Abstract
This paper is devoted to the analysis of a nutrient-plankton model with delayed nutrient cycling. Firstly, stability and Hopf bifurcation of the positive equilibrium are given, and the direction and stability of Hopf bifurcation are also studied. We show that delay, which is considered in the decomposition of dead phytoplankton, can induce stability switches, such that the positive equilibrium switches from stability to instability, to stability again and so on. One can observe that the influence of delay on the system dynamics is essential. Then, we prove that there exists at least one positive periodic solution as the time delay varies in some regions using the global Hopf bifurcation result of Wu (1998, Trans Am Math Soc 350:4799–4838) for functional differential equations. Furthermore, the impact of input rate of nutrient is discussed along with numerical results, and the role of delay in the nutrient cycling is interpreted ecologically. Finally, several groups of illustrations are performed to justify analytical findings.
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References
Abdllaoui, A.E., Chattopadhyay, J., Arino, O.: Comparisons, by models, of some basic mechanisms acting on the dynamics of the zooplankton-toxic phytoplankton systems. Math. Mod. Meth. Appl. S. 12(10), 1421–1451 (2002)
Odum, E.P.: Fundamentals of Ecology. Saunders, Philadelphia (1971)
Anderson, D.M.: Turning back the harmful red tide. Nature 338(7), 513–514 (1997)
Huppert, A., Blasius, B., Stone, L.: A model of phytoplankton blooms. Am. Nat. 159, 156–171 (2002)
Hallegraeff, G.M.: A review of harmful algae blooms and their apparent global increase. Phycologia 32, 79–99 (1993)
Chattopadhyay, J., Sarkar, R.R., El-Abdllaoui, A.: A delay differential equation model on harmful algal blooms in the presence of toxic substances. IMA J. Math. Appl. Med. Biol. 19, 137–161 (2002)
Mei, L.F., Zhang, X.Y.: Existence and nonexistence of positive steady states in multi-species phytoplankton dynamics. J. Differ. Equat. 253, 2025–2063 (2012)
Roy, S.: The coevolution of two phytoplankton species on a single resource: Allelopathy as a pseudo-mixotrophy. Theor. Popul. Biol. 75, 68–75 (2009)
Wang, Y., Jiang, W., Wang, H.: Stability and global Hopf bifurcation in toxic phytoplankton-zooplankton model with delay and selective harvesting. Nonlinear Dyn. 73, 881–896 (2013)
Saha, T., Bandyopadhyay, M.: Dynamical analysis of toxin producing phytoplankton-zooplankton interactions. Nonlinear Anal. RWA 10, 314–332 (2009)
Zhao, J.T., Wei, J.J.: Stability and bifurcation in a two harmful phytoplankton-zooplankton system. Chaos. Solitons Fractals 39, 1395–1409 (2009)
Banerjee, M., Venturino, E.: A phytoplankton-toxic phytoplankton-zooplankton model. Ecol. Complex. 8, 239–248 (2011)
He, X., Ruan, S.: Global stability in chemostat-type plankton models with delayed nutrient recycling. J. Math. Biol. 37, 253–271 (1998)
Pardo, O.: Global stability for a phytoplankton-nutrient system. J. Biol. Systems 8, 195–209 (2000)
Das, S., Ray, S.: Effect of delay on nutrient cycling in phytoplankton-zooplankton interactions in estuarine system. Ecol. Model. 215, 69–76 (2008)
Zhang, T.R., Wang, W.D.: Hopf bifurcation and bistability of a nutrient-phytoplankton-zooplankton model. Appl. Math. Model. 36, 6225–6235 (2012)
Barton, A.D., Dutkiewicz, S., et al.: Patterns of diversity in marine phytoplankton. Science 327, 1509–1511 (2010)
Hale, J.K.: Verduyn Lunel. Introduction to Functional Differential Equations. Springer, New York, S.M. (1993)
Holling, C.S.: The components of predation as revealed by a study of small-mammal predation of the European pine sawfly. Can. Entomol. 91, 293–320 (1959)
Ruan, S.G., Wei, J.J.: On the zeros of transcendental function with applications to stability of delay differential equations with two delays. Dyn. Contin Discret. Impulse Systems 10, 863–874 (2003)
Ruan, S.G., Wei, J.J.: On the zeros of a third degree exponential polynomial with applications to a delayed model for the control of testosterone secretion. IMA J. Math. Appl. Med. Biol. 18, 41–52 (2001)
Hassard, B.D., Kazarinoff, N., Wan, Y.: Theory and Applications of Hopf Bifurcation. Cambridge University Press, Cambridge (1981)
Wu, J.H.: Symmetric functional differential equations and neural networks with memory. Transac. Am. Math. Soc. 350, 4799–4838 (1998)
Lakshmikantham, V., Leela, S.: Differential and Integral Inequalities (Theory and Application): Ordinary Differential Equations I. Academic Press, New York and London (1969)
Qu, Y., Wei, J.J., Ruan, S.G.: Stability and bifurcation analysis in hematopoietic stem cell dynamics with multiple delays. Physica D 239, 2011–2024 (2010)
Muldowney, J.S.: Compound matrices and ordinary differential equations. Rocky Mountain J. Math. 20, 857–872 (1990)
Li, M.Y., Muldowney, J.: On Bendixson’s criterion. J. Differ. Equ. 106, 27–39 (1994)
Wang, W.Q., Wang, M.: The Mangroves of China. Sciences Press, Beijing (2007). (in chinese)
Pierre, N.T.: Dynamical Systems: An Introduction with Applications in Economics and Biology. Springer-Verlag, Heidelberg (1995)
Acknowledgments
The authors wish to express their gratitude to the editors and the reviewers for the helpful comments. This work is supported in part by NNSF of China(No.11371112), by the Heilongjiang Provincial Natural Science Foundation (No.A201208), and by the Fundamental Research Founds for the Central Universities Grant No. HIT. IBRSEM. 201332).
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Appendix
Appendix
1.1 Properties of Hopf bifurcation
In this section, based on numerical evaluation of Hopf bifurcation (see Hassard et al. [22], Chap. 3), and using a similar computation process as in [6], we give the computing process of the properties of Hopf bifurcation and stability of the bifurcating periodic solutions from \(S^{*}\) under the conditions of Theorem 1 \((ii)\). We obtain the coefficients determining the important quantities:
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\(g_{20}=2\bar{D}(\Delta _{11}+\bar{\rho }_{1}^{*}\Delta _{21} + \bar{\rho }_{2}^{*}\Delta _{31}), g_{11}=\bar{D}(\Delta _{12} + \bar{\rho }_{1}^{*}\Delta _{22}+\bar{\rho }_{2}^{*}\Delta _{32}),\)
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\(g_{02}=2\bar{D}(\Delta _{13}+\bar{\rho }_{1}^{*}\Delta _{23} + \bar{\rho }_{2}^{*}\Delta _{33}), g_{21}=2\bar{D}(\Delta _{14} + \bar{\rho }_{1}^{*}\Delta _{24} + \bar{\rho }_{2}^{*}\Delta _{34}),\)
where
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\(\Delta _{11}=\rho _{1} b_{12}+b_{20}, \Delta _{12} = (\rho _{1}+\bar{\rho }_{1}) b_{12}+2b_{20}, \Delta _{13}=\bar{\rho }_{1} b_{12}+b_{20},\)
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\(\Delta _{14}=b_{12}(W_{11}^{2}(0)+\rho _{1}W_{11}^{1}(0)+\frac{1}{2}W_{20}^{2}(0) +\frac{1}{2}\bar{\rho }_{1}W_{20}^{1}(0))+b_{20}(W_{20}^{1}(0)+2W_{11}^{1}(0))\),
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\(\Delta _{21}=c_{12}\rho _{1}+c_{23}\rho _{1}\rho _{2}+c_{20}\rho _{1}^{2},\)
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\(\Delta _{22}=c_{12}(\rho _{1}+\bar{\rho }_{1})+c_{23}(\rho _{1}\bar{\rho }_{2} + \bar{\rho }_{1}\rho _{2})+2c_{20}\rho _{1}\bar{\rho }_{1},\)
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\(\Delta _{23}=c_{12}\bar{\rho }_{1}+c_{23}\bar{\rho }_{1}\bar{\rho }_{2} + c_{20}\bar{\rho }_{1}^{2},\)
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\(\Delta _{24}\!=\!c_{12}(W_{11}^{2}(0)+\rho _{1}W_{11}^{1}(0) + \frac{1}{2}W_{20}^{2}(0)+\frac{1}{2}\bar{\rho }_{1}W_{20}^{1}(0)) +c_{23}(\frac{1}{2}\bar{\rho }_{2}W_{20}^{2}(0) +\frac{1}{2}\bar{\rho }_{1}W_{20}^{3} (0)+\rho _{2}W_{11}^{2}(0) + \rho _{1}W_{11}^{3}(0))+c_{20}(\bar{\rho }_{1} W_{20}^{2}(0)+2\rho _{1} \qquad W_{11}^{2}(0))\)
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\(\Delta _{31}=d_{23}\rho _{1}\rho _{2}+d_{20}\rho _{1}^{2},\)
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\(\Delta _{32}=d_{23}(\rho _{1}\bar{\rho }_{2}+\bar{\rho }_{1}\rho _{2}) + 2d_{20}\rho _{1}\bar{\rho }_{1},\)
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\(\Delta _{33}=d_{23}\bar{\rho }_{1}\bar{\rho }_{2}+d_{20}\bar{\rho }_{1}^{2},\)
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\(\Delta _{34}=d_{23}(\frac{1}{2}\bar{\rho }_{2}W_{20}^{2}(0) + \frac{1}{2}\bar{\rho }_{1}W_{20}^{3}(0)+\rho _{2}W_{11}^{2}(0) +\rho _{1}W_{11}^{3}(0))+d_{20}(\bar{\rho }_{1} W_{20}^{2}(0) +2\rho _{1}W_{11}^{2}(0)),\)
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\(D=\frac{1}{1+\rho _{1}^{*}\bar{\rho }_{1}+\rho _{2}^{*}\bar{\rho }_{2} + a_{13}\bar{\rho }_{1}\tau _{0}e^{i\omega _{k}\tau _{j}^{k}}},\)
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\(\rho _{1}=\frac{i\omega _{k}-a_{11}}{a_{12}+a_{13}e^{-i\omega _{k}\tau _{j}^{k}}}, \rho _{2}=\frac{a_{32}}{i\omega _{k}}\rho _{1},\)
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\(\rho _{1}^{*}=-\frac{i\omega _{k}+a_{11}}{a_{21}}, \rho _{2}^{*}=-\frac{a_{23}}{i\omega _{k}}\rho _{1}^{*}.\)
and
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\(W_{20}(0)=\frac{ig_{20}}{\omega _{k}}q(0)+\frac{i\bar{g}_{02}}{3\omega _{k}} \bar{q}(0)\),
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\(W_{11}(0)=\frac{-ig_{11}}{\omega _{k}}q(0)+\frac{i\bar{g}_{11}}{\omega _{k}} \bar{q}(0),\)
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\(q(0)=(1,\rho _{1}\), \(\rho _{2})\).
Thus, we can compute the following values:
Then we can determine the properties of bifurcating periodic solutions at the critical value \(\tau ^{*}\). According to Case 1 and Case 2 in [29] (p. 202), we have
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1.
If \(\beta _2<0,~ \mu _{2}>0~ ( \beta _2<0, \mu _{2}<0)\), the bifurcating periodic solutions on the center manifold are stable. This case is referred to as a supercritical bifurcation.
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2.
If \(\beta _2>0,~ \mu _{2}>0~ ( \beta _2>0, \mu _{2}<0)\), the bifurcating periodic solutions on the center manifold are unstable. This case is referred to as a subcritical bifurcation.
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Wang, Y., Wang, H. & Jiang, W. Stability switches and global Hopf bifurcation in a nutrient-plankton model. Nonlinear Dyn 78, 981–994 (2014). https://doi.org/10.1007/s11071-014-1491-1
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DOI: https://doi.org/10.1007/s11071-014-1491-1