- Research Article
- Open Access

# Dynamics of a Predator-Prey System Concerning Biological and Chemical Controls

- HyeKyung Kim
^{1}and - Hunki Baek
^{2}Email author

**2010**:598495

https://doi.org/10.1155/2010/598495

© H. K. Kim and H. Baek. 2010

**Received:**25 August 2010**Accepted:**13 November 2010**Published:**29 November 2010

## Abstract

We investigate an impulsive predator-prey system with Monod-Haldane type functional response and control strategies, especially, biological and chemical controls. Conditions for the stability of the prey-free positive periodic solution and for the permanence of the system are established via the Floquet theory and comparison theorem. Numerical examples are also illustrated to substantiate mathematical results and to show that the system could give birth to various kinds of dynamical behaviors including periodic doubling, and chaotic attractor. Finally, in discussion section, we consider the dynamic behaviors of the system when the growth rate of the prey varies according to seasonal effects.

## Keywords

- Natural Enemy
- Integrate Pest Management
- Periodic Doubling
- Intrinsic Growth Rate
- Impulsive Differential Equation

## 1. Introduction

In recent years controlling insects and other arthropods has become an increasingly complex issue. There are many ways that can be used to help control the population of insect pests. Integrated Pest Management (IPM) is a pest control strategy that uses an array of complementary methods: natural predators and parasites, pest-resistant varieties, cultural practices, biological controls, various physical techniques, and the strategic use of pesticides.

Chemical control is one of simple methods for pest control. Pesticides are often useful because they quickly kill a significant portion of a pest population. However, there are many deleterious effects associated with the use of chemicals that need to be reduced or eliminated. These include human illness associated with pesticide applications, insect resistance to insecticides, contamination of soil and water, and diminution of biodiversity. As a result, it is required that we should combine pesticide efficacy tests with other ways of control. Another important way to control pest populations is biological control. It is defined as the reduction of pest populations by natural enemies and typically involves an active human role. Natural enemies of insect pests, also known as biological control agents, include predators, parasites, and pathogens. Virtually all pests have some natural enemies, and the key to successful pest control is to identify the pest and its natural enemies and release them at fixed times for pest control. Biological control can be an important component of Integrated Pest Management (IPM) programs. Such different pest control tactics should work together rather than against each other to accomplish an IPM program successfully [1, 2].

where the parameters and are the periods of the impulsive immigration or stock of the predator, present the fraction of the prey which dies due to the harvesting or pesticides and so forth, and is the size of immigration or stock of the predator.

In fact, impulsive control methods can be found in almost every field of applied sciences. The theoretical investigation and its application analysis can be found in Bainov and Simeonov [14], Lakshmikantham et al. [15]. Moreover, the impulsive differential equations dealing with biological population dynamics are literate in [16–21]. In particular, Zhang et al. [20] studied the system (1.3) without chemical control. That is, . They investigated the abundance of complex dynamics of the system (1.3) theoretically and numerically.

The main purpose of this paper is to investigate the dynamics of the system (1.3). In Section 3, we study qualitative properties of the system (1.3). In fact, we show the local stability of the prey-free periodic solution under some conditions and give a sufficient condition for the permanence of the system (1.3) by applying the Floquet theory. In Section 4 we numerically investigate the system (1.3) to figure out the influences of impulsive perturbations on inherent oscillation. Finally, in Section 5, we consider the dynamic behaviors of the system when the growth rate of the prey varies according to seasonal effects.

## 2. Basic Definitions and Lemmas

Before stating our main results, firstly, we give some notations, definitions and lemmas which will be useful for our main results.

Let , and . Denote as the set of all of nonnegative integers and as the right hand of the system (1.3). Let , then is said to be in a class if

and exists for each ;

(2) is locally Lipschitzian in .

Definition 2.1.

It is from [15] that the smoothness properties of guarantee the global existence and uniqueness of solutions to the system (1.3).

- (H)

Lemma 2.2 (see [15]).

defined on . Then implies that , where is any solution of (2.3).

Similar result can be obtained when all conditions of the inequalities in the Lemma 2.2 are reversed. Note that if we have some smoothness conditions of to guarantee the existence and uniqueness of the solutions for (2.4), then is exactly the unique solution of (2.4).

From Lemma 2.2, it is easily proven that the following lemma holds.

Lemma 2.3.

Let be a solution of the system (1.3). Then one has the following:

(1)if then for all ;

(2)if then for all .

It follows from Lemma 2.3 that the positive quadrant is an invariant region of the system (1.3).

Then we introduce the following conditions.

() and , where is a set of all piecewise continuous matrix functions which is left continuous at , and is a set of all matrices.

() , .

() There exists a such that .

By equality (2.6) there corresponds to the fundamental matrix and the constant matrix which we call the monodromy matrix of (2.5) (corresponding to the fundamental matrix of ). All monodromy matrices of (2.5) are similar and have the same eigenvalues. The eigenvalues of the monodromy matrices are called the Floquet multipliers of (2.5).

Lemma 2.4 (Floquet theory [14]).

Let conditions (H_{1})–(H_{3}) hold. Then the linear
-periodic impulsive equation (2.5) is

(1)stale if and only if all multipliers of (2.5) satisfy the inequality , and moreover, to those for which , there correspond simple elementary divisors;

(2)asymptotically stable if and only if all multipliers of (2.5) satisfy the inequality ;

(3)unstable if for some .

## 3. Mathematical Analysis

In this section, we have focused on two main subjects, one is about the extinction of the prey and the other is about the coexistence of the prey and the predator. For the extinction, we have found out a condition that the population of the prey goes to zero as time goes by via the study of the stability of a prey-free periodic solution. For example, if the prey is regarded as a pest, it is important to figure out when the population of the prey dies out. For the reason, it is necessary to consider the stability of the prey-free periodic solution. On the other hand, for the coexistence, we have investigated that the populations of the prey and the predator become positive and finite under certain conditions.

### 3.1. Stability for a Prey-Free Periodic Solution

is the solution of (3.1). From (3.2) and (3.3), the following results can be easily obtained without the proof.

Lemma 3.1.

For every solution and every positive periodic solution of the system (3.1), it follows that tend to as . Thus, the complete expression for the prey-free periodic solution of the system (1.3) is obtained .

Now, in the next theorem, the stability of the periodic solution is investigated.

Theorem 3.2.

Proof.

According to Lemma 2.4, is locally stable.

- (1)
It follows from Theorem 3.2 that the population of the prey could be controlled by using chemical or biological control parameters, , , if the other parameters are fixed. (2) Figure 2 illustrates this phenomenon.

### 3.2. Permanence

It might be difficult to find out a necessary condition for the stability of the prey-free periodic solution . Due to this fact, it is natural to have a question what a condition that makes all species coexist is. Before answering the question, first of all, we introduce a definition which keeps the concept of coexistence of the prey and the predator.

Definition 3.4.

From a biological point of view, the populations of the prey and the predator in the system (1.3) cannot increase up to infinity due to restriction of resources. To show this phenomenon for the system (1.3) mathematically, we prove that all solutions to the system (1.3) are uniformly ultimately bounded in the next proposition.

Proposition 3.5.

There is an such that for all large enough, where is a solution of the system (1.3).

Proof.

for . Therefore, is bounded by a constant for sufficiently large . Hence there is an such that for a solution with all large enough.

Thanks to Proposition 3.5, we have only to prove the existence of a positive lower bound for the populations of the prey and the predator to justify the system is permanent.

Theorem 3.6.

Proof.

Suppose is any solution of the system (1.3) with . From Proposition 3.5, we may assume that , , and . Let , . So, it is easily induced from Lemma 3.1 that for all large enough. Now we shall find an such that for all large enough. We will do this in the following two steps.

Step 1.

for . Let and . Integrating (3.20) on , , we have . Then we have as which is a contradiction. Hence there exists a such that .

Step 2.

If for all , then we are done. If not, we may let . Then for and, by the continuity of , we have . In this step, we have only to consider two possible cases.

Case 1.

Thus which is a contradiction. Now, let = . Then for and . So, we have, for , .

Case 2.

Thus in both case the similar argument can be continued since for some . This completes the proof.

## 4. Numerical Analysis on Impulsive Perturbations

It is from [5] that the system (1.3) with and has an unique limit cycle. Moreover, Figure 1 shows that the phase portrait of the system (1.3) with , , and has a limit cycle too. From Theorem 3.2, we know that the prey-free periodic solution is locally asymptotically stable provided that . A typical prey-free periodic solution of the system (1.3) is shown in Figure 2, where we observe how the variable oscillates in a stable cycle while the prey rapidly decreases to zero. On the other hand, if the amount of releasing species is smaller than , then the prey and the predator can coexist on a stable positive periodic solution (see Figure 1) and the system (1.3) can be permanent, which follows from Theorem 3.6.

## 5. Discussion

In this paper, we have studied the effects of control strategies on a predator-prey system with Monod-Haldane type functional response. Conditions for the system to be extinct are given by using the Floquet theory of impulsive differential equation and small amplitude perturbation skills. Also, it is proved that the system the system (1.3) is permanent via the comparison theorem. Moreover, numerical examples on impulsive perturbations have been illustrated to substantiate our mathematical results and to show that the system we have considered in this paper gives birth to various kinds of dynamical behaviors.

And then we get the following results via similar methods used in the previous sections.

Theorem 5.1.

Proposition 5.2.

There is an such that for all large enough, where is a solution of the system (5.2).

Theorem 5.3.

Thus, the seasonal effect on the prey may have also deeply influences on dynamics of the system (1.3).

## Declarations

### Acknowledgments

The first author is supported by Catholic University of Daegu Research Grant. The second author was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0004426).

## Authors’ Affiliations

## References

- Lu Z, Chi X, Chen L: Impulsive control strategies in biological control of pesticide.
*Theoretical Population Biology*2003, 64(1):39–47. 10.1016/S0040-5809(03)00048-0View ArticleMATHGoogle Scholar - Tang S, Xiao Y, Chen L, Cheke RA: Integrated pest management models and their dynamical behaviour.
*Bulletin of Mathematical Biology*2005, 67(1):115–135. 10.1016/j.bulm.2004.06.005MathSciNetView ArticleGoogle Scholar - Holling CS: The functional response of predator to prey density and its role in mimicry and population regulations.
*Memoirs of the Entomological Society of Canada*1965, 45: 1–60.View ArticleGoogle Scholar - Hsu SB, Huang TW: Global stability for a class of predator-prey systems.
*SIAM Journal on Applied Mathematics*1995, 55(3):763–783. 10.1137/S0036139993253201MathSciNetView ArticleMATHGoogle Scholar - Ruan S, Xiao D: Global analysis in a predator-prey system with nonmonotonic functional response.
*SIAM Journal on Applied Mathematics*2001, 61(4):1445–1472. 10.1137/S0036139999361896MathSciNetView ArticleMATHGoogle Scholar - Baek HK: Qualitative analysis of Beddington-DeAngelis type impulsive predator-prey models.
*Nonlinear Analysis: Real World Applications*2010, 11(3):1312–1322. 10.1016/j.nonrwa.2009.02.021MathSciNetView ArticleMATHGoogle Scholar - Beddington JR: Mutual interference between parasites or predator and its effect on searching efficiency.
*Journal of Animal Ecology*1975, 44: 331–340. 10.2307/3866View ArticleGoogle Scholar - Fan M, Kuang Y: Dynamics of a nonautonomous predator-prey system with the Beddington-DeAngelis functional response.
*Journal of Mathematical Analysis and Applications*2004, 295(1):15–39. 10.1016/j.jmaa.2004.02.038MathSciNetView ArticleMATHGoogle Scholar - Hwang T-W: Uniqueness of limit cycles of the predator-prey system with Beddington-DeAngelis functional response.
*Journal of Mathematical Analysis and Applications*2004, 290(1):113–122. 10.1016/j.jmaa.2003.09.073MathSciNetView ArticleMATHGoogle Scholar - Feng J-W, Chen S-H: Global asymptotic behavior for the competing predators of the Ivlev types.
*Mathematica Applicata*2000, 13(4):85–88.MathSciNetMATHGoogle Scholar - Ivlev VS:
*Experimental Ecology of the Feeding of Fishes*. Yale University Press; 1961.Google Scholar - Sugie J: Two-parameter bifurcation in a predator-prey system of Ivlev type.
*Journal of Mathematical Analysis and Applications*1998, 217(2):349–371. 10.1006/jmaa.1997.5700MathSciNetView ArticleMATHGoogle Scholar - Sokol W, Howell JA: Kineties of phenol oxidation by ashed cell.
*Biotechnology and Bioengineering*1980, 23: 2039–2049.View ArticleGoogle Scholar - Bainov DD, Simeonov PS:
*Impulsive Differential Equations:Periodic Solutions and Applications, Pitman Monographs and Surveys in Pure and Applied Mathematics*.*Volume 66*. Longman Science & Technical, Harlo, UK; 1993.Google Scholar - Lakshmikantham V, Baĭnov DD, Simeonov PS:
*Theory of Impulsive Differential Equations, Series in Modern Applied Mathematics*.*Volume 6*. World Scientific, Teaneck, NJ, USA; 1989:xii+273.View ArticleGoogle Scholar - Li Z, Wang W, Wang H: The dynamics of a Beddington-type system with impulsive control strategy.
*Chaos, Solitons & Fractals*2006, 29(5):1229–1239. 10.1016/j.chaos.2005.08.195MathSciNetView ArticleMATHGoogle Scholar - Liu B, Zhang Y, Chen L: Dynamic complexities in a Lotka-Volterra predator-prey model concerning impulsive control strategy.
*International Journal of Bifurcation and Chaos*2005, 15(2):517–531. 10.1142/S0218127405012338MathSciNetView ArticleMATHGoogle Scholar - Wang H, Wang W: The dynamical complexity of a Ivlev-type prey-predator system with impulsive effect.
*Chaos, Solitons & Fractals*2008, 38(4):1168–1176. 10.1016/j.chaos.2007.02.008MathSciNetView ArticleMATHGoogle Scholar - Wang W, Wang H, Li Z: The dynamic complexity of a three-species Beddington-type food chain with impulsive control strategy.
*Chaos, Solitons & Fractals*2007, 32(5):1772–1785. 10.1016/j.chaos.2005.12.025MathSciNetView ArticleMATHGoogle Scholar - Zhang S, Tan D, Chen L: Chaos in periodically forced Holling type IV predator-prey system with impulsive perturbations.
*Chaos, Solitons & Fractals*2006, 27(4):980–990. 10.1016/j.chaos.2005.04.065MathSciNetView ArticleMATHGoogle Scholar - Zhang S, Dong L, Chen L: The study of predator-prey system with defensive ability of prey and impulsive perturbations on the predator.
*Chaos, Solitons & Fractals*2005, 23(2):631–643. 10.1016/j.chaos.2004.05.044MathSciNetView ArticleMATHGoogle Scholar - Cushing JM: Periodic time-dependent predator-prey systems.
*SIAM Journal on Applied Mathematics*1977, 32(1):82–95. 10.1137/0132006MathSciNetView ArticleMATHGoogle Scholar - Gakkhar S, Naji RK: Chaos in seasonally perturbed ratio-dependent prey-predator system.
*Chaos, Solitons & Fractals*2003, 15(1):107–118. 10.1016/S0960-0779(02)00114-5MathSciNetView ArticleMATHGoogle Scholar

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