Math. Model. Nat. Phenom.
Volume 11, Number 4, 2016Ecology, Epidemiology and Evolution
|47 - 72
|19 July 2016
Detecting Tipping points in Ecological Models with Sensitivity Analysis
Biometris, Wageningen University & Research, the Netherlands
2 Faculty of Earth and Life Sciences, VU University, the Netherlands
* Corresponding author. E-mail: firstname.lastname@example.org
Simulation models are commonly used to understand and predict the development of ecological systems, for instance to study the occurrence of tipping points and their possible ecological effects. Sensitivity analysis is a key tool in the study of model responses to changes in conditions. The applicability of available methodologies for sensitivity analysis can be problematic if tipping points are involved. In this paper we demonstrate that not considering these tipping points may result in misleading statistics on model behaviour. In turn, this limits the applicability of simulation models in ecological research. Tipping points are best revealed when asymptotic model behaviour is considered, i.e. by applying bifurcation analysis. Bifurcation analysis, however, is limited to deterministic dynamic models, whereas many ecological simulation models are nondeterministic and can only be analysed using sensitivity analysis methodologies. In this paper we explore the possibilities for applying methodologies of sensitivity analysis to analyse models with tipping points. The Bazykin-Berezovskaya model, a deterministic ecological model of which the structure regarding tipping points is known a priori, is used as case study. We conclude that important clues about the occurrence of tippings points can be revealed from different sensitivity analysis methodologies, if proper statistical and graphical measures are used. The results raise awareness about how tipping points affect temporal model responses in ecological simulation models, and may also be more generally applicable for nondeterministic models that cannot be analysed using bifurcation analysis.
Mathematics Subject Classification: 49Q12 / 34K18 / 65C05
Key words: Allee effect / bifurcation analysis / sensitivity analysis / sampling method / tipping point
© EDP Sciences, 2016
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