Present address: Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research, PO Box 447, Migdal 14950, Israel
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A novel approach to detecting a regime shift in a lake ecosystem
Article first published online: 8 JAN 2010
DOI: 10.1111/j.2041-210X.2009.00006.x
© 2009 The Authors. Journal compilation © 2009 British Ecological Society
Additional Information
How to Cite
Gal, G. and Anderson, W. (2010), A novel approach to detecting a regime shift in a lake ecosystem. Methods in Ecology and Evolution, 1: 45–52. doi: 10.1111/j.2041-210X.2009.00006.x
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Present address: Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research, PO Box 447, Migdal 14950, Israel
Correspondence site: http://www.respond2articles.com/MEE/
Publication History
- Issue published online: 23 FEB 2010
- Article first published online: 8 JAN 2010
- Received 08 September 2009; accepted 23 November 2009 Handling Editor: Robert P. Frecklenton
Keywords:
- free-knot spline;
- Lake Kinneret;
- Markov-switching vector autoregression;
- zooplankton
Summary
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.