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Revealing the role of predator interference in a predator–prey system with disease in prey population
Institution:1. Business School, University of Shanghai for Science and Technology, Shanghai 200093, China;2. College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China;3. School of Mathematics and Computer Science, Ningxia Normal University, Ningxia, Guyuan 756000, China;4. Department of Mathematics, Swinburne University of Technology, Hawthorn, VIC 3122, Australia;1. LMA, Department of Mathematics, Faculty of Sciences and Techniques Tangier, B.P. 416, Morocco;2. College of Sciences, Department of Mathematics, University of Sharjah, United Arab Emirates;3. Department of Mathematical Sciences, United Arab Emirates University, Al-Ain, United Arab Emirates;4. Laboratory of PDE’s, Algebra and Spectral geometry, Ibn Tofail University, Faculty of Sciences, Department of Mathematics, FS, Kenitra BP 133, Morocco;5. The University of Durham England, School of Engineering and Computing Sciences, England, United Kingdom
Abstract:Predation on a species subjected to an infectious disease can affect both the infection level and the population dynamics. There is an ongoing debate about the act of managing disease in natural populations through predation. Recent theoretical and empirical evidence shows that predation on infected populations can have both positive and negative influences on disease in prey populations. Here, we present a predator–prey system where the prey population is subjected to an infectious disease to explore the impact of predator on disease dynamics. Specifically, we investigate how the interference among predators affects the dynamics and structure of the predator–prey community. We perform a detailed numerical bifurcation analysis and find an unusually large variety of complex dynamics, such as, bistability, torus and chaos, in the presence of predators. We show that, depending on the strength of interference among predators, predators enhance or control disease outbreaks and population persistence. Moreover, the presence of multistable regimes makes the system very sensitive to perturbations and facilitates a number of regime shifts. Since, the habitat structure and the choice of predators deeply influence the interference among predators, thus before applying predators to control disease in prey populations or applying predator control strategy for wildlife management, it is essential to carefully investigate how these predators interact with each other in that specific habitat; otherwise it may lead to ecological disaster.
Keywords:Predator interference  Disease control through predation  Beddington–DeAngelis functional response  Regime shift  Bistability
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