2026 Volume 16 Issue 1
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Jiarui Zhang, Wei Li, Mi Wang. ANALYSIS OF THE KINETIC PROPERTIES OF THE DISCRETE FOREST DISEASE AND INSECT PEST MODELS[J]. Journal of Applied Analysis & Computation, 2026, 16(1): 136-154. doi: 10.11948/20240542
Citation: Jiarui Zhang, Wei Li, Mi Wang. ANALYSIS OF THE KINETIC PROPERTIES OF THE DISCRETE FOREST DISEASE AND INSECT PEST MODELS[J]. Journal of Applied Analysis & Computation, 2026, 16(1): 136-154. doi: 10.11948/20240542

ANALYSIS OF THE KINETIC PROPERTIES OF THE DISCRETE FOREST DISEASE AND INSECT PEST MODELS

  • In this paper, we study the dynamic behavior of discrete forest disease and pest model-spruce aphid model, analyze the properties of the dynamics by using the difference equation theory, including the existence of equilibrium points in the system model, and further analyze the stability and instability conditions of these equilibrium points. In addition, the step h is selected as the bifurcation parameter using the central manifold theorem to analyze the Flip bifurcation and Hopf bifurcation at the equilibrium point, and prove the chaos of the system through the maximum Lyapunov diagram. In order to verify the theoretical proof, the system model is simulated numerically to draw relevant conclusions.

    MSC: 34C23, 37N25
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  • [1] Y. Bai, L. Wang and X. Yuan, Pesticide control, physical control, or biological control, How to manage forest pests and diseases more effectively, Front. Ecol. Evol., 2023, 11. DOI: 10.3389/fevo.2023.1200268.

    CrossRef Google Scholar

    [2] D. Bevacqua, I. Grechi, M. Génard, et al., The consequences of aphid infestation on fruit production become evident in a multi-year perspective: Insights from a virtual experiment, Ecol. Model., 2016, 338, 11-16.

    Google Scholar

    [3] S. J. Crute, Computer simulations of green spruce aphid populations, J. Anim. Ecol., 1992.

    Google Scholar

    [4] B. Dalziel, E. Thomann and J. Medlock, Global analysis of a predator-prey model with variable predator search rate, J. Math. Biol., 2020, 81(1), 159-183.

    Google Scholar

    [5] K. R. Day, H. Armour and M. Docherty, Population responses of a conifer‐dwelling aphid to seasonal changes in its host, Ecol. Entomol., 2004, 29(5), 555-565.

    Google Scholar

    [6] K. R. Day, M. P. Ayres, R. Harrington, et al., Interannual dynamics of aerial and arboreal green spruce aphid populations, Popul. Ecol., 2010, 52, 317-327.

    Google Scholar

    [7] S. A. Estay, M. Lima, F. A. Labra, et al., Increased outbreak frequency associated with changes in the dynamic behaviour of populations of two aphid species, Oikos, 2012, 121(4), 614-622.

    Google Scholar

    [8] B. Hong and C. Zhang, Bifurcations and chaotic behavior of a predator-prey model with discrete time, AIMS Math., 2023, 8(6), 13390-13410.

    Google Scholar

    [9] Y. L. Huang, W. Y. Shi and S. W. Zhang, A stochastic predator-prey model with Holling Ⅱ increasing function in the predator, J. Biol. Dyn., 2021, 15(1), 1-18.

    Google Scholar

    [10] S. R. J. Jang and D. M. Johnson, Dynamics of discrete-time larch budmoth population models, J. Biol. Dyn., 2009, 3(2-3), 209-223.

    Google Scholar

    [11] L. Ji, Z. Wang, X. Wang, et al., Forest insect pest management and forest management in China: An overview, Environ. Manage., 2011, 48, 1107-1121.

    Google Scholar

    [12] J. T. Jones, M. Moens, M. Mota, et al., Bursaphelenchus xylophilus: Opportunities in comparative genomics and molecular host–parasite interactions, Mol. Plant Pathol., 2008, 9(3), 357-368.

    Google Scholar

    [13] G. Lemperiere, K. R. Day, Y. Petit‐Berghem, et al., Interannual population dynamics of the green spruce aphid Elatobium abietinum (Walker) in France, Ann. Appl. Biol., 2020, 176(3), 233-240.

    Google Scholar

    [14] A. H. Li, H. Y. Jing and J. C. Fu, Dynamic characteristic of spruce budworm–its natural enemy–pesticide interaction model, J. Biomathem., 2006, 21(3), 377-383.

    Google Scholar

    [15] T. Li, X. Zhang and C. Zhang, Pattern dynamics analysis of a space–time discrete spruce budworm model, Chaos. Solitons. Fractals., 2024, 179, 114423.

    Google Scholar

    [16] L. Liang, S. Niu and J. Wang, Current situation and future study on effect of invading Bursaphelenchus xylophilus on ecosystem, J. Zhejiang For. Sci. Technol., 2006, 73-78.

    Google Scholar

    [17] M. Lima, R. Harrington, S. Saldaña, et al., Non‐linear feedback processes and a latitudinal gradient in the climatic effects determine green spruce aphid outbreaks in the UK, Oikos, 2008, 117(6), 951-959.

    Google Scholar

    [18] D. Ludwig, D. D. Jones and C. S. Holling, Qualitative analysis of insect outbreak systems: The spruce budworm and forest, J. Anim. Ecol., 1978, 47(1), 315-332.

    Google Scholar

    [19] C. W. Luo and K. Li, The relation of species diversity to pest control in forest plantations, Sci. Silv. Sin., 2006, 109-115.

    Google Scholar

    [20] A. Rasmussen, J. Wyller and J. O. Vik, Relaxation oscillations in spruce–budworm interactions, nonlinear analysis: Real world applications, Chin. J. Biol. Control, 2011, 304-319.

    Google Scholar

    [21] S. Redlich, J. Clemens, M. K. F. Bader, et al., Identifying new associations between invasive aphids and Pinaceae trees using plant sentinels in botanic gardens, Biol. Invas., 2019, 21, 217-228.

    Google Scholar

    [22] J. H. M. Thornley and J. A. Newman, Climate sensitivity of the complex dynamics of the green spruce aphid—Spruce plantation interactions: Insight from a new mechanistic model, Plos. One, 2022, 17(2), e0252911.

    Google Scholar

    [23] D. W. Williams and A. M. Liebhold, Spatial scale and the detection of density dependence in spruce budworm outbreaks in eastern North America, Oecologia, 2000, 124, 544-552.

    Google Scholar

    [24] D. W. Williams and A. M. Liebhold, Spatial synchrony of spruce budworm outbreaks in eastern North America, Ecology, 2000, 81(10), 2753-2766.

    Google Scholar

    [25] H. C. Xu and Y. Q. Luo, Ecosystems attacked by Bursaphelenchus xylophilus: A review, J. Zhejiang For. Coll., 2010, 27(3), 445-450.

    Google Scholar

    [26] J. Xu and S. Yuan, Near‐optimal control of a stochastic pine wilt disease model with prevention strategies, Math. Methods Appl. Sci., 2023, 46(13), 13855-13881.

    Google Scholar

    [27] Q. Xu and C. Zhang, Bifurcation analysis and chaos of a modified Holling-Tanner model with discrete time, J. Appl. Anal. Comput., 2024, 14(6), 3425-3449.

    Google Scholar

    [28] W. Xu, S. Chen and L. Chen, Modeling of the prevention and control of forest pest, J. Biol. Syst., 2007, 15(04), 539-550.

    Google Scholar

    [29] M. Yang, M. Li, L. Qu, et al., Advances in research on pathogenic microorganisms of pine sawfly, Chin. J. Biol. Control, 2007, 23(3), 284-289.

    Google Scholar

    [30] Z. Yang, X. Wang, Y. Zhang, et al., Research advances of Chinese major forest pests by integrated management based on biological control, Chin. J. Biol. Control., 2018, 34(2), 163.

    Google Scholar

    [31] X. Zhang, C. Zhang and Y. Zhang, Pattern dynamics analysis of a time-space discrete FitzHugh-Nagumo (FHN) model based on coupled map lattices, Comput. Math. Appl., 2024, 157, 92-123.

    Google Scholar

    [32] X. Zhang, C. Zhang and Y. Zhang, Discrete kinetic analysis of a general reaction-diffusion model constructed by Euler discretization and coupled map lattices, Math. Comput. Simul., 2024, 1218-1236.

    Google Scholar

    [33] J. Zhao and Y. Yan, Stability and bifurcation analysis of a discrete predator–prey system with modified Holling–Tanner functional response, Adv. Differ. Equ., 2018, 2018(1), 402.

    Google Scholar

    [34] J. Zheng, Y. Xu, H. Zhang, et al., Advances and prospects of target recognition techniques for forest pest control at home and abroad, Sci. Silv. Sin., 2023, 152-166.

    Google Scholar

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