Over the years, predator-prey models described by the ordinary differential equations (ODEs), which were proposed and studied widely due to the pioneering theoretical works by Lotka [1] and Volterra [2].
A most crucial element in these models is the functional response, the function that describes the number of prey consumed per predator per unit time for given quantities of prey $x$ and predator $y.$
Arditi and Ginzburg [3] suggested that the essential properties of predator-dependence could be rendered by a simpler form which was called ratio-dependence. The trophic function is assumed to depend on the single variable $\frac{x}{y}$ rather than on the two separate variables $x$ and $y.$ Generally, a ratio-dependent predator-prey model of Arditi and Ginzburg [3] is
In this paper, we will focus our attention on the ratio-dependent type predator-prey model with Michaelis-Menten type functional response, which takes the form of
where $\alpha, \beta, m, d_{3}$ and $\beta_{1}$ are positive constants. $d_{3}, \beta, m$ and $\beta_{1}$ stand for the predator death rate, capturing rate, half saturation constant, and conversion rate, respectively. The dynamics of predator-prey system was studied extensively [4-11].
In order to reflect that the dynamical behaviors of models that depend on the past history of the system, it is often necessary to incorporate time-delays into the models. Suppose that in a certain environment there are the prey and predator species with respective population densities $x(t)$ and $y(t)$ at time $t.$
Based on the above discussion, by incorporating age-structure of prey and time delay into system (1.2) and suppose that the predator species captures only the adult prey species, we establish the following model
where $x_{1}(t), x_{2}(t), y(t)$ represents the densities of immature prey, mature prey and predator, respectively, $\alpha, d_{1}, d_{2}, d_{3}, \beta, \gamma, m, \mu$ and $\beta_{1}$ stand for the birth rate of prey, the immature prey death rate, the mature prey death rate, the predator death rate, capturing rate, the conversion rate of immature prey to mature prey, half saturation constant, the density dependence rate of the mature prey and conversion rate, respectively. $\tau$ is called the maturation time of the prey species.
In this section, we will discuss the local stability of a positive equilibrium and the existence of Hopf bifurcations in system (1.3). It is easy to deduce that system (1.3) has a unique positive equilibrium $E^{*}=(x_{1}^{*}, x_{2}^{*}, y^{*})$ if the following holds.
(H1) $\alpha>\gamma, \beta_{1}>d_{3}$ and $(\gamma-d_{2})(\beta_{1}-d_{3})>\frac{\beta(\beta_{1}-d_{3})^{2}}{m\beta_{1}}, $ where
Set
Then we can get the linear part of system (1.3),
where $p_{i}~(i=1, 2, 3, 4, 5, 6, 7)$ are defined in (2.1).
Therefore the corresponding characteristic equation [18] of system (2.2) is
It is well-known that the zero steady state of system (2.2) is asymptotically stable if all roots of eq. (2.3) have negative real parts, and is unstable if eq.(2.3) has a root with positive real part. In the following, we will study the distribution of roots of eq.(2.3).
Obviously, $\lambda=p_{1}=-d_{1} < 0$ is a negative root of eq.(2.3).
If $i\omega(\omega>0)$ is a root of eq.(2.3), then
Separating the real and imaginary parts of above formula gives the following equations:
which implies that
Let
further note that if
then $(p_{4}p_{7}-p_{5}p_{6})^{2}-p_{3}^{2}p_{7}^{2}<0, $ we will derive $\triangle>0.$
Positive root of the equation (2.4) is given by
Again from (2.4), we get
Solving for $\tau_{0}, $ we get
where $n=0, 1, 2, 3, \cdots.$
The smallest $\tau_{0}$ is obtained by choosing $n=0, $ then from (2.5), we get
then $(\tau_{0n}, \omega_{0})$ solves eq. (2.4). This means that when $\tau=\tau_{0n}, $ eq. (2.3). has a pair of purely imaginary roots $\pm i\omega_{0}.$
Now let us consider the behavior of roots of eq. (2.3) near $\tau_{0n}.$ Denote $\lambda(\tau)=\alpha(\tau)+i\omega(\tau)$ as the root of eq. (2.3) such that
Substituting $\lambda(\tau)$ into eq. (2.3i) and differentiating both sides of it with respect to $\tau, $ we have
Noting that $\lambda=\pm i\omega_{0}, \omega_{0}$ satisfy (2.5), therefore, we have
where we have used eqs. (2.4), (2.6) and $\Gamma=p_{3}^{2}\omega_{0}^{4}+p_{3}^{2}p_{7}^{2}\omega_{0}^{2}>0.$ Hence, it follows that
Therefore, when the delay $\tau$ near $\tau_{0n}$ is increased, the root of eq. (2.3) crosses the imaginary axis from left to right. In addition, note that when $\tau=0, $ eq. (2.3) has roots with negative real parts only if
(H3) $p_{3}+p_{4}+p_{7}<0$ and $p_{3} p_{7}+p_{4} p_{7}-p_{5} p_{6}>0.$
Thus, summarizing the above remarks and the well-known Rouche theorem, we have the following results on the distribution of roots of eq. (2.3).
Lemma 2.1. Let $\tau_{0n} (n=0, 1, 2, \cdots)$ be defined as in (2.7). Then all roots of eq.(2.3) have negative real parts for all $\tau\in [0, \tau_{0}).$ However, eq. (2.3) has at least one root with positive real part when $\tau> \tau_{0}, $ and eq.(2.3) has a pair of purely imaginary root $\pm i\omega_{0}, $ when $\tau= \tau_{0}.$ More detail, for $\tau\in (\tau_{0n}, \tau_{0n+1}](n=0, 1, 2, \cdots), $ eq. (2.3) has $2(n+1)$ roots with positive real parts. Moreover, all roots of eq. (2.3) with $\tau=\tau_{0n}(n=0, 1, 2, \cdots) $ have negative real parts except $\pm i\omega_{0}.$
Applying Lemma 2.1, Theorem 11.1 developed in [12], we have the following results.
Theorem 2.1. Let (H1), (H2) and (H3) hold. Let $\omega_{0}$ and $\tau_{0n}(n=0, 1, 2, \cdots) $ be defined as in (2.6) and (2.7), respectively.
(ⅰ) The positive equilibrium $E^{*}$ of system (1.2) is asymptotically stable for all $\tau\in [0, \tau_{0})$ and unstable for $\tau>\tau_{0}.$
(ⅱ) System (1.3) undergoes a Hopf Bifurcation at the positive equilibrium $E^{*}$ when $\tau=\tau_{0n}(n=0, 1, 2, \cdots) $.
In section 2, we have proven that system (1.3) has a series of periodic solutions bifurcating from the positive equilibrium $E^{*}$ at the critical values of $\tau.$ In this section, we derive explicit formulae to determine the properties of the Hopf bifurcation at critical values $\tau_{0n}$ by using the normal form theory and center manifold reduction[13].
Without loss of generality, denote the critical values $\tau_{0n}$ by $\bar{\tau}, $ and set $\tau=\bar{\tau}+\mu.$ Then $\mu=0$ is a Hopf bifurcation value of system (1.3). Thus, we can work in the phase space $C=C([-\bar{\tau}, 0], R^{3}).$
Let $u_{1}(t)=x_{1}(t)-x_{1}^{*}, u_{2}(t)=x_{2}(t)-x_{2}^{*}, u_{3}(t)=y(t)-y^{*}.$ Then system (1.3) is transformed into
where
here $f^{(1)}$, $f^{(2)}$ and $f^{(3)}$ are defined in (2.1).
For the simplicity of notations, we rewrite (3.1) as
where $u(t)=(u_{1}(t), u_{2}(t), u_{3}(t))^{T}\in R^{3}, u_{t}(\theta)\in C $ is defined by $u_{t}(\theta)=u(t+\theta), $ and $L_{\mu}: C\rightarrow R, f: R\times C\in R$ are given by
and
respectively. By Riesz representation theorem, there exists a function $\eta(\theta, \mu)$ of bounded variation for $\theta\in [-\bar{\tau}, 0]$ such that
for $\phi \in C.$
In fact, we can choose
where $\delta$ is the vector, whose components are the Dirac delta functions. For $\phi\in C^{1}([-\bar{\tau}, 0], R^{3}), $ define
Then system (3.2) is equivalent to
where $x_{t}(\theta)=x(t+\theta)$ for $ \theta\in [-\bar{\tau}, 0].$
For $\psi\in C^{1}([0, \bar{\tau}], (R^{3})^{*}), $ define
and a bilinear inner product
where $\eta(\theta)=\eta(\theta, 0).$ Then $A(0)$ and $A^{*}$ are adjoint operators. By discussions in Section 2 and foregoing assumption, we know that $\pm i\omega_{0}$ are eigenvalues of $A(0).$ Thus, they are also eigenvalues of $A^{*}.$ We first need to compute the eigenvector of $A(0)$ and $A^{*}$ corresponding to $i\omega_{0}$ and $-i\omega_{0}, $ respectively.
Suppose that $q(\theta)=(\rho_{1}, 1, \rho_{2})^{T}e^{i\omega_{0}\theta}$ is the eigenvector of $A(0), $ (3.5) and (3.6) that
We therefore derive that
On the other hand, suppose that $q^{*}(s)=D(\sigma_{1}, 1, \sigma_{2})e^{i\omega_{0}s}$ is the eigenvector of $A^{*}$ corresponding to $-i\omega_{0}.$ From the definition of $A^{*}, $ (3.5) and (3.6), we have
which yields
In order to assure $〈q^{*}(s), q(\theta)〉=1, $ we need to determine the value of D. From (3.7), we have
Thus, we can choose
such that $〈q^{*}(s), q(\theta)〉 =1, $ $〈q^{*}(s), \bar{q}(\theta)〉 =0.$
In the remainder of this section, we will compute the coordinates to describe the center manifold $C_{0}$ at $\mu=0.$ Let $u_{t}$ be the solution of eq.(3.2) with $\mu=0.$
Define
On the center manifold $C_{0}$ we have $W(t, \theta)=W(z(t), \bar{z}(t), \theta), $ where
$z$ and $\bar{z}$ are local coordinates for center manifold $C_{0}$ in the direction of $q^{*}$ and $\bar{q}^{*}.$
Note that $W$ is real if $u_{t}$ is real. We only consider real solutions. For the solution $u_{t}\in C_{0}$ of (3.2), since $\mu=0, $ we have
We rewrite (3.10) as $\dot{z}=i\omega_{0}z+g(z, \bar{z})$ with
Noting that
and $q(\theta)=(\rho_{1}, 1, \rho_{2})^{T}e^{i\theta\omega_{0}}, $ we have
thus, it follows from (3.4) and (3.11) that
Comparing the coefficients in (3.11), we get
We now compute $W_{20}(\theta)$ and $W_{11}(\theta).$ It follows from (3.7) and (3.9) that
On the other hand, on $C_{0}$ near the origin
we derive from (3.13)-(3.15) that
It follows from (3.11) and (3.13) that for $\theta\in [-\bar{\tau}, 0), $
Comparing the coefficients in (3.14) and formula of $g(z, \bar{z})$ gives that for $\theta\in [-\bar{\tau}, 0), $
We derive from (3.16) and (3.18) and the definition of A that
Note that $q(\theta)=q(0)e^{i\omega_{0}\theta}, $ it follows that
where $C_{1}=(C_{1}^{(1)}, C_{1}^{(2)}, C_{1}^{(3)})\in R^{3}$ is a constant vector.
Similarly, from (3.16) and (3.19), we can obtain
where $C_{2}=(C_{2}^{(1)}, C_{2}^{(2)}, C_{2}^{(3)})\in R^{3}$ is a constant vector.
In the following, we seek appropriate $C_{1}$ and $C_{2}.$ From the definition of A and (3.16), we obtain
where $\eta(\theta)=\eta(0, \theta).$ From (3.13), it follows that
Substituting (3.20) and (3.24) into (3.22) and noticing that
we obtain
which leads to
It follows that
Similarly, substituting (3.21) and (3.25) into (3.23), we get
Thus, we can determine $W_{20}(\theta)$ and $W_{11}(\theta)$ from $(3.20)$ and $(3.21).$ Furthermore, we can determine $g_{21}.$ Therefore, each $g_{ij}$ in (3.12) is determined by the parameters and delay in system (3.1). Thus, we can compute the following values
which determine the quantities of bifurcating periodic solutions in the center manifold at the critical value $\bar{\tau}, $ i.e., $\mu_{2}$ determines the direction of the Hopf bifurcation: if $\mu_{2}>0(\mu_{2}<0), $ then the Hopf bifurcation is supercritical(subcritical) and the bifurcating periodic solutions exist for $\tau>\bar{\tau}(\tau<\bar{\tau});$ $\beta_{2}$ determines the stability of the bifurcating periodic solutions: the period increase (decrease) if $T_{2}>0(T_{2}<0).$
From what has been discussed above, we could determine the stability and direction of periodic solutions bifurcating from the positive equilibrium $E^{*}$ at the critical pint $\tau_{0n}.$