Abstract

Growth of critical fluctuations prior to catastrophic state transition is generally regarded as a universal phenomenon, providing a valuable early warning signal in dynamical systems. Using an ecological fisheries model of three populations (juvenile prey J, adult prey A and predator P), a recent study has reported silent early warning signals obtained from P and A populations prior to saddle-node (SN) bifurcation, and thus concluded that early warning signals are not universal. By performing a full eigenvalue analysis of the same system we demonstrate that while J and P populations undergo SN bifurcation, A does not jump to a new state, so it is not expected to carry early warning signs. In contrast with the previous study, we capture a significant increase in the noise-induced fluctuations in the P population, but only on close approach to the bifurcation point; it is not clear why the P variance initially shows a decaying trend. Here we resolve this puzzle using observability measures from control theory. By computing the observability coefficient for the system from the recordings of each population considered one at a time, we are able to quantify their ability to describe changing internal dynamics. We demonstrate that precursor fluctuations are best observed using only the J variable, and also P variable if close to transition. Using observability analysis we are able to describe why a poorly observable variable (P) has poor forecasting capabilities although a full eigenvalue analysis shows that this variable undergoes a bifurcation. We conclude that observability analysis provides complementary information to identify the variables carrying early-warning signs about impending state transition.

Highlights

  • Near a bifurcation point, a dynamical system may suddenly switch states without a significant change in the external drive forces

  • Boerjlist et al have shown that not every variable of a structured prey-predator ecological model presents precursors of upcoming saddle-node collapse [1]. They performed a series of numerical simulations in which different noise types were added to model variables in a search for early signs of upcoming state transition

  • They extracted the coefficient of variation of noise-induced fluctuations of model variables while forwarding the system towards the SN point by gradually increasing the predator mortality rate μP as a control parameter

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Summary

Introduction

A dynamical system may suddenly switch states without a significant change in the external drive forces Such transitions are possible when the system has access to two (or more) stable states for the same control parameters. A 2013 article by Boerlijst et al [1] stated that catastrophic collapse in a structured three-variable predator-prey model can occur silently without occurrence of early warning signals in some model variables. We extend the repertoire of analytic tools for detecting early warning signals by applying observability concepts adopted from control theory. This analysis allows us to identify which system variables are most representative of internal dynamics, and as a result carry information about bifurcation proximity. We compute the observability coefficients related to the three system variables and demonstrate how these coefficient describe the changes in fluctuation variance on approach to impending saddle-node induced regime shift

Methods and Results
À J2 ð1 þ J2Þ2
Discussion
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