Research ArticleThe Dynamical Analysis of a Prey-Predator Model witha Refuge-Stage Structure Prey Population
Raid Kamel Naji1 and Salam Jasim Majeed1,2
1Department of Mathematics, College of Science, Baghdad University, Baghdad, Iraq2Department of Physics, College of Science, Thi-Qar University, Nasiriyah, Iraq
Correspondence should be addressed to Salam Jasim Majeed; [email protected]
Received 20 July 2016; Accepted 1 November 2016
Academic Editor: Jaume Gine
Copyright Β© 2016 R. K. Naji and S. J. Majeed. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.
We proposed and analyzed a mathematical model dealing with two species of prey-predator system. It is assumed that the prey is astage structure population consisting of two compartments known as immature prey and mature prey. It has a refuge capability asa defensive property against the predation. The existence, uniqueness, and boundedness of the solution of the proposed model arediscussed. All the feasible equilibrium points are determined. The local and global stability analysis of them are investigated. Theoccurrence of local bifurcation (such as saddle node, transcritical, and pitchfork) near each of the equilibrium points is studied.Finally, numerical simulations are given to support the analytic results.
1. Introduction
The development of the qualitative analysis of ordinarydifferential equations is deriving to study many problemsin mathematical biology. The modeling for the populationdynamics of a prey-predator system is one of the importantand interesting goals in mathematical biology, which hasreceived wide attention by several authors [1β6]. In thenatural world many kinds of prey and predator specieshave a life history that is composed of at least two stages:immature andmature, and each stage has different behavioralproperties. So, some works of stage structure prey-predatormodels have been provided in a good number of papers in theliteratures [7β12]. Zhang et al. in [9] and Cui and Takeuchiin [11] proposed two mathematical models of prey stagestructure; in these models the predator species consumesexclusively the immature prey. Indeed, there are many factorsthat impact the dynamics of prey-predator interactions suchas disease, harvesting, prey refuge, delay, and many otherfactors. Several prey species have gone to extinction, andthis extinction must be caused by external effects such asoverutilization, overpredation, and environmental factors(pollution, famine). Prey may avoid becoming attacked by
predators either by protecting themselves or by living ina refuge where it will be out of sight of predators. Sometheoretical and empirical studies have shown and testedthe effects of prey refuges and making an opinion that therefuges used by prey have a stabilizing influence on prey-predator interactions; also prey extinction can be preventedby the addition of refuges; for instance, we can refer to[13β23]. Therefore, it is important and worthwhile to studythe effects of a refuge on the prey population with preystage structure. Consequently, in this paper, we proposed andanalyzed the prey-predator model involving a stage structurein prey population together with a preys refuge property as adefensive property against the predation.
2. Mathematical Model
In this section a prey-predator model with a refuge-stagestructure prey population is proposed for study. Let π₯(π)represent the population size of the immature prey at timeπ; π¦(π) represents the population size of the mature prey attimeπ, while π§(π) denotes the population size of the predatorspecies at timeπ.Therefore in order to describe the dynamics
Hindawi Publishing CorporationInternational Journal of Differential EquationsVolume 2016, Article ID 2010464, 10 pageshttp://dx.doi.org/10.1155/2016/2010464
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of this model mathematically the following hypotheses areadopted:
(1) The immature prey grows exponentially dependingcompletely on its parents with growth rate π > 0.There is an intraspecific competition between theirindividuals with intraspecific competition rate πΏ1 > 0.The immature prey individual becomes mature withgrownup rate π½ > 0 and faces natural death with arate π1 > 0.
(2) There is an intraspecific competition between theindividuals of mature prey population with intraspe-cific competition rate πΏ2 > 0. Further the mature preyspecies faces natural death rate too with a rate π2 > 0.
(3) The environment provides partial protection of preyspecies against the predation with a refuge rate 0 <π < 1; therefore there is 1βπ of prey species availablefor predation.
(4) There is an intraspecific competition between theindividuals of predator population with intraspecificcompetition rate πΏ3 > 0. Further the predator speciesfaces natural death rate too with a rate π3 > 0.
The predator consumes the prey in both the compartmentsaccording to the mass action law represented by LotkaβVolterra type of functional response with conversion rates0 < π1 < 1 and 0 < π2 < 1 for immature and matureprey, respectively. Consequently, the dynamics of this modelcan be represented mathematically with the following set ofdifferential equations.οΏ½οΏ½ = ππ¦ β πΏ1π₯2 β π1π₯ β π½π₯ β πΎ1 (1 β π) π₯π§οΏ½οΏ½ = π½π₯ β πΏ2π¦2 β π2π¦ β πΎ2 (1 β π) π¦π§οΏ½οΏ½ = π1πΎ1 (1 β π) π₯π§ + π2πΎ2 (1 β π) π¦π§ β πΏ3π§2 β π3π§
(1)
with initial conditions, π₯(0) > 0, π¦(0) > 0, and π§(0) > 0.In order to simplify the analysis of system (1) the number
of parameters in system (1) is reduced using the followingdimensionless variables in system (1):
π¦1 = π1πΎ1 (1 β π)π2 π₯,π¦2 = π2πΎ2 (1 β π)π2 π¦,π¦3 = πΏ3π2 π§,π‘ = π2π.
(2)
Accordingly, the dimensionless form of system (1) can bewritten as οΏ½οΏ½1 = π1π¦2 β π2π¦21 β π3π¦1 β π4π¦1π¦3οΏ½οΏ½2 = π1π¦1 β π2π¦22 β π¦2 β π3π¦2π¦3οΏ½οΏ½3 = π¦1π¦3 + π¦2π¦3 β π¦23 β π4π¦3,
(3)
where the dimensionless parameters are given by
π1 = π1πΎ1ππ2πΎ2π2 ,π2 = πΏ1π1πΎ1 (1 β π) ,π3 = π1 + π½π2 ,π4 = πΎ1 (1 β π)πΏ3 ,π1 = π2πΎ2π½π1πΎ1π2 ,π2 = πΏ2π2πΎ2 (1 β π) ,π3 = πΎ2 (1 β π)πΏ3 ,π4 = π3π2 .
(4)
According to the equations given in system (3), all theinteraction functions are continuous and have a continuouspartial derivatives.Therefore they are Lipschitzain and hencethe solution of system (3) exists and is unique. Moreover thesolution of system (3) is bounded as shown in the followingtheorem.
Theorem 1. All the solutions of system (3) that initiate in thepositive octant are uniformly bounded.
Proof. Let π = π¦1 + π¦2 + π¦3 be solutions of system (3) withinitial conditions, π¦1(0) > 0, π¦2(0) > 0, and π¦3(0) > 0. Thenby differentiation π with respect to π‘ we getππππ‘ β€ π1π¦2 (1 β π¦2π1/π2) + π1π¦1 (1 β π¦1π1/π2) β π1π
β€ π2 β π1π; (5)
here π1 = min {1, π3, π4} and π2 = π21/4π2 + π21 /4π2. Now byusing comparison theorem, we get
0 < π β€ (π0πβπ1π‘ + π2π1 (1 β πβπ1π‘)) . (6)
Thus for π‘ β β we obtain 0 < π β€ π2/π1. Hence, allsolutions of system (3) in π 3+ are uniformly bounded andtherefore we have finished the proof.
3. Local Stability Analysis
It is observed that system (3) has at most three biologicallyfeasible equilibrium points; namely, πΈπ, π = 0, 1, 2. Theexistence conditions for each of these equilibrium points arediscussed below:
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(1) The trivial equilibrium points πΈ0 = (0, 0, 0) existalways.
(2) The predator free equilibrium point is denoted byπΈ1 = (οΏ½οΏ½1, οΏ½οΏ½2, 0), whereοΏ½οΏ½1 = 1π1 (π2οΏ½οΏ½22 + οΏ½οΏ½2) (7)
while οΏ½οΏ½2 is a positive root of the following third-orderpolynomialπ΄1π¦32 + π΄2π¦22 + π΄3π¦2 + π΄4 = 0; (8)
here, π΄1 = π2π22 /π21 , π΄2 = 2π2π2/π21 , π΄3 = (π2 +π3π1π2)/π21 , and π΄4 = (π3 β π1π1)/π1 exist uniquely inthe interior of π¦1π¦2-plane if and only if the followingcondition holds: π3 < π1π1. (9)
(3) The interior (positive) equilibrium point is given byπΈ2 = (π¦β1 , π¦β2 , π¦β3 ), whereπ¦β1 = [(π2 + π3) π¦β2 + (1 β π3π4)] π¦β2π1 β π3π¦β2 ,π¦β3 = π¦β1 + π¦β2 β π4 (10)
while π¦β2 is a positive root of the following third-orderpolynomial:π΅1π¦32 + π΅2π¦22 + π΅3π¦2 + π΅4 = 0; (11)
here,π΅1 = π2 (π2 + π3)2 + π4π2 (π2 + π3) > 0,π΅2 = [2π2 (π2 + π3) + 2π4π2 + π4π3] (1 β π3π4)β [π3π2π3 + π23 (π3 + π1)] ,π΅3 = 2π1π1π3 + (π2 + π4) (1 β π3π4)2+ π1 (π3 β π4π4) (π2 + π3)+ [π1π4 β π3 (π3 β π4π4)] (1 β π3π4) ,π΅4 = π1 [π3 β π1π1 β π3π3π4 β π4π4 (1 β π3π4)] .
(12)
Clearly, (11) has a unique positive root represented byπ¦β2 if the following set of conditions hold:π΅4 < 0 with (π΅2 > 0 or π΅3 < 0) (13)
Therefore, πΈ2 exists uniquely in int. π 3+ if in additionto condition (13) the following conditions are satis-fied. π¦β1 + π¦β2 > π4π3π4 β 1π2 + π3 < π¦β2 < π1π3
or π1π3 < π¦β2 < π3π4 β 1π2 + π3 .(14)
Now to study the local stability of these equilibrium points,the Jacobian matrix π½(π¦1, π¦2, π¦3) for the system (3) at anypoint (π¦1, π¦2, π¦3) is determined as
(β2π2π¦1 β π3 β π4π¦3 π1 βπ4π¦1π1 β2π2π¦2 β 1 β π3π¦3 βπ3π¦2π¦3 π¦3 π¦1 + π¦2 β 2π¦3 β π4). (15)
Thus, system (3) has the following Jacobian matrix near πΈ0 =(0, 0, 0).π½ (πΈ0) = (βπ3 π1 0π1 β1 00 0 βπ4). (16)
Then the characteristic equation of π½(πΈ0) is given by
(π + π4) [π2 + (π3 + 1) π + π3 β π1π1] = 0. (17)
Clearly, all roots of (17) have negative real parts if and only ifthe following condition holds:
π3 > π1π1. (18)
So, πΈ0 is locally asymptotically stable under condition (18)and saddle point otherwise. Therefore, πΈ0 is locally asymp-totically stable whenever πΈ1 does not exist and unstablewhenever πΈ1 exists.
The Jacobianmatrix of system (3) around the equilibriumpoint πΈ1 = (οΏ½οΏ½1, οΏ½οΏ½2, 0) reduced to
π½ (πΈ1) = (β2π2οΏ½οΏ½1 β π3 π1 βπ4οΏ½οΏ½1π1 β2π2οΏ½οΏ½2 β 1 βπ3οΏ½οΏ½20 0 οΏ½οΏ½1 + οΏ½οΏ½2 β π4)= (πππ)3Γ3 .(19)
Then the characteristic equation of π½(πΈ1) is written by
[π β π33] [π2 β (π11 + π22) π + π11π22 β π12π21] = 0. (20)
Straightforward computation shows that all roots of (20) havenegative real part provided that
οΏ½οΏ½1 + οΏ½οΏ½2 < π4 (21)(2π2οΏ½οΏ½1 + π3) (2π2οΏ½οΏ½2 + 1) > π1π1. (22)
So, πΈ1 is locally asymptotically stable if the above twoconditions hold.
Finally the Jacobian matrix of system (3) around theinterior equilibrium point πΈ2 = (π¦β1 , π¦β2 , π¦β3 ) is written
π½ (πΈ2) = (πππ)3Γ3 ; (23)
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here π11 = β (2π2π¦β1 + π4π¦β3 + π3) ,π12 = π1,π13 = βπ4π¦β1 ,π21 = π1,π22 = β (2π2π¦β2 + π3π¦β3 + 1) ,π23 = βπ3π¦β2 ,π31 = π¦β3 ,π32 = π¦β3 ,π33 = βπ¦β3 .
(24)
Hence, the characteristic equation of π½(πΈ2) becomes
π3 + π·1π2 + π·2π + π·3 = 0 (25)
withπ·1 = β (π11 + π22 + π33) > 0,π·2 = π11π22 β π12π21 + π11π33 β π13π31 + π22π33β π23π32,π·3 = π33 (π12π21 β π11π22) + π11π23π32 β π12π23π31+ π22π13π31 β π21π13π32.(26)
Consequently, Ξ = π·1π·2 β π·3 can be written as
Ξ = (π11 + π22) (π12π21 β π11π22) β π11π22π33β (π11 + π22) (π11π33 β π13π31) .β π222π33 β π11π233 β π22π233 + π13π31 (π33 + π21)+ π23π32 (π33 + π12)(27)
Since π·1 > 0, then according to Routh-Hurwitz criterion πΈ2is locally asymptotically stable if and only if π·3 > 0 and Ξ =π·1π·2 βπ·3 > 0. According to the form ofπ·3 and the signs ofJacobian elements the last four terms are positive, while thefirst term will be positive under the sufficient condition (28)below. However Ξ becomes positive if and only if in additionto condition (28) the second sufficient condition given by (29)holds.
(2π2π¦β1 + π4π¦β3 + π3) (2π2π¦β2 + π3π¦β3 + 1) > π1π1 (28)π¦β3 > π1,π¦β3 > π1. (29)
Therefore under these two sufficient conditions πΈ2 is locallyasymptotically stable.
4. Global Stability
In this section the global stability for the equilibrium pointsof system (3) is investigated by using the Lyapunov methodas shown in the following theorems.
Theorem 2. Assume that the vanishing equilibrium pointπΈ0 islocally asymptotically stable; then it is globally asymptoticallystable in π 3+ if and only if the following condition holds:π4π1π3 < π3 < π4π1 . (30)
Proof. Consider the following positive definite real valuedfunction: π0 (π¦1, π¦2, π¦3) = 1π4π¦1 + 1π3π¦2 + π¦3. (31)
Straightforward computation shows that the derivative of π0with respect to π‘ is given byππ0ππ‘ < (π4π1 β π3π3π4π3 )π¦1 + (π1π3 β π4π4π3 )π¦2 β π4π¦3. (32)
Therefore, by using condition (30), we obtain ππ0/ππ‘ whichis negative definite in π 3+, and thenπ0 is a Lyapunov functionwith respect to πΈ0. Hence πΈ0 is globally asymptotically stablein π 3+ and the proof is complete.
Theorem 3. Assume that the predator free equilibrium pointπΈ1 = (οΏ½οΏ½1, οΏ½οΏ½2, 0) is locally asymptotically stable; then it isglobally asymptotically stable in π 3+ if the following conditionholds:
( π1π4π¦1 + π1π3π¦2)2< 4( π1οΏ½οΏ½2π4π¦1οΏ½οΏ½1 + π2π4)( π1οΏ½οΏ½1π3π¦2οΏ½οΏ½2 + π2π3) . (33)
Proof. Consider the following positive definite real valuedfunction:
π1 (π¦1, π¦2, π¦3) = 1π4 (π¦1 β οΏ½οΏ½1 β οΏ½οΏ½1 ln π¦1οΏ½οΏ½1)+ 1π3 (π¦2 β οΏ½οΏ½2 β οΏ½οΏ½2 ln π¦2οΏ½οΏ½2) + π¦3. (34)
Straightforward computation shows that the derivative of π1with respect to π‘ is given byππ1ππ‘ = β( π1οΏ½οΏ½2π4π¦1οΏ½οΏ½1 + π2π4) (π¦1 β οΏ½οΏ½1)2
β ( π1οΏ½οΏ½1π3π¦2οΏ½οΏ½2 + π2π3) (π¦2 β οΏ½οΏ½2)2+ ( π1π4π¦1 + π1π3π¦2) (π¦1 β οΏ½οΏ½1) (π¦2 β οΏ½οΏ½2) β π¦23β (π4 β οΏ½οΏ½1 β οΏ½οΏ½2) π¦3.
(35)
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Now using condition (33) gives us thatππ1ππ‘ < β[β π1οΏ½οΏ½2π4π¦1οΏ½οΏ½1 + π2π4 (π¦1 β οΏ½οΏ½1)β β π1οΏ½οΏ½1π3π¦2οΏ½οΏ½2 + π2π3 (π¦2 β οΏ½οΏ½2)]2 β (π4 β οΏ½οΏ½1 β οΏ½οΏ½2) π¦3.
(36)
Clearly ππ1/ππ‘ is negative definite due to local stabilitycondition (21). Hence π1 is a Lyapunov function with respectto πΈ1, and then πΈ1 is globally asymptotically stable, whichcompletes the proof.
Theorem 4. Assume that the interior equilibrium point πΈ2 =(π¦β1 , π¦β2 , π¦β3 ) is locally asymptotically stable in π 3+; then itis globally asymptotically stable if and only if the followingcondition holds:
(π¦β2 π1π3π¦β1 π1 β π4)2 < 4π¦β2 π1π2π3π4π¦β1 π1 . (37)
Proof. Consider the following positive definite real valuedfunction around πΈ2:π1 (π¦1, π¦2, π¦3) = (π¦1 β π¦β1 β π¦β1 ln π¦1π¦β1 )
+ π¦β2 π1π¦β1 π1 (π¦2 β π¦β2 β π¦β2 ln π¦2π¦β2 )+ π¦β2 π1π3π¦β1 π1 (π¦3 β π¦β3 β π¦β3 ln π¦3π¦β3 ) .
(38)
Our computation for the derivative of π2 with respect to π‘gives thatππ2ππ‘ = β π1π¦1π¦2π¦β1 (π¦2π¦β1 β π¦1π¦β2 )2 β π2 (π¦1 β π¦β1 )2
β π¦β2 π1π2π¦β1 π1 (π¦2 β π¦β2 )2+ (π¦β2 π1π3π¦β1 π1 β π4) (π¦1 β π¦β1 ) (π¦3 β π¦β3 )β π¦β2 π1π3π4π¦β1 π1 (π¦3 β π¦β3 )2 .
(39)
Now by using the condition (37) we obtain thatππ2ππ‘< β π1π¦1π¦2π¦β1 (π¦2π¦β1 β π¦1π¦β2 )2 β π¦β2 π1π2π¦β1 π1 (π¦2 β π¦β2 )2
β [βπ2 (π¦1 β π¦β1 ) β βπ¦β2 π1π3π4π¦β1 π1 (π¦3 β π¦β3 )]2 .(40)
According to the above inequality we have ππ2/ππ‘ whichis negative definite; therefore, πΈ2 is globally asymptoticallystable in π 3+ and hence the proof is complete.
5. Local Bifurcation
In this section the local bifurcation near the equilibriumpoints of system (3) is investigated using Sotomayorβs the-orem for local bifurcation [24]. It is well known that theexistence of nonhyperbolic equilibrium point is a necessarybut not sufficient condition for bifurcation to occur. Nowrewrite system (3) in the form
οΏ½οΏ½ = π (π) , (41)
where π = (π¦1, π¦2, π¦3)π ,π = (π1, π2, π3)π . (42)
Then according to Jacobian matrix of system (3) given in(15), it is simple to verify that for any nonzero vector π =(π’1, π’2, π’3)π we haveπ·2π (π¦1, π¦2, π¦3) (π, π)
= π2πππ¦21 π’21 + π2πππ¦1ππ¦2 π’1π’2 + π2πππ¦2ππ¦1 π’2π’1 + π2πππ¦22 π’22+ π2πππ¦1ππ¦3 π’1π’3 + π2πππ¦3ππ¦1 π’3π’1 + π2πππ¦2ππ¦3 π’2π’3+ π2πππ¦3ππ¦2 π’3π’2 + π2πππ¦23 π’23.
(43)
Consequently, we obtain that
π·2π (π¦1, π¦2, π¦3) (π, π) = ( β2π2π’21 β 2π4π’1π’3β2π2π’22 β 2π3π’2π’32π’1π’3 + 2π’2π’3 β 2π’23) (44)
and therefore
π·3π (π¦1, π¦2, π¦3) (π, π,π) = (000) . (45)
Thus system (3) has no pitchfork bifurcation due to (45).Moreover, the local bifurcation near the equilibrium pointsis investigated in the following theorems:
Theorem 5. System (3) undergoes a transcritical bifurcationnear the vanishing equilibrium point, but saddle node bifurca-tion cannot occur, when the parameter π3 passes through thebifurcation value πβ3 = π1π1.Proof. According to the Jacobian matrix π½(πΈ0) given by (16),system (3) at the equilibrium point πΈ0 with π3 = πβ3 has zeroeigenvalue, say πβ0 = 0, and the Jacobian matrix π½(πΈ0, πβ3 )becomes
π½ (πΈ0, πβ3 ) = π½β0 = (βπβ3 π1 0π1 β1 00 0 βπ4). (46)
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Now let π[0] = (π’[0]1 , π’[0]2 , π’[0]3 )π be the eigenvector corre-sponding to the eigenvalue πβ0 = 0. Thus π½β0π[0] = 0 givesπ[0] = (π’[0]1 , π1π’[0]1 , 0)π, where π’[0]1 represents any nonzeroreal number. Also, let π[0] = (π€[0]1 , π€[0]2 , π€[0]3 )π representsthe eigenvector corresponding to the eigenvalue πβ0 = 0 ofπ½βπ0 . Hence π½βπ0 π[0] = 0 gives that π[0] = (π€[0]1 , π1π€[0]1 , 0)π,where π€[0]1 denotes any nonzero real number. Now, since
ππππ3 = ππ3 (π, π3) = (ππ1ππ3 , ππ2ππ3 , ππ3ππ3)π= (βπ¦1, 0, 0)π (47)
thusππ3(πΈ0, πβ3 ) = (0, 0, 0)π, which gives (π[0])πππ3(πΈ0, πβ3 ) =0. So, according to Sotomayorβs theorem for local bifurcation,system (3) has no saddle node bifurcation at π3 = πβ3 . Also,since
π·ππ3 (πΈ0, π3) = (β1 0 00 0 00 0 0) (48)
then,
(π[0])π (π·ππ3 (πΈ0, πβ3 ) π[0])= (π€[0]1 , π1π€[0]1 , 0) (βπ’[0]1 , 0, 0)π = βπ’[0]1 π€[0]1 = 0. (49)
Moreover, by substituting πΈ0, πβ3 , and π[0] in (44) we get that
π·2π (πΈ0, πβ3 ) (π[0], π[0])= (β2π2 (π’[0]1 )2 , β2π2π21 (π’[0]1 )2 , 0)π . (50)
Hence, it is obtain that
(π[0])ππ·2π (πΈ0, πβ3 ) (π[0], π[0])= β2 (π2 + π1π2π21 ) (π’[0]1 )2 π€[0]1 = 0. (51)
Thus, according to Sotomayorβs theorem system (3) has atranscritical bifurcation at πΈ0 as the parameter π3 passesthrough the value πβ3 ; thus the proof is complete.
Theorem 6. Assume that condition (22) holds; then system(3) undergoes a transcritical bifurcation near the predator freeequilibrium pointπΈ1, but saddle node bifurcation cannot occur,when the parameter π4 passes through the bifurcation valueπβ4 = οΏ½οΏ½1 + οΏ½οΏ½2.Proof. According to the Jacobian matrix π½(πΈ1) given by (19),system (3) at the equilibrium point πΈ1 with π4 = πβ4 has zeroeigenvalue, say πβ1 = 0, and the Jacobian matrix π½(πΈ1, πβ4 )becomes π½ (πΈ1, πβ4 ) = π½β1 = (πβππ)3Γ3 , (52)
where πβππ = πππ; βπ, π = 1, 2, 3, with πβ33 = 0. Now let,π[1] = (π’[1]1 , π’[1]2 , π’[1]3 )π be the eigenvector correspondingto the eigenvalue πβ1 = 0. Thus π½β1π[1] = 0 gives π[1] =(Ξ 1π’[1]3 , Ξ 2π’[1]3 , π’[1]3 )π, whereΞ 1 = (π12π23βπ22π13)/(π11π22βπ12π21) and Ξ 2 = (π21π13 β π11π31)/(π11π22 β π12π21) arenegative according to the sign of the Jacobian elements andπ’[1]3 represents any nonzero real numbers. Also, let π[1] =(π€[1]1 , π€[1]2 , π€[1]3 )πrepresent the eigenvector corresponding toeigenvalue πβ1 = 0 of π½βπ1 . Hence π½βπ1 π[1] = 0 gives thatπ[1] = (0, 0, π€[1]3 )π, where π€[1]3 stands for any nonzero realnumbers. Now, sinceππππ4 = ππ4 (π, π4) = (ππ1ππ4 , ππ2ππ4 , ππ3ππ4)π = (0, 0, βπ¦3)π (53)
thus ππ4(πΈ1, πβ4 ) = (0, 0, 0)π, which gives (π[1])πππ4(πΈ1, πβ4 ) =0. So, according to Sotomayorβs theorem for local bifurcation,system (3) has no saddle node bifurcation at π4 = πβ4 . Also,since
π·ππ4 (πΈ1, π4) = (0 0 00 0 00 0 β1) (54)
then, we can have
(π[1])π (π·ππ4 (πΈ1, πβ4 ) π[1])= (0, 0, π€[1]3 ) (0, 0, βπ’[1]3 )π = βπ’[1]3 π€[1]3 = 0. (55)
Moreover, substituting πΈ1, πβ4 , and π[1] in (44) gives
π·2π (πΈ1, πβ4 ) (π[1], π[1]) = 2 (π’[1]3 )2β (βπ2Ξ21 β π4Ξ 1, βπ2Ξ22 β π3Ξ 2, Ξ 1 + Ξ 2 β 1)π . (56)
Hence, it is obtained that
(π[1])ππ·2π (πΈ1, πβ4 ) (π[1], π[1])= 2 (Ξ 1 + Ξ 2 β 1) (π’[1]3 )2 π€[1]3 = 0. (57)
Thus, according to Sotomayorβs theorem system (3) has atranscritical bifurcation at πΈ1 as the parameter π4 passesthrough the value πβ4 ; thus the proof is complete.
Theorem 7. Assume that condition (21) holds; then system(3) undergoes a saddle node bifurcation near the predator freeequilibrium point πΈ1 when the parameter π1 passes through thebifurcation value πβ1 = (2π2οΏ½οΏ½1 + π3)(2π2οΏ½οΏ½2 + 1)/π1.Proof. According to the Jacobian matrix π½(πΈ1) given by (19),system (3) at the equilibrium point πΈ1 with π1 = πβ1 has zeroeigenvalue, say πββ1 = 0, and the Jacobian matrix π½(πΈ1, πβ1 )becomes π½ (πΈ1, πβ1 ) = π½ββ1 = (πββππ )
3Γ3, (58)
International Journal of Differential Equations 7
where πββππ = πππ; βπ, π = 1, 2, 3, with πββ12 = πβ1 . Now letπ[11] = (π’[11]1 , π’[11]2 , π’[11]3 )π be the eigenvector correspondingto the eigenvalue πββ1 = 0. Thus π½ββ1 π[11] = 0 gives π[11] =(β(πβ1 /π11)π’[11]2 , π’[11]2 , 0)π, where π’[11]2 represents any nonzeroreal numbers. Also, letπ[11] = (π€[11]1 , π€[11]2 , π€[11]3 )π representthe eigenvector corresponding to eigenvalue πββ1 = 0 ofπ½ββπ1 . Hence π½ββπ1 π[11] = 0 gives that π[11] = (β(π21/π11)π€[11]2 , π€[11]2 , (Ξ¨/π11π33)π€[11]2 )π, where Ξ¨ = π13π21 β π11π23is negative due to the sign of the Jacobian elements and π€[11]2denotes any nonzero real numbers. Now, sinceππππ1 = ππ1 (π, π1) = (ππ1ππ1 , ππ2ππ1 , ππ3ππ1)π = (π¦2, 0, 0)π (59)
thus ππ1(πΈ1, πβ1 ) = (οΏ½οΏ½2, 0, 0)π; hence (π[11])πππ1(πΈ1, πβ1 ) =β(π21/π11)π€[11]2 οΏ½οΏ½2 = 0. So, according to Sotomayorβs theoremfor local bifurcation the first condition of saddle nodebifurcation is satisfied in system (3) at π1 = πβ1 . Moreover,substituting πΈ1, πβ1 , and π[11] in (44) gives
π·2π (πΈ1, πβ1 ) (π[11], π[11])= (π’[11]2 )2 (β2π2πβ21π211 , β2π2, 0)π . (60)
Hence, it is obtained that
(π[11])ππ·2π (πΈ1, πβ1 ) (π[11], π[11])= 2(π2πβ21 π21π311 β π2)(π’[11]2 )2 π€[11]2 = 0. (61)
Thus, according to Sotomayorβs theorem system (3) has asaddle node bifurcation at πΈ1 as the parameter π1 passesthrough the value πβ1 ; thus the proof is complete.
Theorem 8. Assume that(2π2π¦β1 + π4π¦β3 + π3) (2π2π¦β2 + π3π¦β3 + 1) < π1π1 (62)
π¦β1 < π1π4 . (63)
Then system (3) undergoes a saddle node bifurcation nearthe interior equilibrium point πΈ2, as the parameter π1 passesthrough the bifurcation value πβ1 = Ξ1/Ξ2, where Ξ1 and Ξ2 aregiven in the proof.
Proof. According to the determinant of the Jacobian matrixπ½(πΈ2) given by π·3 in (25), condition (62) represents anecessary condition to have nonpositive determinant forπ½(πΈ2). Now rewrite the form of the determinant as follows:π·3 = Ξ1 β π1Ξ2. (64)
Here Ξ1 = π11π23π32 + π22π31π13 β π11π22π33 β π12π23π31 andΞ2 = π13π32βπ33π12. Obviously, Ξ1 is positive always, while Ξ2 ispositive under the condition (63).Thus it is easy to verify that
π·3 = 0 and hence π½(πΈ2) has zero eigenvalue, say πβ2 = 0, asπ1 passes through the value πβ1 = Ξ1/Ξ2, which means that πΈ2becomes a nonhyperbolic point. Let now the Jacobian matrixof system (3) at πΈ2 with π1 = πβ1 be given by
π½ (πΈ2, πβ1 ) = π½β2 = (πβππ)3Γ3 , (65)
where πβππ = πππ βπ, π = 1, 2, 3, and πβ21 = πβ1 .Let π[β] = (π’[β]1 , π’[β]2 , π’[β]3 )π be the eigenvector corre-
sponding to the eigenvalue πβ2 = 0. Thus π½β2π[β] = 0gives π[β] = (Ξ¦1π’[β]3 , Ξ¦2π’[β]3 , π’[β]3 )π, where Ξ¦1 = (π12π23 βπ22π13)/(π11π22 β π12πβ1 ) and Ξ¦2 = (πβ1 π13 β π11π23)/(π11π22 βπ12πβ1 ) are positive due to the Jacobian elements and π’[β]3represents any nonzero real number. Also, let π[β] =(π€[β]1 , π€[β]2 , π€[β]3 )π represent the eigenvector correspondingto eigenvalue πβ2 = 0 of π½βπ2 . Hence π½βπ2 π[β] = 0 givesthat π[β] = (Ξ1π€[β]3 , Ξ2π€[β]3 , π€[β]3 )π, where Ξ1 = (π21π32 βπ22π31)/(π11π22 β π12πβ1 ) and Ξ2 = (π12π31 β π11π32)/(π11π22 βπ12πβ1 ) are negative due to the Jacobian elements and π€[β]3denotes any nonzero real numbers. Now, since
ππππ1 = ππ1 (π, π1) = (ππ1ππ1 , ππ2ππ1 , ππ3ππ1)π = (0, π¦1, 0)π (66)
thus ππ1(πΈ2, πβ1 ) = (0, π¦β1 , 0)π, which gives (π[β])πππ1(πΈ2,πβ1 ) = Ξ2π¦β1π€[β]3 = 0. Consequently the first condition ofsaddle node bifurcation is satisfied.Moreover, by substitutingπΈ2, πβ1 , and π[β] in (44) we get that
π·2π (πΈ2, πβ1 ) (π[β], π[β]) = 2 (π’[β]3 )2β (βπ2Ξ¦21 β π4Ξ¦1, βπ2Ξ¦22 β π3Ξ¦2, Ξ¦1 + Ξ¦2 β 1)π . (67)
Hence, it is obtained that
(π[β])ππ·2π (πΈ2, πβ1 ) (π[β], π[β]) = 2 (π’[β]3 )2 π€[β]3Γ [β (π2Ξ¦21 + π4Ξ¦1)Ξ1 β (π2Ξ¦22 + π3Ξ¦2)Ξ2+ (Ξ¦1 + Ξ¦2 β 1)] = 0.(68)
So, according to Sotomayorβs theorem, system (3) has a saddlenode bifurcation as π1 passes through the value πβ1 and hencethe proof is complete.
6. Numerical Simulations
In this section, the global dynamics of system (3) is investi-gated numerically. The objectives first confirm our obtainedanalytical results and second specify the control set of param-eters that control the dynamics of the system. Consequently,system (3) is solved numerically using the following biologi-cally feasible set of hypothetical parameters with different sets
8 International Journal of Differential Equations
00.5
11.5
2
00.5
11.5
(0.5, 1, 1.7)
(1.5, 1.5, 1.5)
(0.2, 0.2, 0.2)
(0.9, 0.8, 0.7)
(0.46, 0.15, 0.42)
y1
y2
0
0.5
1
1.5
2
y3
Figure 1: 3D phase plot of the system (3) for the data given by(69) starting from different initial values in which the solutionapproaches asymptotically to 0.46, 0.15, and 0.42.
of initial points and then the resulting trajectories are drawnin the form of phase portrait and time series figures.π1 = 2,π2 = 0.1,π3 = 0.4,π4 = 0.5,π1 = 0.4,π2 = 0.1,π3 = 0.5,π4 = 0.2.
(69)
Clearly, Figure 1 shows the asymptotic approach of thesolutions, which started from different initial points to apositive equilibrium point (0.46, 0.15, 0.42), for the datagiven by (69). This confirms our obtained result regardingthe existence of globally asymptotically stable positive pointof system (3) provided that certain conditions hold.
Now in order to discuss the effect of the parameters valuesof system (3) on the dynamical behavior of the system, thesystem is solved numerically for the data given in (69) withvarying one parameter each time. It is observed that varyingparameters values π2, π4, π2, π3, and π4 have no qualitativeeffect on the dynamical behavior of system (3) and thesystem still approaches to a positive equilibrium point. Onthe other hand, when π1 decreases in the range (π1 β€ 1.05)keeping other parameters fixed as given in (69) the dynamicalbehavior of system (3) approaches asymptotically to thevanished equilibrium point as shown in the typical figuregiven by Figure 2. Similar observations have been obtained onthe behavior of system (3) in case of increasing the parameterπ3 in the range (π3 β₯ 0.8) or decreasing the parameter π1 inthe range (π1 β€ 0.2), with keeping other parameters fixed asgiven in (69), and then the solution of system (3) is depictedin Figures 3 and 4, respectively. Finally, for the parametersπ2 = 0.9 and π4 = 0.7 with other parameters fixed as given in
y1
y2
y3
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Popu
latio
ns
2000 4000 6000 8000 100000Time
Figure 2: Time series of system (3) approaches asymptotically tothe vanishing equilibrium point for π1 = 0.8 with other parametersgiven by (69).
y1
y2
y3
5000 10000 150000Time
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Popu
latio
ns
Figure 3: Time series of system (3) approaches asymptotically tothe vanishing equilibrium point for π3 = 0.85with other parametersgiven by (69).
(69), the solution of system (3) approaches asymptotically tothe predator free equilibrium point as shown in the Figure 5.
7. Discussion
In this paper, amodel that describes the prey-predator systemhaving a refuge and stage structure properties in the preypopulation has been proposed and studied analytically aswell as numerically. Sufficient conditions which ensure the
International Journal of Differential Equations 9
0
0.2
0.4
0.6
0.8
1
Popu
latio
ns
1000 2000 3000 4000 5000 6000 7000 8000 9000 100000Time
y1
y2
y3
Figure 4: Time series of system (3) approaches asymptotically tothe vanishing equilibrium point for π1 = 0.15 with other parametersgiven by (69).
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Popu
latio
ns
2000 4000 6000 8000 100000Time
y1
y2
y3
Figure 5: Time series of system (3) approaches asymptotically to thepredator free equilibrium point πΈ1 = (0.42, 0.16, 0) for π2 = 0.9 andπ4 = 0.7 with other parameters given by (69).
stability of equilibria and the existence of local bifurcationare obtained. The effect of each parameter on the dynam-ical behavior of system (3) is studied numerically and thetrajectories of the system are drowned in the typical figures.According to these figures, which represent the solutionof system (3) for the data given by (69), the followingconclusions are obtained.
(1) System (3) has no periodic dynamics rather than thefact that the system approaches asymptotically to oneof their equilibrium points depending on the set of
parameter data and the stability conditions that aresatisfied.
(2) Although the position of the positive equilibriumpoint in the interior of π 3+ changed as varying inthe parameters values π2, π4, π2, π3, and π4, there isno qualitative change in the dynamical behavior ofsystem (3) and the system still approaches to a positiveequilibrium point. Accordingly adding the refugefactorwhich is included implicitly in these parametersplays a vital role in the stabilizing of the system at thepositive equilibrium point.
(3) Decreasing in the value of growth rate of immatureprey or in the value of conversion rate from immatureprey tomature prey keeping the rest of parameter as in(69) leads to destabilizing of the positive equilibriumpoint and the system approaches asymptotically to thevanishing equilibrium point, which means losing thepersistence of system (3).
(4) Increasing in the value of grownup rate of immatureprey keeping the rest of parameter as in (69) leadsto destabilizing of the positive equilibrium pointand the system approaches asymptotically to thevanishing equilibrium point too, which means losingthe persistence of system (3).
(5) Finally, for the data given by (69), increasing intraspe-cific competition of immature prey and natural deathrate of the predator leads to destabilizing of the pos-itive equilibrium point and the solution approachesinstead asymptotically to the predator free equilib-rium point, which confirm our obtained analyticalresults represented by conditions (21)-(22).
Competing Interests
The authors declare that they have no competing interests.
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