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Effect of habitat complexity on rhinoceros and tiger population model with additional food and poaching in Kaziranga National Park, Assam

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  • Saikia, Munmi
  • Maiti, Atasi Patra
  • Devi, Anuradha

Abstract

This paper studies the effect of habitat complexity on Greater one-horned rhinoceros (Rhinoceros unicornis) and tiger (Panthera tigris) population model in Kaziranga National Park (KNP), Assam, India. Based on the analysis of the data collected from PCCF, Wildlife, Assam, three mathematical models are formulated and studied. In view of ecology, the main objective of the study is to increase the size of rhino population in aforesaid park. The mathematical stability and the complex dynamical behavior of systems are analyzed here. In KNP, the immature rhinos are killed by tiger, so the first system describes a stage structured prey–predator interaction , where the rhino is the prey and is divided into immature (horn not developed) and mature (horn developed) category and the tiger is the predator. The immature rhino is killed by the tiger following Holling type-II functional response, while the mature rhino falls prey to human induced poaching activities [Source: PCCF Wildlife, Assam, India]. Though Kaziranga is famous all over the world for the Greater one-horned rhinoceros, many other herbivores are also present in really good number and the tiger preys on them too. Thus, the previous system is modified by modifying the Holling type-II functional response incorporating the effect of additional food availability. To increase the number of rhino and to maintain the ecological balance of KNP, the second system is further extended by introducing habitat complexity in the Holling type-II functional response. In each system, equilibrium points have been obtained and their stability are discussed. Finally, numerical simulations are carried out to illustrate the analytical results. Based on the simulation results, it can be stated that the size of the rhino population increases in the presence of additional food and habitat complexity in spite of the poaching activities to a certain extent. The system shows complex dynamical behavior like Hopf bifurcation with respect to Poaching activity. Sensitivity analysis with respect to four important parameters viz., poaching effect, quality and quantity of the additional food and habitat complexity is also discussed.

Suggested Citation

  • Saikia, Munmi & Maiti, Atasi Patra & Devi, Anuradha, 2020. "Effect of habitat complexity on rhinoceros and tiger population model with additional food and poaching in Kaziranga National Park, Assam," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 169-191.
    • Handle: RePEc:eee:matcom:v:177:y:2020:i:c:p:169-191
    DOI: 10.1016/j.matcom.2020.04.007
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    References listed on IDEAS

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    1. Rai, Vikas, 2008. "Modeling a wetland system: The case of Keoladeo National Park (KNP), India," Ecological Modelling, Elsevier, vol. 210(3), pages 247-252.
    2. Patra, Atasi & Tushar, Jai & Dubey, B., 2017. "Modeling and simulation of a wetland park: An application to Keoladeo National Park, India," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 134(C), pages 54-78.
    3. Liu, Qun & Jiang, Daqing & Hayat, Tasawar & Ahmad, Bashir, 2018. "Stationary distribution and extinction of a stochastic predator–prey model with additional food and nonlinear perturbation," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 226-239.
    4. Lacitignola, Deborah & Diele, Fasma & Marangi, Carmela, 2015. "Dynamical scenarios from a two-patch predator–prey system with human control – Implications for the conservation of the wolf in the Alta Murgia National Park," Ecological Modelling, Elsevier, vol. 316(C), pages 28-40.
    5. Sen, Moitri & Srinivasu, P.D.N. & Banerjee, Malay, 2015. "Global dynamics of an additional food provided predator–prey system with constant harvest in predators," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 193-211.
    6. Ghosh, Joydev & Sahoo, Banshidhar & Poria, Swarup, 2017. "Prey-predator dynamics with prey refuge providing additional food to predator," Chaos, Solitons & Fractals, Elsevier, vol. 96(C), pages 110-119.
    7. Sahoo, Banshidhar & Poria, Swarup, 2014. "The chaos and control of a food chain model supplying additional food to top-predator," Chaos, Solitons & Fractals, Elsevier, vol. 58(C), pages 52-64.
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