Analysis of a stochastic two-patch model with nonlinear birth rate and dispersal driven by the Ornstein–Uhlenbeck process

Beijia Li , Xiaohui Ai

Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (5) : 3145 -3165.

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Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (5) :3145 -3165. DOI: 10.3934/era.2026142
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Analysis of a stochastic two-patch model with nonlinear birth rate and dispersal driven by the Ornstein–Uhlenbeck process
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Abstract

This paper proposes a novel stochastic two-patch model that incorporates a Beverton–Holt-type nonlinear birth rate and dispersal driven by an Ornstein–Uhlenbeck process. We first establish the existence and uniqueness of a global positive solution, thereby ensuring the biological well-posedness of the model. By constructing appropriate Lyapunov functions and applying Itô’s formula, we further demonstrate the existence of a stationary distribution, which characterizes the long-term statistical behavior of the system. Sufficient conditions for population extinction are then derived, providing criteria for predicting when the population is destined to disappear. We perform numerical simulations using the Euler–Maruyama method to validate the main theoretical results. Finally, as an empirical application, the stochastic model achieves a good fit to zooplankton data, confirming its practical validity and offering important insights for mathematical ecology, as well as for species conservation, population regulation, and resource management in fragmented habitats.

Keywords

stochastic two-patch model / Ornstein-Uhlenbeck process / stationary distribution / extinction

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Beijia Li, Xiaohui Ai. Analysis of a stochastic two-patch model with nonlinear birth rate and dispersal driven by the Ornstein–Uhlenbeck process. Electronic Research Archive, 2026, 34 (5) : 3145-3165 DOI:10.3934/era.2026142

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References

[1]

I. H. Andrén, Effects of habitat fragmentation on birds and mammals in landscapes with different proportions of suitable habitat: A review, Oikos, 71 (1994), 355-366. https://doi.org/10.2307/3545823

[2]

I. Hanski, Metapopulation Ecology , Oxford University Press, 1999.

[3]

C. Grumbach, F. N. Reurik, J. Segura, D. Franco, F. M. Hilker, The effect of dispersal on asymptotic total population size in discrete- and continuous-time two-patch models, J. Math. Biol., 87 (2023), 60. https://doi.org/10.1007/s00285-023-01984-8

[4]

R. M. May, Stability and Complexity in Model Ecosystems , Princeton University Press, Princeton, (2019), 146-157. https://doi.org/10.15789/9780691199121

[5]

H. L. Wei, W. H. Li, Dynamical behaviors of a Lotka-Volterra competition system with the Ornstein-Uhlenbeck process, Math. Biosci. Eng., 20 (2023), 7882-7904. https://doi.org/10.3934/mbe.2023341

[6]

X. Liu, H. Cao, L. F. Nie, Insights into infectious diseases with horizontal and environmental transmission: A stochastic model with logarithmic Ornstein-Uhlenbeck process and nonlinear incidence, Chaos Solitons Fractals, 191 (2025), 115888. https://doi.org/10.1016/j.chaos.2024.115888

[7]

H. Wu, Y. S. Wang, Y. F. Li, D. L. DeAngelis, Dispersal asymmetry in a two-patch system with source-sink populations, Theor. Popul. Biol., 131 (2020), 54-65. https://doi.org/10.1016/j.tpb.2019.11.004

[8]

L. J. Chen, T. T. Liu, F. D. Chen, Stability and bifurcation in a two-patch model with additive Allee effect, AIMS Math., 7 (2022), 536-551. https://doi.org/10.3934/math.2022034

[9]

S. Tang, L. Chen, Density-dependent birth rate, birth pulses and their population dynamic consequences, J. Math. Biol., 44 (2002), 185-199. https://doi.org/10.1007/s002850100121

[10]

Q. Yue, Permanence of a delayed biological system with stage structure and density-dependent juvenile birth rate, Eng. Lett., 27 (2019), 1-5.

[11]

X. Mao, G. Marion, E. Renshaw, Environmental Brownian noise suppresses explosions in population dynamics, Stochastic Processes Appl., 97 (2002), 95-110. https://doi.org/10.1016/S0304-4149(01)00126-0

[12]

X. Zhang, R. Yuan, A stochastic chemostat model with mean-reverting Ornstein-Uhlenbeck process and Monod-Haldane response function, Appl. Math. Comput., 394 (2021), 125833. https://doi.org/10.1016/j.amc.2020.125833

[13]

Q. Liu, D. Jiang, Analysis of a stochastic within-host model of dengue infection with immune response and Ornstein-Uhlenbeck process, J. Nonlinear Sci., 34 (2024), 28. https://doi.org/10.1007/s00332-023-10004-4

[14]

R. Khasminskii, Stochastic Stability of Differential Equations , Springer Science & Business Media, Berlin, (2011), 43-58. https://doi.org/10.1007/978-3-642-19947-9

[15]

R. McVinish, P. K. Pollett, Y. S. Chan, A metapopulation model with Markovian landscape dynamics, Theor. Popul. Biol., 112 (2016), 1-12. https://doi.org/10.1016/j.tpb.2016.08.005

[16]

D. Y. Xu, Y. M. Huang, Z. G. Yang, Existence theorems for periodic Markov process and stochastic functional differential equations, Discrete Contin. Dyn. Syst., 24 (2009), 1005-1023. https://doi.org/10.3934/dcds.2009.24.1005

[17]

H. D. Nguyen, H. N. Dang, G. G. Yin, Conditions for permanence and ergodicity of certain stochastic predator-prey models, J. Appl. Probab., 53 (2016), 187-202. https://doi.org/10.1017/jpr.2015.18

[18]

A. Y. Kutoyants, Statistical Inference for Ergodic Diffusion Processes , Springer Science & Business Media, Berlin, (2004), 17-23.

[19]

Y. Cai, J. Jiao, Z. Gui, Y. Liu, W. Wang, Environmental variability in a stochastic epidemic model, Appl. Math. Comput., 329 (2018), 210-226. https://doi.org/10.1016/j.amc.2018.02.009

[20]

O. P. Nave, Modification of semi-analytical method applied system of ode, Mod. Appl. Sci., 14 (2020), 75. https://doi.org/10.5539/mas.v14n6p75

[21]

G. Y. Lv, H. J. Gao, J. L. Wei, J. L. Wu, The effect of noise intensity on parabolic equations, Discrete Contin. Dyn. Syst. Ser. B, 24 (2019), 6247-6266. https://doi.org/10.3934/dcdsb.2019248

[22]

X. R. Mao, The truncated Euler-Maruyama method for stochastic differential equations, J. Comput. Appl. Math., 290 (2015), 370-384. https://doi.org/10.1016/j.cam.2015.06.002

[23]

S. E. Jørgensen, Handbook of Environmental Data and Ecological Parameters: Environmental Sciences and Applications , Pergamon, 1979. https://doi.org/10.1016/C2013-0-05856-2

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