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Global Hopf bifurcation of a delayed phytoplankton-zooplankton system considering toxin producing effect and delay dependent coefficient

  • In this paper, a delayed phytoplankton-zooplankton system with the coefficient depending on delay is investigated. Firstly, it gives the nonnegative and boundedness of solutions of the delay differential equations. Secondly, it gives the asymptotical stability properties of equilibria in the absence of time delay. Then in the presence of time delay, the existence of local Hopf bifurcation is discussed when the delay changes. In addition to that, the stability of periodic solution and bifurcation direction are also obtained through the use of central manifold theory. Furthermore, he global continuity of the local Hopf bifurcation is discussed by using the global Hopf bifurcation result of FDE. At last, some numerical simulations are presented to show the rationality of theoretical analyses.

    Citation: Zhichao Jiang, Xiaohua Bi, Tongqian Zhang, B.G. Sampath Aruna Pradeep. Global Hopf bifurcation of a delayed phytoplankton-zooplankton system considering toxin producing effect and delay dependent coefficient[J]. Mathematical Biosciences and Engineering, 2019, 16(5): 3807-3829. doi: 10.3934/mbe.2019188

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  • In this paper, a delayed phytoplankton-zooplankton system with the coefficient depending on delay is investigated. Firstly, it gives the nonnegative and boundedness of solutions of the delay differential equations. Secondly, it gives the asymptotical stability properties of equilibria in the absence of time delay. Then in the presence of time delay, the existence of local Hopf bifurcation is discussed when the delay changes. In addition to that, the stability of periodic solution and bifurcation direction are also obtained through the use of central manifold theory. Furthermore, he global continuity of the local Hopf bifurcation is discussed by using the global Hopf bifurcation result of FDE. At last, some numerical simulations are presented to show the rationality of theoretical analyses.


    Almost all aquatic life is based on plankton, the most abundant form of life, floating freely on well known aquatic surfaces such as wells, lakes, rivers, estuaries and oceans. The studies on plankton materials is an important area for the researchers who engaged in the field of marine ecology. The phytoplankton, the plant forms of plankton enables to engage with the process of photo-synthesis when sunlight placed on them and serves as the fundamental food source. The zooplankton, the animal forms of plankton consumes phytoplankton which is the most favorite food source of aquatic animals such as fish, shellfish, molluscs and jellyfish. One of the merits of the phytoplankton is that it can release oxygen by absorbing carbon dioxide, this process contributes to make a cleaner environment. On the other side, some phytoplankton can release toxin substances which are hazards for the aquatic animals, and even can kill the aquatic animals.

    Under certain conditions, phytoplankton can develop rapidly. These bodies of water which are enriched in phytoplankton may become red tide, while the predator of zooplankton will have a certain impact on the number of phytoplankton, so it is of great significance to study their relationship for the occurrence of phytoplankton bloom. Mathematical models have made considerable contributions to the understandings of the relationship between phytoplankton and zooplankton [1,2,3,4,5,6,7,8,9,10,11,12,13]. Toxin available in water sources impact on plankton materials and also can be used to suppress the growth of plankton blooms. J. Chattopadhyay et al. [14] proposed a mathematical model to study the behavior of toxic-phytoplankton (TPP) and zooplankton as well as study their interactions. The general form of mathematical model proposed in [14] can be governed by the following two nonlinear ordinary differential equations,

    {˙X(t)=rX(t)(1X(t)A)βψ(X(t))Y(t),˙Y(t)=β1ψ(X(t))Y(t)νY(t)ρϕ(X(t))Y(t), (1.1)

    where X(t) represents the density of TPP population and Y(t) is the density of zooplankton population at time t. In system (1.1), r represents the growth rate, and A is the environmental carrying capacity for TPP. The functional response functions for zooplankton grazing phytoplankton and the toxin distribution causing zooplankton death are denoted by ψ(X) and ϕ(X), respectively. Further, β is the maximum uptake rate and β1 is the ratio of conversion satisfying β1<β. The natural death rate of zooplankton is ν. The parameter ρ represents the rate of toxin release of phytoplankton. All parameters are positive.

    We know that the delay caused by the maturity of TPP plays a crucial role on the dynamic behavior of phytoplankton zooplankton system, which seems that delay could cause rich dynamics [15,16,18,17,19]. In phytoplankton zooplankton system, many researchers assumed that the releasing of toxin is an instantaneous process, while the real case is that time delay may have an essential influence on the dynamics of mathematical models. In [16], Chattopadhyay et al. analyzed the following delayed system

    {˙X(t)=rX(t)(1X(t)A)βψ(X(t))Y(t),˙Y(t)=β1ψ(X(t))Y(t)νY(t)ρϕ(X(tτ))Y(t). (1.2)

    In system (1.2), functions ψ and ϕ are assumed to ψ(X)=X and ϕ(X)=X/(γ+X). The process of toxin releasing follows a discrete variation and τ is the maturation time of phytoplankton for releasing toxin, the authors studied the oscillation behavior of phytoplankton and zooplankton populations based on system (1.2) with a condition that helps the oscillatory behavior to be stable. By regarding delay as the bifurcation parameter, Saha and Bandyopadhyay [20] modified system (1.2) by using Holling type Ⅱ function instead of ψ(X) and by discussed the oscillatory behavior of phytoplankton and zooplankton. Moreover, the authors also established a set of conditions for the existence of globally periodic solutions. In the view of real ecological meaning, a gestation period of zooplankton is likely to delay the contact with phytoplankton. Rehim and Imran [21] put on a more general model:

    {˙X(t)=rX(t)(1X(t)A)βX(t)Y(t),˙Y(t)=eντβ1X(tτ)Y(tτ)νY(t)ρeντX(tτ)γ+X(tτ)Y(tτ), (1.3)

    where the first term and the final term with delay in the second equation of system define the zooplankton's gestation delay and TPP's maturity delay, respectively. The authors obtained the globally asymptotical stability properties of equilibria and established some conditions such that occurring of local Hopf bifurcation at the positive equilibrium. Based on Rehim and Imran [21], Wang et al. [22] introduced the harvesting term in zooplankton population, and the globally asymptotical stability properties of equilibrium and occurrence of Hopf bifurcation are obtained. They also established excellent result that the system had at least one positive periodic solution when delay changes. Furthermore, Jiang et al. [23] replaced the functions ψ(X) and ϕ(X) by Holling Ⅱ type functions with the different half-saturation constants. They established the globally asymptotical stability properties of boundary equilibrium and the existence of local and global Hopf bifurcation under certain conditions.

    Motivated by the systems considered in [21,22,23] and in this paper, we formulated a generalized system as shown below,

    {˙X(t)=rX(t)(1X(t)A)βX(t)Y(t),˙Y(t)=eντβ1X(tτ)Y(tτ)νY(t)ρeντϕ(X(tτ))Y(tτ), (1.4)

    where ϕ(X) conforms to the following hypothesis:

    ϕ(0)=0,0<ϕ(X)<β1/ρ,forallX0. (1.5)

    The prototypes of response function ϕ(X) can be found in the literatures[24,25,26,27], for example, ϕ(X)=X (Holling type Ⅰ or Lotka-Volterra kinetics), ϕ(X)=X/(m+X) (Holling type Ⅱ or Michaelis-Menten kinetics), ϕ(X)=X2/(m+X2) (Holling type Ⅲ) and, ϕ(X)=1eαX (Ivlev's functional response).

    This paper is organized as follows. In section 2, it will give the positivity and boundedness of solutions of system (1.4). In section 3, a special case of system (1.4) that is without considering time delay will be properly studied and also the stability properties of each of the equilibria have been extensively presented. In section 4, we obtain results related to stability of equilibria and existence of Hopf bifurcation of system (1.4) with delay. In section 5, employing the center manifold theory that are presented in scholar manuscript [28,29,30], the properties of Hopf bifurcation are derived. For delayed systems, are there exist of large-scale periodic solutions when τ increases from the first Hopf bifurcation values? Authors [31,32] studied the global Hopf bifurcation of a delayed system by using a the result due to Wu [33]. In the following, by using the global Hopf bifurcation result [33], we obtain the results that are related the global existence of periodic solution with delay varying in section 6. In section 7, numerical simulations are given with the purpose of verifying the theoretical results. At last, some conclusions are given in section 8.

    Let n be an integer, for any n1, define Rn+={(x1,x2,,xn)Rn,xi0,1in} and IntRn+={(x1,x2,,xn)Rn,xi>0,1in}. For τ>0, denote the space C([τ,0],R2) with the supermum norm. Let C2+=C([τ,0],R2+) and IntC2+=C([τ,0],IntR2+). For system (1.4), let us take any initial function on Int C2+ and it always assume that β>β1.

    Lemma 2.1. Let X(θ):=φ1(θ),Y(θ):=φ2(θ)0 for θ[τ,0), and φ1(0),φ2(0)>0. Then for some σ>0, all solutions of system (1.4) uniquely exist on [0,σ) when the initial function φ=(φ1,φ2)TInt C2+, and all solutions are positive for t[0,σ).

    Proof. By [34], solutions of system (1.4) with initial function φIntC2+ uniquely exist on t[0,σ) for some σ>0. Suppose that (X(t),Y(t)) is the solution of (1.4) for t[0,σ). Without loss of generality, it assumes that [0,σ) is the maximum existence internal of solution. If the solution exists for all t>0, then σ=. Integrating the first equation of system (1.4) gives

    X(t)=φ1(0)et0(rA(AX(u))Y(u))du>0,   t[0,σ).

    Next, the proof by contradiction is used to show Y(t)>0. Suppose that there exists t[0,σ) such that

    Y(t)=0,˙Y(t)0and Y(t)>0 for any t[τ,t).

    In the equation of Y(t), exchanging t for t, it has

    ˙Y(t)=β1eντX(tτ)Y(tτ)νY(t)ρeντϕ(X(tτ))Y(tτ)>eντ(β1ρ(β1/ρ))X(tτ)Y(tτ)=0.

    It is a contradiction to ˙Y(t)0. So that, Y(t)>0 for all t[0,σ). This completes the proof.

    Lemma 2.2. The nonnegative solutions of system (1.4) are bounded on the interval t[0,σ). Further, limtsupX(t)A.

    Proof. Let (X(θ),Y(θ)) be the solution of system (1.4). From the equation of X(t) in system (1.4), it has that ˙X(t)rAX(t)(AX(t)), which yields that limtsupX(t)A. Define

    W(t)=Y(t)+β1eντβX(tτ).

    Then

    ˙W(t)=β1eντX(tτ)Y(tτ)νY(t)ρeντϕ(X(tτ))Y(tτ)+β1rβAeντX(tτ)(AX(tτ))β1eντX(tτ)Y(tτ)=νW(t)+β1βeντX(tτ)(ν+rrAX(tτ))ρeντϕ(X(tτ))Y(tτ)νW(t)+β1βeντX(tτ)(ν+rrAX(tτ))νW(t)+β1A4βreντ(ν+r)2.

    By the comparison theory [35], W(t)ϝ(t), where ϝ(t)=ϝ(0)eνt+β1A4βrνeντ(ν+r)2(1eνt) is the solution of initial value problem

    ˙ϝ(t)=νϝ(t)+β1A4βreντ(ν+r)2,ϝ(0)=W(0).

    Consequently, W(t)W(0)+β1A4βrνeνt(ν+r)2. Furthermore, it has

    Y(t)+β1βeντX(tτ)=W(t)W(0)+14νβ1eνt(1+ν)2φ2(0)+β1βeντφ1(τ)+β1A4βrνeνt(r+ν)2.

    Up to now, it has obtained that the nonnegative solutions of system (1.4) are bounded on the interval t[0,σ). This completes the proof.

    According to the continuation theorem of solutions for FDE [34], we can get the following theorem.

    Theorem 2.1. The solutions (X(t),Y(t)) of system (1.4) with the initial function φIntC2+ is uniquely existent, nonnegative and bounded on [0,+) and satisfies

    limt+supX(t)A,limt+supY(t)M,

    where

    M:=φ2(0)+β1βeντφ1(τ)+β1A4βrνeνt(r+ν)2.

    The following result is given for our need.

    Lemma 2.3. For the following system

    y(t)=ay(tτ)by(t),

    if a<b, then the solution satisfies limty(t)=0, where a,b,τ>0 and y(t)>0 for t[τ,0].

    In this part, it investigates the stability of ODE system, that is, τ=0. When τ=0, system (1.4) has three equilibria E0(0,0),E1(A,0) and E(X(0),Y(0)), where X(0) and Y(0) satisfy r(AX(0))AβY(0)=0, and β1X(0)ρϕ(X(0))=ν. The positive equilibrium E is existent and unique if β1Aρϕ(A)>ν. We can obtain E0 is always a saddle point. If β1Aρϕ(A)<ν, then E1 is locally asymptotically stable (LAS), and, if the inequality is reversed, then E1(A,0) is unstable and E is locally asymptotically stable. Furthermore, it has the global stability result of E1.

    Theorem 3.1. If β1Aρϕ(A)<ν, then E1 is globally asymptotically stable (GAS).

    Proof. By the positivity of solutions, it has that ˙X(t)rX(t)(1X(t)/A). This implies that limtsupX(t)A. Consequently, ˙Y(t)=νY(t)+β1X(t)Y(t)ρϕ(X(t))Y(t)=[ν+β1X(t)ρϕ(X)]Y(t) [ν+β1Aρϕ(A)]Y(t). Let y(t) be the solution of ˙y(t)=[ν+β1Aρϕ(A)]y(t). Since β1Aρϕ(A)<ν, it has y(t)0. Hence, Y(t)0. By comparison theorem, Y(t) is bounded. Let η(0,A), then there exists Tη>0 such that ˙X(t)rAX(t)(AηX(t)) for tTη, hence, we have limtinfX(t)Aη. Since η(0,A) is arbitrary, limtinfX(t)A. We already have limtX(t)A. Then, limtX(t)=A. Hence E1 is GAS.

    Now let us return the case τ0. System (1.4) has three equilibria E0(0,0),E1(A,0) and E(X(τ),Y(τ)), where X(τ),Y(τ) satisfy r(1X(τ)/A)βY(τ)=0,β1X(τ)ρϕ(X(τ))=νeντ. Therefore, we have that E exists and is unique if 0τ<τc(1/ν)ln[(1/ν)(β1Aρϕ(A))] and EE1. If τ>τc, then E is not existent.

    That is clear that E0 is always a saddle point. To E1, the characteristic equation of system (1.4) at E1 is given by

    (λ+r)[λ+νe(λ+ν)τ(β1Aρϕ(A))]=0. (4.1)

    Then we have the following theorem.

    Theorem 4.1. If 0τ<τc, then E1 is unstable. If τ>τc, then E1 is GAS.

    Proof. One of the roots of (4.1) is λ=r, and the other roots satisfy

    H(λ)(λ+ν)e(λ+ν)τ=β1Aρϕ(A). (4.2)

    It has H(0)=νeντ,˙H(λ)>0,H(+)=. Since τ<τc, there exists a unique positive root λ such that (4.2) holds and (4.1) has at least one positive root λ. Hence, E1 is unstable when τ[0,τc).

    Now, one proves E1 is GAS when τ>τc. From the second equation, it has that ˙Y(t)=νY(t)+eντ[β1X(tτ)ρϕ(X(tτ))]Y(tτ)νY(t)+eντ[β1Aρϕ(A)]Y(tτ). Let y(t) be the solution of ˙y(t)=νy(t)+eντ[β1Aρϕ(A)]y(tτ). Since τ>τc, Lemma 3 guarantees that y(t)0. Hence, Y(t)0. Furthermore, it can get that X(t)A, which implies the global stability of E1. This completes the proof.

    Let

    P1(λ,τ)=λ2+(r+ν)λ+rν, Q1(λ,τ)=eντ(ν+r)[β1Aρϕ(A)],

    then

    P1(0,τ)+Q1(0,τ)0, P1(iω,τ)+Q1(iω,τ)0.

    Let λ=±iω0(τ) (ω0(τ)>0) be a pair of simple pure imaginary roots of (4.1). The stability switches may occur at the τ values:

    τ±n(τ)=θ0±(τ)+2nπω0±(τ), nN,

    where

    (ω0±(τ))2=12{R2(ν2+r2)±|ν2r2R2|}

    and θ0±(τ)[0,2π) satisfy

    sinθ0±(τ)=ω0±(τ)R,cosθ0±(τ)=νR,

    where R=eντ[β1Aρϕ(A)]. Hence, ω0(τ) is infeasible; ω0+(τ) is feasible if τ[0,τc) and τ+n(τ)=(1/R2ν2){2πarcos(ν/R)+2nπ}; ω0+(τ) is infeasible for τ>max{0,τc}.

    Define

    Zn(τ):=ττ+n(τ),nN,J0={τj: τj[0,τc)andZn(τj)=0}.

    Theorem 4.2. If 0τ<τc, then ±iω0+(τ) are a pair of simple pure imaginary roots of system (1.4), and Zn(τ)=0 for some nN and some τ[0,τc). This pair of roots cross the imaginary axis from left (right) to right (left) if κ0+(τ)>0(<0), where

    κ0+(τ):=Sign{dReλdτ|λ=iω0+(τ)}=Sign{Zn(τ)|τ=τ}.

    If J0 is not empty. For all τjJ0, if Zn(τj)0 holds, then system (1.4) undergoes Hopf bifurcations at E1 when τ=τj.

    Remark 4.1. It has proved that there are only two equilibria E0 (unstable) and E1 (GAS) when τ>τc. However if τ[0,τc) and β1Aρϕ(A)>ν, then both E0 and E1 are unstable, at the same time, E exists and is LAS.

    For convenience, we denote X(τ)=X,Y(τ)=Y. Let x=XX,y=YY, then system (1.4) becomes

    {˙x(t)=rAXx(t)βXy(t)rAx2(t)βx(t)y(t)˙y(t)=νy+eντ[β1Yρϕ(X)Y]x(tτ)+νy(tτ)+ρeντ[12ϕ(X)Yx2(tτ)ϕ(X)x(tτ)y(tτ)]+ρeντ[16ϕ(X)Yx3(tτ)12ϕ(X)x2(tτ)y(tτ)]+O(4), (4.3)

    whose characteristic equation is

    Δ(λ,τ):=λ2+pλ+q+(sνλ)eλτ=0, (4.4)

    where

    p=rXA+ν,q=rXνA,s=eντβXY[β1ρf(X)]rXνA.

    Equation (4.4) converts to the general form

    P(λ,τ)+Q(λ,τ)eλτ=0, (4.5)

    where

    P(λ,τ)=λ2+pλ+q,Q(λ,τ)=sνλ.

    Equation (4.5) takes all the coefficients of P and Q depending on τ. We apply the criterion due to Bereta and Kuang [36], let λ=iω(ω=ω(τ)>0) be a root of (4.5), then ω satisfies

    {scosωτνsinωτ=ω2q,νωcosωτ+ssinωτ=pω,

    and

    sinωτ=(ω2q)νω+ωpsω2ν2+s2,  cosωτ=(qω2)sω2pνω2ν2+s2. (4.6)

    By the definitions of P and Q, and applying the property (i), (4.6) becomes:

    sinωτ=Im(P(iω,τ)Q(iω,τ)),  cosωτ=Re(P(iω,τ)Q(iω,τ)),

    which yields

    ϝ(ω,τ)=ω4+a1(τ)ω2+a2(τ)=0,

    and its roots are given by

    ω2±=12[a1(τ)±Δ],

    where

    a1(τ)=r2X2A2>0,a2(τ)=q2s2,Δ=a21(τ)4a2(τ).

    Let

    I={τ[0,τc):q<s}={τ[0,τc):2rνeντ<AβY[β1ρf(X)]}.

    If I is non-empty, then ω=ω+ and ω is not feasible for all τI, and ω is not definited for τI.

    Then, for τI, let θ(τ)[0,2π) be defined by

    sinθ(τ)=(ω2q)νω+ωpsω2ν2+s2,  cosθ(τ)=(qω2)sω2pνω2ν2+s2.

    Hence, it can define the maps τn(τ) given by

    τn(τ):=θ(τ)+2nπω,nN,τI.

    Next, let us introduce the following continuous and differentiable functions

    Sn(τ):=ττn(τ),τI,nN.

    Theorem 4.3. Let λ=±iω+(τ) be a pair of simple pure imaginary roots of Eq (4.5), and at some τI,

    Sn(τ)=0forsomenN.

    This pair of roots crosses the imaginary axis from left (right) to right (left) if k+(τ)>0(<0), where

    k+(τ):=Sign{dReλdτ|λ=iω+(τ)}=Sign{Sn(τ)|τ=τ}.

    Remark 4.2. For τI, it has the following one sequence of functions:

    Sn(τ)=τθ+(τ)+2nπω+(τ).

    Clearly S+n(τ)>S+n+1(τ) for all nN,τI.

    Theorem 4.4. For system (1.4), if β1Aρϕ(A)>ν, then it has the following conclusions.

    (i) If I= or non-empty set, but Sn(τ)=0 has no positive root in I, then E is LAS for all τ[0,τc);

    (ii) If I and Sn=0 has positive roots in I, denoted by τjn, for some nN. it assumes that Sn(τjn)0. Rearrange these roots as the set J:={τ0,τ1,...,τm} with τj<τj+1,j=0,...,m1. Then E is LAS for τ[0,τ0)(τm,ˉτ) and unstable for τ(τ0,τm). Hopf bifurcations occur at E when τ=τj.

    In section 4, we have obtained the sufficient conditions which ensure that system (1.4) undergoes Hopf bifurcation at E. In this section, using the center manifold theory presented by Hassard et al. [28], we can establish an explicit formula to determine the bifurcating direction and stability of periodic solutions at τ=τ0. In fact, let ω0=ω(τ0). Furthermore, let τ=τ0+μ, then μ=0 is a Hopf bifurcation value of system (1.4). We rewrite (4.3) as

    (˙x(t)˙y(t))=B1(x(t)y(t))+B2(x(tτ)y(tτ))+G, (5.1)

    where

    B1=(rAXβX0ν),B2=(00(β1Yρϕ(X)Y)eντ0ν),
    G=(rAx2(t)βx(t)y(t)β1eντx(tτ)y(tτ)ρeντ[12ϕ(X)Yx2(tτ)+ϕ(X)x(tτ)y(tτ)]ρeντ[16ϕ(X)Yx3(tτ)+12ϕ(X)x2(tτ)y(tτ)]+O(4)),

    and for φC, define

    Lμ(φ)=B1(φ1(0)φ2(0))+B2(φ1(τ)φ2(τ)).

    By the Riesz representation theorem, there exists a matrix ζ(θ,μ) in θ[τ,0] whose elements are bounded variation functions such that

    Lμφ=0τdζ(θ,μ)φ(θ).

    In fact, it can choose

    ζ(θ,μ)=B1υ(θ)B2υ(θ+τ),

    where

    υ(θ)={1,θ=0,0,θ0.

    Choose φC1=C([0,τ],(R2)), define

    A(μ)φ={˙φ(θ),θ[τ,0),0τdζ(h,μ)φ(h),θ=0,

    and

    R(μ)φ={0,θ[τ,0),F(μ,φ),θ=0,

    where

    F(μ,φ)=(rAXφ21(0)βφ1(0)φ2(0)β1eντφ1(τ)φ2(τ)ρeντ[12ϕ(X)Yφ21(τ)+ϕ(X)φ1(τ)φ2(τ)]ρeντ[16ϕ(X)Yφ21(τ)+12ϕ(X)φ21(τ)φ2(τ)]+O(4)).

    Let u=(x,y)T, then system (5.1) becomes

    ˙ut=A(μ)ut+R(μ)ut. (5.2)

    For ψC1, define

    Aψ(s)={˙ψ(s),s(0,τ],0τdζT(t,0)ψ(t),s=0,

    and a bilinear form

    ψ,φ=ˉψ(0)φ(0)0τθ0ˉψ(ξθ)dζ(θ)φ(ξ)dξ.

    Then A and A are adjoint operators, and they have the same eigenvalues ±iω0. By computation, we obtain that the eigenvector of A(0) corresponding to iω0 is q(θ)=(1,q2)eiω0θ and the eigenvector of A corresponding to iω0 is q(s)=ˉD(1,q2)Teiω0s, where

    q2=iω0A+rXAβX,q2=e(ν+iω0)τ0(iω0A+rX)A[β1Yρϕ(X)Y].

    Moreover,

    q(s),q(θ)=1,q(s),ˉq(θ)=0,

    where

    D={1+q2ˉq2+rAX+βXq2ˉq2[(β1Yρϕ(X)Y)e(ν+iω0)τ0+q2ν(eiω0τ01)]}1.

    Let ut be the solution of (5.1) with τ=τ0. Define z(t)=q,ut,ut=(xt,yt), then

    ˙z(t)=q,˙ut=iω0z(t)+ˉq(0)ˆF(z,ˉz), (5.3)

    where

    ˆF=F(0,W(z,ˉz)+2Re{zq}),W(z,ˉz)=ut2Re{zq},
    W(z,ˉz)=W20z22+W11zˉz+W02ˉz22+.

    Rewriting (5.3) as

    ˙ut=iω0z(t)+g(z,ˉz),

    where

    g(z,ˉz)=g20z22+g11zˉz+g02ˉz22+g21z2ˉz2.

    Substituting (5.2) and (5.3) into ˙W=˙ut˙zq˙ˉzq, it has

    ˙W={AW2Re{ˉq(0)ˆFq(θ)},θ[τ,0)AW2Re{ˉq(0)ˆFq(θ)}+ˆF,θ=0def=AW+H(z,ˉz,θ),

    where

    H(z,ˉz,θ)=H20(θ)z22+H11(θ)zˉz+H02(θ)ˉz22+. (5.4)

    By comparing the coefficients, it yields

    (A2iω0I)W20(θ)=H20(θ), AW11=H11(θ).

    For

    ut=W(z,ˉz,θ)+zq(θ)+ˉz¯q(θ),

    then

    (z,ˉz)=g20z22+g11zˉz+g02ˉz22+=ˉq(0)ˆF(z,ˉz).

    Notice that

    x(t)=z+ˉz+W(1)20(0)z22+W(1)11(0)zˉz+W(1)02(0)ˉz22+,y(t)=q2z+ˉq2ˉz+W(2)20(0)z22+W(2)11(0)zˉz+W(2)02(0)ˉz22+,x(tτ0)=eiω0τ0z+eiω0τ0ˉz+W(1)20(τ0)z22+W(1)11(τ0)zˉz+,y(tτ0)=q2eiω0τ0z+ˉq2eiω0τ0ˉz+W(2)20(τ0)z22+W(2)11(τ0)zˉz+,

    Comparing the coefficients, it can obtain

    g20=2D{rAβq2+ˉq2[β1q2ρ(12ϕ(X)Y+ϕ(X)q2)]e(ν+2iω0)τ0},g11=D{rAβq2+ˉq2[β1q2ρ(12ϕ(X)Y+ϕ(X)q2)]e(ν+2iω0)τ0},g02=2D{2rAβ(ˉq2+q2)+ˉq2[(β1ϕ(X))eντ0(ˉq2+q2)ρeντ0ϕ(X)Y]},g21=2D{rA[2W(1)11(0)+W(1)20(0)]β[W(2)11(0)+12W(2)20(0)+12W(1)20(0)ˉq2+W(1)11(0)q2]+ˉq2[β1eντ0(eiω0τ0W(2)11(τ0)+12eiω0τ0W(2)20(τ0)+12eiω0τ0W(1)20(τ0)ˉq2+eiω0τ0W(1)11(τ0)q2)ρeντ0(12ϕ(X)Y(2eiω0τ0W(1)11(τ0)+eiω0τ0W(1)20(τ0))+ϕ(X)(eiω0τ0W(2)11(τ0)+12eiω0τ0W(2)20(τ0)+12eiω0τ0W(1)20(τ0)ˉq2+eiω0τ0W(1)11(τ0)q2))ρe(ν+iω0)τ0(12ϕ(X)Y+12ϕ(X)(ˉq2+2q2))]}.

    It still needs to compute W20(θ) and W11(θ). When θ[τ,0),

    H(z,ˉz,θ)=2Re{ˉq(0)ˆFq(θ)}=ˉqˆFq(θ)ˉq(0)ˆFq(θ)=gq(θ)ˉgˉq(θ).

    By comparing the coefficients with (5.4), it can yield that

    H20(θ)=g20q(θ)ˉg02ˉq(θ),H11(θ)=g11q(θ)ˉg11ˉq(θ).

    In addition,

    ˙W20(θ)=2iω0W20(θ)H20(θ)=2iω0W20(θ)+g20q(θ)+ˉg20ˉq(θ).

    Furthermore,

    W20(θ)=ig20ω0q(0)eiω0θ+iˉg203ω0ˉq(0)eiω0θ+E1e2iω0θ,

    and similarly

    W11(θ)=ig11ω0q(0)eiω0θ+iˉg11ω0ˉq(0)eiω0θ+E2,

    where E1 can be determined by setting θ=0 in H. In fact,

    H20(0)=g20q(0)ˉg02ˉq(0)+ˆFz2,H11(0)=g11q(0)ˉg11ˉq(0)+ˆFzˉz,

    where

    ˆF=ˆFz2z22+ˆFzˉzzˉz+ˆF2ˉzˉz22+.

    Hence,

    0τdζ(θ)W20(θ)=AW20(0)=2iω0W20(0)+g20q(0)+ˉg02ˉq(0)ˆFz2

    and

    0τdζ(θ)W11(θ)=g11q(0)+ˉg11ˉq(0)ˆFzˉz.

    Notice that

    {(iω0I0τeiω0θdζ(θ))q(0)=0,(iω0I0τeiω0θdζ(θ))ˉq(0)=0,

    hence,

    (2iω0I0τe2iω0θdζ(θ))E1=ˆFz2.

    Similarly, it has

    (0τdζ(θ))E2=ˆFzˉz.

    Furthermore, we get

    E1=(2iω0+rAXβX(ρϕ(X)Yβ1Y)e(ν+2iω0)τ02iω0+ννe2iω0τ0)1×(rAβq2β1q2ρ[12ϕ(X)Y+ϕ(X)q2]e(ν+2iω0)τ0),

    and

    E2=(rAXβX[ρϕ(X)Yβ1Y]eντ00)1×(2rA+β(q2+ˉq2)[β1ρϕ(X)]eντ0(q2+ˉq2)+ρeντ0ϕ(X)Y).

    Then g21 can be computed. Hence each gij can be determined by the parameters. Thus, the following quantities can be computed:

    C1(0)=i2ω0(g20g112|g11|213|g02|2)+g212,U2=Re{C1(0)}Reλ(0),B2=2Re{C1(0)},T2=Im{C1(0)}+μ2Imλ(0)ω0.

    Hence, we have the following theorem.

    Theorem 5.1. If U2>0(<0), the direction of Hopf bifurcation is supercritical (subcritical); if B2<0(>0), the bifurcation periodic solutions are orbitally stable (unstable); if T2>0(<0), the period increase (decrease).

    In this part, it will consider the global existence of periodic solution. Firstly, one gives some notations [37].

    Define

    J0={τJ:S0(τ)=0},J+:=JJ0,Aj={max{τj:τjJ0,τj<τjJ+},J0(0,τj),0,else,Bj={min{τj:τjJ0,τj>τjJ+},J0(τj,supI),supI,else,
    Aj=max{τi:τiJ0J, τi<τjJ+},Bj=min{τi:τiJ0J,τi>τjJ+}.

    It assumes that J+. In the following, the global existence of periodic solutions bifurcating from (E,τj,2πω+j) for system (1.4) is investigated by using global Hopf bifurcation theorem [33], where ω+j=ω+(τj) (τjJ+), and ±iω+j is a pair of simple roots of (4.5) when τ=τj.

    Next, it always assumes that τ[0,τc) and β1Aρϕ(A)>ν are satisfied. For convenience, let Zt=(Xt,Yt), system (1.4) can be rewritten as the following FDE:

    ˙Z(t)=F(Zt,τ,p), (6.1)

    where Zt(θ)=Z(t+θ). By the results in [33], it can define the following signs:

    X=C([τ,0],R2+),L=Cl{(Zt,τ,p)X×R×R+:Zt+p=Zt},N={(ˉZ,τ,p):F(ˉZ,τ,p)=0},

    and let C(Z,τj,2πω+j) denote the connected component of (Z,τj,2πω+j) in L, and Projτ(Z,τj,2πω+j) represents its projection on τ space, where Z=E. On the basis of Theorem 2.1, it has

    Lemma 6.1. All periodic solutions of system (6.1) are uniformly bounded in R2+.

    Lemma 6.2. System (6.1) does not exist non-trivial τ-periodic solution.

    Proof. It can know that X-axis and Y-axis are the invariable manifold of system (6.1) and the trajectories of system (6.1) are disjoint one another, which means that if there are the periodic solutions in the first quadrant, then E must be in its interior. Using the proof by contradiction,

    It assumes that system (6.1) has non-trivial τ-periodic solution in the first quadrant, then the following system has the non-trivial periodic solution:

    {˙X=rX(1XA)βXY:=P,˙Y=eντβ1XYνYρeντϕ(X)Y:=Z. (6.2)

    For another, define Dulac function Q=1/(XY), then

    (PQ)X+(ZQ)Y=rAY<0.

    Therefore, according to Dulac theorem, system (6.2) has no any periodic solution in the first quadrant, which leads to a contradiction.

    Theorem 6.1. If J+, τ[0,τc) and β1Aρϕ(A)>ν hold, then for each τjJ+, there must be τiJ0J{τj}, such that system (6.1) exists at least one positive periodic solution when τ varies between τi and τj.

    Proof. Firstly, it will prove that Projτ(Z,τj,2πω+j) is unbounded for each j. The characteristic matrix of system (6.1) at ˉZ=(ˉZ(1),ˉZ(2))R2+ satisfies:

    Δ(ˉZ,τ,p)(Λ)=(Λ+rAˉZ(1)βˉZ(1)e(ν+Λ)τ[ρϕ(ˉZ(1))ˉZ(2)β1ˉZ(2)] Λ+ν(1eΛτ)). (6.3)

    System (6.1) has three equilibria ˉZ1,ˉZ2 and Z. It knows from section 4 that (ˉZ1,τ,p) is not center while (ˉZ2,τ,p) and (Z,τ,p) are isolated centers. Base on Theorem 4.4 and the condition Sn(τj)0, there exist ϵ>0, υ>0 and a smooth curve Λ: (τjυ,τj+υ)C, such that, det((Λ(τj)))=0, |Λ(τj)iω+j|<ϵ for all τ[τjυ,τj+υ] and Λ(τj)=iω+j, dReΛ(τj)/dτ0.

    Let Ωϵ,2πω+j={(η,p):0<η<ε,|p2πω+j|<ε}, then, on [τjυ,τj+υ]×Ωε,2πω+j, Δ(Z,τ,p)(η+2πpi)=0 iff η=0,τ=τj,p=2πω+j. Furthermore, define

    H±(Z,τj,2πω+j)(η,p)=Δ(Z,τj±υ,p)(η+2πpi),

    then it has the crossing number:

    r(Z,τj,2πω+j)=degB(H(Z,τj,2πω+j),Ωϵ,2πω+j)degB(H+(Z,τj,2πω+j),Ωϵ,2πω+j)={1,Sn(τj)>0,1,Sn(τj)<0.

    Hence it has

    (ˉZ,τ,p)C(Z,τj,2πω+j) r(ˉZ,τ,p)0,

    where (ˉZ,τ,p) takes the form of either (Z,τj,2πω+j) or (ˉZ2,τj,2πω+j). Hence the connected component C(Z,τj,2πω+j) through (Z,τj,2πω+j) in L is unbounded [33].

    By representation of τj, there exists a j>0 such that

    τjj+1<2πω+j<τj,τjJ+.

    Therefore, it has that τj+1<T<τ if (ˉZ,τ,T)C(Z,τj,2πω+j), which shows that the projection of C(Z,τj,2πω+j) is bounded onto the T-space. On the other hand, Lemmas 4 and 5 imply that the projection of C(Z,τj,2πω+j) is bounded for τProjτ(Z,τj,2πω+j)(Aj,Bj) onto the Z-space. Therefore, either [Aj,τj]Projτ(Z,τj,2πω+j)(Aj,Bj) or [τj,Bj]Projτ(Z,τj,2πω+j)(Aj,Bj) holds. If not, C(Z,τj,2πω+j) is unbounded and Projτ(Z,τj,2πω+j)(Aj,Bj), which leads to a contradict.

    In this section, we shall use Matlab to perform some numerical simulations on system (1.4). We choose ϕ(X)=X and the parameter values as follows:

    r=2,A=50,β=1,β1=0.6,ν=0.5,ρ=0.4. (7.1)

    By computing, we obtain τc5.9915. From Figures 1 and 2, we can see that, for n=0, Sn(τ)=0 has two roots and θ(τ) intersects τω+(τ) twice at τ00.123 and τ13.5462. When n1 and τ[0,τc), Sn(τ)=0 has no roots and θ(τ)+2nπ has no point of intersection with τω+(τ). We choose the initial functions X(t)=2 and Y(t)=1 for t[τ,0].

    Figure 1.  (τ,Sn(τ)) plots, n=0,1,2.
    Figure 2.  θ(τ)+2nπ(n=0,1,2) and τω+ plots.

    Under the parameters (7.1), one can easily verify that E(2.5,1.9) is stable in absence of delay. For a small delay (τ=0.05), the equilibrium E is stable (see Figure 3). However, when τ increases to τ00.123, E becomes unstable because a Hopf bifurcation occurs at the moment. At the same time, a periodic orbit surrounding E produces (see Figure 4 for τ=0.13), and by computing in sections 4 and 5, we can obtain ω0=0.9415,ReC1(0)=273.9906<0, hence, the bifurcation periodic solution is stable. When τ changes from 0.13, the periodic solution changes its shape slightly (see Figure 5). As τ increasing, it returns to a periodic solution (see Figure 6). When τ4, the periodic orbit disappears and E restores stability (see Figure 7) and remains stability until τ5.9915. When τ=7>5.9915, zooplankton population dies out (see Figure 8). It can find that these results are consistent with the ahead theoretical analyses.

    Figure 3.  For τ=0.05, E is stable.
    Figure 4.  For τ=0.13, E is unstable and a stable periodic solution appears.
    Figure 5.  For τ=0.5, a periodic-like solution appears.
    Figure 6.  For τ=3.5, the periodic solution appears again.
    Figure 7.  Periodic solution disappears and E regains stability for τ=4.
    Figure 8.  E disappears and E1 regains stability when τ=7>5.9915.

    In this paper, a system of describing the relationship between TPP and zooplankton is investigated. The process of toxin liberation uses the general function ϕ(X) with the restrictions (1.5). We induce two discrete delays to the consume response function and distribution of toxin term to explore the dynamical behavior as delay varying. By analysing the ODE system, we obtains the parameters conditions for the asymptotical stability of equilibrium. At the same time, if the natural death rate of zooplankton exceeds the threshold parameter, then zooplankton will die out ultimately and phytoplankton will persist, which means that phytoplankton bloom may break out. On the contrary, if the natural death rate of zooplankton is less than the threshold parameter, then phytoplankton and zooplankton will persistent coexistence and the number remains at a certain level, which means phytoplankton bloom can't occur. In this situation, the natural death rate of zooplankton is an important factor to the occurrence of phytoplankton bloom.

    By analysing the system with time delay, we find that system (1.4) may occur the stable switches as delay changing. And Theorem 4.4 shows that although system (1.4) undergoes stability switches, system (1.4) is ultimately stable, which is significantly different from the stability switching phenomenon of a time-delay system with coefficients without parameters. Moreover, the global existence of periodic solutions is obtained, that is, under certain conditions, multiple positive periodic solutions will exist as delay changing. The results show that the delay (gestation delay from zooplankton and maturity delay of TPP) is a key factor to the periodic outbreaks of phytoplankton bloom. If the delay is more than some value, then zooplankton will die out and phytoplankton bloom can occur. If the delay is less than some value, then under the certain conditions, phytoplankton number will have periodic oscillations, which means the periodic outbreaks of phytoplankton bloom. System (1.4) generalize the system in [21,22,23] and these results obtained in this paper can also apply to above systems.

    Z. Jiang was supported by National Natural Science Foundation of China (Nos. 11801014 and 11875001), Natural Science Foundation of Hebei Province (No. A2018409004), Support Plan for Hundred Outstanding Innovative Talents of Colleges and Universities in Hebei Province and Talent Training Project of Hebei Province; T. Zhang was supported by SDUST Research Funds (No. 2014TDJH102) and Scientific Research Foundation of Shandong University of Science and Technology for Recruited Talents.

    The authors declare that there are no conflicts of interest regarding the publication of this paper.



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