Spatiotemporal dynamics of a modified Leslie–Gower predator–prey model: Effects of diffusion and taxis-driven movements on pattern formation
Articles
Anand Singh
Birla Institute of Technology and Science Pilani
https://orcid.org/0009-0005-6685-1566
Sayan Mandal
Indian Institute of Information Technology
Pankaj Kumar Tiwari
Indian Institute of Information Technology
https://orcid.org/0000-0001-5342-3961
Balram Dubey
Birla Institute of Technology and Science Pilani
Published 2025-10-10
https://doi.org/10.15388/namc.2025.30.43767
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Keywords

fear effect
carry-over effect
bifurcations
prey-taxis
Turing pattern

How to Cite

Singh, A. (2025) “Spatiotemporal dynamics of a modified Leslie–Gower predator–prey model: Effects of diffusion and taxis-driven movements on pattern formation”, Nonlinear Analysis: Modelling and Control, 30, pp. 1–24. doi:10.15388/namc.2025.30.43767.

Abstract

In this manuscript, we investigate a Leslie–Gower predator–prey model with Crowley–Martin-type functional response. We also explore the dynamics of reaction–diffusion as well as reaction–diffusion–advection model. Specifically, our study focuses on an ecological model involving a generalist predator that induces fear, has carry-over effects, and experiences competitive interference. For the temporal model, a detailed mathematical analysis is carried out, investigating the positivity and boundedness of the solutions. We observe both monostability and bistability phenomena, and explore various local and global bifurcations by varying the fear and carry-over parameters. Interestingly, the fear and its carry-over effects have opposing roles in influencing stability within the temporal model. We incorporated prey-taxis into a general reaction–diffusion framework to represent the directed movement of predators towards regions with higher prey densities or when tracking signals such as scent to locate their prey. We perform the complete analysis of diffusion-driven and taxis-driven instability for reaction–diffusion and reaction–diffusion–advection models, respectively. Our findings emphasize the significant influence of predator diffusion and prey-taxis on pattern formation, revealing that increased random predator movement, combined with a moderate level of prey-taxis, can stabilize the model.

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