American Institute of Mathematical Sciences

doi: 10.3934/dcdsb.2021208
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An analysis approach to permanence of a delay differential equations model of microorganism flocculation

 1 School of Science, Beijing University of Civil Engineering and Architecture, Beijing 102616, China 2 Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China 3 School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China

* Corresponding author

Received  February 2021 Revised  July 2021 Early access August 2021

Fund Project: This work is supported in part by the National Natural Science Foundation of China (Nos. 11901027, 11871093 and 11971055), the Scientific Research Project of Beijing Municipal Education Commission (No. KM201910016001), the Pyramid Talent Training Project of BUCEA (JDYC20200327) and the Bill & Melinda Gates Foundation (INV-005834)

In this paper, we develop a delay differential equations model of microorganism flocculation with general monotonic functional responses, and then study the permanence of this model, which can ensure the sustainability of the collection of microorganisms. For a general differential system, the existence of a positive equilibrium can be obtained with the help of the persistence theory, whereas we give the existence conditions of a positive equilibrium by using the implicit function theorem. Then to obtain an explicit formula for the ultimate lower bound of microorganism concentration, we propose a general analysis method, which is different from the traditional approaches in persistence theory and also extends the analysis techniques of existing related works.

Citation: Songbai Guo, Jing-An Cui, Wanbiao Ma. An analysis approach to permanence of a delay differential equations model of microorganism flocculation. Discrete & Continuous Dynamical Systems - B, doi: 10.3934/dcdsb.2021208
References:
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Smith, Competition between plasmid-bearing and plasmid-free microorganisms in a chemostat with distinct removal rates, Canad. Appl. Math. Quart., 7 (1999), 251-281.   Google Scholar [27] Z. Li and R. Xu, Stability analysis of a ratio-dependent chemostat model with time delay and variable yield, Int. J. Biomath., 3 (2010), 243-253.  doi: 10.1142/S1793524510000921.  Google Scholar [28] C. Liu, Modelling and parameter identification for a nonlinear time-delay system in microbial batch fermentation, Appl. Math. Model., 37 (2013), 6899-6908.  doi: 10.1016/j.apm.2013.02.021.  Google Scholar [29] A. J. Lotka, Elements of Mathematical Biology, Dover Publications, New York, 1956. Google Scholar [30] H. L. Smith, Monotone Dynamical Systems: An Introduction to the Theory of Competitive and Cooperative Systems, Math. Surveys Monogr. 41, American Mathematical Society, Providence, RI, 1995.  Google Scholar [31] H. L. Smith and P. Waltman, Theory of the Chemostat: Dynamics of Microbial Competition, Cambridge University Press, Cambridge, 1995.  doi: 10.1017/CBO9780511530043.  Google Scholar [32] H. L. Smith and X.-Q. Zhao, Robust persistence for semidynamical systems, Nonlinear Anal., 47 (2001), 6169-6179.  doi: 10.1016/S0362-546X(01)00678-2.  Google Scholar [33] K. Song, W. Ma and S. Guo, et al., A class of dynamic model describing microbial flocculant with nutrient competition and metabolic products in wastewater treatment, Adv. Differ. Equ., 2018 (2018), Paper No. 33, 14 pp. doi: 10.1186/s13662-018-1473-6.  Google Scholar [34] H. R. Thieme, Mathematics in Population Biology, Princeton University Press, Princeton, 2003.   Google Scholar [35] H. R. Thieme, Persistence under relaxed point-dissipativity (with application to an endemic model), SIAM J. Math. Anal., 24 (1993), 407-435.  doi: 10.1137/0524026.  Google Scholar [36] P. van den Driessche and J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29-48.  doi: 10.1016/S0025-5564(02)00108-6.  Google Scholar [37] V. Volterra, Variazioni e fluttuazioni del numero d'individui in specie animali conviventi, Mem. R. Accad. Naz. dei Lincei, 2 (1926), 31-113.   Google Scholar [38] W. Wang, Global behavior of an SEIRS epidemic model with time delays, Appl. Math. Lett., 15 (2002), 423-428.  doi: 10.1016/S0893-9659(01)00153-7.  Google Scholar [39] W. Wang, W. Ma and H. Yan, Global dynamics of modeling flocculation of microorganism, Appl. Sci., 6 (2016), 221. doi: 10.3390/app6080221.  Google Scholar [40] G. S. K. Wolkowicz, H. Xia and S. Ruan, Competition in the chemostat: A distributed delay model and its global asymptotic behavior, SIAM J. Math. Anal., 57 (1997), 1281-1310.  doi: 10.1137/S0036139995289842.  Google Scholar [41] H. Xia, G. S. K. Wolkowicz and L. Wang, Transient oscillations induced by delayed growth response in the chemostat, J. Math. Biol., 50 (2005), 489-530.  doi: 10.1007/s00285-004-0311-5.  Google Scholar [42] T. Zhang, N. Gao and T. Wang, et al., Global dynamics of a model for treating microorganisms in sewage by periodically adding microbial flocculants, Math. Biosci. Eng., 17 (2020), 179-201. doi: 10.3934/mbe.2020010.  Google Scholar [43] T. Zhang, W. Ma and X. Meng, Global dynamics of a delayed chemostat model with harvest by impulsive flocculant input, Adv. Difference Equ., 2017 (2017), Paper No. 115, 17 pp. doi: 10.1186/s13662-017-1163-9.  Google Scholar [44] X.-Q. Zhao, Uniform persistence and periodic coexistence states in infinite-dimensional periodic semiflows with applications, Canad. Appl. Math. Quart., 3 (1995), 473-495.   Google Scholar [45] X.-Q. Zhao, Dynamical Systems in Population Biology, 2$^{nd}$ ed., Springer, Cham, 2017. doi: 10.1007/978-3-319-56433-3.  Google Scholar

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References:
 [1] R. Arditi and L. R. Ginzburg, Coupling in predator-prey dynamics: Ratio-dependence, J. Theor. Biol., 139 (1989), 311-326.  doi: 10.1016/S0022-5193(89)80211-5.  Google Scholar [2] J. R. Beddington, Mutual interference between parasites or predator and its effect on searching efficiency, J. Anim. Ecol., 44 (1975), 331-340.  doi: 10.2307/3866.  Google Scholar [3] A. W. Bush and A. E. Cook, The effect of time delay and growth rate inhibition in the bacterial treatment of wastewater, J. Theoret. Biol., 63 (1976), 385-395.  doi: 10.1016/0022-5193(76)90041-2.  Google Scholar [4] J. Caperon, Time lag in population growth response of isochrysis galbana to a variable nitrate environment, Ecology, 50 (1969), 188-192.  doi: 10.2307/1934845.  Google Scholar [5] T. Caraballo, X. Han and P. E. Kloeden, Nonautonomous chemostats with variable delays, SIAM J. Math. Anal., 47 (2015), 2178-2199.  doi: 10.1137/14099930X.  Google Scholar [6] T. Chatsungnoen and Y. Chisti, Harvesting microalgae by flocculation-sedimentation, Algal Res., 13 (2016), 271-283.  doi: 10.1016/j.algal.2015.12.009.  Google Scholar [7] P. H. Crowley and E. K. Martin, Functional responses and interference within and between year classes of a dragonfly population, J. N. Am. Benthol. Soc., 8 (1989), 211-221.  doi: 10.2307/1467324.  Google Scholar [8] D. L. DeAngelis, R. A. Goldstein and R. V. O'Neill, A model for trophic interaction, Ecology, 56 (1975), 881-892.   Google Scholar [9] D. M. Di Toro, D. J. O'Connor and R. V. Thomann, A dynamic model of the phytoplankton population in the Sacramento–San Joaquin Delta, in Nonequilibrium Systems in Natural Water Chemistry (ed. J. D. Hem), Adv. Chem. Series, No. 106, American Chemical Society, Washington, (1971), 131–180. Google Scholar [10] O. Diekmann, S. A. van Gils and S. M. Verduyn Lunel, et al., Delay Equations: Functional-, Complex-, and Nonlinear Analysis, Springer-Verlag, New York, 1995. doi: 10.1007/978-1-4612-4206-2.  Google Scholar [11] Q. Dong and W. Ma, Qualitative analysis of the chemostat model with variable yield and a time delay, J. Math. Chem., 51 (2013), 1274-1292.  doi: 10.1007/s10910-013-0144-9.  Google Scholar [12] S. F. Ellermeyer, Competition in the chemostat: Global asymptotic behavior of a model with delayed response in growth, SIAM J. Appl. Math., 54 (1994), 456-465.  doi: 10.1137/S003613999222522X.  Google Scholar [13] S. Guo and W. Ma, Global behavior of delay differential equations model of HIV infection with apoptosis, Discrete Contin. Dyn. Syst. Ser. B, 21 (2016), 103-119.  doi: 10.3934/dcdsb.2016.21.103.  Google Scholar [14] S. Guo and W. Ma, Global dynamics of a microorganism flocculation model with time delay, Commun. Pure Appl. Anal., 16 (2017), 1883-1891.  doi: 10.3934/cpaa.2017091.  Google Scholar [15] S. Guo, W. Ma and X.-Q. Zhao, Global dynamics of a time-delayed microorganism flocculation model with saturated functional responses, J. Dynam. Differential Equations, 30 (2018), 1247-1271.  doi: 10.1007/s10884-017-9605-3.  Google Scholar [16] J. K. Hale and S. M. Verduyn Lunel, Introduction to Functional Differential Equations, Springer-Verlag, New York, 1993. doi: 10.1007/978-1-4612-4342-7.  Google Scholar [17] M. P. Hassell and G. C. Varley, New inductive population model for insect parasites and its bearing on biological control, Nature, 223 (1969), 1133-1137.  doi: 10.1038/2231133a0.  Google Scholar [18] C. S. Holling, The components of predation as revealed by a study of small mammal predation of the European pine sawfly, Can. Entomol., 91 (1959), 293-320.  doi: 10.4039/Ent91293-5.  Google Scholar [19] C. S. Holling, The functional response of predators to prey density and its role in mimicry and population regulation, Mem. Entomol. Soc. Can., 97 (1965), 5-60.  doi: 10.4039/entm9745fv.  Google Scholar [20] S. B. Hsu, Limiting behavior for competing species, SIAM J. Appl. Math., 34 (1978), 760-763.  doi: 10.1137/0134064.  Google Scholar [21] V. S. Ivlev, Experimental Ecology of the Feeding of Fishes, Yale University Press, New Haven, 1961.   Google Scholar [22] R. E. Kooij and A. Zegeling, A predator-prey model with Ivlev's functional response, J. Math. Anal. Appl., 198 (1996), 473-489.  doi: 10.1006/jmaa.1996.0093.  Google Scholar [23] Y. Kuang, Limit cycles in a chemostat-related model, SIAM J. Appl. Math., 49 (1989), 1759-1767.  doi: 10.1137/0149107.  Google Scholar [24] Y. Kuang, Delay Differential Equations with Applications in Population Dynamics, Academic Press, Boston, 1993.   Google Scholar [25] B. Li and Y. Kuang, Simple food chain in a chemostat with distinct removal rates, J. Math. Anal. Appl., 242 (2000), 75-92.  doi: 10.1006/jmaa.1999.6655.  Google Scholar [26] B. Li, Y. Kuang and H. L. Smith, Competition between plasmid-bearing and plasmid-free microorganisms in a chemostat with distinct removal rates, Canad. Appl. Math. Quart., 7 (1999), 251-281.   Google Scholar [27] Z. Li and R. Xu, Stability analysis of a ratio-dependent chemostat model with time delay and variable yield, Int. J. Biomath., 3 (2010), 243-253.  doi: 10.1142/S1793524510000921.  Google Scholar [28] C. Liu, Modelling and parameter identification for a nonlinear time-delay system in microbial batch fermentation, Appl. Math. Model., 37 (2013), 6899-6908.  doi: 10.1016/j.apm.2013.02.021.  Google Scholar [29] A. J. Lotka, Elements of Mathematical Biology, Dover Publications, New York, 1956. Google Scholar [30] H. L. Smith, Monotone Dynamical Systems: An Introduction to the Theory of Competitive and Cooperative Systems, Math. Surveys Monogr. 41, American Mathematical Society, Providence, RI, 1995.  Google Scholar [31] H. L. Smith and P. Waltman, Theory of the Chemostat: Dynamics of Microbial Competition, Cambridge University Press, Cambridge, 1995.  doi: 10.1017/CBO9780511530043.  Google Scholar [32] H. L. Smith and X.-Q. Zhao, Robust persistence for semidynamical systems, Nonlinear Anal., 47 (2001), 6169-6179.  doi: 10.1016/S0362-546X(01)00678-2.  Google Scholar [33] K. Song, W. Ma and S. Guo, et al., A class of dynamic model describing microbial flocculant with nutrient competition and metabolic products in wastewater treatment, Adv. Differ. Equ., 2018 (2018), Paper No. 33, 14 pp. doi: 10.1186/s13662-018-1473-6.  Google Scholar [34] H. R. Thieme, Mathematics in Population Biology, Princeton University Press, Princeton, 2003.   Google Scholar [35] H. R. Thieme, Persistence under relaxed point-dissipativity (with application to an endemic model), SIAM J. Math. Anal., 24 (1993), 407-435.  doi: 10.1137/0524026.  Google Scholar [36] P. van den Driessche and J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29-48.  doi: 10.1016/S0025-5564(02)00108-6.  Google Scholar [37] V. Volterra, Variazioni e fluttuazioni del numero d'individui in specie animali conviventi, Mem. R. Accad. Naz. dei Lincei, 2 (1926), 31-113.   Google Scholar [38] W. Wang, Global behavior of an SEIRS epidemic model with time delays, Appl. Math. Lett., 15 (2002), 423-428.  doi: 10.1016/S0893-9659(01)00153-7.  Google Scholar [39] W. Wang, W. Ma and H. Yan, Global dynamics of modeling flocculation of microorganism, Appl. Sci., 6 (2016), 221. doi: 10.3390/app6080221.  Google Scholar [40] G. S. K. Wolkowicz, H. Xia and S. Ruan, Competition in the chemostat: A distributed delay model and its global asymptotic behavior, SIAM J. Math. Anal., 57 (1997), 1281-1310.  doi: 10.1137/S0036139995289842.  Google Scholar [41] H. Xia, G. S. K. Wolkowicz and L. Wang, Transient oscillations induced by delayed growth response in the chemostat, J. Math. Biol., 50 (2005), 489-530.  doi: 10.1007/s00285-004-0311-5.  Google Scholar [42] T. Zhang, N. Gao and T. Wang, et al., Global dynamics of a model for treating microorganisms in sewage by periodically adding microbial flocculants, Math. Biosci. Eng., 17 (2020), 179-201. doi: 10.3934/mbe.2020010.  Google Scholar [43] T. Zhang, W. Ma and X. Meng, Global dynamics of a delayed chemostat model with harvest by impulsive flocculant input, Adv. Difference Equ., 2017 (2017), Paper No. 115, 17 pp. doi: 10.1186/s13662-017-1163-9.  Google Scholar [44] X.-Q. Zhao, Uniform persistence and periodic coexistence states in infinite-dimensional periodic semiflows with applications, Canad. Appl. Math. Quart., 3 (1995), 473-495.   Google Scholar [45] X.-Q. Zhao, Dynamical Systems in Population Biology, 2$^{nd}$ ed., Springer, Cham, 2017. doi: 10.1007/978-3-319-56433-3.  Google Scholar
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