Hydra effects predator-prey bazykin's model with stage-structure and intraspecific for predator

Rian Ade Pratama, A. Muh. Amil Siddik, Oswaldus Dadi, Kasbawati Kasbawati

Abstract


Bazykin's predator-prey population model is considered to represent the exchange stability condition of population growth. The existence of the hydra effect and, at the same time, analyzing its influence on population growth. The condition of the model divides the species into a stage structure, namely, prey, immature predators, and mature predators. The population growth of the three species has its own characteristics. This research revealed that the Holling type II and intraspecific predatory function responses together induce the Hydra effect. In the model formed, there are 12 equilibrium points, with details for every seven points of negative imaginary equilibrium and five points of non-negative equilibrium. The findings of research studies center on five points of non-negative equilibrium. All real roots that interpret the species population's growth conditions are taken and tested for long-term stability. The test results show one point of equilibrium that meets the Routh-Hurwitz criteria and their characteristic equations. In numerical simulations, the maximum sustained yield is in the local asymptotic stable state. The growth of prey trajectories increased significantly, although at the beginning of the interaction there was a slowdown in population growth. Meanwhile, the population of immature predators and mature predators was not significantly different. Both populations grow steadily toward the point of population stability. It turns out that the two populations grow inversely, the faster the rate of predation by predators, the faster the growth rate of the prey population.

Keywords


Predator-prey Bazykin’s; Stage-Structure; Hydra Effects.

Full Text:

PDF

References


Adhikary, P. Das, Mukherjee, S., & Ghosh, B. (2021). Bifurcations and hydra effects in bazykin’s predator–prey model. Theoretical Population Biology, 140(xxxx), 44–53. https://doi.org/10.1016/j.tpb.2021.05.002

Anjos, L. dos, Costa, M. I. da S., & Almeida, R. C. (2020). Characterizing the existence of hydra effect in spatial predator-prey models and the influence of functional response types and species dispersal. Ecological Modelling, 428(April), 109109. https://doi.org/10.1016/j.ecolmodel.2020.109109

Bajeux, N., & Ghosh, B. (2020). Stability switching and hydra effect in a predator–prey metapopulation model. BioSystems, 198, 104255. https://doi.org/10.1016/j.biosystems.2020.104255

Cortez, M. H., & Abrams, P. A. (2016). Hydra effects in stable communities and their implications for system dynamics. Ecology, 97(5), 1135–1145. https://doi.org/10.1890/15-0648.1

Cortez, M. H., & Yamamichi, M. (2019). How (co)evolution alters predator responses to increased mortality: Extinction thresholds and hydra effects. Ecology, 100(10), 1–17. https://doi.org/10.1002/ecy.2789

Esteves, P. V, & Caxias, D. De. (2021). Multiple stage hydra effect in a stage – structured prey–predator model. 1–12.

Garain, K., & Mandal, P. S. (2021). Bubbling and hydra effect in a population system with allee effect. Ecological Complexity, 47(May), 100939. https://doi.org/10.1016/j.ecocom.2021.100939

Iskin da S. Costa, M., & Dos Anjos, L. (2018). Multiple hydra effect in a predator–prey model with allee effect and mutual interference in the predator. Ecological Modelling, 373(November 2017), 22–24. https://doi.org/10.1016/j.ecolmodel.2018.02.005

Lee, A. H., Fraz, S., Purohit, U., Campos, A. R., & Wilson, J. Y. (2020). Chronic exposure of brown (hydra oligactis) and green hydra (hydra viridissima) to environmentally relevant concentrations of pharmaceuticals. Science of the Total Environment, 732, 139232. https://doi.org/10.1016/j.scitotenv.2020.139232

Liz, E., & Sovrano, E. (2022). Stability, bifurcations and hydra effects in a stage-structured population model with threshold harvesting. Communications in Nonlinear Science and Numerical Simulation, 109(January), 106280. https://doi.org/10.1016/j.cnsns.2022.106280

Lu, M., Xiang, C., Huang, J., & Wang, H. (2022). Bifurcations in the diffusive bazykin model. Journal of Differential Equations, 323, 280–311. https://doi.org/10.1016/j.jde.2022.03.039

Martcheva, M. (2015). An introduction to mathematical epidemiology. Springer, New York.

Pal, D., Ghosh, B., & Kar, T. K. (2019). Hydra effects in stable food chain models. BioSystems, 185(December 2018), 104018. https://doi.org/10.1016/j.biosystems.2019.104018

Pratama, R. A., Fransina, M., Ruslau, V., & Musamus, U. (2022). Application of beddington deangelis response function in ecological mathematical system: Study fish endemic oliv predator species in merauke. JTAM (Jurnal Teori Dan Aplikasi Matematika), 6(1), 51–60.

Sieber, M., & Hilker, F. M. (2012). The hydra effect in predator-prey models. Journal of Mathematical Biology, 64(1–2), 341–360. https://doi.org/10.1007/s00285-011-0416-6

Weide, V., Varriale, M. C., & Hilker, F. M. (2019). Hydra effect and paradox of enrichment in discrete-time predator-prey models. Mathematical Biosciences, 310, 120–127. https://doi.org/10.1016/j.mbs.2018.12.010




DOI: http://dx.doi.org/10.24042/djm.v5i3.13160

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Desimal: Jurnal Matematika

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

  Creative Commons License
Desimal: Jurnal Matematika is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.