The implementation of ecological pest-management strategies is an important trend in the global agricultural development, which makes integrated pest management become an important research field. In this study, to achieve a scientific and reasonable pest-management objective, three aspects of work were carried out. 1) Modeling and analysis: a pest-natural enemy Gomportz-type model with a variable searching rate was put forward, and two pest-management models were formulated. The dynamic characteristics of the continuous model were investigated, and the results indicated that the search speed of natural enemies had an effect on the coexistence equilibrium. 2) Control effect: the sliding mode dynamics of the Filippov system including the existence of pseudo-equilibrium was analyzed to illustrate the effect of the non-smooth control strategy on the system. A Poincaré map was constructed for the system with a threshold control, and the complex dynamics induced by the threshold control was investigated. 3) Verifications: computer simulations were presented step by step to illustrate and verify the correctness of the theoretical results. A comprehensive study of predation relationships as well as the effects of different management strategies on the system can serve as a valuable reference for advancing sustainable agricultural practices and pest control.
Citation: Yuan Tian, Xinlu Tian, Xinrui Yan, Jie Zheng, Kaibiao Sun. Complex dynamics of non-smooth pest-natural enemy Gomportz models with a variable searching rate based on threshold control[J]. Electronic Research Archive, 2025, 33(1): 26-49. doi: 10.3934/era.2025002
The implementation of ecological pest-management strategies is an important trend in the global agricultural development, which makes integrated pest management become an important research field. In this study, to achieve a scientific and reasonable pest-management objective, three aspects of work were carried out. 1) Modeling and analysis: a pest-natural enemy Gomportz-type model with a variable searching rate was put forward, and two pest-management models were formulated. The dynamic characteristics of the continuous model were investigated, and the results indicated that the search speed of natural enemies had an effect on the coexistence equilibrium. 2) Control effect: the sliding mode dynamics of the Filippov system including the existence of pseudo-equilibrium was analyzed to illustrate the effect of the non-smooth control strategy on the system. A Poincaré map was constructed for the system with a threshold control, and the complex dynamics induced by the threshold control was investigated. 3) Verifications: computer simulations were presented step by step to illustrate and verify the correctness of the theoretical results. A comprehensive study of predation relationships as well as the effects of different management strategies on the system can serve as a valuable reference for advancing sustainable agricultural practices and pest control.
[1] | W. C. Liu, X. M. Zhu, F. Y. Zhuo, Strengthening the implementation of prevention and control responsibilities along the main line of implementing the "Regulations on the Prevention and Control of Crop Diseases and Pests" to ensure national food security, China Plant Protect., 41 (2021), 5–9. |
[2] |
M. X. Chen, H. M. Srivastava, Existence and stability of bifurcating solution of a chemotaxis model, Proc. Am. Math. Soc., 151 (2023), 4735–4749. https://doi.org/10.1090/proc/16536 doi: 10.1090/proc/16536
![]() |
[3] |
Q. Zhang, S. Tang, X. Zou, Rich dynamics of a predator-prey system with state-dependent impulsive controls switching between two means, J. Differ. Equations, 364 (2023), 336–377. https://doi.org/10.1016/j.jde.2023.03.030 doi: 10.1016/j.jde.2023.03.030
![]() |
[4] |
Y. Tian, X. R. Yan, K. B. Sun, Dual effects of additional food supply and threshold control on the dynamics of a Leslie-Gower model with pest herd behavior, Chaos Solitons Fractals, 185 (2024), 115163. https://doi.org/10.1016/j.chaos.2024.115163 doi: 10.1016/j.chaos.2024.115163
![]() |
[5] |
X. R. Yan, Y. Tian, K. B. Sun, Dynamic analysis of a delayed pest-natural enemy model: Triple effects of non-monotonic functional response, additional food supply and habitat complexity, Int. J. Biomath., (2024), 2450062. https://doi.org/10.1142/S1793524524500621 doi: 10.1142/S1793524524500621
![]() |
[6] |
M. X. Chen, R. C. Wu, Dynamics of a harvested predator-prey model with predator-taxis, Bull. Malays. Math. Sci. Soc., 46 (2023), 76. https://doi.org/10.1007/s40840-023-01470-w doi: 10.1007/s40840-023-01470-w
![]() |
[7] |
H. Nie, S. X. Xin, H. Y. Shu, Effects of diffusion and advection on predator-prey dynamics in closed environments, J. Differ. Equations, 367 (2023), 290–331. https://doi.org/10.1016/j.jde.2023.05.004 doi: 10.1016/j.jde.2023.05.004
![]() |
[8] |
H. K. Qi, B. Liu, Stationary distribution of a stochastic reaction-diffusion predator-prey model with additional food and fear effect, Appl. Math. Lett. 150 (2024), 108978. https://doi.org/10.1016/j.aml.2023.108978 doi: 10.1016/j.aml.2023.108978
![]() |
[9] |
M. X. Chen, S. Ham, Y. Choi, H. Kim, J. Kim, Pattern dynamics of a harvested predator-prey model, Chaos Solitons Fractals, 176 (2023), 114153. https://doi.org/10.1016/j.chaos.2023.114153 doi: 10.1016/j.chaos.2023.114153
![]() |
[10] |
Y. H. Sun, Invasion analysis of a reaction-diffusion-advection predator-prey model in spatially heterogeneous environment, Nonlinear Anal. Real World Appl., 77 (2024), 104048. https://doi.org/10.1016/j.nonrwa.2023.104048 doi: 10.1016/j.nonrwa.2023.104048
![]() |
[11] |
M. X. Chen, Pattern dynamics of a Lotka-Volterra model with taxis mechanism, Appl. Math. Comput., 484 (2025), 129017. https://doi.org/10.1016/j.amc.2024.129017 doi: 10.1016/j.amc.2024.129017
![]() |
[12] |
A. J. Lotka, Eelements of physical biology, Am. J. Public Health, 21 (1926), 341–343. https://doi.org/10.2307/2298330 doi: 10.2307/2298330
![]() |
[13] |
V. Volterra, Fluctuations in the abundance of a species considered mathematically, Nature, 118 (1926), 558–560. https://doi.org/10.1038/119012b0 doi: 10.1038/119012b0
![]() |
[14] | B. Gompertz, On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies, Philos. Trans. R. Soc. London, 115 (1825), 513–583. https://www.jstor.org/stable/107756 |
[15] |
G. F. Gause, N. P. Smaragdova, A. A. Witt, Further studies of interaction between predators and prey, J. Anim. Ecol., 5 (1936), 1–18. https://doi.org/10.2307/1087 doi: 10.2307/1087
![]() |
[16] |
F. E. Smith, Population dynamics in daphnia magna and a new model for population growth, Ecology, 44 (1963), 651–663. https://doi.org/10.2307/1933011 doi: 10.2307/1933011
![]() |
[17] | C. S. Holling, The functional response of predators to prey density and its role in mimicry and population regulation, Mem. Entomol. Soc. Can. Suppl., 45 (1965), 5–60. https://doi.org10.4039/entm9745fv |
[18] | M. Hassell, C. Varley, New inductive population model for insect parasites and its bearing on biological control, Nature, 223 (1969), 1133–1177. https://doi.org 10.1038/2231133a0. |
[19] |
R. E. Kooij, A. Zegeling, A predator-prey model with Ivlev's functional response, J. Math. Anal. Appl., 198 (1996), 473–489. https://doi.org/10.1006/jmaa.1996.0093 doi: 10.1006/jmaa.1996.0093
![]() |
[20] |
Y. Kuang, E. Beretta, Global qualitative analysis of a ratio-dependent predator-prey system, J. Math. Biol., 36 (1998), 389–406. https://doi.org/10.1007/s002850050105 doi: 10.1007/s002850050105
![]() |
[21] | P. M. Stoner, Fitting the exponential function and the Gompertz function by the method of least squares, J. Am. Stat. Assoc., 35 (1941), 515–518. https://www.jstor.org/stable/2278959 |
[22] |
K. Y. Liu, X. Z. Meng, L. S. Chen, A new stage structured predator-prey Gomportz model with time delay and impulsive perturbations on the prey, Appl. Math. Comput., 196 (2008), 705–719. https://doi.org/10.1016/j.amc.2007.07.020 doi: 10.1016/j.amc.2007.07.020
![]() |
[23] |
K. M. C. Tjørve, E Tjørve, The use of Gompertz models in growth analyses, and new Gompertz-model approach: An addition to the Unified-Richards family, PLoS One, 12 (2017), e0178691. https://doi.org/10.1371/journal.pone.0178691 doi: 10.1371/journal.pone.0178691
![]() |
[24] |
M. P. Hassell, H. N. Comins, Sigmoid functional responses and population stability, Theor. Popul. Biol., 14 (1978), 62–67. https://doi.org/10.1016/0040-5809(78)90004-7 doi: 10.1016/0040-5809(78)90004-7
![]() |
[25] |
H. Guo, Y. Tian, K. B. Sun, X.Y. Song, Dynamic analysis of two fishery capture models with a variable search rate and fuzzy biological parameters, Math. Biosci. Eng., 20 (2023), 21049–21074. https://doi.org/10.3934/mbe.2023931 doi: 10.3934/mbe.2023931
![]() |
[26] |
A. Wang, Y. Xiao, R. Smith, Using non-smooth models to determine thresholds for microbial pest management, J. Math. Biol., 78 (2019), 1389–1424. https://doi.org/10.1007/s00285-018-1313-z doi: 10.1007/s00285-018-1313-z
![]() |
[27] |
W. J. Li, J. C. Ji, L. H. Huang, J. F. Wang, Bifurcations and dynamics of a plant disease system under non-smooth control strategy, Nonlinear Dyn., 99 (2020), 3351–3371. https://doi.org/10.1007/s11071-020-05464-2 doi: 10.1007/s11071-020-05464-2
![]() |
[28] |
W. X. Li, L. H. Huang, J. F. Wang, Global asymptotical stability and sliding bifurcation analysis of a general Filippov-type predator-prey model with a refuge, Appl. Math. Comput., 405 (2021), 126263. https://doi.org/10.1016/j.amc.2021.126263 doi: 10.1016/j.amc.2021.126263
![]() |
[29] |
N. S. Chong, B. Dionne, R. Smith, An avian-only Filippov model incorporating culling of both susceptible and infected birds in combating avian influenza, J. Math. Biol., 73 (2016), 751–784. https://doi.org/10.1007/s00285-016-0971-y doi: 10.1007/s00285-016-0971-y
![]() |
[30] |
X. Jiao, X. Li, Y. Yang, Dynamics and bifurcations of a Filippov Leslie-Gower predator-prey model with group defense and time delay, Chaos Solitons Fractals, 162 (2022), 112436. https://doi.org/10.1016/j.chaos.2022.112436 doi: 10.1016/j.chaos.2022.112436
![]() |
[31] |
C. C. García, Bifurcations on a discontinuous Leslie-Grower model with harvesting and alternative food for predators and Holling Ⅱ functional response, Commun. Nonlinear Sci. Numer. Simul., 116 (2023), 106800. https://doi.org/10.1016/j.cnsns.2022.106800 doi: 10.1016/j.cnsns.2022.106800
![]() |
[32] |
W. X. Li, L. H. Huang, J. F. Wang, Global dynamics of Filippov-type plant disease models with an interaction ratio threshold, Math. Method Appl. Sci., 43 (2020), 6995–7008. https://doi.org/10.1002/mma.6450 doi: 10.1002/mma.6450
![]() |
[33] |
W. X. Li, Y. M. Chen, L. H. Huang, J. F. Wang, Global dynamics of a filippov predator-prey model with two thresholds for integrated pest management, Chaos Solitons Fractals, 157 (2022), 111881. https://doi.org/10.1016/j.chaos.2022.111881 doi: 10.1016/j.chaos.2022.111881
![]() |
[34] |
B. Liu, Y. Zhang, L. Chen, The dynamical behaviors of a Lotka-Volterra predator-prey model concerning integrated pest management, Nonlinear Anal. Real World Appl., 6 (2005), 227–243. https://doi.org/10.1016/j.nonrwa.2004.08.001 doi: 10.1016/j.nonrwa.2004.08.001
![]() |
[35] |
X. Y. Song, Y. F. Li, Dynamic behaviors of the periodic predator-prey model with modified Leslie-Gower Holling-type Ⅱ schemes and impulsive effect, Nonlinear Anal. Real World Appl., 9 (2008), 64–79. https://doi.org/10.1016/j.nonrwa.2006.09.004 doi: 10.1016/j.nonrwa.2006.09.004
![]() |
[36] |
X. R. Yan, Y. Tian, K. B. Sun, Effects of additional food availability and pulse control on the dynamics of a Holling-(p+1) type pest-natural enemy model, Electron. Res. Arch., 31 (2023). 6454–6480. https://doi.org/10.3934/era.2023327 doi: 10.3934/era.2023327
![]() |
[37] |
J. Jia, Z. Zhao, J. Yang, A. Zeb, Parameter estimation and global sensitivity analysis of a bacterial-plasmid model with impulsive drug treatment, Chaos Solitons Fractals, 183 (2024), 114901. https://doi.org/10.1016/j.chaos.2024.114901 doi: 10.1016/j.chaos.2024.114901
![]() |
[38] |
S. Y. Tang, R. A. Cheke, State-dependent impulsive models of integrated pest management (IPM) strategies and their dynamic consequences, J. Math. Biol., 50 (2005), 257–292. https://doi.org/10.1007/s00285-004-0290-6 doi: 10.1007/s00285-004-0290-6
![]() |
[39] |
S. Y. Tang, W. Pang, R. A. Cheke, J. H. Wu, Global dynamics of a state-dependent feedback control system, Adv. Differ. Equations, 2015 (2015), 1–70. https://doi.org/10.1186/s13662-015-0661-x doi: 10.1186/s13662-015-0661-x
![]() |
[40] |
Y. Tian, H. Li, K. B. Sun, Complex dynamics of a fishery model: Impact of the triple effects of fear, cooperative hunting and intermittent harvesting, Math. Comput. Simul., 218 (2024), 31–48. https://doi.org/10.1016/j.matcom.2023.11.024 doi: 10.1016/j.matcom.2023.11.024
![]() |
[41] |
L. Nie, Z. Teng, H. Lin, J. Peng, Qualitative analysis of a modified Leslie-Gower and Holling-type Ⅱ predator-prey model with state dependent impulsive effects, Nonlinear Anal.-RWA, 11 (2010), 1364–1373. https://doi.org/10.1016/j.nonrwa.2009.02.026 doi: 10.1016/j.nonrwa.2009.02.026
![]() |
[42] | X. R. Yan, Y. Tian, K. B. Sun, Dynamic analysis of additional food provided non-smooth pest-natural enemy models based on nonlinear threshold control, J. Appl. Math. Comput., 2024, in press. https://doi.org/10.1007/s12190-024-02318-7 |
[43] |
Y. Tian, Y. Liu, K. B. Sun, Complex dynamics of a predator-prey fishery model: The impact of the Allee effect and bilateral intervention, Electron. Res. Arch., 32 (2024), 6379–6404. https://doi.org/10.3934/era.2024297 doi: 10.3934/era.2024297
![]() |
[44] |
L. Nie, Z. Teng, H. Lin, J. Peng, The dynamics of a Lotka-Volterra predator-prey model with state dependent impulsive harvest for predator, Biosystems, 98 (2009), 67–72. https://doi.org/10.1016/j.biosystems.2009.06.001 doi: 10.1016/j.biosystems.2009.06.001
![]() |
[45] |
W. Li, J. Ji, L. Huang, Global dynamic behavior of a predator-prey model under ratio-dependent state impulsive control, Appl. Math. Model., 77 (2020), 1842–1859. https://doi.org/10.1016/j.apm.2019.09.033 doi: 10.1016/j.apm.2019.09.033
![]() |
[46] |
Q. Zhang, S. Tang, Bifurcation analysis of an ecological model with nonlinear state-dependent feedback control by poincaré map defined in phase set, Commun. Nonlinear Sci. Numer. Simul., 108 (2022), 106212. https://doi.org/10.1016/j.cnsns.2021.106212 doi: 10.1016/j.cnsns.2021.106212
![]() |
[47] |
Y. Tian, Y. Gao, K. B. Sun, Global dynamics analysis of instantaneous harvest fishery model guided by weighted escapement strategy, Chaos Solitons Fractals, 164 (2022), 112597. https://doi.org/10.1016/j.chaos.2022.112597 doi: 10.1016/j.chaos.2022.112597
![]() |
[48] |
Y. Tian, Y. Gao, K. B. Sun, Qualitative analysis of exponential power rate fishery model and complex dynamics guided by a discontinuous weighted fishing strategy, Commun. Nonlinear Sci. Numer. Simul., 118 (2023), 107011. https://doi.org/10.1016/j.cnsns.2022.107011 doi: 10.1016/j.cnsns.2022.107011
![]() |
[49] |
Y. Tian, Y. Gao, K. B. Sun, A fishery predator-prey model with anti-predator behavior and complex dynamics induced by weighted fishing strategies, Math. Biosci. Eng., 20 (2023), 1558–1579. https://doi.org/10.3934/mbe.2023071 doi: 10.3934/mbe.2023071
![]() |
[50] |
Y. Tian, H. Guo, K. B. Sun, Complex dynamics of two prey-predator harvesting models with prey refuge and interval-valued imprecise parameters, Math. Method Appl. Sci., 46 (2023). 14278–14298. https://doi.org/10.1002/mma.9319 doi: 10.1002/mma.9319
![]() |
[51] |
H. Guo, Y. Tian, K. Sun, X. Y. Song, Study on dynamic behavior of two fishery harvesting models: effects of variable prey refuge and imprecise biological parameters, J. Appl. Math. Comput., 69 (2023), 4243–4268. https://doi.org/10.1007/s12190-023-01925-0 doi: 10.1007/s12190-023-01925-0
![]() |