There is a recognized need to anticipate tipping points, or critical transitions, in social-ecological systems(1,2). Studies of mathematical(3-5) and experimental(6-9) systems have shown that systems may 'wobble' before a critical transition. Such early warning signals(10) may be due to the phenomenon of critical slowing down, which causes a system to recover slowly from small impacts, or to a flickering phenomenon, which causes a system to switch back and forth between alternative states in response to relatively large impacts. Such signals for transitions in social-ecological systems have rarely been observed(11), not the least because high-resolution time series are normally required. Here we combine empirical data from a lake-catchment system with a mathematical model and show that flickering can be detected from sparse data. We show how rising variance coupled to decreasing autocorrelation and skewness started 10-30 years before the transition to eutrophic lake conditions in both the empirical records and the model output, a finding that is consistent with flickering rather than critical slowing down(4,12). Our results suggest that if environmental regimes are sufficiently affected by large external impacts that flickering is induced, then early warning signals of transitions in modern social-ecological systems may be stronger, and hence easier to identify, than previously thought.