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1. Introduction
The study of dynamical behavior of the predator-prey model has been an important theme in mathematical biology; see, for instance [1–5], and references therein. The results of these studies could give us substantial elucidation about the qualitative behavior of the density of each population in the future time, such as stability, bifurcations, and chaos, without having any experimental laboratory. In the last few decades, special attention has been paid to the merger of the predator-prey model with the model for transmissible disease as a new branch of mathematical biology known as the eco-epidemiological model. It becomes an important tool in analyzing the effect of infectious diseases on the existence (extinction) of prey or/and predator populations. Several researchers have discussed the eco-epidemiological model incorporating ecological factors, such as harvesting [6], prey refuge [7, 8], social behavior [9], and the Alee effect [10].
One interesting phenomenon was introduced by [11] which demonstrated a condition where, at low densities of population, the presence of conspecifics could increase the per capita growth rate of the population. This phenomenon is called the Allee effect. Some population models involving the Allee effect have been developed to exhibit the important impact of this phenomenon on many aspects of population ecology, such as conservation of threatened species [12, 13], controlling pest species [14], and harvesting management [15, 16]. In general, there are two types of the Allee effects: the strong Allee effect and the weak Allee effect. The strong Allee effect has a threshold size population which is called the Allee threshold. When the density of population is under this threshold then the per capita growth rate of the population becomes negative. On the other hand, the weak Allee effect gives a reduction in the per capita growth rate when the population is low. Furthermore, several researchers investigate the dynamical behavior of a system incorporating any situation in which two or more components of the Allee effect can work simultaneously on a single population which is called the double Allee effect [1, 17]. These components could arrive from the reproduction or/and survival mechanisms such as the difficulty of finding a mate, cooperative breeding dependencies, cooperative antipredator behavior, and environmental conditioning, as shown in Table 1 [18].
Table 1
Parameter description in system (2).
Parameters | Ecological descriptions |
Intrinsic growth rate of prey | |
Intrinsic growth rate of susceptible predator | |
Carrying capacity of prey | |
Capture rate of susceptible predator | |
Prey saturation constant | |
Another saturation constant | |
The strength of interference between susceptible predators in predation process | |
The Allee threshold | |
The auxiliary Allee effect constant | |
Intraspecific competition rate among predators | |
Alternative food for the predator | |
Transmission rate of the disease | |
Death rate of infected predator |
Nowadays, fractional-order derivative modelling has become popular in many fields of science, such as physics, thermodynamics, biology, control theory, and many others (see, for example, [19–22]). Modeling using a fractional-order derivative has a major advantage in that it involves memory which comes from the fact that the fractional-order operators are nonlocal. More precisely, all of the previous conditions are captured in defining the fractional-order derivative. It has some advantages over the integer order derivative, especially the ability to describe the memory and hereditary properties which are inherent in various processes [23–25]. Some scholars had proven that systems with memory are more consistent and adequate with the real phenomena [26, 27].
Recently, [28] studied a fractional-order predator-prey model by assuming that the predation follows the Beddington-DeAngelis functional response and the double Allee effect on the predator population. By the last assumption, there is always a bistability condition for the strong Allee effect case. In other words, there is an extinction or existing condition for the predator depending on the choice of the initial condition. In this paper, we consider a predator-prey model in [28] by adding the assumption that there is a transmission of disease in the predator population. Biologically, the growth rates of a population must depend on the history of its previous conditions not only on the local conditions, and for this reason, the proposed model will use the fractional-order derivative which has a memory effect, to make it more accurate in predicting the future condition of the population. To the best of our knowledge, no investigation has been carried out on the dynamics of the proposed system. An important objective of this paper is to study how the spread of disease may affect changes in predator densities over time, where the intrinsic growth rate of the predator is affected by the double Allee effect.
We have arranged this paper in the following manner. First, we propose a model and give some useful preliminaries which are used in our analysis briefly. Next, we prove the basic properties of solutions. We also study the existence of the equilibrium points, their local stability, and the Hopf bifurcation. The global stability conditions for the equilibrium points are also examined. Moreover, some numerical simulations with a set of hypothetical parameters are demonstrated to validate the theoretical results and further explore the role of the disease in the predator-prey interaction. Finally, conclusions are given in the last section.
2. Formulation Model and Useful Preliminaries
In [28], the author’s considered a predator-prey model with memory effect, which is a modification of the Leslie–Gower model using the Caputo fractional derivative. The model abandoned the mass conservation principle held by the Lotka–Volterra model because of the assumption that both prey and predator obey the logistic law. They also assume that the predation process is governed by the Beddington-DeAngelis type functional response [29] which is a nonlinear prey-predator-dependent functional response, and that the intrinsic growth rate of the predator population is influenced by the double Allee effect, as given in the following form:
In this paper, we assume that the predator population is split into two subpopulations, namely the susceptible predator
Considering the above assumptions, we construct a fractional-order model with the double Allee effect and disease in predator as follows:
Since the right hand side of system (2) have time dimension
For the sake of convenience, we redefine parameters of the system (3) as
Definition 1.
(see [32]). Let
To verify the non-negativity and uniform boundedness of the solutions of the system (4), we require the following lemma for the fractional derivative.
Lemma 2 (see [33]).
Suppose that
Lemma 3 (see [33]).
Suppose that
Lemma 4 (comparison lemma [34]).
Suppose
Next, we use the following theorem to determine the local stability behavior of the equilibrium points of the system (4).
Theorem 5 (Matignon condition [35]).
Consider the following Caputo fractional-order system with initial value
To establish the conditions for the global stability of the equilibrium points of the system (4), we provide the following lemma.
Lemma 6 (Volterra-type Lyapunov function [36]).
Let
Lemma 7 (generalized LaSalle invariance principle [37]).
Suppose
3. Basic Properties of Solutions
In this section, we present some basic properties of solutions of the system (4) such as the non-negativity, boundedness, existence, and uniqueness of solutions.
3.1. Non-Negativity and Boundedness of Solutions
From the biological point of view, we only concern to system (4) in the non-negative and bounded solutions. We consider
Theorem 8.
All solutions of the system (4) which initiate in
Proof.
Let
According to Lemma 3, we get
Next, we show the boundedness of solutions of the system (4) by using the fractional comparison lemma. From the first equation of system (4), we obtain
Based on Lemma 4, we have
Thus, for any
Define
For
If we choose
Using the same argument as before and letting
On the other hand, for the strong Alee effect
Thus, for any
3.2. Existence and Uniqueness of the Solution
To investigate the existence and uniqueness of solution of system (4), we apply the locally Lipschitz condition in the region
Theorem 9.
For each
Proof.
For any
It follows that
Since
3.3. Existence and Stability of Equilibrium Points
To study the dynamical behaviors of system (4), we first investigate the equilibrium points of the system (4) which are the constant solutions to the following system:
Next, the local stability of equilibrium points of system (4) is evaluated by computing the eigenvalues of the Jacobian matrix of system (4) at the equilibrium point
3.4. Equilibrium Analysis in the Case of the Weak Allee Effect in Predator
In this subsection, the existence and stability of the equilibrium points of the system (4) for the weak Alee effect
(a) Trivial equilibrium point:
(b) Axial equilibrium point:
(c) Planar equilibrium point:
where
(d) Interior equilibrium point:
Assume that
(a) If
(b) If
(c) If
Theorem 10.
The local stability of trivial, axial, and planar equilibrium points of system (4) for the weak Alee effect
(a)
(b)
(c)
(d) Let
(i)
(ii)
(e) Suppose that
(i)
(ii)
Proof.
(a) In view of (28), around
The corresponding eigenvalues of (35) are
(b) The Jacobian matrix in (28) around
Then, the corresponding eigenvalues of (36) are
(c) By substituting
where
The corresponding eigenvalues of (37) are
(d) The Jacobian matrix in (28) around
where
The corresponding eigenvalues of (39) are
Equation (41) has the following eigenvalues:
where
Notice that if
(e) The Jacobian matrix (10) calculated at
The eigenvalues of (44) are
If
Theorem 11.
Stability condition of interior equilibrium point for weak Alee effect
(i)
(ii)
(iii)
(iv)
Proof.
The Jacobian matrix (10) evaluated at interior equilibrium point
The corresponding eigenvalues of (48) are the roots of the cubic equation
If
3.5. Equilibrium Analysis in the Strong Allee Effect in Predator
In this subsection, the existence and stability of the equilibrium points of system (4) for the strong Alee effect
(a) Trivial equilibrium point:
(b) Axial equilibrium point:
(i) If
(ii) If
(iii) If
(c) Planar equilibrium point:
and
(d) Interior equilibrium point:
Assume that
(a) If
(b) If
(c) If
Theorem 12.
The local stability of all equilibrium points of system (4) for the strong Alee effect
(a)
(b)
(c)
(d) Let
(i)
(ii)
(e) Suppose that
(i)
(ii)
(f) Suppose that
(i)
(ii)
(iii)
(iv)
Theorem 12 has similar proof to Theorem 10 and Theorem 11.
3.6. Hopf Bifurcation
In this subsection, we study the conditions of a Hopf bifurcation around the equilibrium point of system (4) when a parameter is varied. This bifurcation ensures a stability change when system (4) passes the critical value which coincides with the emergence of the limit cycle. Hopf bifurcation can occur both in the first-order systems and fractional-order systems. The fundamental difference between the two is the convergence of the limit set of solutions, known as the limit cycle, to the solution of the system. In the first-order systems, the limit cycle converges to the periodic solution; in the fractional-order systems, instead of converging to the periodic solution, the limit cycle converges to the periodic signal [40, 41].
Let us consider the following three-dimensional fractional order system:
According to Theorem 5, the stability of the system dynamics is significantly affected by the order of the derivative
(1) The Jacobian matrix at
(2)
(3) The transversality condition:
Note that the critical value of
Theorem 13.
Existence of Hopf bifurcation driven by
(i) Suppose that
(ii) If
(iii) Suppose that characteristic equation
Remark 14.
In addition to the existence of Hopf bifurcation driven by order of the fractional derivative
4. Global Stability
By using the appropriate Lyapunov function, we investigate the global stability of the stable equilibrium points of system (4), both for the weak Allee effect and the strong Allee effect cases in the predator.
4.1. For the Weak Allee Effect in Predator
Theorem 15.
Proof.
Let
Further, from Theorem 8, we have
By using Lemma 6, the fractional time derivative of
If condition in (61) is satisfied then we obtain the following:
In this case,
Theorem 16.
The planar equilibrium point
Proof.
Assume that
From Theorem 8, we also have that
As before, we have the fractional time derivative of
Observe that when the condition of (66) is fulfilled, then we have the following:
One can easily show that
Theorem 17.
The planar equilibrium point of system (4)
Proof.
Let
Also, from Theorem 8, we have that
Based on Lemma 6 and by calculating the fractional time derivative of
If condition in (72) is achieved, then we have the following:
It is obvious that
Theorem 18.
Suppose that
If
Proof.
Let
Again, using Lemma 6, we have the following equation:
Since we have
4.2. For the Strong Allee Effect in Predator
Theorem 19.
If
Proof.
Let
By taking the fractional time derivative of
Regarding that
5. Numerical Simulations
In this section, we demonstrate the numerical simulations based on the Adams–Bashforth–Moulton predictor-corrector method provided by Diethelm et al. [43] to verify the theoretical results established in the previous section. In addition, we also present the complex dynamics of system (4) such as the existence of bistability, forward, backward, saddle-node, and Hopf bifurcations as the effects of the disease and the fractional derivative.
The first simulation is given to observe the role of the transmission rate
In view of the existence conditions of the equilibrium points, Theorem 10 and Theorem 11, we plot a bifurcation diagram for the weak Allee effect case as shown in Figure 1. Here,
[figure(s) omitted; refer to PDF]
In Figure 1, when
[figure(s) omitted; refer to PDF]
A further investigation shows that the stable branch interior point
[figure(s) omitted; refer to PDF]
Next, we discuss the contribution of transmission rate
Notice that, for the strong Alee effect case
[figure(s) omitted; refer to PDF]
Remark 20.
According to Figures 1, 2, and 4, the transmission rate of disease
Remark 21.
From an ecological point of view, as the transmission rate of disease
In the next simulation, we will show the influence of the order of fractional derivative
For the above parameter values, it is found that system (4) has four equilibrium points, where
We next exhibit the existence of two limit cycles as the solutions of system (4) by varying the order of the derivative
[figure(s) omitted; refer to PDF]
Remark 22.
From the ecological point of view, a phenomenon which is given in Figure 6(c) show that if the initial value of prey population is relatively small then the susceptible and infected predators will oscillate even in the absence of prey population. On the other side, when the initial prey population is relatively large, all populations may oscillate for a long period of time.
Remark 23.
The analytical results and numerical simulations of the model in the absence of disease in predator population (system (1)) had been found by Rahmi et al. [28]. Numerically, the recent model with disease in predator population has more rich dynamical behaviors than the former model. One of the reasons comes from varying the transmission rate of disease parameter. When there is no disease, there is only bistability, forward and Hopf bifurcations, meanwhile there is bistability, saddle-node, backward, forward, and Hopf bifurcations for the model with disease. More specifically, the proposed model exhibits a new phenomenon in the fractional order system, which is the existence of two limit cycles driven by the order of derivative as given in Figure 6(c).
6. Conclusion
In this paper, we have merged a predator-prey model and epidemiology model into the eco-epidemiological model. In ecological literature, there is much evidence that the double Allee effect may be acting on a single population. Moreover, it is natural to assume that there is a deadly infectious disease spreading within the population. Thus, we have developed an eco-epidemiological model incorporating the double Allee effect and disease spread on the predator population. This eco-epidemiological model has been modelled by a system with fractional-order differential equations in Caputo sense. We have split the predator population into two subpopulations: the susceptible predator and the infected predator. We proved that the solution of system (4) exists uniquely and whenever we started with a positive initial condition then all solutions remain non-negative and bounded. We showed that our system (4) has four types of equilibrium points, i.e., the trivial, two axial, two planar, and the interior equilibrium points. The trivial equilibrium point for both the strong and weak Allee effect cases is always unstable, which means that there is no condition of extinction of all populations in the future. The first axial equilibrium point (the predator extinction point) is always unstable for the weak Allee effect case, while for the strong Alee effect case, it is always stable. It means that the predator population can go to extinction in the strong Allee effect, which is contrary to the weak Allee effect case. The second axial equilibrium point (the prey and infected predator extinction point) is conditionally stable. We have observed that the dynamics of the axial equilibrium point do not depend on the order of the fractional derivative. Then, we have two planar equilibrium points (the prey extinction point and the infected predator extinction point) which are conditionally stable. The interior equilibrium point is also conditionally stable for both weak and strong Allee effects. The stability conditions of the last two types of equilibrium points show that the order of the fractional derivative
Authors’ Contributions
All authors have contributed equally and have finalized the manuscript.
Acknowledgments
This work was supported by the FMIPA via DPA PTNBH-University of Brawijaya, according to the Doctoral (Associate Professor) Research Grant, with contract number: 3110.12/UN10.F09/PN/2022, dated May 30, 2022.
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Abstract
In this paper, a fractional order of a modified Leslie–Gower predator-prey model with disease and the double Allee effect in predator population is proposed. Then, we analyze the important mathematical features of the proposed model such as the existence and uniqueness as well as the non-negativity and boundedness of solutions to the fractional-order system. Moreover, the local and global asymptotic stability conditions of all possible equilibrium points are investigated using Matignon’s condition and by constructing a suitable Lyapunov function, respectively. Finally, numerical simulations are presented to verify the theoretical results. We show numerically the occurrence of two limit cycles simultaneously driven by the order of the derivative, the bistability phenomenon for both the weak and strong Allee effect cases, and more dynamic behaviors such as the forward, backward, and saddle-node bifurcations which are driven by the transmission rate. We have found that the risk of extinction for the predator with a strong Allee effect is much higher when the spread of disease is relatively high.
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1 Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Brawijaya, Malang 65145, Indonesia; Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo, Bone Bolango 96119, Indonesia
2 Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Brawijaya, Malang 65145, Indonesia