Integrated pest management is a pest control strategy that combines biological and chemical methods to reduce environmental pollution and protect biodiversity. Recent research indicated that the fear caused by predators had a significant effect on the growth, development, and reproductive processes of prey. Therefore, we have proposed a pest-natrual enemy system, which is a nonlinear state-dependent feedback control model that incorporated the fear effect in the predator-prey relationship. We discussed impulsive sets and phase sets of the model and derived an expression for the Poincaré map. Furthermore, we analyzed the existence and stability of order-$ 1 $ periodic solutions and explored the existence of order-$ k $ $ (k\ge2) $ periodic solutions. Finally, numerical simulations were conducted to validate our theoretical results and reveal their biological implications.
Citation: Zhanhao Zhang, Yuan Tian. Dynamics of a nonlinear state-dependent feedback control ecological model with fear effect[J]. AIMS Mathematics, 2024, 9(9): 24271-24296. doi: 10.3934/math.20241181
Integrated pest management is a pest control strategy that combines biological and chemical methods to reduce environmental pollution and protect biodiversity. Recent research indicated that the fear caused by predators had a significant effect on the growth, development, and reproductive processes of prey. Therefore, we have proposed a pest-natrual enemy system, which is a nonlinear state-dependent feedback control model that incorporated the fear effect in the predator-prey relationship. We discussed impulsive sets and phase sets of the model and derived an expression for the Poincaré map. Furthermore, we analyzed the existence and stability of order-$ 1 $ periodic solutions and explored the existence of order-$ k $ $ (k\ge2) $ periodic solutions. Finally, numerical simulations were conducted to validate our theoretical results and reveal their biological implications.
[1] | Wangersky, J. Peter, Lotka-Volterra population models, Annu. Rev. Ecol. Syst., 9 (1978), 189–218. https://www.jstor.org/stable/2096748 |
[2] | B. Liu, Y. Zhang, L. Chen, Dynamic complexities of a Holling Ⅰ predator–prey model concerning periodic biological and chemical control, Chaos Soliton. Fract., 22 (2004), 123–134. https://doi.org/10.1016/j.chaos.2003.12.060 doi: 10.1016/j.chaos.2003.12.060 |
[3] | X. Liu, L. Chen, Complex dynamics of Holling type Ⅱ Lotka–Volterra predator–prey system with impulsive perturbations on the predator, Chaos Soliton. Fract., 16 (2003), 311–320. https://doi.org/10.1016/S0960-0779(02)00408-3 doi: 10.1016/S0960-0779(02)00408-3 |
[4] | X. Xu, Y. Qiu, X. Chen, H. Zhang, Z. Liang, B. Tian, Bifurcation analysis of a food chain chemostat model with Michaelis-Menten functional response and double delays, AIMS Math., 7 (2022), 12154–12176. https://doi.org/10.3934/math.2022676 doi: 10.3934/math.2022676 |
[5] | J. H. P. Dawes, M. O. Souza, A derivation of Holling's type Ⅰ, Ⅱ and Ⅲ functional responses in predator–prey systems, J. Theor. Biol., 327 (2013), 11–22. https://doi.org/10.1016/j.jtbi.2013.02.017 doi: 10.1016/j.jtbi.2013.02.017 |
[6] | T. Namba, Y. Takeuchi, M. Banerjee, Stabilizing effect of intra-specific competition on prey-predator dynamics with intraguild predation, Math. Model. Nat. Pheno., 13 (2018), 29. https://doi.org/10.1051/mmnp/2018033 doi: 10.1051/mmnp/2018033 |
[7] | A. Yousef, A. A. Thirthar, A. L. Alaoui, P. Panja, T. Abdeljawad, The hunting cooperation of a predator under two prey's competition and fear-effect in the prey-predator fractional-order model, AIMS Math., 7 (2022), 5463–5479. https://doi.org/10.3934/math.2022303 doi: 10.3934/math.2022303 |
[8] | B. Tang, Y. Xiao, Bifurcation analysis of a predator–prey model with anti-predator behaviour, Chaos Soliton. Fract., 70 (2015), 58–68. https://doi.org/10.1016/j.chaos.2014.11.008 doi: 10.1016/j.chaos.2014.11.008 |
[9] | L. Y. Zanette, A. F. White, M. C. Allen, et al., Perceived predation risk reduces the number of offspring songbirds produce per year, Science, 334 (2011), 1398–1401. http://doi.org/10.1126/science.1210908 doi: 10.1126/science.1210908 |
[10] | S. Eggers, M. Griesser, J. Ekman, Predator-induced plasticity in nest visitation rates in the Siberian jay (Perisoreus infaustus), Behav. Ecol., 16 (2005), 309–315. https://doi.org/10.1093/beheco/arh163 doi: 10.1093/beheco/arh163 |
[11] | C. K. Ghalambor, S. I. Peluc, T. E. Martin, Plasticity of parental care under the risk of predation: How much should parents reduce care?, Biol. Letters., 9 (2013), 20130154. https://doi.org/10.1098/rsbl.2013.0154 doi: 10.1098/rsbl.2013.0154 |
[12] | F. Hua, J. R. J. Fletcher, K. E. Sieving, R. M. Dorazio, Too risky to settle: avian community structure changes in response to perceived predation risk on adults and offspring, P. Roy. Soc. B-biol. Sci., 280 (2013), 20130762. https://doi.org/10.1098/rspb.2013.0762 doi: 10.1098/rspb.2013.0762 |
[13] | F. Hua, K. E. Sieving, J. R. J. Fletcher, C. A. Wright, Increased perception of predation risk to adults and offspring alters avian reproductive strategy and performance, Behav. Ecol., 25 (2014), 509–519. https://doi.org/10.1093/beheco/aru017 doi: 10.1093/beheco/aru017 |
[14] | J. J. Fontaine, T. E. Martin, Parent birds assess nest predation risk and adjust their reproductive strategies, Ecol. Lett., 9 (2006), 428–434. https://doi.org/10.1111/j.1461-0248.2006.00892.x doi: 10.1111/j.1461-0248.2006.00892.x |
[15] | S. Creel, D. Christianson, S. Liley, J. A. Winnie, Predation risk affects reproductive physiology and demography of elk, Science, 315 (2007), 960–960. http://doi.org/10.1126/science.1135918 doi: 10.1126/science.1135918 |
[16] | M. J. Sheriff, C. J. Krebs, R. Boonstra, The sensitive hare: sublethal effects of predator stress on reproduction in snowshoe hares, J. Anim. Ecol., 78 (2009), 1249–1258. https://doi.org/10.1111/j.1365-2656.2009.01552.x doi: 10.1111/j.1365-2656.2009.01552.x |
[17] | A. J. Wirsing, W. J. Ripple, A comparison of shark and wolf research reveals similar behavioral responses by prey, Front. Ecol. Environ., 9 (2011), 335–341. https://doi.org/10.1890/090226 doi: 10.1890/090226 |
[18] | M. A. McPeek, M. Grace, J. M. L. Richardson, Physiological and behavioral responses to predators shape the growth/predation risk trade-off in damselflies, Ecology, 82 (2001), 1535–1545. https://doi.org/10.1890/0012-9658(2001)082[1535:PABRTP]2.0.CO;2 doi: 10.1890/0012-9658(2001)082[1535:PABRTP]2.0.CO;2 |
[19] | G. Kunert, W. W. Weisser, The interplay between density-and trait-mediated effects in predator-prey interactions: A case study in aphid wing polymorphism, Oecologia, 135 (2003), 304–312. https://doi.org/10.1007/s00442-003-1185-8 doi: 10.1007/s00442-003-1185-8 |
[20] | E. B. Mondor, B. D. Roitberg, Pea aphid, Acyrthosiphon pisum, cornicle ontogeny as an adaptation to differential predation risk, Can. J. Zool., 80 (2002), 2131–2136. https://doi.org/10.1139/z02-209 doi: 10.1139/z02-209 |
[21] | Y. Xue, Impact of both-density-dependent fear effect in a Leslie–Gower predator–prey model with Beddington–DeAngelis functional response, Chaos Soliton. Fract., 185 (2024), 115055. https://doi.org/10.1016/j.chaos.2024.115055 doi: 10.1016/j.chaos.2024.115055 |
[22] | S. Pal, N. Pal, S. Samanta, J. Chattopadhyay, Effect of hunting cooperation and fear in a predator-prey model, Ecol. Complex., 39 (2019), 100770. https://doi.org/10.1016/j.ecocom.2019.100770 doi: 10.1016/j.ecocom.2019.100770 |
[23] | Y. Xue, F. Chen, X. Xie, S. Chen, An analysis of a predator-prey model in which fear reduces prey birth and death rates, AIMS Math., 9 (2024), 12906–12927. https://doi.org/10.3934/math.2024630 doi: 10.3934/math.2024630 |
[24] | X. Wang, L. Zanette, X. Zou, Modelling the fear effect in predator–prey interactions, J. Math. Biol., 73 (2016), 1179–1204. https://doi.org/10.1007/s00285-016-0989-1 doi: 10.1007/s00285-016-0989-1 |
[25] | J. Mei, S. Wang, X. Xia, W. Wang, An economic model predictive control for knowledge transmission processes in multilayer complex networks, IEEE. T. Cybernetics., 54 (2022), 1442–1455. https://doi.org/10.1109/TCYB.2022.3204568 doi: 10.1109/TCYB.2022.3204568 |
[26] | C. Li, S. Tang, Analyzing a generalized pest-natural enemy model with nonlinear impulsive control, Open. Math., 16 (2018), 1390–1411. https://doi.org/10.1515/math-2018-0114 doi: 10.1515/math-2018-0114 |
[27] | J. Mei, S. Wang, D. Xia, J. Hu, Global stability and optimal control analysis of a knowledge transmission model in multilayer networks, Chaos Soliton. Fract., 164 (2022), 112708. http://dx.doi.org/10.1016/j.chaos.2022.112708 doi: 10.1016/j.chaos.2022.112708 |
[28] | Y. Tian, S. 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 |
[29] | S. Wang, J. Mei, D. Xia, Z. Yang, J. Hu, Finite-time optimal feedback control mechanism for knowledge transmission in complex networks via model predictive control, Chaos Soliton. Fract., 164 (2022), 112724. http://dx.doi.org/10.1016/j.chaos.2022.112724 doi: 10.1016/j.chaos.2022.112724 |
[30] | S. Tang, L. Chen, Modelling and analysis of integrated pest management strategy, Discrete. Cont. Dyn-B., 4 (2004), 759–768. https://doi.org/10.3934/dcdsb.2004.4.759 doi: 10.3934/dcdsb.2004.4.759 |
[31] | L. S. Chen, H. D. Cheng, Modeling of integrated pest control drives the rise of semi-continuous dynamical system theory, Int. Math. Model. Appl., 10 (2021), 1–16. http://dx.doi.org/10.19943/j.2095-3070.jmmia.2021.01.01 doi: 10.19943/j.2095-3070.jmmia.2021.01.01 |
[32] | P. F. J. Wolf, J. A. Verreet, An integrated pest management system in Germany for the control of fungal leaf diseases in sugar beet: The IPM sugar beet model, Plant. Dis., 86 (2002), 336–344. https://doi.org/10.1094/PDIS.2002.86.4.336 doi: 10.1094/PDIS.2002.86.4.336 |
[33] | S. 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 |
[34] | X. Song, Z. Xiang, The prey-dependent consumption two-prey one-predator models with stage structure for the predator and impulsive effects, J. Theor. Biol., 242 (2006), 683–698. https://doi.org/10.1016/j.jtbi.2006.05.002 doi: 10.1016/j.jtbi.2006.05.002 |
[35] | J. Yang, S. Tang, Holling type Ⅱ predator–prey model with nonlinear pulse as state-dependent feedback control, J. Comput. Appl. Math., 291 (2016), 225–241. https://doi.org/10.1016/j.cam.2015.01.017 doi: 10.1016/j.cam.2015.01.017 |
[36] | Y. Tian, S. Tang, R. A. Cheke, Nonlinear state-dependent feedback control of a pest-natural enemy system, Nonlinear. Dynam., 94 (2018), 2243–2263. https://doi.org/10.1007/s11071-018-4487-4 doi: 10.1007/s11071-018-4487-4 |
[37] | S. Y. Tang, W. H. Pang, On the continuity of the function describing the times of meeting impulsive set and its application, Math. Biosci. Eng., 14 (2017), 1399–1406. http://dx.doi.org/10.3934/mbe.2017072 doi: 10.3934/mbe.2017072 |
[38] | C. Li, S. Tang, R. A. Cheke, Complex dynamics and coexistence of period-doubling and period-halving bifurcations in an integrated pest management model with nonlinear impulsive control, Adv. Differ. Equ-NY., 2020 (2020), 1–23. https://doi.org/10.1186/s13662-020-02971-9 doi: 10.1186/s13662-020-02971-9 |
[39] | I. U. Khan, S. Y. Tang, The impulsive model with pest density and its change rate dependent feedback control, Discrete Dyn. Nat. Soc., 1 (2020), 4561241. https://doi.org/10.1155/2020/4561241 doi: 10.1155/2020/4561241 |
[40] | V. Křivan, Effects of optimal antipredator behavior of prey on predator–prey dynamics: The role of refuges, Theor. Popul. Biol., 53 (1998), 131–142. https://doi.org/10.1006/tpbi.1998.1351 doi: 10.1006/tpbi.1998.1351 |
[41] | H. Zhang, Y. Cai, S. Fu, W. Wang, Impact of the fear effect in a prey-predator model incorporating a prey refuge, Appl. Math. Comput., 356 (2019), 328–337. https://doi.org/10.1016/j.amc.2019.03.034 doi: 10.1016/j.amc.2019.03.034 |
[42] | H. Molla, S. Sarwardi, M. Haque, Dynamics of adding variable prey refuge and an Allee effect to a predator–prey model, Alex. Eng. J., 61 (2022), 4175–4188. https://doi.org/10.1016/j.aej.2021.09.039 doi: 10.1016/j.aej.2021.09.039 |