Abstract
The stability of traveling waves for the Lotka–Volterra competition system with three species is investigated in this paper. Specifically, we first show the asymptotic behavior of traveling wave solutions and then establish the local stability and the global stability under the weighted functional space. For local stability, the spectrum approach is used, while for global stability, the comparison principle and squeezing theorem are combined.
Keywords:
asymptotic behavior; Lotka–Volterra model; three species; global stability; weighted functional space MSC:
35K57; 35B35; 92D25
1. Introduction
The aim of this paper is to study the stability of traveling waves for the Lotka–Volterra competition system with three species as follows:
To proceed, we first transform the variables so that , , and the system (1) is converted into the following cooperative system:
with the initial value , and for . In this system, and w are the population densities of three species, respectively; is the diffusion coefficient of species i; and denote the competition coefficients between the other two species j and the first species; and and stand for the growth rates of the two species of , respectively. All the coefficients are positive. Further, we can understand that there are three species and w living together, and species u is a predator, while species are both prey. However, do not directly affect each other, and the predator u acts as a mediator for v and w.
The Lotka–Volterra model is well-known for better describing changes in biological populations, and many mathematicians are interested in its dynamics. In particular, many studies on the existence, stability, and invasion speed of traveling wave solutions have been generated on the two species competitive model, see [1,2,3,4,5,6,7,8,9]. For the three-species competition model, the studies on the dynamical behaviors are also receiving increased attention. The existence of traveling wave solutions for the three-species system has been extensively studied in [10,11,12,13,14]. In addition, many scholars [15,16,17,18] investigated the speed selection, and for more studies on other aspects of the three-species system, please see [19,20,21]. Among them, Pan et al. [15] converted the competitive system into a cooperative system and investigated the determinism of the invasion velocity by the upper and lower solution method. We shall directly employ some results in [15] for this study.
For a competitive system, understanding the conditions under which a species survives or dies is always an important and interesting topic in dynamics, and traveling wave solutions can be used to help us answer this question. By a simple calculation, we can find that (2) admits at least five equilibrium points in the range , i.e., (0, 0, 0), (0, 1, 0), (0, 0, 1), (0, 1, 1) and (1, 1, 1). Then, this paper focuses on the traveling waves connecting the equilibrium points and in the form
where c is called the wave speed and is called the wave profile. For the convenience of discussion, we always assume that
A Similar assumption has been made in other papers studying the three-species model, such as [15,17,22], and the assumption is essential for stability properties in this paper. This condition means that are weak competitors of u and it makes the point unstable and the point is stable. By substituting (3) into (2), we have
The existence of the traveling wave has been given in other related literature. Pan et al. [15] gave the existence of the traveling wave when and the minimal wave speed is linearly determined for . Apart from that, the asymptotic behavior of near the equilibrium point is also given in [15], see the following lemma.
Lemma 1.
For any and constants or with , when , has the following asymptotic behavior:
where , and
Throughout this article, for better determining the weight function later, we always assume that is the minimum between . To make the assumption true, we summarize the required parameter conditions and we can find that restrictions are only proposed for c and . It is not contrary with other assumptions in our paper.
In order to study the stability of the traveling wave, we need to determine the solution with as the initial value whether converges to . Hence, a change of variables further transforms (2) into a partial differential model
We know that is the steady-state to the above new system. We need to add the following extra assumption about the steady-state in order to obtain global stability:
It is not difficult to find that we can demonstrate that the condition (9) is not empty by using the linear selection condition in Theorem 4.1 in [15]. By choosing , and combining the condition (4), we have because of the linear selection condition .
The attention, which focused on the stability of traveling waves, has increased and various methods have been shed light on, where the weighted energy method and the spectral analysis were widely used. In terms of local stability, Hou and Li [23] demonstrated the local stability of traveling waves of nonlinear reaction-diffusion equations in different weighted Banach spaces by employing a new method to analyze the location of the spectra. To investigate the stability of the traveling wave solutions with non-critical wave speeds, Leung et al. [24] similarly analyzed the spectrum of the linearization operator in the exponentially weighted Banach space. In terms of global stability, Wu and Xing [25] proved that traveling front solutions with critical speeds are globally exponentially stable in some exponentially weighted spaces. By using a combination of the weighted energy method and the Green’s function technique, the global stability of monostable traveling waves for nonlocal time-delayed reaction-diffusion equations was given in [26]. For additional research on stability by using the weighted energy method, see also [27,28,29,30].
More specifically, in recent years, there have been numerous investigations on the stability of the Lotka–Volterra diffusion model. Chen et al. [31] applied the weighted energy method to study the nonlinear stability of a discrete three-species Lotka–Volterra competitive diffusion system with monostable traveling wavefronts. The global asymptotic stability of a diffuse multispecies Lotka–Volterra interaction model for the non-homogeneous coexistence equilibrium state was established by using the Lyapunov function method in [32]. Ma and Guo [33] combined the monotonic dynamical systems theory, the sub-super solutions method, master spectrum theory to study the global asymptotic stability of the coexisting steady state of a competitive Lotka–Volterra reaction-diffusion model with an advection term arising. Alhasanat and Ou [2] showed the global stability of the traveling waves of the Lotka–Volterra diffusion model by using the upper–lower solution method together with the squeezing technique. Further reading on the stability of the Lotka–Volterra diffusion model may be found at [28,34,35,36,37,38].
Research on the existence of traveling waves and the choice of linear and nonlinear minimal wave speeds for the three-species competition model has been successful. However, the stability of traveling waves has received less attention. In light of this, we investigate both the local and global stability of the steady-state under the weighted functional space in this research.
Theorem 1.
For any and the weight function
with some constants , , the traveling wave solution is locally stable in the weighted functional space , which is defined in Definition 1.
Theorem 2.
Suppose , conditions (4)–(9) hold true and the initial data of the solution to (8) are
which satisfy
and
then the traveling wave solution exists globally with
and for positive constants k and η, there are
i.e., any solution satisfying the conditions converges exponentially to the equilibrium solution .
Despite the fact that the local stability of the Lotka–Volterra competition system with three species has been demonstrated in [28], we refer to its methodology for the verification of global stability before introducing a new weighted functional space to prove our Theorem 1. The spectral problem is explored in the weighted functional space to determine the sign of the real part of the eigenvalues and further obtain the result of local stability. For global stability, to prove our Theorem 2, we construct the upper solution based on the assumptions (4)–(9), and then the comparison principle is utilized for global stability.
The rest of this paper is organized as follows. In Section 2, we linearize the model and perform a spectral analysis on it in the suitable weighted functional space, which led to the conclusion of local stability. Then, also under the weighted functional space, the global stability is proved by combining the upper-lower solution method and the squeezing theorem in Section 3. Conclusions are shown in Section 4.
2. The Local Stability
We first introduce a weighted functional space different from [28] before studying the local stability for the subsequent proof of global stability.
Definition 1.
is the well-known Lebesgue space of integrable functions. Define a weighted functional space as follows:
The norm is
and the weight function is
where
with some constants and , where are positive.
In this paper, we study the local stability in the presence of perturbations. By analyzing the behavior of the traveling waves under this small perturbation over a long period of time, the solution can be considered as locally stable if it converges to the steady-state solution.
Let
where , are real functions and is a parameter.
Let and in order to facilitate the exploration of the spectrum of the operator on the space , we write in the following form:
where belong to .
By substituting (20) into (8) and linearizing it at , we can obtain the following spectral problem:
where
By examining the maximum real part sign of the spectrum of the operator , we can now evaluate the local stability of the traveling wave solution.
Then, we can use the following details from Theorem A.2 in [39] to determine the essential spectrum of the operator . After choosing the weight function to compel the essential spectrum to locate in the left-half complex plane, we may determine the sign of the maximum real part of the point spectrum in the weighted space. We choose
such that
where are defined in (7). and are bound by the preconditions mentioned above. Therefore, we define
and an algebraic curves ,
The union of areas within or on the curves and contains the essential spectrum of the operator . If we prove that for , respectively, then are on the left-half complex plane, which implies that the essential spectrum of lies on the left-half complex plane, for further details, see [28].
Because is the smallest parameter, we choose , where a is a constant and . Then, the weight function is as follows:
where is defined in (19).
In order to obtain the local stability for (22), we next determine the sign of the major eigenvalue in the point spectrum.
Lemma 2.
For , the real part of the eigenvalue λ of (22) is all negative.
Proof.
Consider an associated linear partial differential system
where . By comparing with (22), we know that is a solution of the above system with the same and as in (22). According to the well-known Krein–Rutman theorem in [40], a compact linear operator which is strongly positive has a simple principal eigenvalue with a strongly positive eigenvector. For each given initial data set , let indicate the solution semiflow of (33) and we can find that satisfies the requirements of the theorem. So, we have
where is the simple principal eigenvalue. To proceed, we can prove by contradiction for two cases.
Case 1. .
For any , obviously we have as and are the same asymptotic behaviors as . So, the operator defined in (22) has an eigenvalue with the one-sign eigenvector , which is strongly positive. Because of (32) and , we can check that is not inside the weighted functional space .
Case 2. .
For and , there is obviously that except for sets of measure zero.
For , assume that the eigenfunction of (22) possesses the asymptotic behavior as for some positive constants . Thus, we can obtain the corresponding characteristic equation as follows:
which exist three positive roots,
These statements demonstrate that increases with , which also implies that .
Hence, we can choose a sufficiently large such that . Both and are solutions of (33), so by using the comparison principle, we have , which is not correct for a sufficiently large t. Thus, we complete the proof. □
3. The Global Stability
This section will analyze the global stability of the equilibrium solution in the weighted functional space with , where the norm is defined as with a special weight function . Based on Theorem 1, we choose the weight function , which is defined in (32), and let
where is a sufficiently small positive number.
First of all, assume the initial data of the solution of (8) as
which satisfy
and
Based on the above conditions, for , we define
which can be viewed as the initial value of the solutions and for (8). That is to say that and satisfy
By using the comparison principle, we have
Next, we need to demonstrate the convergence of to the wavefront in the subsequent lemmas, respectively.
Proof.
We define
with the initial value
It is simple to see from inequality (43) that
for . Afterwards, by combining (5) and (42) and performing some transformations, we obtain
Let
where and is defined in (32). We will then demonstrate this lemma in two scenarios.
Case 1. Assume for any fixed .
Substituting (48) into (47), we have
where D is defined in (23),
and
where and are given in Lemma 1. Assume that is the eigenvector of the matrix at eigenvalue and a direct calculation gives
Then, we also define
where are positive. Since , thus we can choose
For , by using (9), substituting (54) into the right side of (49) and performing the calculation, we find
This means that we can find a suitable such that the inequality
holds.
Hence, is equivalent to an upper solution. Then, by using the comparison principle on an unbounded domain, see [41], we have
Now, we also need to verify the convergence of to (0,0,0) at .
Case 2. Assume for any fixed .
System (47) can be represented in another form:
where is defined in (24) and we write as . Now, we present a new matrix ,
for some given small . When , due to the fact that is nearing (1, 1, 1) for any z in this range, the inequality holds.
If we build an autonomous system related to with as the solution:
and the initial value satisfies
then we can verify that is an upper solution to the system (58).
We must now determine if converges to as . We can use the Jacobi matrix to examine the behavior close to , which is one of its fixed points. By using (60), the equation has three eigenvalues denoted as . As a result, the point at is stable, meaning that the flow in the -space converges to the origin for every in the range with The maximum possible value of depends on the position of the nonconstant fixed point to the system (3.24) near or inside the box . If the point is far away from the box, then can be 1; If the point is near the boundary of the box, then the maximum possible value of in and in ; if the point is inside the box, then is close to and is close to . Thus, we find that
Here, and is the eigenvector of with the eigenvalue .
Finally, we have
at by choosing a large enough and . And by comparison on the domain, see [42], we find that
Up to here, the proof is complete. □
Proof.
We define
with the initial value
By inequalities (43), it is easy to see that
Then, repeat the steps above, and I, K and S satisfy the system
where is defined in (24). Similarly, we analyze it in two cases.
Case 1. Let .
By using an approach similar to the proof of Lemma 3 with (9) and the facts . There exist and
such that
Case 2. Let .
Now, we need to introduce defined in (32) with to study the stability under the weighted functional space . Defined
and the initial date satisfies
We can check that is an upper solution to the system (68). As in Lemma 3, also converges to when all initial value on the space except by analyzing the phase plane. Finally, for some , we have
This completes the proof. □
In the end, we can prove Theorem 2 on the global stability.
Proof of Theorem 2.
From (43), we have
for . Combining Lemmas 3 and 4 and the squeezing theorem, it is easy to find that, for all ,
where . Hence, the proof is done. □
4. Conclusions
We examined if traveling waves in the Lotka–Volterra competition model with three species (2) display both local and global stability under the condition (4). Theorem 1 demonstrates, utilizing linearization and the crucial spectrum analysis, that the traveling wave solution is locally stable in a weighted functional space. Additionally, Theorem 2 demonstrates that all solutions converge to the wavefront solution using the upper-and-lower solution method and the squeezing theorem under the added constraint (9).
Author Contributions
S.H., C.P. and L.W. analyzed the method and revised the manuscript text together, S.H. and C.P. wrote and prepared the original draft, while L.W. supervised the writing. All authors have read and agreed to the published version of the manuscript.
Funding
This work is supported by the Teaching Research and Reform Project of South China University of Technology grant (C9213136).
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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