A novel approach to detecting a regime shift in a lake ecosystem

1. Certain classes of change in the characteristics of an ecosystem, labelled regime shifts, have been observed in marine and freshwater ecosystems world-wide. Few tools, however, have been offered to detect and identify regime shifts in time-series data. 2. We use a novel approach based on tools taken from the world of statistics, and econometrics to examine the occurrence of a regime shift in the predatory zooplankton population of Lake Kinneret, Israel. The tools are a free-knot spline mean function estimation method and a Markov-switching vector autoregression model. 3. Our approach detected, with high probability, the occurrence of a regime shift in the zooplankton population in the early to mid-1990s. This was in-line with expectations based on similar events observed in the lake. 4. The suggested approach is a step forward from existing approaches in that it does not require any pre-determent of threshold values but rather relies on a hidden underlying stochastic process that yields probabilities of regime shifts. Thus, it can therefore be applied without introducing any prior biases into the analysis. The approach is, therefore, an objective method in detecting the likely occurrence of a regime shift.