusive regarding the last shift (2016), because STARS tends to detect false regime shifts in the last cut‐off window (Stirnimann et al, 2019).…”

“…We cannot be conclusive regarding the last shift (2016), because STARS tends to detect false regime shifts in the last cut-off window (Stirnimann et al, 2019).…”

On the changing relationship between North Pacific climate variability and synoptic activity over the Hawaiian Islands

“…In addition, we deployed a regime shift detection method (Rodionov, 2004; Rodionov and Overland, 2005) on the windowed correlation time series to support the timing of the change in the correlations. We used code developed for R (Stirnimann et al ., 2019). These auxiliary tests are presented in the SI material (Table S1, Figure S3).…”