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Which System Variables Carry Robust Early Signs of Upcoming Phase Transition? An Ecological Example
Ehsan Negahbani1, D Alistair Steyn-Ross1, Moira L Steyn-Ross1
1School of Engineering, The University of Waikato, Hamilton, Waikato, New Zealand.
Plos One
|September 16, 2016
Summary
Early warning signals for catastrophic state transitions are not always universal. Observability analysis reveals which population variables best predict these critical transitions in ecological models.
Area of Science:
- Ecology
- Dynamical Systems Theory
- Control Theory
Background:
- Critical fluctuations are generally considered universal early warning signals for catastrophic state transitions in dynamical systems.
- A recent study questioned the universality of these signals using an ecological fisheries model, reporting silent early warning signals from predator (P) and adult prey (A) populations.
Purpose of the Study:
- To re-evaluate the universality of early warning signals in an ecological fisheries model.
- To investigate why some populations may not exhibit expected early warning signals prior to bifurcation.
- To apply observability measures from control theory to identify reliable early warning indicators.
Main Methods:
- Performed a full eigenvalue analysis of the three-population (juvenile prey J, adult prey A, predator P) fisheries model.
- Utilized observability analysis by computing the observability coefficient for each population variable.
- Quantified the ability of each population variable to describe changing internal dynamics.
Main Results:
- Eigenvalue analysis confirmed saddle-node (SN) bifurcation for juvenile prey (J) and predator (P) populations, but not for adult prey (A).
- Observability analysis demonstrated that precursor fluctuations are best observed using the juvenile prey (J) variable.
- The predator (P) variable showed increased fluctuations only near the bifurcation point, with observability analysis explaining its initially poor forecasting capability despite undergoing bifurcation.
Conclusions:
- Observability analysis provides complementary information to eigenvalue analysis for identifying variables that carry early warning signs.
- The study resolves the puzzle of decaying variance trends in poorly observable variables, clarifying their forecasting limitations.
- Early warning signals are best identified by considering the observability of system variables, not solely the presence of bifurcation.
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