Dynamic behaviors of a stage-structured

Similar documents
Permanence and global stability of a May cooperative system with strong and weak cooperative partners

Permanence and global attractivity of a nonautonomous modified Leslie-Gower predator-prey model with Holling-type II schemes and a prey refuge

Research Article On the Stability Property of the Infection-Free Equilibrium of a Viral Infection Model

ALMOST PERIODIC SOLUTION OF A MULTISPECIES DISCRETE LOTKA-VOLTERRA MUTUALISM SYSTEM

Bifurcation and Stability Analysis of a Prey-predator System with a Reserved Area

Global attractivity and positive almost periodic solution of a multispecies discrete mutualism system with time delays

Dynamics of Modified Leslie-Gower Predator-Prey Model with Predator Harvesting

Research Article The Mathematical Study of Pest Management Strategy

DYNAMICS IN A COMPETITIVE LOTKA-VOLTERRA PREDATOR-PREY MODEL WITH MULTIPLE DELAYS. Changjin Xu 1. Yusen Wu. 1. Introduction

Dynamical Analysis of a Harvested Predator-prey. Model with Ratio-dependent Response Function. and Prey Refuge

Stability and Hopf bifurcation of a ratio-dependent predator prey model with time delay and stage structure

Global dynamics of two systems of exponential difference equations by Lyapunov function

On a non-autonomous stochastic Lotka-Volterra competitive system

x 2 F 1 = 0 K 2 v 2 E 1 E 2 F 2 = 0 v 1 K 1 x 1

Stability analysis of a prey-predator model with a reserved area

Harvesting Model for Fishery Resource with Reserve Area and Modified Effort Function

PERMANENCE IN LOGISTIC AND LOTKA-VOLTERRA SYSTEMS WITH DISPERSAL AND TIME DELAYS

Existence of Positive Periodic Solutions of Mutualism Systems with Several Delays 1

Stability and optimal harvesting in a stage structure predator-prey switching model

A Comparison of Two Predator-Prey Models with Holling s Type I Functional Response

ROLE OF TIME-DELAY IN AN ECOTOXICOLOGICAL PROBLEM

Global Properties for Virus Dynamics Model with Beddington-DeAngelis Functional Response

Optimal harvesting policy of a stochastic delay predator-prey model with Lévy jumps

Dynamics of an almost periodic facultative mutualism model with time delays

Analysis of a predator prey model with modified Leslie Gower and Holling-type II schemes with time delay

Optimal bounds for Neuman-Sándor mean in terms of the convex combination of the logarithmic and the second Seiffert means

Analysis of a delayed predator-prey model with ratio-dependent functional response and quadratic harvesting. Peng Feng

Hopf-Fold Bifurcation Analysis in a Delayed Predator-prey Models

DYNAMIC STUDY OF A PREDATOR-PREY MODEL WITH WEAK ALLEE EFFECT AND HOLLING TYPE-III FUNCTIONAL RESPONSE

LOTKA-VOLTERRA SYSTEMS WITH DELAY

EXISTENCE OF POSITIVE PERIODIC SOLUTIONS OF DISCRETE MODEL FOR THE INTERACTION OF DEMAND AND SUPPLY. S. H. Saker

Global Stability Analysis on a Predator-Prey Model with Omnivores

Physics: spring-mass system, planet motion, pendulum. Biology: ecology problem, neural conduction, epidemics

JOURNAL OF MATH SCIENCES -JMS- Url: Jl. Pemuda, No. 339 Kolaka Southeast Sulawesi, Indonesia

Applied Mathematics Letters. Stationary distribution, ergodicity and extinction of a stochastic generalized logistic system

Global dynamics of a predator-prey system with Holling type II functional response

MUtualism, an interaction of two-species of organisms

SPIRAL WAVE GENERATION IN A DIFFUSIVE PREDATOR-PREY MODEL WITH TWO TIME DELAYS

New results on the existences of solutions of the Dirichlet problem with respect to the Schrödinger-prey operator and their applications

Global Qualitative Analysis for a Ratio-Dependent Predator Prey Model with Delay 1

Dynamics Analysis of Anti-predator Model on Intermediate Predator With Ratio Dependent Functional Responses

Global attractivity and positive almost periodic solution of a discrete multispecies Gilpin-Ayala competition system with feedback control

Oscillation theorems for nonlinear fractional difference equations

HARVESTING IN A TWO-PREY ONE-PREDATOR FISHERY: A BIOECONOMIC MODEL

On the stabilizing effect of specialist predators on founder-controlled communities

Stability Analysis of a Population Dynamics Model with Allee Effect

Functional Response to Predators Holling type II, as a Function Refuge for Preys in Lotka-Volterra Model

Persistence and global stability in discrete models of Lotka Volterra type

Stationary distribution and pathwise estimation of n-species mutualism system with stochastic perturbation

BOUNDARY VALUE PROBLEMS OF A HIGHER ORDER NONLINEAR DIFFERENCE EQUATION

ESAIM: M2AN Modélisation Mathématique et Analyse Numérique M2AN, Vol. 37, N o 2, 2003, pp DOI: /m2an:

Some new sequences that converge to the Ioachimescu constant

Research Article Adaptive Control of Chaos in Chua s Circuit

Approximations to inverse tangent function

BIBO STABILITY AND ASYMPTOTIC STABILITY

Research Article Permanence of a Discrete Predator-Prey Systems with Beddington-DeAngelis Functional Response and Feedback Controls

A Stochastic Viral Infection Model with General Functional Response

2 One-dimensional models in discrete time

Global Attractivity of a Higher-Order Nonlinear Difference Equation

THE ROSENZWEIG-MACARTHUR PREDATOR-PREY MODEL

Boundary value problems for fractional differential equations with three-point fractional integral boundary conditions

Ordinary Differential Equations

Multiplesolutionsofap-Laplacian model involving a fractional derivative

Math 2930 Worksheet Introduction to Differential Equations. What is a Differential Equation and what are Solutions?

Research Article Almost Periodic Solutions of Prey-Predator Discrete Models with Delay

Analysis of a Prey-Predator System with Modified Transmission Function

A REMARK ON THE GLOBAL DYNAMICS OF COMPETITIVE SYSTEMS ON ORDERED BANACH SPACES

Wirtinger inequality using Bessel functions

Non-Autonomous Predator Prey Model. with Application

A delayed Holling type III functional response predator-prey system with impulsive perturbation on the prey

Global Attractivity in a Higher Order Nonlinear Difference Equation

Prey Predator Model with Asymptotic. Non-Homogeneous Predation

Complex Dynamics Behaviors of a Discrete Prey-Predator Model with Beddington-DeAngelis Functional Response

Monotone variational inequalities, generalized equilibrium problems and fixed point methods

Modeling and Simulation Study of Mutuality Interactions with Type II functional Response and Harvesting

Analysis of bacterial population growth using extended logistic Growth model with distributed delay. Abstract INTRODUCTION

On the Dynamics of a Rational Difference Equation, Part 1

Math 2930 Worksheet Introduction to Differential Equations

PDC-based fuzzy impulsive control design with application to biological systems: predator-prey system

Global dynamics of a mutualism competition model with one resource and multiple consumers

Research Article Multiple Periodic Solutions of a Nonautonomous Plant-Hare Model

Some new continued fraction sequence convergent to the Somos quadratic recurrence constant

Anti-synchronization of a new hyperchaotic system via small-gain theorem

The iterative methods for solving nonlinear matrix equation X + A X 1 A + B X 1 B = Q

Key words and phrases. Bifurcation, Difference Equations, Fixed Points, Predator - Prey System, Stability.

Stability Analysis of a Continuous Model of Mutualism with Delay Dynamics

Impulsive Stabilization and Application to a Population Growth Model*

International Journal of PharmTech Research CODEN (USA): IJPRIF, ISSN: Vol.8, No.7, pp , 2015

Nonstandard Finite Difference Methods For Predator-Prey Models With General Functional Response

Dynamical analysis of a delayed predator-prey system with modified Leslie-Gower and Beddington-DeAngelis functional response

Dynamics and Bifurcations in Predator-Prey Models with Refuge, Dispersal and Threshold Harvesting

Solution of Additional Exercises for Chapter 4

Research Article Existence and Duality of Generalized ε-vector Equilibrium Problems

Tracking Control of a Class of Differential Inclusion Systems via Sliding Mode Technique

Stochastic Viral Dynamics with Beddington-DeAngelis Functional Response

1.Introduction: 2. The Model. Key words: Prey, Predator, Seasonality, Stability, Bifurcations, Chaos.

Lotka-Volterra Models Nizar Ezroura M53

On complete convergence and complete moment convergence for weighted sums of ρ -mixing random variables

Numerical Solution of a Fractional-Order Predator-Prey Model with Prey Refuge and Additional Food for Predator

Existence and multiplicity of positive solutions of a one-dimensional mean curvature equation in Minkowski space

Transcription:

Lei Advances in Difference Equations 08 08:30 https://doi.org/0.86/s366-08-76- R E S E A R C H Open Access Dynamic behaviors of a stage-structured commensalism system Chaoquan Lei * * Correspondence: leichaoquan07@63.com Department of Mathematics, Ningde Normal University, Ningde, China Abstract A two species stage-structured commensalism model is proposed and studied in this paper. Local and global stability property of the boundary equilibrium and the positive equilibrium are investigated, respectively. If the stage-structured species is extinct, then depending on the intensity of cooperation, the species may still be extinct or become persistent. If the stage-structured species is permanent, then the final system is always globally asymptotically stable, which means the species is always permanent. Our study shows that increasing the intensity of the cooperation between the species is one of very useful methods to avoid extinction of the endangered species. Such a finding may be useful in protecting the endangered species. An example together with its numeric simulations is presented to verify our main results. MSC: 34C5; 9D5; 34D0; 34D40 Keywords: Stage structure; Commensalism; Lyapunov function; Global stability Introduction The aim of this paper is to investigate the dynamic behaviors of the following stagestructured commensalism system: dx = αx βx δ x, dx = βx δ x γ x + dx y, dy = yb a y,. with x 0 > 0, x 0 > 0, and y0 > 0, where α, β, δ, δ, d, b, a,andγ are all positive constants, x t andx t are the densities of the immature and mature first species at time t, y is the density of the second species at time t. For the simplicity of our model, we only consider the stage structure of immaturity and maturity of the first species and do not consider the stage structure of the second species. The following assumptions are made in formulating model.:. For the first species, the per capita birth rate of the immature population is α >0; The per capita death rate of the immature population is δ >0;Thepercapitadeath rate of the mature population is proportional to the current mature population with The Authors 08. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original authors and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Lei Advances in Difference Equations 08 08:30 Page of 0 a proportionality constant δ >0; β >0denotes the surviving rate of immaturity to reach maturity; The mature species is density-dependent with the parameter γ >0.. The second species is only beneficial to the mature first species, and their relationship is bilinear dx y. 3. The second species satisfies the logistic model, where b is the intrinsic growth rate of the second species, and a b is the catching capacity of the second species. During the last decade, many scholars investigated the dynamic behaviors of the mutualism model or commensalism model [ 5]. Han and Chen [5] proposed the following commensalism model with feedback controls: dx t dx t du t du t = x t b a x t+a x t α u t, = x t b a x t α u t, = η u t+a x t, = η u t+a x t.. They first showed that the subsystem, i.e., the two species commensalism model dx t dx t = x t b a x t+a x t, = x t b a x t,.3 admits a unique globally asymptotically stable positive equilibrium. After that, they further showed that system. admits a unique globally stable positive equilibrium, which means that feedback control variables have no influence on the stability property of system.. Several scholars argued that discrete models are more suitable if the species have non-overlapping generations. Xie et al. [6] proposed the following discrete commensal symbiosis model: x k +=x k exp { a k b kx k+c kx k }, x k +=x k exp { a k b kx k }..4 They obtained a set of sufficient conditions which ensure the existence of the positive periodic solution of system.4. Xue et al. [7] further proposed a discrete commensalism model with delays, they investigated the almost periodic solution of the system. Li et al. [] studied the positive periodic solution of a discrete commensalism model with Holling II functional response. Wu [3] argued that it may be more suitable to assume that the relationship between two species is of nonlinear type instead of linear one, and she established the following two species commensal symbiosis model: dx a = x b x + c y p, +y p dy = ya b y,.5

Lei Advances in Difference Equations 08 08:30 Page 3 of 0 where a i, b i, i =,,pand c are all positive constants, p. The results of [3]werethen generalized by Wu et al. [] to the following commensalism model with Allee effect: dx a = x b x + c y p, +y p.6 dy = ya y b y u + y, where a i, b i, i =,,p, u,andc are all positive constants, p. Recently, several scholars studied the influence of partial closure on the non-selective harvesting commensalism model. Deng and Huang [] studied the dynamic behaviors of the following system: dx = r x xk + α yk q Emx,.7 dy = r y yk q Emy, where r, r, K, K, α are all positive constants. E is the combined fishing effort used to harvest, and m 0 < m < is the fraction of the stock available for harvesting. They showed that depending on the fraction of the stock available for harvesting, the system may undergo extinction, partial survival, or two species may coexist in a stable state. The dynamic behaviors of the system become complicated compared with the non-harvesting system. Lin [0] further studied the dynamic behaviors of a commensal symbiosis model with non-monotonic functional response and non-selective harvesting in a partial closure. On the other hand, many scholars investigated the dynamic behaviors of the stagestructured species, see [6 45], and the references cited therein. In constructing a stagestructured model, two different ideas were applied. Firstly, assume that the species needs time to grow up, and this leads to the delayed model. Aiello and Freedman [4]forthefirst time proposed the following stage-structured single species model: dx t dx t = αx t γ x t αe γτ x t τ, = αe γτ x t τ βx t..8 They showed that system.8 admits a unique positive equilibrium which is globally asymptotically stable. Many scholars [6 39] used the idea of Aiello and Freedman to establish stage-structured ecological models. For example, Chen et al. [8] studied the persistence property of the following stage-structured predator prey model: dx t dx t dy t dy t = r x t d x t r e d τ x t τ, = r e d τ x t τ d x t b x t c x ty t, = r y t d y t r e d τ y t τ, = r e d τ y t τ d y t b y t+c y tx t..9

Lei Advances in Difference Equations 08 08:30 Page 4 of 0 They obtained a set of sufficient conditions which ensure the global asymptotic stability of the positive equilibrium. Chen et al. [34] proposed and studied the following May type stage-structured cooperation model: ẋ t=b e d τ x t τ d x t a x t c + f x t a x t, ẏ t=b x t d y t b e d τ x t τ, ẋ t=b e d τ x t τ d x t a x t c + f x t a x t,.0 ẏ t=b x t d y t b e d τ x t τ. They showed that with introduction of the stage structure, the May type cooperative system may admit partial survival property, that is, despite the cooperation between the species, the species may still be driven to extinction due to the stage structure. They finally drew the conclusion: the cooperation between the species has no influence on the persistence property of the system. Another way to construct a stage-structured ecosystem is to assume that there is a proportional number of immature species that become mature species [40, 4, 43, 44]. Recently, Khajanchi and Banerjee [4] proposed the following stage-structured predator prey model with ratio-dependent functional response: dx = αx t βx t δ x t, dx = βx t δ x t γx t η θx tyt g θx t+hyt,. dy = uη θx tyt g θx t+hyt δ 3y t The authors investigated the stability property of the positive equilibrium and boundary equilibrium. In system., without predator species, the system will reduce to the following single species stage-structured system: dx = αx t βx t δ x t, dx = βx t δ x t γx t.. Though system. seems very simple, in[43], we showed that if αβ < δ β + δ.3 holds, the equilibrium O0, 0 is globally asymptotically stable, which means extinction of the species. Therefore, the dynamic behaviors of system. are very different to the dynamic behaviors of system.8. It is in this sense that we need to do more work on a non-delay stage-structured ecosystem.

Lei Advances in Difference Equations 08 08:30 Page 5 of 0 Recently, in [43], we proposed the following single species stage-structured system incorporating partial closure for the populations and non-selective harvesting: dx = αx βx δ x q Emx, dx = βx δ x γ x q Emx,.4 where α, β, δ, δ, q, q, E,andγ are all positive constants, x tandx tarethedensities of the immature and mature species at time t. Our study showed that the birth rate of the immature species and the fraction of the stocks for the harvesting play a crucial role in the dynamic behaviors of the system. One could easily see that in system., without the cooperation of the second species, the first species is described by.. Hence, one interesting issue is proposed: Assume that without the cooperation of the second species, the first species in system. will be driven to extinction, i.e., assume inequality.3 holds. Is it possible for the species to avoid the extinction due to the cooperation of the second species, or will the first species be driven to extinction despite the cooperation of the second species, just like the dynamic behaviors of system.0? We will try to find the answer in the rest of the paper. The paper is arranged as follows. We investigate the existence and local stability property of the equilibria of system. insect.. InSect.3, by constructing some suitable Lyapunov function, we are able to investigate the global stability property of the equilibria. Section 4 presents some numerical simulations to show the feasibility of the main results. We end this paper with a brief discussion. Local stability of the equilibria Before we study the local stability property of the equilibrium points of system., we would like to introduce the stability result of equilibrium of system.. The following lemma is Theorems 4. and 4. of [43]. Lemma. Assume that αβ < δ β + δ. holds, then the boundary equilibrium O0, 0 of system. is globally stable. Assume that αβ > δ β + δ. holds, then the positive equilibrium Bx, x of system. is globally stable, where x = αx, x β + δ = αβ δ β + δ. γ β + δ Lemma. R + 3 is the invariant set of system.. Proof Note that from system., for all x, x, y >0,onehas ẋ x =0 = αx >0,

Lei Advances in Difference Equations 08 08:30 Page 6 of 0 ẋ x =0 = βx >0, yt =y0 exp t 0 b a ys ds >0. It immediately follows that R + 3 is the invariant set of system.. Now we are in a position to investigate the local stability property of system.. The equilibria of system. are determined by the following system: αx βx δ x =0, βx δ x γ x + dx y =0,.3 yb a y=0. The system always admits two boundary equilibria: A 0,0,0,A 0, 0, b a. Also, if αβ > δ β + δ,.4 then the system admits another boundary equilibrium A 3 x, x,0,where x = αx, x β + δ = αβ δ β + δ..5 γ β + δ Assume that αβ δ db β + δ >0,.6 a then system. admits a unique positive equilibrium A 4, x, y, where = αx β + δ, = αβ δ db a β + δ, β + δ γ.7 y = b a. Obviously,, x,andy satisfy the equations α βx δ =0, β δ γ b a y =0. + dx y =0,.8 We shall now investigate the local stability property of the above equilibria. The variational matrix of system.is β δ α 0 Jx, x, y= β δ γx + dy dx..9 0 0 a y + b

Lei Advances in Difference Equations 08 08:30 Page 7 of 0 Theorem. A 0,0,0is unstable. Proof From.9wecouldseethattheJacobianmatrixofthesystemabouttheequilibrium point A 0,0,0isgivenby β δ α 0 β δ 0..0 0 0 b The characteristic equation of the above matrix is λ b λ +δ + δ + βλ + βδ + δ δ αβ = 0.. Hence, it has one positive characteristic root λ = b ;consequently,a 0,0,0isunstable. This ends the proof of Theorem.. Remark. Theorem. showsthatitisimpossibleforthesystemtobedriventoextinc- tion, that is, the two species in system.couldnotbeextinctatthesametime. Theorem. Assume that β + δ δ db αβ > 0,. a then A 0, 0, b a is locally asymptotically stable. Assume that β + δ δ db αβ < 0,.3 a then A 0, 0, b a is unstable. Proof From.9wecouldseethattheJacobianmatrixofthesystemabouttheequilibrium point A 0, 0, b a isgivenby β δ α 0 db β a δ 0..4 0 0 b The characteristic equation of the above matrix is [ λ + b λ + δ + δ + β db λ +β + δ δ db ] αβ = 0..5 a a Hence, it has one negative characteristic root λ = b < 0, the other two characteristic roots are determined by the equation λ + δ + δ + β db λ +β + δ δ db αβ = 0..6 a a

Lei Advances in Difference Equations 08 08:30 Page 8 of 0 Note that the two characteristic roots of Eq..6 satisfy λ + λ 3 = δ + δ + β db, a λ λ 3 =β + δ δ db αβ. a.7 Under assumption.3, λ λ 3 < 0, hence at least one characteristic root is positive; consequently, A 0, 0, b a is unstable. Under assumption., it implies that δ > db a,andso, from.7, one has λ + λ 3 <0, λ λ 3 >0.Hence,λ <0,λ 3 < 0. That is, under assumption., three characteristic roots of matrix.4areallnegative;consequently,a 0, 0, b a is locally asymptotically stable. This ends the proof of Theorem.. Remark. Assume that. holds, then for the system without cooperation, it follows from Lemma. that the first species will be driven to extinction. If the cooperative coefficient d is small enough, then inequality. holds. It follows from the first part of Theorem. that in this case the first species will still be driven to extinction despite the cooperation of the second species. Theorem.3 A 3 x, x,0is unstable. Proof From.9wecouldseethattheJacobianmatrixofthesystemabouttheequilibrium point A 3 x, x,0isgivenby β δ α 0 β δ γx dx..8 0 0 b The characteristic equation of the above matrix is λ b λ + δ +γ x + β λ +β + δ δ +γ x αβ = 0..9 Hence, it has one positive characteristic root λ = b ;consequently,a 3 x, x,0isunstable. This ends the proof of Theorem.3. Remark.3 Theorem.3 shows that it is impossible for the second species to be driven to extinction while the first species is asymptotically stable. Theorem.4 Assume that.6 holds, then A 4, x, y is locally asymptotically stable. Proof From.9wecouldseethattheJacobianmatrixofthesystemabouttheequilibrium point A 4, x, y isgivenby β δ α 0 β δ γ + dy d..0 0 0 a y + b

Lei Advances in Difference Equations 08 08:30 Page 9 of 0 Noting that a y + b = a b a + b = b, also, from the second equation of.6, we have δ γ + dy = βx γ = αβ β + δ γ. The characteristic equation of the above matrix is λ + b [ λ + B λ + B ] = 0,. where B = β + δ + βα β + δ + γ, βα B =β + δ + γ αβ. β + δ Hence, it has one negative characteristic root λ = b < 0, the other two characteristic roots are determined by the equation λ + B λ + B = 0.. Note that from the expression of and condition.6, the two characteristic roots of Eq..satisfy λ + λ 3 = B <0, βα λ λ 3 =β + δ + γ αβ β + δ βα =β + δ + αβ δ β + δ β + δ β + δ αβ.3 = αβ δ β + δ >0. Hence, λ <0,λ 3 < 0, therefore, all of the three characteristic roots are negative. Consequently, A 4, x, y is locally asymptotically stable. This ends the proof of Theorem.4. Remark.4 Condition.6 is necessary to ensure the existence of the positive equilibrium. Theorem.4 shows that if the positive equilibrium exists, it is locally asymptotically stable.

Lei Advances in Difference Equations 08 08:30 Page 0 of 0 3 Global stability We showed in Sect. that A 0,0,0andA 3 x, x, 0 are unstable, while under assumption., A 0, 0, b a is locally asymptotically stable; and if the positive equilibrium exists, it is locally asymptotically stable. One interesting issue is to investigate the global stability property of the equilibria. In this section we will try to obtain some sufficient conditions which could ensure the global asymptotic stability of the equilibria A and A 4 of system.. Theorem 3. Assume that β + δ δ db αβ > 0, 3. a then A 0, 0, b a is globally asymptotically stable. Proof We will prove Theorem 3. by constructing some suitable Lyapunov function. Let us define a Lyapunov function where V x, x, y= β β + δ x + x + d 4γ a y y y ln yy, 3. y = b a. 3.3 One could easily see that the function V is zero at the boundary equilibrium A 0, 0, b a and is positive for all other positive values of x and x. The time derivative of V along the trajectories of.is D + V t= = = β αx βx δx β + δ + βx δ x γ x + dyx + d y y b a y 4γ a αβ δ x γ x β + δ + dyx + d y y b a y 4γ a αβ δ + db x γ x β + δ a + dx y y + d = β + δ y y a y a y 4γ a αβ δ db a + dx y y d 4γ y y β + δ x γ x

Lei Advances in Difference Equations 08 08:30 Page of 0 = β + δ γ αβ δ db [ x d γ y y a β + δ x ]. 3.4 It then follows from 3. and3.4 thatd + V t < 0 strictly for all x, x, y >0except the boundary equilibrium A 0, 0, b a, where D + V t=0.thus,v x, x, y satisfieslyapunov s asymptotic stability theorem, and the boundary equilibrium A 0, 0, b a ofsystem. is globally asymptotically stable. This completes the proof of Theorem 3.. Remark 3. Under the assumption αβ < δ β + δ, it follows from Lemma. that the first species will be driven to extinction. Obviously, if db a is small enough, then inequality 3. holds. Moreover, it follows from Theorem 3. that A 0, 0, b a is globally asymptotically stable, which means that the first species is still driven to extinction. That is, if the cooperation is limited, then, despite the cooperation between the two species, the species is still driven to extinction. Theorem 3. Assume that αβ δ db β + δ > 0 3.5 a holds, then A 4, x, y is globally asymptotically stable. Proof We will prove Theorem 3. by constructing some suitable Lyapunov function. Let us define a Lyapunov function V x, x, y=k x x ln x + k x x ln x + k 3 y y y ln y y, 3.6 where k, k, k 3 are some positive constants to be determined later. One could easily see that the function V is zero at the equilibrium A 4, x, y and is positive for all other positive values of x, x,andy. The time derivative of V along the trajectories of.is D + x V t=k x ẋ + k x x x x = k αx β + δ x x y y ẋ + k 3 ẏ y x + k βx δ x γ x x + dyx + k 3 y y b a y. 3.7

Lei Advances in Difference Equations 08 08:30 Page of 0 Note that from the relationship of, x,andy see.8 we have αx β + δ x = α x x Also, from.7and.8, we have + x x. 3.8 βx δ x γ x dux = β x x = β + = β + + βx δ x γ x + dyx x x x + x x x αβ β + δ δ + db a x x x αβ β + δ δ + db a x γ x + dx y y + x x = β x x x + x x γ x + γ x + dx y y x γ x + dx y y = β x x x + x x γ x x + dx y y, 3.9 from the third equation of.8, we have b a y = a y a y = a y y. 3.0 Applying 3.8 3.0to3.7leadsto D + x V t=k x α x + k x x x β x k γ x x k 3 a y y = k αx x k βx x x x x + x x + x x x x + k dx y y x x k α + x + k d x + k β k γ x x y y k 3 a y y. x

Lei Advances in Difference Equations 08 08:30 Page 3 of 0 Now let us choose k =,k = βx x α, k 3 = d 4γ a,then D + V t= βx x x x x + β x x x x x βx x x x x γ x x + d x y y d a y y 4γ a = β [ ] x x x x x x x x x [ γ x x d y y ]. 3. γ Hence, D + V t < 0 strictly for all x, x, y > 0 except the positive equilibrium A 4, x, y, where D + V t=0.thus,v x, x, y satisfies Lyapunov s asymptotic stability theorem, and the positive equilibrium A 4, x, y ofsystem. is globally asymptotically stable. This completes the proof of Theorem 3.. Remark 3. Condition 3.5 is necessary to ensure the existence of positive equilibrium. Theorem 3.showsthatifthepositive equilibriumexists, itis globallyasymptoticallystable. Hence, it is impossible for the system to have a bifurcation phenomenon. Remark 3.3 Assume that αβ > δ β + δ holds, then inequality 3.5 alwaysholds.from Lemma.,we know that in this case system. admits a unique positive equilibrium. That is, if system. admits the unique positive equilibrium, then for the commensalism model, the system still admits the unique positive equilibrium which is globally asymptotically stable. Remark 3.4 Assume that αβ < δ β + δ holds,thenif db a is large enough, inequality 3.5 still holds. From Lemma., we know that in this case the boundary equilibrium O0, 0 of system. is globally asymptotically stable, which means extinction of the species. Then, for the commensalism model, if the cooperative effect is large enough, then the system admits the unique positive equilibrium which is globally asymptotically stable, which means the species is permanent. Therefore, for the endangered species, the intensity of cooperation between the species plays the essential role in the persistence property of the species. Remark 3.5 Theorems 3. and 3. depict a very intuitive biological phenomenon. From Zhang et al. [45], we can regard α δ as a relative birth rate of the first mature species, β β+δ as a relative transformation rate of the first immature species. Then conditions 3. and 3.5areequivalentto α δ db a β β + δ < 3.

Lei Advances in Difference Equations 08 08:30 Page 4 of 0 and α δ db a β β + δ >, 3.3 respectively. Hence, with the help of the second species, the relative birth rate of the first mature species is increasing, this finally increases the chance of the survival of the first species. 4 Numeric simulations Now let us consider the following example. Example 4. Let us consider the two species stage-structured commensalism model: dx = x x x, dx = x x x + dx y, dy = y y. 4. Here we choose α = β = δ = δ = γ = a = b =.Hence αβ =<=δ β + δ. It follows from Lemma. that the boundary equilibrium O0, 0 of the following system is globally asymptotically stable. dx = x x x, dx = x x x. 4. That is, without the cooperation of the second species, the first species will be driven to extinction Fig. supports this assertion. Now let us choose d =0.5in system 4., then β + δ δ db αβ = 0.5 > 0, 4.3 a and it follows from Theorem 3. that A 0,0,is globally asymptotically stable. Figure Fig. 4 support this assertion. Now let us choose d =in system 4., then αβ β + δ δ db = 3 > 0, 4.4 a and it follows from Theorem 3. that A 4 3 4, 3,is globally asymptotically stable. Figure 5 Fig. 7 support this assertion.

Lei Advances in Difference Equations 08 08:30 Page 5 of 0 Figure Dynamic behaviors of system 4., the initial conditions x 0, x 0 = 0.5,,,, and, 0.5, respectively Figure Dynamic behaviors of the first component x tofsystem4., here we take d = /4 and the initial conditions x 0, x 0, y0 = 0.5, 0.5, 0.5, 0., 0., 0.,,,, and 0.3, 0.3, 0.3, respectively 5 Conclusion Recently, many scholars investigated the dynamic behaviors of the mutualism and commensalism model [ ]. The traditional Lotka Volterra commensalism model was studied by many scholars, and in [5], by constructing some suitable Lyapunov function, Han and Chen showed that system. admits the unique positive equilibrium. However, to this day, still no scholar has proposed and studied the dynamic behaviors of the stage-

Lei Advances in Difference Equations 08 08:30 Page 6 of 0 Figure 3 ynamic behaviors of the second component x tofsystem4., here we take d =/4anhe initial conditions x 0, x 0, y0 = 0.5, 0.5, 0.5, 0., 0., 0.,,,, and 0.3, 0.3, 0.3, respectively Figure 4 Dynamic behaviors of the third component ytofsystem4., here we take d = /4 and the initial conditions x 0, x 0, y0 = 0.5, 0.5, 0.5, 0., 0., 0.,,,, and 0.3, 0.3, 0.3, respectively structured commensalism model. This motivated us to propose system., which is the most simple commensalism system with stage structure. In system., without the cooperation of the second species, depending on the relationship of the coefficients, the species may be driven to extinction or become persistent in the long run. Such dynamic behaviors are different to those of the stage-structured system.8, which was introduced by Aeillo and Freedman. We argue that such kind of

Lei Advances in Difference Equations 08 08:30 Page 7 of 0 Figure 5 Dynamic behaviors of the first component x tofsystem4., here we take d = and the initial conditions x 0, x 0, y0 = 0.5, 0.5, 0.5, 0., 0., 0.,,,, and,,, respectively Figure 6 Dynamic behaviors of the second component x tofsystem4., here we take d = and the initial conditions x 0, x 0, y0 = 0.5, 0.5, 0.5, 0., 0., 0.,,,, and,,, respectively property the species could be driven to extinction is one of the new characters due to the introduction of the stage structure. For the extinction case, we show that depending on the intensity of cooperation, the species may still be driven to extinction or become persistent. Therefore, the cooperation between the two species is one of the essential factors that lead to the persistence of species. Such a property is quite different to that of the stage-structured cooperative

Lei Advances in Difference Equations 08 08:30 Page 8 of 0 Figure 7 Dynamic behaviors of the third component ytofsystem4., here we take d = and the initial conditions x 0, x 0, y0 = 0.5, 0.5, 0.5, 0., 0., 0.,,,, and,,, respectively system.0,which wasproposedby Chen et al. [34]. They showed that the cooperation between species has no influence on the persistence property of the system. To sum up, to increase the intensity of cooperation between the species is one of the essential methods to avoid the extinction of the endangered species. Acknowledgements The author is grateful to two anonymous referees for their excellent suggestions, which have greatly improved the presentation of the paper. Funding This work is supported by the National Natural Science Foundation of China under Grant 60085 and the Natural Science Foundation of Fujian Province 07J0400. Competing interests The authors declare that there is no conflict of interests. Authors contributions All authors contributed equally to the writing of this paper. All authors read and approved the final manuscript. Publisher s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Received: 9 May 08 Accepted: 3 August 08 References. Yang, K., Miao, Z.S., et al.: Influence of single feedback control variable on an autonomous Holling-II type cooperative system. J. Math. Anal. Appl. 435, 874 888 06. Chen, F., Xie, X., et al.: Extinction in two species nonautonomous nonlinear competitive system. Appl. Math. Comput. 74, 9 4 06 3. Yang, K., Xie, X.D., et al.: Global stability of a discrete mutualism model. Abstr. Appl. Anal. 04, Article ID 7094 04 4. Chen, L.J., Xie, X.D.: Feedback control variables have no influence on the permanence of a discrete N-species cooperation system. Discrete Dyn. Nat. Soc. 009, ArticleID30645 009 5. Chen, F.D.: Permanence for the discrete mutualism model with time delays. Math. Comput. Model. 473 4,43 435 008 6. Chen, F.D., Yang, J.H., et al.: On a mutualism model with feedback controls. Appl. Math. Comput. 4, 58 587 009 7. Chen, L.J., Chen, L.J., et al.: Permanence of a delayed discrete mutualism model with feedback controls. Math. Comput. Model. 50, 083 089 009

Lei Advances in Difference Equations 08 08:30 Page 9 of 0 8. Xie, X.D., Chen, F.D., et al.: Note on the stability property of a cooperative system incorporating harvesting. Discrete Dyn. Nat. Soc. 04, Article ID 3783 04 9. Xie, X.D., Chen, F.D., et al.: Global attractivity of an integrodifferential model of mutualism. Abstr. Appl. Anal. 04, Article ID 9876 04 0. Lin, Q.F.: Dynamic behaviors of a commensal symbiosis model with non-monotonic functional response and non-selective harvesting in a partial closure. Commun. Math. Biol. Neurosci. 08, Article ID408. Han, R., Chen, F., et al.: Global stability of May cooperative system with feedback controls. Adv. Differ. Equ. 05, Article ID 360 05. Wu, R.X., Li, L., et al.: A Holling type commensal symbiosis model involving Allee effect. Commun. Math. Biol. Neurosci. 08, Article ID 6 08 3. Wu, R.X., Li, L., et al.: A commensal symbiosis model with Holling type functional response. Int. J. Math. Comput. Sci. 6, 364 37 06 4. Yang, L., Xie, X., et al.: Permanence of the periodic predator prey-mutualist system. Adv. Differ. Equ. 05, ArticleID 33 05 5. Han, R.Y., Chen, F.D.: Global stability of a commensal symbiosis model with feedback controls. Commun. Math. Biol. Neurosci. 05,Article ID 5 05 6. Xie, X.D., Miao, Z.S., Xue, Y.: Positive periodic solution of a discrete Lotka Volterra commensal symbiosis model. Commun. Math. Biol. Neurosci. 05, Article ID 05 7. Xue, Y.L., Xie, X.D., et al.: Almost periodic solution of a discrete commensalism system. Discrete Dyn. Nat. Soc. 05, Article ID 95483 05 8. Chen, J.H., Wu, R.X.: A commensal symbiosis model with non-monotonic functional response. Commun. Math. Biol. Neurosci. 07,Article ID 5 07 9. Deng, H., Huang, X.Y.: The influence of partial closure for the populations to a harvesting Lotka Volterra commensalism model. Commun. Math. Biol. Neurosci. 08, ArticleID0 08 0. Zhao, L., Bin, Q., et al.: Permanence and global stability of a May cooperative system with strong and weak cooperative partners. Adv. Differ. Equ. 08, Article ID7 08. Li, T.T., Lin, Q.X., et al.: Positive periodic solution of a discrete commensal symbiosis model with Holling II functional response. Commun. Math. Biol. Neurosci. 06, Article ID 06. Wu, R.: Dynamic behaviors of a nonlinear amensalism model. Adv. Differ. Equ. 08, Article ID 87 08 3. Chen, B.: Dynamic behaviors of a commensal symbiosis model involving Allee effect and one party can not survive independently. Adv. Differ. Equ. 08, Article ID 08 4. Lin, Q.: Allee effect increasing the final density of the species subject to the Allee effect in a Lotka Volterra commensal symbiosis model. Adv. Differ. Equ. 08, Article ID 96 08 5. Lin, Q.: Stability analysis of a single species logistic model with Allee effect and feedback control. Adv. Differ. Equ. 08, Article ID 90 08 6. Chen, F.D., Chen, W.L., et al.: Permanence of a stage-structured predator prey system. Appl. Math. Comput. 97, 8856 886 03 7. Chen, F.D., Xie, X.D., et al.: Partial survival and extinction of a delayed predator prey model with stage structure. Appl. Math. Comput. 98,457 46 0 8. Chen, F.D., Wang, H.N., et al.: Global stability of a stage-structured predator prey system. Appl. Math. Comput. 3, 45 53 03 9. Lin, Q., Xie, X., et al.: Dynamical analysis of a logistic model with impulsive Holling type-ii harvesting. Adv. Differ. Equ. 08, 08 30. Li, T.T., Chen, F.D., et al.: Stability of a mutualism model in plant pollinator system with stage-structure and the Beddington DeAngelis functional response. J. Nonlinear Funct. Anal. 07, Article ID50 07 3. Li, Z., Chen, F.D.: Extinction in periodic competitive stage-structured Lotka Volterra model with the effects of toxic substances. J. Comput. Appl. Math. 3, 43 53 009 3. Li, Z., Han, M.A., Chen, F.: Global stability of stage-structured predator prey model with modified Leslie Gower and Holling-type II schemes. Int. J. Biomath. 56, Article ID 50057 0.https://doi.org/0.4/S79354550057X 33. Li, Z., Han, M., et al.: Global stability of a predator prey system with stage structure and mutual interference. Discrete Contin. Dyn. Syst., Ser. B 9, 73 87 04 34. Chen, F.D., Xie, X.D., et al.: Dynamic behaviors of a stage-structured cooperation model. Commun. Math. Biol. Neurosci. 05,Article ID 4 05 35. Lin, X., Xie, X., et al.: Convergences of a stage-structured predator prey model with modified Leslie Gower and Holling-type II schemes. Adv. Differ. Equ. 06, 8 06 36. Chen, F.D., You, M.S.: Permanence, extinction and periodic solution of the predator prey system with Beddington DeAngelis functional response and stage structure for prey. Nonlinear Anal., Real World Appl. 9, 07 008 37. Liu, Y., Xie, X., et al.: Permanence, partial survival, extinction, and global attractivity of a nonautonomous harvesting Lotka Volterra commensalism model incorporating partial closure for the populations. Adv. Differ. Equ. 08, Article ID 08 38. Xue, Y.L., Xie, X.D., Lin, Q., Chen, F.: Global attractivity and extinction of a discrete competitive system with infinite delays and single feedback control. Discrete Dyn. Nat. Soc. 08, Article ID8938 08. https://doi.org/0.55/08/8938 39. Song, X., Cai, L., et al.: Ratio-dependent predator prey system with stage structure for prey. Discrete Contin. Dyn. Syst., Ser. B 43, 747 758 0 40. Wu, H.L., Chen, F.D.: Harvesting of a single-species system incorporating stage structure and toxicity. Discrete Dyn. Nat. Soc. 009, Article ID 903 009 4. Khajanchi, S., Banerjee, S.: Role of constant prey refuge on stage structure predator prey model with ratio dependent functional response. Appl. Math. Comput. 34,93 98 07 4. Aiello, W.G., Freedman, H.I.: A time-delay model of single-species growth with stage structure. Math. Biosci. 0, 39 44 990

Lei Advances in Difference Equations 08 08:30 Page 0 of 0 43. Xiao, A., Lei, C.Q.: Dynamic behaviors of a non-selective harvesting single species stage structure system incorporating partial closure for the populations. Adv. Differ. Equ. 08, Article ID 45 08. https://doi.org/0.86/s366-08-709-5 44. Lei, C.Q.: Dynamic behaviors of a stage structure amensalism system with a cover for the first species. Adv. Differ. Equ. 08, Article ID 7 08. https://doi.org/0.86/s366-08-79-45. Zhang, X., Chen, L., Neumann, A.U.: The stage-structured predator prey model and optimal harvesting policy. Math. Biosci. 68, 0 0 000