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Existence and stability of a unique almost periodic solution for a preypredator system with impulsive effects and multiple delays
Advances in Difference Equations volumeÂ 2016, ArticleÂ number:Â 187 (2016)
Abstract
In this paper, a nonautonomous almost periodic preypredator system with impulsive effects and multiple delays is considered. By the meanvalue theorem of multiple variables, integral inequalities, differential inequalities, and other mathematical analysis skills, sufficient conditions which guarantee the permanence of the system are obtained. Furthermore, by constructing a series of Lyapunov functionals, we derive that there exists a unique almost periodic solution of the system which is uniformly asymptotically stable. Finally, a numerical example and some simulations are presented to support our theoretical results.
1 Introduction
It is widely known that predation is a very common ecological phenomenon in the natural world, and research on the dynamics of the preypredator system is extremely meaningful and important in many fields, such as protecting varieties of the biological species, maintaining ecological balance, agricultural pests control and management, etc. As research of the preypredator system is concerned, the earliest work dates back to the great contribution of Lotka (1925) and Volterra (1926). However, based on the classic LotkaVolterra model, many ecologists found that the predation rate was not just simply proportional to the product of the density of the predator and prey. It was always different for different systems. Then the conception of the functional response was proposed. Functional response refers to the predation rate per predator with a response to changes in the prey density, i.e., predation effects of predators on the prey.
Since then, studies depending on all kinds of functional responses sprang up quickly, such as of Holling type [1â€“3], MichaelisMenton type [4], BeddingtonDeAngelis type [5], Ivlev type [6], HassellVarley type [7], and so on. In 1989, Crowley and Martin [8] proposed a new functional response that can accommodate interference between predators. It is similar to the wellknown BeddingtonDeAngelis functional response but has an additional term in the first right term equation modeling mutual interference between the predator terms.
CrowleyMartin type functional response is used for data sets that indicate feeding rate that is affected by predator density. It is assumed that predator feeding rate decreases by higher predator density even when prey density is high, and effects of predator interference in feeding rate remain important all the time whenever an individual predator is handling or searching for a prey at a given instant of time. And the formula of the per capita feeding rate Crowley and Martin proposed in [8] is as follows:
Here m, Î±, Î² are positive parameters that describe the effects of capture rate handling time and the magnitude of interference among predators, respectively, on the feeding rate.
On the one hand, since models with CrowlyMartin functional response can be generated by a number of natural mechanisms and admits rich but biological dynamics. However, to the best of our knowledge, references reported on this functional response seems to much less until recent several years (see [9â€“13]) for the form of the functional response is relatively complex, for the form of this functional response is relatively complex, and it is worthwhile to further study the models with it.
Recently, Liu et al. in [12] considered a stochastic preypredator system with CrowleyMartin type functional response as follows:
in which they obtained the condition of the global existence of a unique positive solution and the stochastic permanence of the positive solution to the model. Furthermore, it is shown that both the prey and the predator species will become extinct with probability one if the noise is sufficiently large.
Yin et al. in [13] studied the following modified LeslieGower predatorprey model with CrowleyMartin functional response and spatial diffusion under a homogeneous Neumann boundary condition:
in which they obtained some important qualitative properties, including the existence of the global positive solution, the dissipation and persistence of the two species, the local and global asymptotic stability of the constant equilibria, and Hopf bifurcation around the interior constant equilibrium.
On the other hand, it is well known that there are many natural or manmade factors in the real world, such as earthquake, flooding, drought, cropdusting, planting, hunting and harvesting. These kinds of factors can bring sudden changes to an ecological system, and the intrinsic discipline of the environment or the species in the system will often undergoes these changes in a relatively short interval, usually we could regard it happens at some fixed times. From the viewpoint of mathematics, such sudden changes could be described by the impulsive effects to the system. In addition, when a preypredator system is studied, it is more reasonable to consider time delay during the predation, because there is often a digest time instead of transforming food into intrinsic growth rate of the predator. As far as the impulsive system is concerned, there have appeared much excellent work in the last decades, such as impulsive effects in ecological systems (see [14â€“21]), in epidemic systems (see [22]) and in the neural network models (see [23â€“25]). Besides, there are many important monographs in this field (see [26â€“28]).
Particularly, research on the impulsive system with delays still seems to be a hot issue (see [29â€“37]), and these kinds of hybrid systems are usually called impulsive functional systems. When an impulsive functional system is concerned, the difficulty both in the impulsive differential equation and in the functional differential equation will occur at the same time, then the dynamical behaviors, such as permanence, periodic solution, almost periodic solution, and its asymptotical stability properties, as well as bifurcations and chaotic behaviors etc., might be richer, more complex, and more interesting.
Enlightened by the above literature, we propose an almost periodic preypredator system with CrowlyMartin type functional response and impulsive effects in this paper, in which digest delays are also considered in the process of predation, and the final model is as follows:
where \(x(t)\), \(y(t)\) are population densities of the predator and the prey at time t, respectively. \(\tau_{i}\) (\(i=1,2,3,4\)) are all nonnegative constants, \(d_{j}(t)\) (\(j = 1,2\)) denote the inner density resistance of the predator and of the prey. \(h_{jk}>1\), \(j = 1,2\), \(k\in N\), when \(h_{jk}>0\), the impulsive effects represent planting, while \(h_{jk}<0\) represents the impulsive denote harvesting.
Throughout the present paper, we define
for any bounded function \(f(t)\) defined on \(R^{+}=[0,+\infty)\).
Further, we assume that

(C1)
\(r_{i}(t)\), \(c_{i}(t)\), \(d_{i}(t)\) (\(i=1,2\)), \(\alpha(t)\) and \(\beta(t)\) are all bounded and positive almost periodic functions;

(C2)
\(H_{i}(t)= \prod_{0< t_{k}< t}(1+h_{ik})\), \(i=1,2\), \(k\in N\) is almost period functions and there exist positive constants \(H^{u}_{i}\) and \(H^{l}_{i}\) such that \(H^{l}_{i}\leq H_{i}(t)\leq H^{u}_{i}\).
The rest of this article is organized as follows: In SectionÂ 2, we will give some definitions and several useful lemmas for the proof of our main results. In SectionÂ 3, we will state and prove our main results such as permanence of the system, existence, and the uniqueness of an almost periodic solution which is uniformly asymptotically stable by constructing a series of Lyapunov functionals. In the last section, we give a numerical examples to support our theoretical results, then provide a brief discussion and summary of our main results.
2 Preliminaries
In this section, we will state the following definitions and lemmas, which will be used in the next sections.
We have \(K= \{{t_{k}}\in R t_{k}< t_{k+1}, k\in N, \lim_{k\rightarrow\pm\infty}t_{k}=\pm\infty \}\), and we thus denote the set of all sequences that are unbounded and increasing. Let \(D\subset\Omega\), \(\Omega\neq\Phi\), \(\tau= \max_{1\leq i\leq4}\{2\tau_{i}\}\), \(\xi_{0}\in R\). Also, we denote \(\operatorname{PC}(\xi_{0})\) is the space of all functions \(\phi:[\xi_{0}\tau,\xi_{0}]\rightarrow\Omega\) having points of discontinuity at \(\mu_{1},\mu_{2},\ldots\in [\xi_{0}\tau,\xi_{0}]\) of the first kind and left continuous at these points.
For \(J\subset R\), \(\operatorname{PC}(J,R)\) is the space of all piecewise continuous functions from J to R with points of discontinuity of the first kind \(t_{k}\), at which we have left continuity.
Let \(\phi_{1}, \phi_{2} \in \operatorname{PC}(0)\), denote by \(x(t)=x(t;0,\phi_{1})\), \(y(t)=y(t;0,\phi_{2})\), \(x,y \in\Omega\) the solution of system (4) satisfying the following initial conditions:
Since the solution of system (4) with initial conditions (5) is a piecewise continuous function with points of discontinuity of the first kind, \(t_{k}\), \(k\in Z\), we introduce the following definitions for the almost periodicity.
Definition 2.1
(see [38])
The set of sequence \(\{t_{k}^{j}\}\), \(t^{k}_{j}=t_{k+j}t_{k}\), \(k,j\in N\), \({t_{k}}\in K\) is said to be uniformly almost periodic, if for arbitrary \(\varepsilon>0\) there exists a relatively dense set of Îµalmost periodic common for any sequences.
Definition 2.2
(see [38])
The function \(\varphi\in \operatorname{PC}(R,R)\) is said to be almost periodic if the following conditions hold:

(1)
The set of sequences \(\{t_{k}^{j}\}\), \(t^{k}_{j}=t_{k+j}t_{k}\), \(k,j\in N\), \({t_{k}}\in K\) is uniformly almost periodic.

(2)
For any \(\varepsilon>0\), there exists a real number \(\delta>0\), such that if the points \(t_{1}\) and \(t_{2}\) belong to one and the same interval of continuity of \(\varphi(t)\) and satisfy the inequality \( t_{1}t_{2} <\delta\), then \(\varphi(t_{1})\varphi(t_{2}) < \varepsilon\).

(3)
For any \(\varepsilon>0\), there exists a relatively dense set T such that if \(\eta\in T\), then \(\varphi(t+\eta)\varphi(t)  <\varepsilon\) for all \(t\in R\) satisfying the condition \( tt_{k} > \varepsilon\), \(k\in N\). The elements of T are called Îµalmost periods.
For the following system:
with initial value
Here the expressions of the functions \(A(t)\), \(B(t)\), \(C_{i}(t)\), \(D_{i}(t)\), \(i=1,2\), are given as follows:
In the following, we will give some useful lemmas, which will be used in the next sections.
Lemma 2.1
Assume that \((u(t),v(t))^{T}\) is any solution of system (6) with the initial conditions (7), then \(u(t)>0\), \(v(t)>0\) for all \(t\in R^{+}\).
Proof
Let
Then from system (6) we have
This completes the proof of this lemma.â€ƒâ–¡
Lemma 2.2
For system (4) and system (6), we have the following results:

(1)
If \((u(t),v(t))^{T}\) is a solution of system (6), then
$$\bigl(x(t),y(t)\bigr)^{T}= \biggl( \prod_{0< t_{k}< t}(1+h_{1k})u(t), \prod_{0< t_{k}< t}(1+h_{2k})v(t) \biggr)^{T} $$is a solution of system (4).

(2)
If \((x(t),y(t))^{T}\) is a solution of system (4), then
$$\bigl(u(t),v(t)\bigr)^{T}= \biggl( \prod_{0< t_{k}< t}(1+h_{1k})^{1}x(t), \prod_{0< t_{k}< t}(1+h_{2k}) (1+h_{1k})^{1}y(t) \biggr)^{T} $$is a solution of system (6).
Proof
(1) \((u(t),v(t))^{T}\) is a solution of system (6). That is, for any \(t\neq t_{k}\), \(k\in N\),
is a solution of system (6), which yields
By the previous definitions of the functions \(A(t)\), \(B(t)\), \(C_{i}(t)\), and \(D_{i}(t)\), \(i=1,2\), it follows from the simplification of (8) and (9) that
On the other hand, when \(t=t_{k}\), \(k\in N\), we have
Combined (10) with (11) and (12), we can see that \((x(t),y(t))^{T}\) is the solution of the impulsive system (4).
(2) Because \(u(t)\) and \(v(t)\) are continuous on each interval \((t_{k},t_{k+1}]\), we only need to check the continuity of \(u(t)\) and \(v(t)\) at the impulsive point \(t=t_{k}\), \(k\in N\).
Since
we have
Similarly, we can check that
Thus, \(u(t)\) and \(v(t)\) are continuous on \([0,+\infty)\).
On the other hand, similar to the above proof of step (1), we can verify that \((u(t),v(t))^{T}\) satisfies system (6).
Then \((u(t),v(t))^{T}\) is a solution of the nonimpulsive system (6).
This completes the proof of LemmaÂ 2.2.â€ƒâ–¡
Lemma 2.3
(see [39])

(1)
Assume that for \(w(t)>0\), \(t\geq0\), we have
$$w'(t) \leq w(t) \bigl(abw(t\tau) \bigr) $$with initial conditions \(w(s)=\phi(s) \geq0\), \(s\in[\tau,0]\), where a, b are positive constants, then there exists a positive constant \(w^{*}\) such that
$$\lim_{t\rightarrow\infty}\sup w(t) \leq w^{*}:= \frac{ae^{a\tau}}{b}. $$ 
(2)
Assume that for \(w(t)>0\), \(t\geq0\), we have
$$w'(t) \geq w(t) \bigl(cdw(t\tau) \bigr) $$with initial conditions \(w(s)=\phi(s) \geq0\), \(s\in[\tau,0]\), where c, d are positive constants, then there exists a positive constant \(w_{*}\) such that
$$\lim_{t\rightarrow\infty}\inf w(t) \geq w_{*}:= \frac{ce^{(cdw^{*})\tau}}{d}. $$
Let \(R^{2}\) be the plane Euclidean space with element \(X=(x,y)^{T}\) and norm \(X_{0}=x+y\), \(C=C([\tau,0],R^{2})\), \(B\in R^{+}\), and denote \(C_{B}= \{\varphi=(\varphi_{1}(s),\varphi_{2}(s))^{T} \in C \\varphi \\leq B \}\) with \(\\varphi\= \sup_{s\in[\tau ,0]}\varphi(s)_{0}= \sup_{s\in[\tau,0]} (\varphi_{1}(s)+\varphi_{2}(s) )\).
Consider the following almost periodic system with delay:
where \(f(t,\varphi)\) is continuous in \((t,\varphi)\in R\times C_{B}\) and almost periodic in t uniformly for \(\varphi\in C_{B}\), \(\forall \rho>0\), \(\exists M(\rho)>0\) such that \(f(t,\varphi) \leq M(\rho)\) as \(t\in R\), \(\varphi\in C_{\rho}\), while \(x_{t}\in C_{B}\) is defined as \(x_{t}(s)=x(t+s)\) for \(s\in[\tau,0]\).
The associated product system of (16) is in the form of
Then by the conclusions of [38, 40], we have LemmaÂ 2.4.
Lemma 2.4
(see [40])
For \(\phi,\psi\in C_{B}\), suppose that there exists a Lyapunov function \(V(t,\phi,\psi)\) defined on \(R^{+}\times C_{B}\times C_{B}\) satisfying the following three conditions:

(1)
\(u (\\phi\psi\ ) \leq V(t,\phi,\psi) \leq v (\\phi\psi\ )\), where \(u,v\in\mathcal{P}\) = {\(u:R^{+}\rightarrow R^{+} u\) is continuous increasing function and \(u(s)\rightarrow0\), as \(s\rightarrow0\)};

(2)
\(V(t,\bar{\phi},\bar{\psi})V(t,\hat{\phi}, \hat {\psi})\leq L (\\bar{\phi}\hat{\phi}\+\\bar{\psi }\hat{\psi}\ )\), where L is a positive constant;

(3)
\(D^{+}V(t,\phi,\psi)_{\text{(17)}}\leq\gamma V(t,\phi,\psi)\), where Î³ is a positive constant.
Further, assume that (16) has a solution \(x(t,v,\phi)\) such that \(x(t,v,\phi)\leq B_{1}\) for \(t\geq v \geq0\), \(B>B_{1}>0\). Then system (16) has a unique almost periodic solution which is uniformly asymptotically stable.
Lemma 2.5
(see [36])
For any \(x,y,u,v\in R\), we have the following important inequality:
3 Main results
First in this section we will give some notations as follows:
Theorem 3.1
Assume that (C1) and (C2) hold, suppose further that

(C3)
\(C^{u}_{1}< B^{l}r^{l}_{1}\),
then any positive solution \((u(t),v(t))^{T}\) of system (6) satisfies
Proof
Let \((u(t),v(t))^{T}\) be any solution of system (6), then from the first equation of (6),
By the first conclusion of LemmaÂ 2.3, we have
Similarly, by the second equation of system (6),
which leads to
Therefore, there exists a \(T_{1}>0\), such that \(v(t)\leq v^{*}\) when \(t>T_{1}\).
Thus, when \(t>T_{1}+\tau\), from the first equation of system (6) again we have
Then by the second conclusion of LemmaÂ 2.3, we have
On the other hand, from the second equation of system (6) again, we can get
Then, by the second conclusion of LemmaÂ 2.3 again, we have
Thus, we complete the proof of this theorem by combining (19), (20), (21), and (22).â€ƒâ–¡
Theorem 3.2
Assume that (C1)(C3) hold, then any positive solution \((x(t),y(t))^{T}\) of system (4) satisfies
Proof
Since \((x(t),y(t))^{T}\) is a solution of system (4), then by the second conclusion of LemmaÂ 2.2,
is a solution of system (6).
Then it follows from TheoremÂ 3.1 that
which implies that
This completes the proof of this theorem.â€ƒâ–¡
Remark 3.1
Suppose that (C1)(C3) hold, then system (6) is permanent.
Before we discuss the existence and uniformly asymptotically stability of a unique almost periodic solution of system (4), we will introduce the following notations first:
where
Theorem 3.3
Assume that (C1)(C3) hold, further assume that

(C4)
positive \(\lambda_{1}\) and \(\lambda_{2}\) exist, such that \(\frac{\alpha_{1}}{\beta_{1}}<\frac{\lambda_{1}}{\lambda _{2}}<\frac{\alpha_{2}}{\beta_{2}}\),
then system (4) admits a unique almost periodic solution which is uniformly asymptotically stable.
Proof
At first, we prove that system (6) has a unique uniformly asymptotically stable almost periodic solution.
In order to achieve this aim, we take a transformation
Then system (6) is transformed into following system:
Suppose that \(U_{1}(t)= (x_{1}(t),y_{1}(t) )^{T}\) and \(U_{2}(t)= (x_{2}(t),y_{2}(t) )^{T}\) are any two solutions of system (29), then the product system of (29) reads
Denote
For any \(\Phi=(\phi_{1},\phi_{2})^{T}=(x_{1t},y_{1t})^{T}\in S^{*}\), we can choose \(\Psi=(\psi_{1},\psi_{2})^{T}=(x_{2t},y_{2t})^{T}\in S^{*}\) such that
Consider a Lyapunov functional \(V(t)=V(t,\Phi,\Psi )=V(t,(x_{1t},y_{1t})^{T},(x_{2t},y_{2t})^{T})\) defined on \(R^{+}\times S^{*}\times S^{*}\) as follows:
where
According to the definitions of \(S^{*}\) and \(V(t)=V(t,\Phi,\Psi)\), there is some positive constant M large enough such that
By the structure of \(V(t)\), it is easy to see that
where \(\underline{\lambda}=\min\{\lambda_{1},\lambda_{2}\}>0\).
Moreover, by the integrative inequality and the absolutevalue inequality properties we have
where
Let \(u,v\in C(R^{+},R^{+})\), choose \(u=\underline{\lambda}s\), \(v=\bar {\lambda}s\), then the first condition of LemmaÂ 2.4 is satisfied.
For \(\forall \bar{\Phi}=(x_{1t},y_{1t})^{T},\bar{\Psi }=(x_{2t},y_{2t})^{T},\hat{\Phi}=(x^{*}_{1t},y^{*}_{1t})^{T},\hat{\Psi }=(x^{*}_{2t},y^{*}_{2t})^{T}\in S^{*}\), then from the previous definitions of \(V_{i}(t)\), \(i=1,2,3,4\), it is easy to calculate that
Then it follows from inequality (19) in LemmaÂ 2.5 that
which yields
This means the second condition of LemmaÂ 2.4 is satisfied.
Finally, we will prove the last condition of LemmaÂ 2.4.
In fact, calculating the right derivative \(D^{+}V_{1}(t)\) of \(V_{1}(t)\) along the solutions of system (30) we have
It follows from the meanvalue theorem and the product system (30) that
Then
where \(\theta_{1}(t)\) lie between \(x_{1}(t\tau_{1})\) and \(x_{2}(t\tau_{1})\), \(\theta_{2}(t)\) lie between \(x_{1}(t\tau_{3})\) and \(x_{2}(t\tau_{3})\), \(\theta_{3}(t)\) lie between \(y_{1}(t\tau_{4})\) and \(y_{2}(t\tau_{4})\).
That is,
Integrating both sides of (42) on the interval \([t\tau_{1},t]\), we have
which implies that
Similarly, we can get
Thus,
By the same argument, from the second and the fourth equation of system (30) we can derive that
where \(\theta_{4}(t)\) lie between \(y_{1}(t\tau_{2})\) and \(y_{2}(t\tau_{2})\), \(\theta_{5}(t)\) lie between \(x_{1}(t\tau_{3})\) and \(x_{2}(t\tau_{3})\), \(\theta_{6}(t)\) lie between \(y_{1}(t\tau_{4})\) and \(y_{2}(t\tau_{4})\).
Integrating both sides of (47) on the interval \([t\tau_{2},t]\), we have
which leads to
By the same argument, we can obtain
On the other hand, it follows from (47) that
Thus, combined (51) with (49)(50), one can deduce that
Therefore,
On the other hand, according to the structure of \(V_{i}(t)\), \(i=2,3,4\), we can easily calculate the right derivatives \(D^{+}V_{2}(t)\), \(D^{+}V_{3}(t)\), and \(D^{+}V_{4}(t)\) along the solution of system (30) as follows:
From (53)(56), by a simple reduction we can easily give the following estimations for the right derivatives of \(V(t)\):
If we denote \(\delta=\min \{\beta_{1}\frac{\lambda _{2}}{\lambda_{1}}\alpha_{1}, \alpha_{2}\frac{\lambda_{1}}{\lambda_{2}}\beta _{2} \}\), then \(\delta>0\) by the condition (C4).
Thus, it follows from equalities (37) and (38) that
Let \(\gamma= \frac{\underline{\lambda}\Phi (0)\Psi(0)_{0}}{M}\delta\), then \(\gamma>0\) and
This means the last condition of LemmaÂ 2.4 is satisfied. By LemmaÂ 2.4, the system admits a unique uniformly asymptotically stable almost periodic solution \((x(t),y(t))^{T}\).
Thus, by the transformation (28), we can conclude that system (6) admits a unique uniformly asymptotically stable almost periodic solution \((u(t),v(t))^{T}=(e^{x(t)},e^{y(t)})^{T}\).
Finally, we will explain that system (4) has a unique uniformly asymptotically stable almost periodic solution.
In fact, from LemmaÂ 2.2, we know that
is a solution of system (4). Since the condition (C2) holds, similar to the proofs of LemmaÂ 31 and TheoremÂ 79 in [28], we can prove that \((x(t),y(t))^{T}\) is almost periodic. Therefore, \((x(t),y(t))^{T}\) is the unique uniformly asymptotically stable almost periodic solution of system (4) because of the uniqueness and the uniformly asymptotical stability of \((u(t),v(t))^{T}\).
This completes the proof of this theorem.â€ƒâ–¡
4 Numerical simulations and discussions
In this section, we will give a numerical example to illustrate the feasibility of our analytical results, then some discussions of the effects of impulsive perturbations and time delays to the system are referred to in the end of the paper.
Example 4.1
Consider the following nonautonomous preypredator system with impulsive effects and delays:
where \(r_{1}(t)=1.04+0.02\sin(2t)\), \(r_{2}(t)=1.19+0.01\sin(3t)\), \(d_{1}(t)=0.90+0.02\cos(3t)\), \(d_{2}(t)=1.92+0.02\sin(2t)\), \(c_{1}(t)=0.03+0.01\sin(3t)\), \(c_{2}(t)= 0.005+0.001\cos(2t)\), \(\alpha(t)=\beta(t)=1\) are all positive, bounded and almost periodic functions which satisfy the condition (C1) in the paper.
If we can set \(h_{1k}=0.05\), \(h_{2k}=0.06\), \(t_{k}=k\), \(t\in[0,20]\), and choose \(H^{l}_{1}=0.3584\), \(H^{l}_{2}=0.2901\), \(H^{u}_{1}=1\), \(H^{u}_{2}=1\), then it is not difficult to verify
which satisfies the condition (C2).
Furthermore, according to the notations in SectionÂ 3 one can make some simple calculations as follows:
Then it is obvious that \(C^{u}_{1}\approx0.04 < B^{l}r^{l}_{1} \approx 0.2959\), which satisfies the condition (C3) in Theorems 3.2 and 3.3. Meanwhile, with the help of mathematical software such as Maple, we can calculate that
Then we can choose positive constants \(\lambda_{1}=\lambda_{2}=1\), which satisfy
That is to say, the condition (C4) in TheoremÂ 3.3 is also satisfied. Thus, all the conditions of Theorems 3.2 and 3.3 hold, according to the theoretical analysis, system (4) should be permanent and admits a unique uniformly asymptotically stable almost periodic solution. In order to verify this point by numerical simulations, we plot the timeseries of the predator \(x(t)\) (see FigureÂ 1(a)) and the prey \(y(t)\) (see FigureÂ 1(b)). One can see that the population density of the predator oscillates around \(x(t)=1.09\) and the population density of the prey oscillates around \(y(t)=0.59\), this indicates the permanence of the system. The almost periodic phenomenon is also easily observed from the figure. Moreover, we can see that the solution \(U_{1}(t)=(x_{1}(t),y_{1}(t))^{T}\) with initial condition \(x(0)=1.2\), \(y(0)=0.8\) gradually approximate the other solution of \(U_{2}(t)=(x_{2}(t),y_{2}(t))^{T}\) with initial condition \(x(0)=1\), \(y(0)=0.2\), and it proved that the almost periodic case is asymptotically stable.
On the other hand, when the system is permanent, we will show the difference with two different impulsive effects (see FigureÂ 2) and different cases of time delays (see FigureÂ 2). From FigureÂ 2, we can see that both the mean density population of the predator and the prey are decreasing with stronger impulsive effects, such as enhancing the harvesting rate, the efficiency of the insecticides for the species, and so on. In addition, in order to show the effects of the delays to the dynamics of the species, we consider two different cases of time delays, Case 1 (with \(\tau _{1}=0.005\), \(\tau_{2}=0.001\), \(\tau_{3}=0.002\), \(\tau_{4}=0.001\) in FigureÂ 3(a)) and Case 2 (with \(\tau _{1}=0.5\), \(\tau_{2}=1\), \(\tau_{3}= 0.2\), \(\tau_{4}=0.1\) in FigureÂ 3(b)) with the same initial condition \(x(0)=1\), \(y(0)=0.5\). We can see that the mean population density of the bigger time delays (Case 2) is bigger that the smaller ones (Case 1). This suggests that a longer digest delay in the predation may be conductive and could increase the possibility of the permanence of the population.
References
Holling, CS: Some characteristics of simple types of predation and parasitism. Can. Entomol. 9, 385398 (1966)
Hwang, J, Xiao, D: Analyses of bifurcations and stability in a predatorprey system with Holling typeIV functional response. Acta Math. Appl. Sin. 20, 167178 (2004)
Peng, R, Wang, M: Positive steady states of the HollingTanner preypredator model with diffusion. Proc. R. Soc. Edinb. A 135, 149164 (2005)
Hsu, SB, Hwang, TW, Kuang, Y: Global analysis of the MichaelisMenten type ratiodependent predatorprey system. J.Â Math. Biol. 42, 489506 (2001)
Beddington, JR: Mutual interference between parasites and predators and its effect on searching efficiency. J. Anim. Ecol. 44, 331340 (1975)
Kooij, RE, Zegeling, A: A predatorprey model with Ivlevâ€™s functional response. J. Math. Anal. Appl. 198, 473489 (1996)
Hsu, SB, Hwang, TW, Kuang, Y: Global dynamics of a predator prey model with HassellVarley type functional response. Discrete Contin. Dyn. Syst., Ser. B 10, 857875 (2005)
Crowley, PH, Martin, EK: Functional responses and interference within and between year classes of a dragonfly population. J. North Am. Benthol. Soc. 8, 211221 (1989)
Upadhyay, RK, Raw, SN, Rai, V: Dynamical complexities in a tritrophic hybrid food chain model with Holling type II and CrowleyMartin functional responses. Nonlinear Anal., Model. Control 15, 366375 (2010)
Zhuang, K, Wen, Z: Analysis for a food chain model with CrowleyMartin functional response and time delay. World Acad. Sci., Eng. Technol. 61, 562565 (2010)
Ali, N, Jazar, M: Global dynamics of a modified LeslieGower predatorprey model with CrowleyMartin functional responses. J. Appl. Math. Comput. 43, 271293 (2013)
Liu, XQ, Zhong, SM, Tian, BD, Zheng, FX: Asymptotic properties of a stochastic predatorprey model with CrowleyMartin functional response. J. Appl. Math. Comput. 43, 479490 (2013)
Yin, HW, Xiao, XY, Wen, XQ, Liu, K: Pattern analysis of a modified LeslieGower predatorprey model with CrowleyMartin functional response and diffusion. Comput. Math. Appl. 67, 16071621 (2014)
Zhang, H, Li, YQ, Jing, B, Zhao, WZ: Global stability of almost periodic solution of multispecies mutualism system with time delays and impulsive effects. Appl. Math. Comput. 232, 11381150 (2014)
Liu, XX: Impulsive periodic oscillation for a predatorprey model with HassellVarleyHolling functional response. Appl. Math. Model. 38, 14821494 (2014)
Joydip Dhar, D, Kunwer, SJ: Mathematical analysis of a delayed stagestructured predatorprey model with impulsive diffusion between two predators territories. Ecol. Complex. 16, 5967 (2013)
Shao, YF, Li, Y: Dynamical analysis of a stage structured predatorprey system with impulsive diffusion and generic functional response. Appl. Math. Comput. 220, 472481 (2013)
Pei, YZ, Li, CG, Fan, SH: A mathematical model of a three species preypredator system with impulsive control and Holling functional response. Appl. Math. Comput. 219, 1094510955 (2013)
Yao, ZJ, Xie, SL, Yu, NF: Dynamics of cooperative predatorprey system with impulsive effects and BeddingtonDeAngelis functional response. J. Egypt. Math. Soc. 21, 213223 (2013)
Yu, H, Zhong, S, Agarwal, P: Mathematics analysis and chaos in an ecological model with an impulsive control strategy. Commun. Nonlinear Sci. Numer. Simul. 16, 776786 (2011)
Liu, ZJ, Wang, QL: An almost periodic competitive system subject to impulsive perturbations. Appl. Math. Comput. 231, 377385 (2014)
Sekiguchi, M, Ishiwata, E: Dynamics of a discretized SIR epidemic model with pulse vaccination and time delay. J.Â Comput. Appl. Math. 236, 9971008 (2011)
Wang, Y, Zheng, CD, Feng, EM: Stability analysis of mixed recurrent neural networks with time delay in the leakage term under impulsive perturbations. Neurocomputing 119, 454461 (2013)
Wang, C: Almost periodic solutions of impulsive BAM neural networks with variable delays on time scales. Commun. Nonlinear Sci. Numer. Simul. 19, 28282842 (2014)
Zhao, HY: Existence and global exponential convergence of almost periodic solutions for cellular neural networks with variable delays. Chin. J. Eng. Math. 22, 295300 (2005)
Lakshmikantham, V, Bainov, DD, Simeonov, PS: Theory of Impulsive Differential Equations. World Scientific, Singapore (1989)
Bainov, DD, Simeonov, PS: Impulsive Differential Equations: Periodic Solutions and Applications. Longman, Burnt Mill (1993)
Samoilenko, AM, Perestyuk, NA: Impulsive Differential Equations. World Scientific, Singapore (1995)
Liu, Y, Zhao, SW: Controllability analysis of linear timevarying systems with multiple time delays and impulsive effects. Nonlinear Anal., Real World Appl. 13, 558568 (2012)
Wang, L, Yu, M, Niu, PC: Periodic solution and almost periodic solution of impulsive LasotaWazewska model with multiple timevarying delays. Comput. Math. Appl. 64, 23832394 (2012)
Chen, L, Chen, F: Dynamic behaviors of the periodic predatorprey system with distributed time delays and impulsive effect. Nonlinear Anal., Real World Appl. 12, 24672473 (2011)
Zhao, M, Wang, XT, Yu, HG, Zhu, J: Dynamics of an ecological model with impulsive control strategy and distributed time delay. Math. Comput. Simul. 82, 14321444 (2012)
Tian, BD, Zhong, SM, Chen, N, Qiu, YH: Dynamical behavior for a foodchain model with impulsive harvest and digest delay. J. Appl. Math. 2014, Article ID 168571 (2014)
Xiang, ZY, Long, D, Song, XY: A delayed LotkaVolterra model with birth pulse and impulsive effect at different moment on the prey. Appl. Math. Comput. 219, 1026310270 (2013)
He, MX, Chen, FD, Li, Z: Almost periodic solution of an impulsive differential equation model of plankton allelopathy. Nonlinear Anal., Real World Appl. 11, 22962301 (2010)
Zhang, TW, Li, YK, Ye, Y: On the existence and stability of a unique almost periodic solution of Schnonerâ€™s competition model with puredelays and impulsive effects. Commun. Nonlinear Sci. Numer. Simul. 17, 14081422 (2012)
Zhang, H, Georgescu, P, Chen, L: An impulsive predatorprey system with BeddingtonDeAngelis functional response and time delay. Int. J. Biomath. 1, 117 (2008)
He, CY: Almost Periodic Differential Equations. Higher Education Press, Beijing (1992)
Nakata, Y, Muroya, Y: Permanence for nonautonomous LotkaVolterra cooperative systems with delays. Nonlinear Anal., Real World Appl. 11, 528534 (2010)
Zheng, ZX: Theory of Functional Differential Equations. Anhui Education Press, Hefei (1994)
Acknowledgements
This work is supported by the National Natural Science Foundation of China (11372294, 51349011), Scientific Research Fund of Sichuan Provincial Education Department (14ZB0115, 15ZB0113), and Doctoral Research Fund of Southwest University of Science and Technology (15zx7138).
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Tian, B., Zhong, S. & Chen, N. Existence and stability of a unique almost periodic solution for a preypredator system with impulsive effects and multiple delays. Adv Differ Equ 2016, 187 (2016). https://doi.org/10.1186/s1366201609152
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DOI: https://doi.org/10.1186/s1366201609152