A spatio-temporal prey-predator (quokka and red fox interaction) model with the fear effect, Holling type Ⅱ functional response, and a generalist predator is proposed. The existence of equilibrium points and their corresponding stability are analyzed under certain conditions to explore the system's dynamics. The occurrence of a Hopf bifurcation, a saddle-node bifurcation, and a Bogdanov-Takens bifurcation are confirmed. The partial rank correlation coefficient method is performed for the sensitivity analysis. Furthermore, the cross-diffusion is incorporated in the formulated model system to identify the spatio-temporal dynamics of the system. All theoretical results are validated through a numerical simulation. The outcome of the temporal model shows a decrease in the fear effect due to the predation by the red fox helps to increase the quokka population. The spatio-temporal model indicates that as the diffusion coefficient and fear parameters vary, the pattern changes from isolated spots to stripes, and again from stripes to spots. This represents the variation in spatial interactions and aggregation. The dispersion of predators and prey increases with an increased diffusion; however, the group formation is restricted by a stronger fear effect that scatters prey.
Citation: Sangeeta Kumari, Sidharth Menon, Abhirami K. Dynamical system of quokka population depicting Fennecaphobia by Vulpes vulpes[J]. Mathematical Biosciences and Engineering, 2025, 22(6): 1342-1363. doi: 10.3934/mbe.2025050
A spatio-temporal prey-predator (quokka and red fox interaction) model with the fear effect, Holling type Ⅱ functional response, and a generalist predator is proposed. The existence of equilibrium points and their corresponding stability are analyzed under certain conditions to explore the system's dynamics. The occurrence of a Hopf bifurcation, a saddle-node bifurcation, and a Bogdanov-Takens bifurcation are confirmed. The partial rank correlation coefficient method is performed for the sensitivity analysis. Furthermore, the cross-diffusion is incorporated in the formulated model system to identify the spatio-temporal dynamics of the system. All theoretical results are validated through a numerical simulation. The outcome of the temporal model shows a decrease in the fear effect due to the predation by the red fox helps to increase the quokka population. The spatio-temporal model indicates that as the diffusion coefficient and fear parameters vary, the pattern changes from isolated spots to stripes, and again from stripes to spots. This represents the variation in spatial interactions and aggregation. The dispersion of predators and prey increases with an increased diffusion; however, the group formation is restricted by a stronger fear effect that scatters prey.
| [1] | P. J. De Tores, M. W. Hayward, M. J. Dillon, R. I. Brazell, Review of the distribution, causes for the decline and recommendations for management of the quokka, Setonix brachyurus (Macropodidae: Marsupialia), an endemic macropodid marsupial from south-west Western Australia, Conserv. Sci. West. Aust., 6 (2007), 13–73. |
| [2] | D. R. King, L. A. Smith, The distribution of the European red fox (Vulpes vulpes) in western Australia, Rec. West. Aust. Mus., 12 (1985), 97–205. |
| [3] |
N. E. Davis, D. M. Forsyth, B. Triggs, C. Pascoe, J. Benshemesh, A. Robley, et al., Interspecific and geographic variation in the diets of sympatric carnivores: Dingoes/wild dogs and red foxes in south-eastern Australia, PLoS One, 10 (2015), e0120975. https://doi.org/10.1371/journal.pone.0120975 doi: 10.1371/journal.pone.0120975
|
| [4] |
M. W. Hayward, P. J. de Tores, M. J. Dillon, B. J. Fox, Local population structure of a naturally occurring metapopulation of the quokka (Setonix brachyurus Macropodidae: Marsupialia), Biol. Conserv., 110 (2003), 343–355. https://doi.org/10.1016/S0006-3207(02)00240-9 doi: 10.1016/S0006-3207(02)00240-9
|
| [5] |
M. W. Hayward, P. J. de Tores, M. L. Augee, P. B. Banks, Mortality and survivorship of the quokka (Setonix brachyurus) (Macropodidae: Marsupialia) in the northern jarrah forest of western Australia, Wildl. Res., 32 (2005), 715–722. https://doi.org/10.1071/WR04111 doi: 10.1071/WR04111
|
| [6] |
P. Roy, S. Jain, M. Maama, Assessing the viability of tri-trophic food chain model in designing a conservation plan: The case of dwindling quokka population, Ecol. Complexity, 41 (2020), 100811. https://doi.org/10.1016/j.ecocom.2020.100811 doi: 10.1016/j.ecocom.2020.100811
|
| [7] |
B. Belew, D. Melese, Modeling and analysis of predator‐prey model with fear effect in prey and hunting cooperation among predators and harvesting, J. Appl. Math., 2022 (2022), 1–14. https://doi.org/10.1155/2022/2776698 doi: 10.1155/2022/2776698
|
| [8] |
C. Arancibia-Ibarra, J. Flores, Dynamics of a Leslie-Gower predator-prey model with Holling type Ⅱ functional response, Allee effect and a generalist predator, Math. Comput. Simul., 188 (2021), 1–22. https://doi.org/10.1016/j.matcom.2021.03.035 doi: 10.1016/j.matcom.2021.03.035
|
| [9] |
P. A. Naik, Z. Eskandari, M. Yavuz, J. Zu, Complex dynamics of a discrete-time Bazykin-Berezovskaya prey-predator model with a strong Allee effect, J. Comput. Appl. Math., 413 (2022), 114401. https://doi.org/10.1016/j.cam.2022.114401 doi: 10.1016/j.cam.2022.114401
|
| [10] |
W. Ishaque, Q. Din, K. A. Khan, R. M. Mabela, Dynamics of predator-prey model based on fear effect with bifurcation analysis and chaos control, Qual. Theory Dyn. Syst., 23 (2024), 1–26. https://doi.org/10.1007/s12346-023-00878-w doi: 10.1007/s12346-023-00878-w
|
| [11] |
P. A. Naik, M. Amer, R. Ahmed, S. Qureshi, Z. Huang, Stability and bifurcation analysis of a discrete predator-prey system of Ricker type with refuge effect, Math. Biosci. Eng., 21 (2024), 4554–4586. https://doi.org/10.3934/mbe.2024201 doi: 10.3934/mbe.2024201
|
| [12] | L. Y. Zanette, M. Clinchy, Ecology of fear, Curr. Biol., 29 (2019), R309–R313. |
| [13] |
K. Sarkar, S. Khajanchi, Impact of fear effect on the growth of prey in a predator-prey interaction model, Ecol. Complexity, 42 (2020), 100826. https://doi.org/10.1016/j.ecocom.2020.100826 doi: 10.1016/j.ecocom.2020.100826
|
| [14] |
Y. Tian, H. M. Li, The study of a predator‐prey model with fear effect based on state‐dependent harvesting strategy, Complexity, 2022 (2022), 1–19. https://doi.org/10.1155/2022/9496599 doi: 10.1155/2022/9496599
|
| [15] |
Y. Huang, Z. Zhu, Z. Li, Modeling the Allee effect and fear effect in predator-prey system incorporating a prey refuge, Adv. Differ. Equations, 2020 (2020), 1–13. https://doi.org/10.1186/s13662-020-02727-5 doi: 10.1186/s13662-020-02727-5
|
| [16] |
A. A. Thirthar, S. J. Majeed, M. A. Alqudah, P. Panja, T. Abdeljawad, Fear effect in a predator-prey model with additional food, prey refuge and harvesting on super predator, Chaos Solitons Fractals, 159 (2022), 112091. https://doi.org/10.1016/j.chaos.2022.112091 doi: 10.1016/j.chaos.2022.112091
|
| [17] |
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
|
| [18] |
X. Zhang, H. Zhu, Q. An, Dynamics analysis of a diffusive predator-prey model with spatial memory and nonlocal fear effect, J. Math. Anal. Appl., 525 (2023), 127123. https://doi.org/10.1016/j.jmaa.2023.127123 doi: 10.1016/j.jmaa.2023.127123
|
| [19] |
K. Sarkar, S. Khajanchi, Spatiotemporal dynamics of a predator-prey system with fear effect, J. Franklin Inst., 360 (2023), 7380–7414. https://doi.org/10.1016/j.jfranklin.2023.05.034 doi: 10.1016/j.jfranklin.2023.05.034
|
| [20] |
X. Sun, Dynamics of a diffusive predator-prey model with nonlocal fear effect, Chaos Solitons Fractals, 177 (2023), 114221. https://doi.org/10.1016/j.chaos.2023.114221 doi: 10.1016/j.chaos.2023.114221
|
| [21] |
T. Ma, X. Meng, Global analysis and Hopf-bifurcation in a cross-diffusion prey-predator system with fear effect and predator cannibalism, Math. Biosci. Eng., 19 (2022), 6040–6071. https://doi.org/10.3934/mbe.2022282 doi: 10.3934/mbe.2022282
|
| [22] |
W. Xu, P. Jiang, H. Shu, S. Tong, Modeling the fear effect in the predator-prey dynamics with an age structure in the predators, Math. Biosci. Eng., 20 (2023), 12625–12648. https://doi.org/10.3934/mbe.2023562 doi: 10.3934/mbe.2023562
|
| [23] |
Y. Kang, S. K. Sasmal, K. Messan, A two-patch prey-predator model with predator dispersal driven by the predation strength, Math. Biosci. Eng., 14 (2017), 843–880. https://doi.org/10.3934/mbe.2017046 doi: 10.3934/mbe.2017046
|
| [24] |
Y. Zhang, X. Rong, J. Zhang, A diffusive predator-prey system with prey refuge and predator cannibalism, Math. Biosci. Eng., 16 (2019), 1445–1470. https://doi.org/10.3934/mbe.2019070 doi: 10.3934/mbe.2019070
|
| [25] |
N. Shigesada, K. Kawasaki, E. Teramoto, Spatial segregation of interacting species, J. Theor. Biol., 79 (1979), 83–99. https://doi.org/10.1016/0022-5193(79)90258-3 doi: 10.1016/0022-5193(79)90258-3
|
| [26] |
M. Banerjee, S. Abbas, Existence and non-existence of spatial patterns in a ratio-dependent predator-prey model, Ecol. Complexity, 21 (2015), 199–214. https://doi.org/10.1016/j.ecocom.2014.05.005 doi: 10.1016/j.ecocom.2014.05.005
|
| [27] |
F. Wang, R. Yang, Spatial pattern formation driven by the cross-diffusion in a predator-prey model with Holling type functional response, Chaos Solitons Fractals, 174 (2023), 113890. https://doi.org/10.1016/j.chaos.2023.113890 doi: 10.1016/j.chaos.2023.113890
|
| [28] |
S. Kumari, S. K. Tiwari, R. K. Upadhyay, Cross-diffusion induced spatiotemporal pattern in diffusive nutrient-plankton model with nutrient recycling, Math. Comput. Simul., 202 (2022), 246–272. https://doi.org/10.1016/j.matcom.2022.05.027 doi: 10.1016/j.matcom.2022.05.027
|
| [29] |
R. K. Upadhyay, S. Mishra, Population dynamic consequences of fearful prey in a spatiotemporal predator-prey system, Math. Biosci. Eng., 16 (2018), 338–372. https://doi.org/10.3934/mbe.2019017 doi: 10.3934/mbe.2019017
|
| [30] |
E. Sáez, E. González-Olivares, Dynamics of a predator-prey model, SIAM J. Appl. Math., 59 (1999), 1867–1878. https://doi.org/10.1137/S0036139997318457 doi: 10.1137/S0036139997318457
|
| [31] |
L. Puchuri, E. González‐Olivares, A. Rojas‐Palma, Multistability in a Leslie-Gower-type predation model with a rational nonmonotonic functional response and generalist predators, Comput. Math. Methods, 2 (2020), 1–18. https://doi.org/10.1002/cmm4.1070 doi: 10.1002/cmm4.1070
|
| [32] | L. Perko, Differential Equations and Dynamical Systems, Springer Science & Business Media, 2013. |
| [33] | Y. A. Kuznetsov, I. A. Kuznetsov, Y. Kuznetsov, Elements of Applied Bifurcation Theory, Springer, New York, 1998. |
| [34] | D. Xiao, S. Ruan, Bogdanov-Takens bifurcations in predator-prey systems with constant rate harvesting, Fields Inst. Commun., 21 (1999), 493–506. |
| [35] | R. K. Upadhyay, S. R. K. Iyengar, Spatial Dynamics and Pattern Formation in Biological Populations, CRC Press, 2021. |
| [36] |
S. Marino, I. B. Hogue, C. J. Ray, D. E. Kirschner, A methodology for performing global uncertainty and sensitivity analysis in systems biology, J. Theor. Biol., 254 (2008), 178–196. https://doi.org/10.1016/j.jtbi.2008.04.011 doi: 10.1016/j.jtbi.2008.04.011
|
| [37] |
A. Dhooge, W. Govaerts, Y. A. Kuznetsov, MATCONT: A MATLAB package for numerical bifurcation analysis of ODEs, ACM Trans. Math. Software, 29 (2003), 141–164. https://doi.org/10.1145/779359.779362 doi: 10.1145/779359.779362
|