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A study of integrated pest management models with instantaneous and non-instantaneous impulse effects

  • Received: 22 October 2023 Revised: 11 December 2023 Accepted: 09 January 2024 Published: 30 January 2024
  • The occurrence of pests and diseases during agricultural production affects the quality and quantity of agricultural products. It is important to evaluate the impact of various factors on pests to achieve optimal results of integrated pest management (IPM) during its implementation. In this paper, we considered the transient and non-transient effects of chemical control on pests and the effects on natural enemies at different times, and developed a corresponding pest control model. Detailed studies and comparisons were conducted for spraying pesticides either more or less frequently as compared to strategies for releasing natural enemies. The threshold conditions for global asymptotic stabilization of the pest extinction period solution was obtained. Using two-parameter and sensitivity analysis techniques, the parameters affecting the variation of the threshold were discussed. By comparing these two pest control strategies, we found the existence of optimal application and release frequencies. Finally, in order to control pests below the economic threshold level, the state-dependent pest model was numerically investigated. The results show that the presence or absence of chemical control of pests can depend on the values taken for the parameters in the model. Based on this information, pest control experts can make decisions about the best spraying time and the best release rate.

    Citation: Liping Wu, Zhongyi Xiang. A study of integrated pest management models with instantaneous and non-instantaneous impulse effects[J]. Mathematical Biosciences and Engineering, 2024, 21(2): 3063-3094. doi: 10.3934/mbe.2024136

    Related Papers:

  • The occurrence of pests and diseases during agricultural production affects the quality and quantity of agricultural products. It is important to evaluate the impact of various factors on pests to achieve optimal results of integrated pest management (IPM) during its implementation. In this paper, we considered the transient and non-transient effects of chemical control on pests and the effects on natural enemies at different times, and developed a corresponding pest control model. Detailed studies and comparisons were conducted for spraying pesticides either more or less frequently as compared to strategies for releasing natural enemies. The threshold conditions for global asymptotic stabilization of the pest extinction period solution was obtained. Using two-parameter and sensitivity analysis techniques, the parameters affecting the variation of the threshold were discussed. By comparing these two pest control strategies, we found the existence of optimal application and release frequencies. Finally, in order to control pests below the economic threshold level, the state-dependent pest model was numerically investigated. The results show that the presence or absence of chemical control of pests can depend on the values taken for the parameters in the model. Based on this information, pest control experts can make decisions about the best spraying time and the best release rate.



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    [1] C. Z. Wang, X. H. Wang, Z. N. Jin, C. Müller, T. A. M. Pugh, A. P. Chen, et al., Occurrence of crop pests and diseases has largely increased in China since 1970, Nat. Food, 3 (2021), 57–65. https://doi.org/10.1038/s43016-021-00428-0 doi: 10.1038/s43016-021-00428-0
    [2] P. Deepika, S. Kaliraj, A survey on pest and disease monitoring of crops, in 2021 3rd International Conference on Signal Processing and Communication (ICPSC), (2021), 156–160. https://doi.org/10.1109/ICSPC51351.2021.9451787
    [3] X. X. Sun, C. X. Hu, H. R. Jia, Q. L. Wu, X. J. Shen, S. Y. Zhao, et al., Case study on the first immigration of fall armyworm, Spodoptera frugiperda invading into China, J. Integr. Agric., 20 (2021), 664–672. https://doi.org/10.1016/S2095-3119(19)62839-X doi: 10.1016/S2095-3119(19)62839-X
    [4] J. H. Liang, S. Y. Tang, J. J. Nieto, R. A. Cheke, Analytical methods for detecting pesticide switches with evolution of pesticide resistance, Math. Biosci., 245 (2013), 249–257. https://doi.org/10.1016/j.mbs.2013.07.008 doi: 10.1016/j.mbs.2013.07.008
    [5] D. Suandi, K. P. Wijaya, M. Apri, K. A. Sidarto, D. Syafruddin, T. GÖtz, A one-locus model describing the evolutionary dynamics of resistance against insecticide in Anopheles mosquitoes, Appl. Math. Comput., 359 (2019), 90–106. https://doi.org/10.1016/j.amc.2019.03.031 doi: 10.1016/j.amc.2019.03.031
    [6] R. Lahlali, S. Ezrari, N. Radouane, J. Kenfaoui, Q. Esmaeel, H. E. Hamss, et al., Biological control of plant pathogens: A global perspective, Microorganisms, 10 (2022), 596. https://doi.org/10.3390/microorganisms10030596 doi: 10.3390/microorganisms10030596
    [7] J. C. V. Lenteren, H. J. W. V. Roermund, S. Susanne, Biological control of greenhouse whitefly (Trialeurodes vaporariorum) with the parasitoid Encarsia formosa: How does it work, Biol. Control, 6 (1996), 1–10. https://doi.org/10.1006/bcon.1996.0001 doi: 10.1006/bcon.1996.0001
    [8] J. C. V. Lenteren, J. Woets, Biological and integrated pest control in greenhouses, Annu. Rev. Entomol., 33 (1988), 239–269. https://doi.org/10.1146/annurev.en.33.010188.001323 doi: 10.1146/annurev.en.33.010188.001323
    [9] H. H. Liang, S. Y. Tang, R. A. Cheke, Beverton-Holt discrete pest management models with pulsed chemical control and evolution of pesticide resistance, Commun. Nonlinear Sci. Numer. Simul., 36 (2016), 327–341. https://doi.org/10.1016/j.cnsns.2915.12.014 doi: 10.1016/j.cnsns.2915.12.014
    [10] S. J. Gao, J. Guo, Y. Xu, H. P. Zhu, Modeling and dynamics of physiological and behavioral resistance of Asian citrus psyllid, Math. Biosci., 340 (2021), 108674. https://doi.org/10.1016/j.mbs.2021.108674 doi: 10.1016/j.mbs.2021.108674
    [11] S. Y. Tang, Y. N. Xiao, Biodynamic System of A Single Population, 1st edition, Science Press, China, 2008.
    [12] S. Y. Tang, Y. N. Xiao, L. S. Chen, R. A. Cheke, Integrated pest management models and their dynamical behaviour, Bull. Math. Biol., 67 (2005), 115–135. https://doi.org/10.1016/j.bulm.2004.06.005 doi: 10.1016/j.bulm.2004.06.005
    [13] B. Liu, G. Hu, B. L. Kan, X. Huang, Analysis of a hybrid pest management model incorporating pest resistance and different control strategies, Math. Biosci. Eng., 17 (2020), 4364–4383. https://doi.org/10.3934/mbe.2020241 doi: 10.3934/mbe.2020241
    [14] Z. Y. Xiang, S. Y. Tang, C. C. Xiang, J. H. Wu, On impulsive pest control using integrated intervention strategies, Appl. Math. Comput., 269 (2015), 930–946. https://doi.org/10.1016/j.amc.2015.07.076 doi: 10.1016/j.amc.2015.07.076
    [15] B. Liu, W. B. Liu, F. M. Tao, J. G. Cong, A dynamical analysis of a piecewise smooth pest control SI model, Int. J. Bifurcation Chaos, 25 (2015), 1550068. https://doi.org/10.1142/S0218127415500686 doi: 10.1142/S0218127415500686
    [16] G. J. Lan, F. J. Fu, C. J. Wei, S. W. Zhang, A research of pest management SI stochastic model concerning spraying pesticide and releasing natural enemies, Commun. Math. Biol. Neurosci., 2018 (2018). https://doi.org/10.28919/CMBN/3648
    [17] S. Y. Tang, G. Y. Tang, R. A. Cheke, Optimum timing for integrated pest management: modelling rates of pesticide application and natural enemy releases, J. Theor. Biol., 264 (2010), 623–638. https://doi.org/10.1016/j.jtbi.2010.02.034 doi: 10.1016/j.jtbi.2010.02.034
    [18] W. J. Qin, Y. Xia, Y, Yang, An eco-epidemic model for assessing the application of integrated pest management strategies, Math. Biosci. Eng., 209 (2023), 16506–16527. https://doi.org/10.3934/mbe.2023736 doi: 10.3934/mbe.2023736
    [19] Y. Tian, S. Y. Tang, R. A. Cheke, Dynamic complexity of a predator-prey model for IPM with nonlinear impulsive control incorporating a regulatory factor for predator releases, Math. Model. Anal., 24 (2019), 134–154. https://doi.org/10.3846/mma.2019.010 doi: 10.3846/mma.2019.010
    [20] Q. Q. Zhang, B. Tang, T. Y. Cheng, S. Y. Tang, Bifurcation analysis of a generalized impulsive Kolmogorov model with applications to pest and disease control, SIAM J. Appl. Math., 80 (2020), 1796–1819. https://doi.org/10.1137/19M1279320 doi: 10.1137/19M1279320
    [21] S. Y. Tang, B. Tang, A. L. Wang, Y. N. Xiao, Holling II predator-prey impulsive semi-dynamic model with complex Poincaré map, Nonlinear Dyn., 81 (2015), 1575–1596. https://doi.org/10.1007/s11071-015-2092-3 doi: 10.1007/s11071-015-2092-3
    [22] B. L. Kang, B. Liu, F. G. Tao, An integrated pest management model with dose-response effect of pesticides, J. Biol. Syst., 26 (2018), 59–86. https://doi.org/10.1142/S0218339018500043 doi: 10.1142/S0218339018500043
    [23] J. H. Liang, S. Y. Tang, R. A. Cheke, An integrated pest management model with delayed responses to pesticide applications and its threshold dynamics, Nonlinear Anal. Real World Appl., 13 (2012), 2352–2374. https://doi.org/10.1016/J.NONRWA.2012.02.003 doi: 10.1016/J.NONRWA.2012.02.003
    [24] S. Y. Tang, J. H. Liang, Y. S. Tan, R. A. Cheke, Threshold conditions for integrated pest management models with pesticides that have residual effects, J. Math. Biol., 66 (2013), 1–35. https://doi.org/10.1007/s00285-011-0501-x doi: 10.1007/s00285-011-0501-x
    [25] J. Yang, Y. S. Tan, Effects of pesticide dose on Holling II predator-prey model with feedback control, J. Biol. Dyn., 12 (2018), 527–550. https://doi.org/10.1080/17513758.2018.1479457 doi: 10.1080/17513758.2018.1479457
    [26] J. Páez Chávez, D. Jungmann, S. Siegmund, A comparative study of integrated pest management strategies based on impulsive control, J. Biol. Dyn., 12 (2018), 318–341. https://doi.org/10.1080/17513758.2018.1446551 doi: 10.1080/17513758.2018.1446551
    [27] Z. Wei, Y. H. Xia, T. H. Zhang, Dynamic analysis of multi-factor influence on a Holling type II predator-prey model, Qual. Theory Dyn. Syst., 21 (2022), 1–30. https://doi.org/10.1007/s12346-022-00653-3 doi: 10.1007/s12346-022-00653-3
    [28] X. L. Hu, W. J. Qin, M. C. Tosato, Complexity dynamics and simulations in a discrete switching ecosystem induced by an intermittent threshold control strategy, Math. Biosci. Eng., 17 (2020), 2164–2179. https://doi.org/10.3934/mbe.2020115 doi: 10.3934/mbe.2020115
    [29] W. J. Qin, J. M. Zhang, Z. J. Dong, Media impact research: a discrete SIR epidemic model with threshold switching and nonlinear infection forces, Math. Biosci. Eng., 20 (2023), 17783–17802. https://doi.org/10.3934/mbe.2023790 doi: 10.3934/mbe.2023790
    [30] M. Q. He, S. Y. Tang, R. A. Cheke, A Holling type II discrete switching host-parasitoid system with a nonlinear threshold policy for integrated pest management, Discrete Dyn. Nat. Soc., 2020 (2020). https://doi.org/10.1155/2020/9425285
    [31] W. J. Qin, X. W. Tan, X. T. Shi, C. C. Xiang, IPM strategies to a discrete switching predator-prey model induced by a mate-finding Allee effect, J. Biol. Dyn., 13 (2019), 586–605. https://doi.org/10.1080/17513758.2019.1682200 doi: 10.1080/17513758.2019.1682200
    [32] J. N. Liu, Q. Qi, B. Liu, S. J. Gao, Pest control switching models with instantaneous and non-instantaneous impulsive effects, Math. Comput. Simul., 205 (2022), 926–938. https://doi.org/10.1016/j.matcom.2022.10.027 doi: 10.1016/j.matcom.2022.10.027
    [33] S. J. Gao, L. Luo, S. X. Yan, X. Z. Meng, Dynamical behavior of a novel impulsive switching model for HLB with seasonal fluctuations, Complexity, 2018 (2018), 1–11. https://doi.org/10.1155/2018/2953623 doi: 10.1155/2018/2953623
    [34] R. M. May, Simple mathematical models with very complicated dynamics, Nature, 261 (1976), 459–467. https://doi.org/10.1038/261459A0 doi: 10.1038/261459A0
    [35] J. P. Eckmann, D. Ruelle, Ergodic theory of chaos and strange attractors, Rev. Mod. Phys., 57 (1985), 617–656. https://doi.org/10.1103/REVMODPHYS.57.617 doi: 10.1103/REVMODPHYS.57.617
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