Exploring the structural sensitivity in some spatially-explicit models of ecological dynamics

Mathematical models are frequently used to infer predictions about population dynamics in real ecosystems. However, parametrization of intra- and interspecific interactions is usually approximate, as the amount and quality of ecological information is never sufficient to make a ‘precise’ decision about the mathematical function(s) to use. The question therefore arises as to how sensitive the model properties can be with regard to the choice of the function - the problem known as “structural sensitivity”. In this article, we explore the structural sensitivity of a predator–prey model with additive Allee effect in prey growth and density-dependent death rate for predator. We test the sensitivity of both temporal (non-spatial) and spatiotemporal (spatially-explicit) models using three qualitatively similar but numerically different parametrizations of the predator functional response, such as Holling type II (fraction-linear), Ivlev (exponential) and hyperbolic (trigonometric) functions. Using an array of the analytical and numerical tools, we show that both the temporal and spatiotemporal dynamics can be qualitatively different for the three chosen parametrizations. Also, our study clearly reveals that any hierarchical ranking of these parametrizations according to their destabilizing potential is not possible. © 2025 The Author(s).

Авторы
Manna Kalyan 1 , Banerjee Malay 2 , Petrovskii Sergei V. 3, 4
Издательство
Elsevier Ltd
Язык
English
Статус
Published
Номер
117759
Том
204
Год
2026
Организации
  • 1 Department of Mathematics, Vellore Institute of Technology, Chennai, Chennai, TN, India
  • 2 Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, UP, India
  • 3 School of Computing and Mathematical Sciences, University of Leicester, Leicester, Leicestershire, United Kingdom
  • 4 RUDN University, Moscow, Moscow Oblast, Russian Federation
Ключевые слова
Functional response; Local bifurcation; Pattern formation; Reaction–diffusion; Spatiotemporal chaos; Structural sensitivity; Turing instability
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