Dynamics of a predator-prey system with prey subject to Allee effects and disease

  • Received: 01 March 2013 Accepted: 29 June 2018 Published: 01 March 2014
  • MSC : Primary: 35B32, 37C75; Secondary: 92B05, 92D30, 92D40.

  • In this article, we propose a general predator-prey system where prey is subject to Allee effects and disease with the following unique features: (i) Allee effects built in the reproduction process of prey where infected prey (I-class) has no contribution; (ii) Consuming infected prey would contribute less or negatively to the growth rate of predator (P-class) in comparison to the consumption of susceptible prey (S-class). We provide basic dynamical properties for this general model and perform the detailed analysis on a concrete model (SIP-Allee Model) as well as its corresponding model in the absence of Allee effects (SIP-no-Allee Model); we obtain the complete dynamics of both models: (a) SIP-Allee Model may have only one attractor (extinction of all species), two attractors (bi-stability either induced by small values of reproduction number of both disease and predator or induced by competition exclusion), or three attractors (tri-stability); (b) SIP-no-Allee Model may have either one attractor (only S-class survives or the persistence of S and I-class or the persistence of S and P-class) or two attractors (bi-stability with the persistence of S and I-class or the persistence of S and P-class). One of the most interesting findings is that neither models can support the coexistence of all three S, I, P-class. This is caused by the assumption (ii), whose biological implications are that I and P-class are at exploitative competition for S-class whereas I-class cannot be superior and P-class cannot gain significantly from its consumption of I-class. In addition, the comparison study between the dynamics of SIP-Allee Model and SIP-no-Allee Model lead to the following conclusions: 1) In the presence of Allee effects, species are prone to extinction and initial condition plays an important role on the surviving of prey as well as its corresponding predator; 2) In the presence of Allee effects, disease may be able to save prey from the predation-driven extinction and leads to the coexistence of S and I-class while predator can not save the disease-driven extinction. All these findings may have potential applications in conservation biology.

    Citation: Yun Kang, Sourav Kumar Sasmal, Amiya Ranjan Bhowmick, Joydev Chattopadhyay. Dynamics of a predator-prey system with prey subject to Allee effects and disease[J]. Mathematical Biosciences and Engineering, 2014, 11(4): 877-918. doi: 10.3934/mbe.2014.11.877

    Related Papers:

  • In this article, we propose a general predator-prey system where prey is subject to Allee effects and disease with the following unique features: (i) Allee effects built in the reproduction process of prey where infected prey (I-class) has no contribution; (ii) Consuming infected prey would contribute less or negatively to the growth rate of predator (P-class) in comparison to the consumption of susceptible prey (S-class). We provide basic dynamical properties for this general model and perform the detailed analysis on a concrete model (SIP-Allee Model) as well as its corresponding model in the absence of Allee effects (SIP-no-Allee Model); we obtain the complete dynamics of both models: (a) SIP-Allee Model may have only one attractor (extinction of all species), two attractors (bi-stability either induced by small values of reproduction number of both disease and predator or induced by competition exclusion), or three attractors (tri-stability); (b) SIP-no-Allee Model may have either one attractor (only S-class survives or the persistence of S and I-class or the persistence of S and P-class) or two attractors (bi-stability with the persistence of S and I-class or the persistence of S and P-class). One of the most interesting findings is that neither models can support the coexistence of all three S, I, P-class. This is caused by the assumption (ii), whose biological implications are that I and P-class are at exploitative competition for S-class whereas I-class cannot be superior and P-class cannot gain significantly from its consumption of I-class. In addition, the comparison study between the dynamics of SIP-Allee Model and SIP-no-Allee Model lead to the following conclusions: 1) In the presence of Allee effects, species are prone to extinction and initial condition plays an important role on the surviving of prey as well as its corresponding predator; 2) In the presence of Allee effects, disease may be able to save prey from the predation-driven extinction and leads to the coexistence of S and I-class while predator can not save the disease-driven extinction. All these findings may have potential applications in conservation biology.


    加载中
    [1] University of Chicago Press, Chicago, 1931.
    [2] Mathematical Biosciences, 152 (1998), 63-85.
    [3] Theoretical Population Biology, 53 (1998), 44-59.
    [4] Conservation Biology, 21 (2007), 1082-1091.
    [5] Journal of Theoretical Biology, 248 (2007), 10-25.
    [6] Epidemiology and Infection, 129 (2002), 147-153.
    [7] Journal of Mathematical Biology, 32 (1994), 857-863.
    [8] Mathematical Biosciences, 149 (1998), 57-76.
    [9] SIAM Journal on Applied Mathematics, 70 (2010), 1821-1839.
    [10] Massachusetts, Boston, 1982.
    [11] Journal of Theoretical Biology, 218 (2002), 375-394.
    [12] Proceedings of the Royal Society B: Biological Sciences, 262 (1995), 235-245.
    [13] Nonlinear Analysis, 36 (1999), 747-766.
    [14] Ecological Modelling, 151 (2002), 15-28.
    [15] Journal of Theoretical Biology, 212 (2001), 295-302.
    [16] Ecological Modelling, 167 (2003), 199-211.
    [17] Biological Conservation, 131 (2006), 230-243.
    [18] Oxford University Press, Oxford, 2008.
    [19] Trends in Ecology & Evolution, 14 (1999), 405-410.
    [20] Animal Conservation, 3 (2000), 277-285.
    [21] Oikos, 91 (2000), 311-322.
    [22] Journal of Biological Dynamics, 6 (2012), 941-958.
    [23] Oikos, 112 (2006), 667-679.
    [24] Risk Analysis, 24 (2004), 795-802.
    [25] Oikos, 87 (1999), 549-560.
    [26] Mathematical Biosciences, 99 (1990), 143-155.
    [27] Journal of Biological Dynamics, 6 (2012), 495-508.
    [28] Journal of Applied Ecology, 41 (2004), 801-810.
    [29] The American Naturalist, 151 (1998), 487-496.
    [30] Journal of Theoretical Biology, 185 (1997), 539-547.
    [31] Springer-Verlag, 1983.
    [32] Cambridge University Press, Cambridge, 1995.
    [33] Journal of Mathematical Biology, 27 (1989), 609-631.
    [34] SIAM Review, 42 (2000), 499-653.
    [35] Theoretical Population Biology, 66 (2004), 259-268.
    [36] Journal of Biological Dynamics, 4 (2010), 86-101.
    [37] The American Naturalist, 173 (2009), 72-88.
    [38] Mathematical Biosciences, 206 (2007), 61-80.
    [39] Journal of Theoretical Biology, 255 (2008), 299-306.
    [40] Canadian Entomologist, 91 (1959), 385-398.
    [41] Mathematical Biosciences, 111 (1992), 1-71.
    [42] Oecologia, 64 (1984), 389-395.
    [43] Journal of Difference Equations and Applications, 17 (2011), 525-539.
    [44] Journal of Difference Equations and Applications, 12 (2006), 165-181.
    [45] Submitted to the Journal of Theoretical Population Biology, 2013. (Under revision).
    [46] Mathematical Biosciences, 241 (2013), 75-87.
    [47] preprint.
    [48] Journal of Biological Dynamics, 6 (2012), 50-79.
    [49] Journal of Discrete and Continuous Dynamical Systems-B, 2013, (Accepted).
    [50] Journal of Mathematical Biology, 62 (2011), 925-973.
    [51] Journal of Mathematical Biology, 67 (2013), 1227-1259.
    [52] Nonlinear Analysis: Real World Applications, 12 (2011), 3329-3345.
    [53] Oikos, 82 (1998), 384-392.
    [54] Oecologia, 94 (1993), 446-450.
    [55] Theoretical Population Biology, 43 (1993), 141-158.
    [56] Trends in Ecology & Evolution, 16 (2001), 295-300.
    [57] Ecology, 35 (1954), 95-97.
    [58] Mathematical Biosciences, 165 (2000), 63-78.
    [59] Proceedings of the Royal Society - Biological Sciences, 279 (2012), 3139-3145.
    [60] Williams and Wilkins Co., Inc., New York, 4th ed., 2000.
    [61] Oikos, 77 (1996), 217-226.
    [62] Theoretical Population Biology, 64 (2003), 201-209.
    [63] Journal of Mathematical Biology, 52 (2006), 807-829.
    [64] Journal of Mathematical Biology, 64 (2012), 341-360.
    [65] Journal of Theoretical Biology, 231 (2004), 153-166.
    [66] Trends in Ecology & Evolution, 14 (1999), 401-405.
    [67] Oikos, 87 (1999), 185-190.
    [68] Marine Ecology Progress Series, 202 (2000), 297-302.
    [69] in 3rd International Conference on Biomedical Engineering and Informatics (BMET 2010), 6 (2010), 2390-2393.
    [70] Bulletin of Mathematical Biology, 70 (2008), 2195-2210.
    [71] Ecology Letters, 8 (2005), 895-908.
    [72] Journal of Mathematical Biology, 30 (1992), 755-763.
    [73] Journal of Biological Dynamics, 3 (2009), 305-323.
    [74] In Arino, O., Axelrod, D., Kimmel, M., Langlais, M. (Eds.), Mathematical Population Dynamics: Analysis of Heterogeneity, 1 (1995), 381-393.
    [75] IMA Journal of Mathematics Applied in Medicine and Biology, 19 (2002), 185-205.
    [76] Mathematical Biosciences, 209 (2007), 451-469.
    [77] Journal of Mathematical Biology, 62 (2011), 291-331.
    [78] Journal of Mathematical Biology, 44 (2002), 150-168.
    [79] Texts in Applied Mathematics, 2, Springer, New York, 1990.
    [80] Mathematical Biosciences, 171 (2001), 59-82.
    [81] Journal of Difference Equations and Applications, 13 (2007), 341-356.
    [82] Theoretical Population Biology, 65 (2004), 29-37.
  • Reader Comments
  • © 2014 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3595) PDF downloads(765) Cited by(47)

Article outline

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog