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Dynamic analysis of a plankton–herbivore state-dependent impulsive model with action threshold depending on the density and its changing rate

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Abstract

A plankton–herbivore state-dependent impulsive model with nonlinear impulsive functions and action threshold including population density and rate of change is proposed. Since the use of action threshold makes the model have complex phase set and pulse set, we adopt the Poincar\(\acute{\text{ e }}\) map as a tool to study its complex dynamics. The Poincar\(\acute{\text{ e }}\) map is defined on the phase set and its properties in different situations are analyzed. Furthermore, the periodic solution of model is discussed, including the existence and stability conditions of the order-1 periodic solution and the existence of the order-k (\(k\ge 2\)) periodic solutions. Compared with the fixed threshold in the existing literature, our results show that the use of action threshold is more practical, which is conducive to the sustainable development of population and makes people obtain more economic benefits. The analysis method used in this paper can study the complex dynamics of the model more comprehensively and deeply.

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The author declares that the data supporting the results of this study are available in the article.

References

  1. Mukhopadhyay, B., Bhattacharyya, R.: Role of gestation delay in a plankton-fish model under stochastic fluctuations. Math. Biosci. 215(1), 26–34 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  2. Lv, Y., Pei, Y., Gao, S., Li, C.: Harvesting of a phytoplankton–zooplankton model. Nonlinear Anal. Real World Appl. 11(5), 3608–3619 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  3. Zhang, T., Liu, X., Meng, X., Zhang, T.: Spatio-temporal dynamics near the steady state of a planktonic system. Comput. Math. Appl. 75(12), 4490–4504 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  4. Yu, X., Yuan, S., Zhang, T.: Asymptotic properties of stochastic nutrient-plankton food chain models with nutrient recycling. Nonlinear Anal. Hybrid Syst. 34, 209–225 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  5. Yu, X., Yuan, S., Zhang, T.: Survival and ergodicity of a stochastic phytoplankton–zooplankton model with toxin-producing phytoplankton in an impulsive polluted environment. Appl. Math. Comput. 347, 249–264 (2019)

    MathSciNet  MATH  Google Scholar 

  6. Jia, D., Zhang, T., Yuan, S.: Pattern dynamics of a diffusive toxin producing phytoplankton–zooplankton model with three-dimensional patch. Int. J. Bifurc. Chaos 29, Article Number: 1930011 (2019)

  7. Yan, S., Jia, D., Zhang, T., Yuan, S.: Pattern dynamics in a diffusive predator-prey model with hunting cooperations. Chaos Solitons Fractals 130, Article Number: 109428 (2020)

  8. Peng, Y., Li, Y., Zhang, T.: Global bifurcation in a toxin producing phytoplankton–zooplankton system with prey-taxis. Nonlinear Anal. Real World Appl. 61 Article Number: 103326 (2021)

  9. Fang, D., Pei, Y., Lv, Y., Chen, L.: Periodicity induced by state feedback controls and driven by disparate dynamics of a herbivore-plankton model with cannibalism. Nonlinear Dyn. 90(5), 1–16 (2017)

    MathSciNet  MATH  Google Scholar 

  10. Tang, S., Tang, B., Wang, A., Xiao, Y.: Holling II predator-prey impulsive semi-dynamic model with complex poincaré map. Nonlinear Dyn. 81(3), 1575–1596 (2015)

    Article  MATH  Google Scholar 

  11. Bainov, D.D., Simeonov, P.S.: Impulsive Differential Equation: Periodic Solutions and Applications. Pergamon Press Inc, Oxford (2015)

    MATH  Google Scholar 

  12. Li, D., Cheng, H., Liu, Y.: Dynamic analysis of beddington–deangelis predator-prey system with nonlinear impulse feedback control. Complexity (2019)

  13. Wang, F., Zhang, X.: Adaptive finite time control of nonlinear systems under time-varying actuator failures. IEEE Trans. Syst. Man Cybern. Syst. 1–8 (2018)

  14. Ciesielski, K.: On stability in impulsive dynamical systems. Bull. Pol. Acad. Sci. Math. 52(84), 81–91 (2010)

    MathSciNet  MATH  Google Scholar 

  15. Bonotto, E.M., Federson, M.: Limit sets and the Poincare–Bendixson theorem in impulsive semidynamical systems. J. Differ. Equ. 244(9), 2334–2349 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  16. Baek, Hunki: The dynamics of a predator-prey system with state-dependent feedback control. Abstr. Appl. Anal. 2012, 1–17 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  17. Yang, J., Tang, S.: Holling type II predator-prey model with nonlinear pulse as state-dependent feedback control. J. Comput. Appl. Math. 291, 225–241 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  18. Liu, H., Cheng, H.: Dynamic analysis of a prey-predator model with state-dependent control strategy and square root response function. Adv. Differ. Equ. 2018(1), 63 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  19. Li, T., Zhao, W.: Periodic solution of a neutral delay Leslie predator-prey model and the effect of random perturbation on the smith growth model. Complexity 2020, 15 (2020)

    MATH  Google Scholar 

  20. Li, Y., Li, Y., Liu, Y., Cheng, H.: Stability analysis and control optimization of a prey-predator model with linear feedback control. Discrete Dyn. Nat. Soc. 2018, 12 (2018)

    MathSciNet  MATH  Google Scholar 

  21. Shi, Z., Cheng, H., Liu, Y., Li, Y.: A cydia pomonella integrated management predator-prey model with smith growth and linear feedback control. IEEE Access 7(1), 126066–126076 (2019)

    Article  Google Scholar 

  22. Wang, Y., Cheng, H., Li, Q.: Dynamic analysis of wild and sterile mosquito release model with Poincaré map. Math. Biosci. Eng. 6(16), 7688–7706 (2019)

    Article  MATH  Google Scholar 

  23. Shi, Z., Cheng, H., Wang, Y.: Optimization of an integrated feedback control for a pest management predator-prey model. Math. Biosci. Eng. 16(6), 7963–7981 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  24. Xu, C., Yuan, S., Zhang, T.: Average break-even concentration in a simple chemostat model with telegraph noise. Nonlinear Anal. Hybrid Syst. 29, 373–382 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  25. Qi, H., Leng, X., Meng, X., Zhang, T.: Periodic solution and ergodic stationary distribution of Seis dynamical systems with active and latent patients. Qual. Theory Dyn. Syst. 18(2), 347–369 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  26. Zhang, T., Wang, J., Li, Y., Jiang, Z., Han, X.: Dynamics analysis of a delayed virus model with two different transmission methods and treatments. Adv. Differ. Equ. 2020(1), 1 (2020)

  27. Wang, W., Lai, X.: Global stability analysis of a viral infection model in a critical case. Math. Biosci. Eng. 17, 1442–1449 (2020)

  28. Li, D., Liu, Y., Cheng, H.: Dynamic complexity of a phytoplankton-fish model with the impulsive feedback control by means of Poincaré map. Complexity (2020)

  29. Jiang, Z., Zhang, W., Zhang, J., Zhang, T.: Dynamical analysis of a Phytoplankton–Zooplankton system with harvesting term and Holling III functional response. Int. J. Bifurc. Chaos 28(13), 1850162 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  30. Zhong, Z., Pang, L., Song, X.: Optimal control of phytoplankton-fish model with the impulsive feedback control. Nonlinear Dyn. 88(3), 2003–2011 (2017)

    Article  MathSciNet  Google Scholar 

  31. Yang, J., Tan, Y.: Effects of pesticide dose on Holling II predator-prey model with feedback control. J. Biol. Dyn. 12(1), 527–550 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  32. Wang, Y., Cheng, H., Li, Q.: Dynamical properties of a herbivore-plankton impulsive semidynamic system with eating behavior. Complexity 2020, 1–15 (2020)

    MATH  Google Scholar 

Download references

Funding

This work is supported by the National Natural Science Foundation of China (11371230), the SDUST Research Fund (2014TDJH102), Research on the basic theoretical framework and symmetry theory of soft robot dynamics(11872335).

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Correspondence to Huidong Cheng.

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Li, W., Zhang, T., Wang, Y. et al. Dynamic analysis of a plankton–herbivore state-dependent impulsive model with action threshold depending on the density and its changing rate. Nonlinear Dyn 107, 2951–2963 (2022). https://doi.org/10.1007/s11071-021-07022-w

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  • DOI: https://doi.org/10.1007/s11071-021-07022-w

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