The fishery resource is a kind of important renewable resource and it is closely connected with people's production and life. However, fishery resources are not inexhaustible, so it has become an important research topic to develop fishery resources reasonably and ensure their sustainability. In the current study, considering the environment changes in the system, a fishery model with a variable predator search rate and fuzzy biological parameters was established first and then two modes of capture strategies were introduced to achieve fishery resource exploitation. For the fishery model in a continuous capture mode, the dynamic properties were analyzed and the results show that predator search rate, imprecision indexes and capture efforts have a certain impact on the existence and stability of the coexistence equilibrium. The bionomic equilibrium and optimal capture strategy were also discussed. For the fishery model in a state-dependent feedback capture mode, the complex dynamics including the existence and stability of the periodic solutions were investigated. Besides the theoretical results, numerical simulations were implemented step by step and the effects of predator search rate, fuzzy biological parameters and capture efforts on the system were demonstrated. This study not only enriched the related content of fishery dynamics, but also provided certain reference for the development and utilization of fishery resources under the environment with uncertain parameters.
Citation: Hua Guo, Yuan Tian, Kaibiao Sun, Xinyu Song. Dynamic analysis of two fishery capture models with a variable search rate and fuzzy biological parameters[J]. Mathematical Biosciences and Engineering, 2023, 20(12): 21049-21074. doi: 10.3934/mbe.2023931
The fishery resource is a kind of important renewable resource and it is closely connected with people's production and life. However, fishery resources are not inexhaustible, so it has become an important research topic to develop fishery resources reasonably and ensure their sustainability. In the current study, considering the environment changes in the system, a fishery model with a variable predator search rate and fuzzy biological parameters was established first and then two modes of capture strategies were introduced to achieve fishery resource exploitation. For the fishery model in a continuous capture mode, the dynamic properties were analyzed and the results show that predator search rate, imprecision indexes and capture efforts have a certain impact on the existence and stability of the coexistence equilibrium. The bionomic equilibrium and optimal capture strategy were also discussed. For the fishery model in a state-dependent feedback capture mode, the complex dynamics including the existence and stability of the periodic solutions were investigated. Besides the theoretical results, numerical simulations were implemented step by step and the effects of predator search rate, fuzzy biological parameters and capture efforts on the system were demonstrated. This study not only enriched the related content of fishery dynamics, but also provided certain reference for the development and utilization of fishery resources under the environment with uncertain parameters.
[1] | FAO, The State of World Fisheries and Aquaculture 2018 - Meeting the sustainable development goals, Rome, 2018 Licence: CC BY-NC-SA 3.0 IGO. |
[2] | A. J. Lotka, Elements of physical biology, in Science Progress in the Twentieth Century (1919–1933), Sage Publications, (1926), 341–343. |
[3] | V. Volterra, Fluctuations in the abundance of a species considered mathematically, Nature, 119 (1926). https://doi.org/10.1038/119012a0 doi: 10.1038/119012a0 |
[4] | G. F. Gause, N. P. Smaragdova, A. A. Witt, Further studies of interaction between predator and prey, J. Anim. Ecol., 5 (1936), 1–18. |
[5] | J. M. Smith, Models in Ecology, Cambridge University Press, Cambridge, 1974. |
[6] | M. Sivakumar, M. Sambath, K. Balachandran, Stability and hopf bifurcation analysis of a diffusive predator–prey model with Smith growth, Int. J. Biomath., 8 (2015), 1550013. https://doi.org/10.1142/S1793524515500138 doi: 10.1142/S1793524515500138 |
[7] | X. L. Han, C. Y. Lei, Bifurcation and turing instability analysis for a space- and time-discrete predator-prey system with Smith growth function, Chaos Solitons Fractals, 166 (2022), 112910. https://doi.org/10.1016/j.chaos.2022.112910 doi: 10.1016/j.chaos.2022.112910 |
[8] | X. Feng, X. Liu, C. Sun, Stability and Hopf bifurcation of a modified Leslie-Gower predator-prey model with Smith growth rate and B-D functional response, Chaos Solitons Fractals, 174 (2023), 113794. https://doi.org/10.1016/j.chaos.2023.113794 doi: 10.1016/j.chaos.2023.113794 |
[9] | V. S. Ivlev, Experimental Ecology of the Feeding of Fishes, Yale University Press, New Haven, 1961. |
[10] | C. S. Holling, The functional response of predators to prey density and its role in mimicry and population regulation, Mem. Entomol. Soc. Can. Suppl., 97 (2012), 5–60. https://doi.org/10.4039/entm9745fv doi: 10.4039/entm9745fv |
[11] | T. Kuang, E. Beretta, Global qualitative analysis of a ratio-dependent predator-prey system, J. Math. Biol., 36 (1998), 389–406. https://doi.org/10.1007/s002850050105 doi: 10.1007/s002850050105 |
[12] | R. S. Cantrell, C. Cosner, On the dynamics of predator–prey models with the Beddington-DeAngelis functional response, J. Math. Anal. Appl., 257 (2001), 206–222. https://doi.org/10.1006/jmaa.2000.7343 doi: 10.1006/jmaa.2000.7343 |
[13] | M. P. Hassell, H. N. Comins, Sigmoid functional responses and population stability, Theor. Popul. Biol., 46 (1978), 62–67. https://doi.org/10.1016/0040-5809(78)90004-7 doi: 10.1016/0040-5809(78)90004-7 |
[14] | F. Yu, Y. S. Wang, Hopf bifurcation and Bautin bifurcation in a prey-predator model with prey's fear cost and variable predator search speed, Math. Comput. Simulat., 196 (2022), 192–209. https://doi.org/10.1016/j.matcom.2022.01.026 doi: 10.1016/j.matcom.2022.01.026 |
[15] | Y. S. Kwon, M. J. Bae, S. J. Hwang, S. H. Kim, Y. S. Park, Predicting potential impacts of climate change on freshwater fish in Korea, Ecol. Inf., 29 (2015), 156–165. https://doi.org/10.1016/j.ecoinf.2014.10.002 doi: 10.1016/j.ecoinf.2014.10.002 |
[16] | N. W. Pankhurst, P. L. Munday, Effects of climate change on fish reproduction and early life history stages, Mar. Freshwater Res., 9 (2011), 1015–1026. https://doi.org/10.1071/MF10269 doi: 10.1071/MF10269 |
[17] | T. M. Van Zuiden, M. M. Chen, S. Stefanoff, L. Lopez, S. Sharma, Projected impacts of climate change on three freshwater fishes and potential novel competitive interactions, Divers. Distrib., 22 (2016), 603–614. https://doi.org/10.1111/ddi.12422 doi: 10.1111/ddi.12422 |
[18] | M. Liu, K. Wang, Global stability of a nonlinear stochastic predator-prey system with Beddington-DeAngelis functional response, Commun. Nonlinear Sci., 16 (2011), 1114–1121. https://doi.org/10.1016/j.cnsns.2010.06.015 doi: 10.1016/j.cnsns.2010.06.015 |
[19] | J. Lv, K. Wang, Asymptotic properties of a stochastic predator–prey system with Holling Ⅱ functional response, Commun. Nonlinear Sci., 16 (2011), 4037–4048. https://doi.org/10.1016/j.cnsns.2011.01.015 doi: 10.1016/j.cnsns.2011.01.015 |
[20] | S. Zhang, S. Yuan, T. Zhang, Dynamic analysis of a stochastic eco-epidemiological model with disease in predators, Stud. Appl. Math., 149 (2022), 5–42. https://doi.org/10.1111/sapm.12489 doi: 10.1111/sapm.12489 |
[21] | J. Xu, Z. Yu, T. Zhang, S. Yuan, Near-optimal control of a stochastic model for mountain pine beetles with pesticide application, Stud. Appl. Math., 149 (2022), 678–704. https://doi.org/10.1111/sapm.12517 doi: 10.1111/sapm.12517 |
[22] | D. Pal, G. S. Mahapatra, G. P. Samanta, Optimal harvesting of prey–predator system with interval biological parameters: A bioeconomic model, Math. Biosci., 241 (2013), 181–187. https://doi.org/10.1016/j.mbs.2012.11.007 doi: 10.1016/j.mbs.2012.11.007 |
[23] | D. Pal, G. S. Mahapatra, G. P. Samanta, Stability and bionomic analysis of fuzzy parameter based prey–predator harvesting model using UFM, Nonlinear Dyn., 79 (2015), 1939–1955. https://doi.org/10.1007/s11071-014-1784-4 doi: 10.1007/s11071-014-1784-4 |
[24] | D. Pal, G. S. Mahapatra, G. P. Samanta, New approach for stability and bifurcation analysis on predator-prey harvesting model for interval biological parameters with time delays, Comp. Appl. Math., 37 (2018), 3145–3171. https://doi.org/10.1007/s40314-017-0504-3 doi: 10.1007/s40314-017-0504-3 |
[25] | X. W. Yu, S. L. Yuan, T. H. Zhang, About the optimal harvesting of a fuzzy predator-prey system: a bioeconomic model incorporating prey refuge and predator mutual interference, Nonlinear Dyn., 94 (2018), 2143–2160. https://doi.org/10.1007/s11071-018-4480-y doi: 10.1007/s11071-018-4480-y |
[26] | S. Das, P. Mahato, S. K. Mahato, A Prey Predator Model in Case of Disease Transmission via Pest in Uncertain Environment, Differ. Equation Dyn. Syst., 31 (2023), 457–483. https://doi.org/10.1007/s12591-020-00551-7 doi: 10.1007/s12591-020-00551-7 |
[27] | Q. Z. Xiao, B. X. Dai, L. Wang, Analysis of a competition fishery model with interval-valued parameters: extinction, coexistence, bionomic equilibria and optimal harvesting policy, Nonlinear Dyn., 80 (2015), 1631–1642. https://doi.org/10.1007/s11071-015-1967-7 doi: 10.1007/s11071-015-1967-7 |
[28] | Y. Tian, C. X. Li, J. Liu, Complex dynamics and optimal harvesting strategy of competitive harvesting models with interval-valued imprecise parameters, Chaos Solitons Fractals, 167 (2023), 113084. https://doi.org/10.1016/j.chaos.2022.113084 doi: 10.1016/j.chaos.2022.113084 |
[29] | Y. Tian, H. Guo, K. Sun, Complex dynamics of two prey-predator harvesting models with prey refuge and interval-valued imprecise parameters, Math. Meth. Appl. Sci., 46 (2023), 14278–14298. https://doi.org/10.1002/mma.9319 doi: 10.1002/mma.9319 |
[30] | H. Guo, Y. Tian, K. B. Sun, X. Y. Song, Study on dynamic behavior of two fishery harvesting models: effects of variable prey refuge and imprecise biological parameters, J. Appl. Math. Comput. https://doi.org/10.1007/s12190-023-01925-0 |
[31] | X. Yu, S. Yuan, T. Zhang, About the optimal harvesting of a fuzzy predatorprey system: A bioeconomic model incorporating prey refuge and predator mutual interference, Nonlinear Dyn., 94 (2018), 2143–2160. https://doi.org/10.1007/s11071-018-4480-y doi: 10.1007/s11071-018-4480-y |
[32] | J. Xu, S. Yuan, T. Zhang, Optimal harvesting of a fuzzy water hyacinth-fish model with Kuznets curve effect, Int. J. Biomath., 16 (2023), 2250082. https://doi.org/10.1142/S1793524522500826 doi: 10.1142/S1793524522500826 |
[33] | R. P. Gupta, M. Banerjee, P. Chandra, Bifurcation analysis and control of Leslie-Gower predator-prey model with Michaelis-Menten type prey-harvesting, Differ. Equation Dyn. Syst., 20 (2012), 339–366. https://doi.org/10.1007/s12591-012-0142-6 doi: 10.1007/s12591-012-0142-6 |
[34] | Y. F. Lv, R. Yuan, Y. Z. Pei, A prey-predator model with harvesting for fishery resource with reserve area, Appl. Math. Model., 37 (2013), 3048–3062. https://doi.org/10.1016/j.apm.2012.07.030 doi: 10.1016/j.apm.2012.07.030 |
[35] | D. P. Hu, H. J. Cao, Stability and bifurcation analysis in a predator-prey system with Michaelis-Menten type predator harvesting, Nonlinear Anal.-Real., 33 (2017), 58–82. https://doi.org/10.1016/j.nonrwa.2016.05.010 doi: 10.1016/j.nonrwa.2016.05.010 |
[36] | T. K. Ang, H. M. Safuan, Dynamical behaviors and optimal harvesting of an intraguild prey-predator fishery model with Michaelis-Menten type predator harvesting, Biosystems, 202 (2021), 104357. https://doi.org/10.1016/j.biosystems.2021.104357 doi: 10.1016/j.biosystems.2021.104357 |
[37] | X. Y. Meng, J. Li, Dynamical behavior of a delayed prey-predator-scavenger system with fear effect and linear harvesting, Int. J. Biomath., 14 (2021), 2150024. https://doi.org/10.1142/S1793524521500248 doi: 10.1142/S1793524521500248 |
[38] | S. Debnath, P. Majumdar, S. Sarkar, U. Ghosh, Global dynamics of a prey-predator model with holling type Ⅲ functional response in the presence of harvesting, J. Biol. Syst., 30 (2022), 225–260. https://doi.org/10.1142/S0218339022500073 doi: 10.1142/S0218339022500073 |
[39] | L. F. Nie, Z. D. Teng, H. Lin, J. G. Peng, The dynamics of a Lotka-Volterra predator-prey model with state dependent impulsive harvest for predator, Biosystems, 98 (2009), 67–72. https://doi.org/10.1016/j.biosystems.2009.06.001 doi: 10.1016/j.biosystems.2009.06.001 |
[40] | H. J. Guo, L. S. Chen, X. Y. Song, Qualitative analysis of impulsive state feedback control to an algae-fish system with bistable property, Appl. Math. Comput., 271 (2015), 905–922. https://doi.org/10.1016/j.amc.2015.09.046 doi: 10.1016/j.amc.2015.09.046 |
[41] | Y. Tian, H. M. Li, The study of a predator-prey model with fear effect based on state-dependent harvesting strategy, Complexity, 2022 (2022), 9496599. http://dx.doi.org/10.1155/2022/9496599 doi: 10.1155/2022/9496599 |
[42] | Y. Tian, Y. Gao, K. B. Sun, Global dynamics analysis of instantaneous harvest fishery model guided by weighted escapement strategy, Chaos Soliton Fractals, 164 (2022), 112597. https://doi.org/10.1016/j.chaos.2022.112597 doi: 10.1016/j.chaos.2022.112597 |
[43] | Y. Tian, Y. Gao, K. B. Sun, A fishery predator-prey model with anti-predator behavior and complex dynamics induced by weighted fishing strategies, Math. Biosci. Eng., 20 (2022), 1558–1579. http://dx.doi.org/10.3934/mbe.2023071 doi: 10.3934/mbe.2023071 |
[44] | Y. Tian, Y. Gao, K. B. Sun, Qualitative analysis of exponential power rate fishery model and complex dynamics guided by a discontinuous weighted fishing strategy, Commun. Nonlinear Sci., 118 (2023), 107011. https://doi.org/10.1016/j.cnsns.2022.107011 doi: 10.1016/j.cnsns.2022.107011 |
[45] | H. Li, Y. Tian, Dynamic behavior analysis of a feedback control predator-prey model with exponential fear effect and Hassell-Varley functional response, J. Franklin I., 360 (2023), 3479–3498. https://doi.org/10.1016/j.jfranklin.2022.11.030 doi: 10.1016/j.jfranklin.2022.11.030 |
[46] | X. N. Liu, L. S. Chen, Complex dynamics of Holling type Ⅱ Lotka-Volterra predator-prey system with impulsive perturbations on the predator, Chaos Soliton Fractals, 16 (2004), 311–320. https://doi.org/10.1016/S0960-0779(02)00408-3 doi: 10.1016/S0960-0779(02)00408-3 |
[47] | B. Liu, Y. J. Zhang, L. S. Chen, Dynamic complexities of a Holling Ⅰ predator-prey model concerning periodic biological and chemical control, Chaos Soliton Fractals, 22 (2004), 123–134. https://doi.org/10.1016/j.chaos.2003.12.060 doi: 10.1016/j.chaos.2003.12.060 |
[48] | X. Y. Song, Y. F. Li, Dynamic complexities of a Holling Ⅱ two-prey one-predator system with impulsive effect, Chaos Soliton Fractals, 33 (2007), 463–478. https://doi.org/10.1016/j.chaos.2006.01.019 doi: 10.1016/j.chaos.2006.01.019 |
[49] | G. R. Jiang, Q. S. Lu, L. N. Qian, Complex dynamics of a Holling type Ⅱ prey-predator system with state feedback control, Chaos Soliton Fractals, 31 (2007), 448–461. https://doi.org/10.1016/j.chaos.2005.09.077 doi: 10.1016/j.chaos.2005.09.077 |
[50] | Y. Tian, K. B. Sun, L. S. Chen, Geometric approach to the stability analysis of the periodic solution in a semi-continuous dynamic system, Int. J. Biomath., 7 (2014), 1450018. https://doi.org/10.1142/S1793524514500181 doi: 10.1142/S1793524514500181 |
[51] | S. Y. Tang, W. H. Pang, R. A. Cheke, J. Wu, Global dynamics of a state-dependent feedback control system, Adv. Differ. Equation, 2015 (2015), 322. https://doi.org/10.1186/s13662-015-0661-x doi: 10.1186/s13662-015-0661-x |
[52] | S. Y. Tang, B. Tang, A. L. Wang, Y. N. Xiao, Holling Ⅱ predator-prey impulsive semi-dynamic model with complex Poincaré map, Nonlinear Dyn., 81 (2015), 1575–1596. https://doi.org/10.1007/s11071-015-2092-3 doi: 10.1007/s11071-015-2092-3 |
[53] | T. Q. Zhang, W. B. Ma, X. Z. Meng, T. H. Zhang, Periodic solution of a prey-predator model with nonlinear state feedback control, Appl. Math. Comput., 266 (2015), 95–107. https://doi.org/10.1016/j.amc.2015.05.016 doi: 10.1016/j.amc.2015.05.016 |
[54] | J. Yang, S. Y. 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 |
[55] | S. Tang, C. Li, B. Tang, X. Wang, Global dynamics of a nonlinear state-dependent feedback control ecological model with a multiple-hump discrete map, Commun. Nonlinear Sci., 79 (2019), 104900. https://doi.org/10.1016/j.cnsns.2019.104900 doi: 10.1016/j.cnsns.2019.104900 |
[56] | Q. Zhang, B. Tang, T. Cheng, S. Tang, Bifurcation analysis of a generalized impulsive Kolmogorov model with applications to pest and disease control, SIAM J. Appl. Math., 80 (2020), 1796–1819. https://doi.org/10.1137/19M1279320 doi: 10.1137/19M1279320 |
[57] | Q. Zhang, S. Tang, X. Zou, Rich dynamics of a predator-prey system with state-dependent impulsive controls switching between two means, J. Differ. Equations, 364 (2023), 336–377. https://doi.org/10.1016/j.jde.2023.03.030 doi: 10.1016/j.jde.2023.03.030 |
[58] | W. Li, J. Ji, L. Huang, Global dynamic behavior of a predator-prey model under ratio-dependent state impulsive control, Appl. Math. Model., 77 (2020), 1842–1859. https://doi.org/10.1016/j.apm.2019.09.033 doi: 10.1016/j.apm.2019.09.033 |
[59] | Q. Zhang, S. Tang, Bifurcation analysis of an ecological model with nonlinear state-dependent feedback control by Poincaré map defined in phase set, Commun. Nonlinear Sci., 108 (2022), 106212. https://doi.org/10.1016/j.cnsns.2021.106212 doi: 10.1016/j.cnsns.2021.106212 |
[60] | L. S. Pontryagin, The Mathematical Theory of Optimal Processes, CRC press, London, 1987. https://doi.org/10.1201/9780203749319 |