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Mathematical analysis on deterministic and stochastic lake ecosystem models

  • Received: 27 January 2019 Accepted: 09 May 2019 Published: 27 May 2019
  • In this paper, we propose and study the deterministic and stochastic lake ecosystem models to investigate the impact of terrestrial organic matter upon persistence of the plankton populations. By constructing Lyapunov function and using the LaSalle's Invariance Principle, we establish global properties of the deterministic model. The dynamical behavior of solutions fits well with some experimental results. It is concluded that the terrestrial organic matter plays an important role in influencing interactions between phytoplankton and zooplankton. Based on the fluctuations of lake ecosystem, we further develop a stochastically perturbed model. Theoretic analysis implies that the stochastic model exists a stationary distribution which is ergodic. The key point of our analysis is to enhance our knowledge of the factors governing the dynamics of plankton population models.

    Citation: Zhiwei Huang, Gang Huang. Mathematical analysis on deterministic and stochastic lake ecosystem models[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 4723-4740. doi: 10.3934/mbe.2019237

    Related Papers:

  • In this paper, we propose and study the deterministic and stochastic lake ecosystem models to investigate the impact of terrestrial organic matter upon persistence of the plankton populations. By constructing Lyapunov function and using the LaSalle's Invariance Principle, we establish global properties of the deterministic model. The dynamical behavior of solutions fits well with some experimental results. It is concluded that the terrestrial organic matter plays an important role in influencing interactions between phytoplankton and zooplankton. Based on the fluctuations of lake ecosystem, we further develop a stochastically perturbed model. Theoretic analysis implies that the stochastic model exists a stationary distribution which is ergodic. The key point of our analysis is to enhance our knowledge of the factors governing the dynamics of plankton population models.


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    [1] M. Rautio, H. Mariash and L. Forsstrom, Seasonal shifts between autochthonous and allochthon-ous carbon contributions to zooplankton diets in a subarctic lake, Limnol. Oceanogr., 56 (2011), 1513–1524.
    [2] S. E. Jones, C. T. Solomon and B. C. Weidel, Subsidy or subtraction: how do terrestrial inputs influence consumer production in lakes, Freshwater Rev., 5 (2012), 37–49.
    [3] K. A. Emery, G. M. Wilkinson, M. L. Pace, et al., Use of allochthonous resources by zooplankton in reservoirs, Hydrobiologia, 758 (2015), 257–269.
    [4] J. Cole, S. R. Carpenter, J. F. Kitchell, et al., Differential support of lake food webs by three types of terrestrial organic carbon, Ecol. Lett., 9 (2006), 558–568.
    [5] M. Berggren, S. E. Ziegler, N. F. Gelais, et al., Contrasting patterns of allochthony among three major groups of crustacean zooplankton in boreal and temperate lakes, Ecology, 95 (2014), 1947–1959.
    [6] M. T. Brett, M. Kainz, S. J. Taipale, et al., Phytoplankton, not allochthonous carbon, sustains herbivorous zooplankton production, Proc. Natl. Acad. Sci. USA, 21 (2009), 197–201.
    [7] M. Berggren, A. Bergstrom and J. Karlsson, Intraspecific autochthonous and allochthonous resource use by zooplankton in a humic lake during the transitions between winter, summer and fall, Plos One, 10 (2014), e0120575.
    [8] A. D. Persaud and P. J. Dillon, Differences in zooplankton feeding rates and isotopic signatures from three temperate lakes, Aquat. SCI., 73 (2011), 261–273.
    [9] N. D. Lewis, M. N. Breckels, M. Steinke, et al., Role of infochemical mediated zooplankton grazing in a phytoplankton competition model, Ecol. Complex., 16 (2013), 41–50.
    [10] Y. Lv and Y. Pei, Harvesting of a phytoplankton-zooplankton model, Nonlinear Anal. Real. World. Appl., 11 (2010), 3608–3619.
    [11] A. Sharma, A. K. Sharma and K. Agnihotri, Analysis of a toxin producing phytoplankton zooplankton interaction with Holling IV type scheme and time delay, Nonlinear Dynam., 81 (2015), 13–25.
    [12] J. E. Truscott and J. Brindley, Ocean plankton population as excitable media, B. Math. Biol., 56 (1994), 981–998.
    [13] Y. Pei, Y. Lv and C. Li, Evolutionary consequences of harvesting for a two-zooplankton one-phytoplankton system, Appl. Math. Model, 36 (2012), 1752–1765.
    [14] L. Qian, Q. Lu, Q. Meng et al., Dynamical behaviors of a prey-predator system with impulsive control, J. Math. Anal. Appl., 1 (2010), 345–356.
    [15] S. R. Jang and E. J. Allen, Deterministic and stochastic nutrient phytoplankton zooplankton models with periodic toxin producing phytoplankton, Appl. Math. Comput., 271 (2015), 52–67.
    [16] S. Ruan, Persistence and coexistence in zooplankton-phytoplankton nutrient models with instantaneous nutrient recycling, J. Math. Biol., 31 (1993), 633–654.
    [17] J. S. Wroblewski, S. L. Sarmiento and G. R. Flierl, An ocean basin scale model of plankton dynamics in the North Atlantic, solutions for the climatological oceanographic condition in May, Global Biogeochem. CY., 2 (1988), 199–218.
    [18] A. J. Tanentzap, B. W. Kielstra, G. M. Wilkinson, et al., Terrestrial support of lake food webs: synthesis reveals controls over cross-ecosystem resource use, Sci. Adv., 3 (2017), e1601765.
    [19] B. C. Mcmeans, A. Koussoroplis, M. T. Arts, et al., Terrestrial dissolved organic matter supports growth and reproduction of Daphnia magna when algae are limiting, J. Plankton. Res., 0 (2015), 1–9.
    [20] U. Forys, M. Qiao and A. Liu, Asymptotic dynamics of a deterministic and stochastic predator- prey model with disease in the prey species, Math. Method. Appl. Sci., 37 (2014), 306–320.
    [21] G. Ge, H. Wang and J. Xu, A stochastic analysis for a phytoplankton zooplankton model, JPCS, 96 (2008), 012168.
    [22] P. Ghosh, P. Das and D. Mukherjee, Persistence and stability of a seasonally perturbed three species stochastic model of salmonoid aquaculture, Differ. Equ. Dyn. Syst., 2016. Available from: https://doi.org/10.1007/s12591-016-0283-0.
    [23] C. Ji, D. Jiang and N. Shi, A note on a predator-prey model with modified Leslie-Gower and Holling-type II schemes with stochastic perturbation, J. Math. Anal. Appl., 377 (2011), 435–440.
    [24] J. Djordjevic, C. J. Silva and D. F. Torres, A stochastic SICA epidemic model for HIV transmission, Appl. Math. Lett., 84 (2018), 168–175.
    [25] R. Rajaji and M. Pitchaimani, Analysis of stochastic viral infection model with immune impairment, Int. J. Ap. Mat. Com-Pol., 3 (2017), 3561–3574.
    [26] F. C. Klebaner, Introduction to Stochastic Calculus with Applications, 2nd edition, World Scientific Publishing, London, 2005.
    [27] X. Mao, Stochastic Diferential Equations and Applications, 1nd edition, Horwood Publishing, Chichester, UK, 2008.
    [28] N. D. Lewis, M. N. Breckels, S. D. Archer, et al., Grazing-induced production of DMS can stabilize food-web dynamics and promote the formation of phytoplankton blooms in a multitrophic plankton model, Biogeochem., 110 (2012), 303–313.
    [29] D. J. Higham, An algorithmic introduction to numerical simulation of stochastic differential equations, SIAM Rev., 43 (2001), 525–546.
    [30] N. Dalal, D. Greenhalgh and X. Mao, A stochastic model for internal HIV dynamics, J. Math. Anal. Appl., 341 (2008), 1084–1101.
    [31] L. Shaikheta and A. Korobeinikov, Stability of a stochastic model for HIV-1 dynamics within a host, Appl. Anal., 6 (2016), 1228–1238.
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