Early Detection of Ecosystem Regime Shifts Figure 5. Shiftogram analysis of indicator time series. The shiftograms show the transition towards a local minimum in the AICC (black) and p- joint (white) for Pseudocalanus acuspes (A) and Acartia spp. (B). In panel (C, D), an alertogram demonstrates the AICC slopes (vertical bars), the estimated probabilities (p-values) of false warnings (white) and false no warnings (i.e., the beta error, black) over a 5-year period before and after the regime shift. The two dotted horizontal lines represent the significance level (p = 0.05) and the upper tolerance limits with regard to the probabilities of false detections (i.e., false alarm limit). doi:10.1371/journal.pone.0038410.g005 may simply increase spatial CVs and vice versa. Furthermore, our results show a continuous increase and decrease in CVs throughout the period, thus partly inconsistent to the theoretical expectation of critical slowing down, which predicts a decrease in variance after a shift as the system reaches its new equilibrium. Whether simply driven by the long-term abundance trends or caused by dynamics not yet having reached (stable) equilibrium, the discrepancies between theory and practical application deserve further attention. The spatial (Moran’s I) correlation showed p-values exceeding their upper confidence intervals one year in advance of the regime shift for both species (Figure 3C–D). This may indicate a strong fragmentation of the zooplankton distribution well before the population sizes changed prior to the regime shift (e.g., even 6–7 years before the shift for Pseudocalanus acuspes; Figure S3A). In the case of Pseudocalanus acuspes this can be explained by the distribution of adults in deep water layer confined by oxygen conditions from below and salinity conditions from above [28,29]. Reduction of oxygen and salinity levels due to a lack of inflows from the North Sea since the early 1980s, a major cause of the Baltic ecosystem regime shift [20], reduced the spatial extent of suitable reproductive habitat for the copepod. Hence, habitat fragmentation may have caused parts of the population to become spatially isolated from each other which may have impaired reproductive capabilities and resulted in the population decline [26]. Nevertheless, it has to be noted that our knowledge on the spatial dynamics of Pseudocalanus acuspes and Acartia spp. is still limited. We are therefore unable to provide a solid interpretation of the observed distribution patterns. Hence, the elevated heterogeneity in the distribution pattern, i.e., the consecutive peaks in p-values during the late-1980s (Figure S3A), may simply represent the natural spatial variability in the dynamics of Baltic Sea copepods and thus render the derived early-warning signals as potential false alarms. Contrary to temporal indicators of slowing down, spatial approaches for detecting changes in correlation and variance patterns [13,14,17] are not primarily constrained by methodolog- ical assumptions associated with a particular method, but are influenced by the quality and consistency of monitoring programs in space and time. However, our spatial analysis of critical slowing down seems robust to the random resampling of monitoring stations, e.g., spatial correlation between stations in each year showed consistent dynamics based on repeated random draws of 6, 8 and 10 stations, respectively (Figure S3), indicating that potential bias from uneven sampling between years may be of less importance or successfully accounted for by performing proper sensitivity analysis. Trend Analysis The trend analysis [34] indicated potential early-warning signals given by a significant decreasing and increasing trend for Pseudocalanus acuspes and Acartia spp. prior to the regime shift PLoS ONE | www.plosone.org 6 July 2012 | Volume 7 | Issue 7 | e38410