Early Detection of Ecosystem Regime Shifts Figure 4. Trend analysis of indicator time series. Smoothed time series of Pseudocalanus acuspes and Acartia spp. based on GAMs using df = 10 (A, C) and df = 20 (B, D). Bootstrapped confidence intervals are shown by grey lines. Acceleration in the rate of change (slope) in each year are shown by statistically significant second derivatives (f ’’), where black and white dots represent major downward- and upward trends, respectively. Vertical dashed lines mark the timing of the regime shift in the late 1980s. doi:10.1371/journal.pone.0038410.g004 increase in SDs depended on the number of years used for the sliding window, being strongest when using a 10 year window (Figure S2). On the contrary, temporal autocorrelation analysis demonstrated a marked and significant decline in AR(1) param- eters (below the lower confidence level) preceding or coinciding with the regime shift (Figure 2C–D); regardless of the number of years used for the sliding window (Figure S2). Since early-warning detection depends on the choice of metric, the use of sliding windows, and constraints in the length of the time series, the potential of temporal indicators of critical slowing down for early- warning may be limited. In contrast to the temporal analysis, spatial approaches for detecting patterns in either variance or correlation yielded rather similar results. The spatial variance in Pseudocalanus acuspes displayed strong inter-annual fluctuations and a significant increase in the coefficient of variation (CV) one year ahead of the regime shift (Figure 3C), while Acartia spp. showed decreasing CV below the lower confidence interval only after the shift (Figure 3B). The reason for opposite patterns in spatial CVs may originate from the pronounced differences in abundance trends, i.e., illustrating a decrease in Pseudocalanus acuspes (Figure 1B) and increase in Acartia spp. (Figure 1C), where decreasing abundances PLoS ONE | www.plosone.org 5 July 2012 | Volume 7 | Issue 7 | e38410