Detecting Tipping points in Ecological Models with Sensitivity Analysis
Mathematical modelling of natural phenomena, Tome 11 (2016) no. 4, pp. 47-72.

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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.
DOI : 10.1051/mmnp/201611405

G.A. ten Broeke 1 ; G.A.K. van Voorn 1 ; B.W. Kooi 2 ; J. Molenaar 1

1 Biometris, Wageningen University & Research, the Netherlands
2 Faculty of Earth and Life Sciences, VU University, the Netherlands
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G.A. ten Broeke; G.A.K. van Voorn; B.W. Kooi; J. Molenaar. Detecting Tipping points in Ecological Models with Sensitivity Analysis. Mathematical modelling of natural phenomena, Tome 11 (2016) no. 4, pp. 47-72. doi : 10.1051/mmnp/201611405. https://geodesic-test.mathdoc.fr/articles/10.1051/mmnp/201611405/

[1] W. C. Allee. Animal aggregations, a study in general sociology. The University of Chicago Press, Chicago, Ill., 1931.

[2] A. D. Bazykin. Nonlinear Dynamics of Interacting Populations. World Scientific, Singapore, 1998.

[3] C. Boettiger, N. Ross, A. Hastings Early warning signals: the charted and uncharted territories Theor. Ecol. 2013 255 264

[4] F. Campolongo, A. Saltelli, J. Cariboni 2011 From screening to quantitative sensitivity analysis. A unified approach Comput. Phys. Commun. 978 988

[5] J. Cariboni, D. Gatelli, R. Liska, A. Saltelli The role of sensitivity analysis in ecological modelling Ecol. Model. 2007 167 182

[6] A. Crooks, C. Castle, M. Batty Key challenges in agent-based modelling for geo-spatial simulation Comput. Environ. Urban Syst. 2008 417 430

[7] A. Dhooge, W. Govaerts, Y. A. Kuznetsov MATCONT: a MATLAB package for numerical bifurcation analysis of ODEs TOMS 2003 141 164

[8] E. J. Doedel, B. Oldeman. AUTO07P: Continuation and Bifurcation software for ordinary differential equations. Concordia University, Montreal, Canada, 2009.

[9] R. P. Dickinson, R. J. Gelinas Sensitivity analysis of ordinary differential equation systems - a direct method Comput. Phys. 1976 123 143

[10] T. Filatova, P. H. Verburg, D. C. Parker, C. A. Stannard Spatial agent-based models for socio-ecological systems: challenges and prospects Environ. Model. Softw. 2013 1 7

[11] C. Folke, S. Carpenter, B. Walker, M. Scheffer, T. Elmqvist, L. Gunderson, C. S. Holling Regime shifts, resilience, and biodiversity in ecosystem management Annu. Rev. Ecol. Evol. Syst. 2004 557 581

[12] G. Glen, K. Isaacs Estimating Sobol' sensitivity indices using correlations Environ. Model. Softw. 2012 157 166

[13] J. Guckenheimer, P. Holmes. Nonlinear Oscillations, Dynamical Systems and Bifurcations of Vector Fields. Springer, Berlin, 1985.

[14] D. Hamby A review of techniques for parameter sensitivity analysis of environmental models Environ. Monit. Assess. 1994 135 154

[15] A. J. Jakeman, R. A. Letcher, J. P. Norton Ten iterative steps in development and evaluation of environmental models Environ. Model. Softw. 2006 602 614

[16] M. J. W. Jansen Analysis of variance designs for model output Comput. Phys. Commun. 1999 35 43

[17] A. M. Kramer, B. Dennis, A. M. Liebhold, J. M. Drake The evidence for Allee effects Popul. Ecol. 2009 341 354

[18] Y. A. Kuznetsov. Elements of Applied Bifurcation Theory. Applied Mathematical Sciences 112, Springer-Verlag, New York, 2004.

[19] S. Levin, T. Xepapadeas, A. S. Crépin, J. Norberg, A. De Zeeuw, C. Folke, T. Hughes, K. Arrow, S. Barrett, G. Daily, P. Ehrlich, N. Kautsky, K. Mäler, S. Polasky, M. Troell, J. R. Vincent, B. Walker Social-ecological systems as complex adaptive systems: modeling and policy implications Environ. Dev. Econ. 2013 111 132

[20] T. A. Mara, S. Tarantola Variance-based sensitivity indices for models with dependent inputs Reliab. Eng. Syst. Safe. 2012 115 121

[21] A. M. Mood, F. A. Graybill, D. C. Boes. Introduction to the Theory of Statistics, McGraw-Hill, Singapore 1974.

[22] O. Rakovec, M. C. Hill, M. P. Clark, A. H. Weerts, A. J. Teuling, R. Uijlenhoet Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models Water Resour. Res. 2014 409 426

[23] R. Richard, J. Casas, E. Mccauley Sensitivity analysis of continuous-time models for ecological and evolutionary theories Theor. Ecol. 2015 481 490

[24] A. Saltelli, S. Tarantola, F. Campolongo, M. Ratto. Sensitivity Analysis in Practice. A Guide to Assessing Scientific Models. John Wiley Sons, 2004.

[25] A. Saltelli, M. Ratto, T. Andres, F. Campolongo, J. Cariboni, D. Gatelli, M. Saisana, S. Tarantola. Global Sensitivity Analyisis: The Primer. John Wiley Sons, 2008.

[26] A. Saltelli, P. Annoni, I. Azzini, F. Campolongo, M. Ratto, S. Tarantola Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index Comput. Phys. Commun. 2010 259 270

[27] M. Scheffer, S. R. Carpenter Catastrophic regime shifts in ecosystems: linking theory to observation Trends Ecol. Evol. 2003 648 656

[28] M. Scheffer, J. Bascompte, W. A. Brock, V. Brovkin, S. R. Carpenter, V. Dakos, H. Held, E. H. Van Nes, M. Rietkerk, G. Sugihara Early-warning signals for critical transitions Nature 2009 53 59

[29] A. Schmolke, P. Thorbek, D. L. Deangelis, V. Grimm Ecological models supporting environmental decision making: a strategy for the future Trends Ecol. Evol. 2010 479 486

[30] M. Schlüter, R. J. J. Mcallister, R. Arlinghaus, N. Bunnefeld, K. Eisenack, F. Hölker, E. J. Milner-Gulland, B. Müller, E. Nicholson, M. Quaas, M. Stöven New horizons for managing the environment: a review of coupled social-ecological systems modeling Nat. Resour. Model. 2012 219 272

[31] R. Seydel. Practical Bifurcation and Stability Analysis, 3rd ed. Springer, New York/Dordrecht Heidelberg, London, 2010.

[32] I. M. Sobol' Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates Math. Comput. Simul. 2001 271 280

[33] I. M. Sobol', S. Kucherenko Derivative based global sensitivity measures and their link with global sensitivity indices Math. Comput. Simul. 2009 3009 3017

[34] P. A. Stephens, W. J. Sutherland, R. Freckleton What is the Allee effect? Oikos 1999 185 190

[35] C. M. Taylor, A. Hastings Allee effects in biological invasions Ecol. Lett. 2005 895 908

[36] G. A. Ten Broeke, G. A. K. Van Voorn, A. Ligtenberg Which sensitivity analysis method should I use for my Agent-based Model? JASSS 2016

[37] E. H. Van Nes, M. Scheffer Alternative attractors may boost uncertainty and sensitivity in ecological models Ecol. Model. 2003 117 124

[38] G. A. K. Van Voorn, L. Hemerik, M. P. Boer, B. W. Kooi Heteroclinic orbits indicate overexploitation in predator-prey systems with a strong Allee effect Math. Biosci. 2007 451 469

[39] G. A. K. Van Voorn, B. W. Kooi, M. P. Boer Ecological consequences of global bifurcations in some food chain models Math. Biosci. 2010 120 133

[40] B. Walker, C. S. Holling, S. R. Carpenter, A. Kinzig Resilience, adaptability and transformability in social-ecological systems Ecol. Soc. 5 2004

[41] S. Wiggins. Introduction to Applied Nonlinear Dynamical Systems and Chaos. Springer, New York, 1990.

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