Abstract
In this paper, a Lotka–Volterra (L-V) competitor–competitor–mutualist system with time-varying delays is studied. Some dynamical behaviors of the considered system are investigated. Firstly, we obtain the boundedness, permanence and periodic solution of the system using the comparison principle of differential equations and inequality estimation method. Then, the global attractiveness of the system is analyzed by multiple Lyapunov functionals. Meanwhile, the existence and global attractivity of positive periodic solutions is derived. In the third section, in order to validate the practicability and feasibility of the obtained theoretical results, we conducted numerical simulations using MATLAB function ddesd. Finally, the fourth section is where conclusions are drawn.
Keywords:
permanence; global attractivity; time-varying delay; Lyapunov functional; periodic solution; Lotka–Volterra competitor–competitor–mutualist system MSC:
34A34; 34D05; 34D23; 34K13; 37B55
1. Introduction
Population dynamics systems often use mathematical models to describe the interactions and relationships between populations and their environment. These models can involve differential equations, integral equations, or difference equations, depending on the specific variables being considered and the level of complexity of the system. The goal of these models is typically to better understand how populations change over time in response to various factors such as resource availability, disease, predation, competition and cooperation [1].
In recent years, various kinds of delay differential equations have been increasingly used in the modeling of complex systems such as ecosystems [2,3], population dynamical systems [4,5], infectious diseases systems [6], neural networks systems [7,8], enterprise clusters systems [9,10] and so on. These equations take into account time delays in the system’s response to its own behavior or external stimuli, which can result in interesting and often unexpected dynamics [11]. For example, in the predator–prey model [5], time delays can play an important role in the dynamics of the system. Time delays can arise due to various factors, such as the time it takes for prey to reproduce or for predators to consume their prey. In addition, when considering the predator–prey model without time delays [12], the dynamics of the system are simpler. In this case, the population sizes of predator and prey species can be modeled using a set of coupled differential equations, which can be solved analytically or numerically to determine the long-term behavior of the system.
On the other hand, the survival of species in a population dynamical system is one of the most important problem, and permanence analysis is an important tool in studying the long-term behavior of population dynamical systems. For example, in the predator model, which describes the interaction between predator and prey populations, permanence analysis is necessary to understand the conditions under which the populations will persist or go extinct over time. Hence, in an ecological system, the permanence analysis is important because the extinction of one or more populations may have significant ecological and economic consequences. Overall, permanence analysis plays a critical role in understanding the dynamics of ecological systems, and it is essential for making informed decisions about conservation and management efforts.
As is well known, the L-V model, also known as the predator–prey model, is a mathematical model that describes the dynamics of two interacting species in an ecosystem. The model was developed independently by Alfred Lotka [13] and Vito Volterra [14] in the early 20th century. The L-V model has been applied to many different ecosystems, including ocean fisheries, terrestrial ecosystems, and even economic systems.
Recently, Lu et al. [15] considered the following L-V cooperative systems with discrete delays:
and derived the conditions for permanence of system (1). Li et al. [16] investigated the following delayed L-V competitive system with feedback controls
and the conditions for the stability of equilibriums, coexistence and exclusion of species are obtained.
However, pure competition, as described by the L-V model, can lead to species exclusion or coexistence with reduced carrying capacity for both species. In addition, while pure competition can drive natural selection, it does not necessarily promote the coexistence of multiple species. In fact, the L-V model, which describes pure competition between two species, predicts that one species will eventually outcompete and exclude the other. Therefore, other factors such as resource partitioning, niche differentiation, and mutualism are necessary to facilitate the coexistence of multiple species in an ecosystem [17]. Based on the above analysis, when modeling ecosystems or populations, it is important to consider the various interactions that occur between species, including competition for resources, cooperation in certain behaviors or activities, and predator–prey relationships. These interactions can significantly affect the dynamics of the system and its stability over time.
In recent years, some L-V type mathematical models on the various interactions have been proposed in the study of delay differential equations [18,19,20,21,22,23,24,25] and several research results have been obtained. For example, in [19], the authors considered the following L-V type predator–prey-competition system with delays
and obtained some conditions on the global attractivity, extinction, and permanence of system (3).
On the other hand, competition–mutualism is a type of ecological interaction where two or more species both compete and mutually benefit from each other, and it is common in nature. A classic example is the relationship between hermit crabs and sea anemones, where the crabs provide protection for the anemones while the anemones offer a home for the crabs. Another example is when two different plant species compete for nutrients from the same tree, but they also provide shade for each other. These interactions are the result of natural selection over time, and which plays a very important role in maintaining the ecosystem and helps us to better protect the balance of the ecosystem.
In [21], the authors considered the following competitor–competitor–mutualist L-V systems with time-varying delays
where , denote the densities of competing species at time t and denotes the density of cooperating species at time t; denote the intra-patch restriction density of species , and at time t; and denote the competition coefficients of competing species and at time t; and denote the cooperation coefficients of species , and at time t. The authors have derived some conditions on the existence of periodic solutions by Krasnosselsii’s fixed point theorem. As for the special case of the model, when , they also derived the global attractivity of positive periodic solution of system (4) by means of the construction of Lyapunov functionals.
Based on the studies cited above and as supplements and extensions of the results in [21], in this paper we further study system (4).
Our main purpose is to study the general case of system (4), and establish several sufficient conditions on the periodic solution, permanence and global attractivity for system (4) by using the inequality analysis, comparison method, and construction of the multiple Lyapunov functional.
Throughout this paper, we denote that
and we define
where is any bounded continuous function defined on .
For system (4), we introduce the following assumptions.
- ()
- and are all continuous bounded functions on with .
- ()
- and are all continuous bounded and -periodic functions on with .
The initial conditions for system (4) are given as follows:
where are satisfying and continuous non-negative functions defined on with .
We need the following lemma in this paper.
Lemma 1
([18]). If for any , there exist constants and such that
then periodic differential equation with solution admits at least one positive -periodic solution. Where is a -dimensional continuous functional and , is a solution of with initial condition .
2. Main Results
Theorem 1.
Assume that holds and let denote any positive solution of system (4),
- (i)
- if , then
- (ii)
- if there exists a such that for any positive solution of system (4),
- (iii)
- , where will defined in the proof,
then system (4) is permanent.
Proof.
Since , then and exist, such that for . According to the first equation of system (4), we have
for . When , integrating (5) from to t, one has
Hence, from (6) we further have
Let , then,
for . Thus,
Integrating from to on both sides of (7), one has
which leads to
On the other hand, one can see that is a rigorous monotone increasing function for sufficient larger with positive constant , , then,
for . Next, according to the second equation of system (4) for , we have
Similarly with the above discussion, for , we can prove that
Next, we seek the positive constants . It follows from the third equation of system (4) for , we have
Integrating (11) from to t, one has,
where, take , if ; take , if .
Thus, we have
Therefore, there exist , one has
for . It follows from the first and second equation of system (4) for , and we further have
where .
Integrating (15) from to t, one has
where, for i = 1, 2 take , if ; take , if .
Thus, we have
Therefore, there exist , one has
for . □
From Theorem 1, we have the following result.
Corollary 1.
Let denote any positive solution of system (4), suppose that hold and following conditions hold:
- (1)
- Ifthen
- (2)
- If there exist a real number such that for any positive solution of system (4),
Then, system (4) is ultimately bounded.
By Lemma 1 and Theorem 1, we can obtain the following result for system (4).
Corollary 2.
If (H2) holds and let denote any positive solution of system (4),
- (i)
- If , then
- (ii)
- If there exists a such that for any positive solution of system (4),
- (iii)
- ,
then system (4) is permanent and has a Ω-periodic solution.
Theorem 2.
If the conditions of Corollary 1 hold and , then system (4) is globally attractive. Where , , and
Proof.
Let and are any positive solutions of system (4), then from the ultimately boundedness of the solutions, there exist real numbers and such that First consider the Lyapunov function
where
Computing the Dini derivative of , we obtain
Define
where
From (19) and (20), we have
Let
where
Finally, define a Lyapunov functional
Then,
Integrating from to t on both sides of (24) produces
Hence, we have
From (26) and the boundedness of the solutions, we can find that and their derivatives remain bounded on . As a consequence, is uniformly continuous on . By Barbalat’s theorem, it follows that
□
Corollary 3.
If the conditions of Corollary 2 hold and , then system (4) has a globally attractive positive Ω-periodic solution. Where , and
Remark 1.
In system (4), if , then condition (27) reduced to the following condition of Theorem 3.1 in [21]
Therefore, the established results in this paper can be seen as the extensions, supplements and improvements of the results obtained in the studies by Lv et al. [21].
3. Numerical Example
We consider the following system:
Let , then we have
Thus, the assumptions of Corollary 3 are satisfied. Then, system (28) is permanent and has a global attractive positive periodic solution. The corresponding numerical simulation is given in Figure 1 by using the MATLAB function ddesd.
Figure 1.
Dynamical behaviors of system (28). Here, we take different initial values. (a) Permanence, periodicity and global attractivity of and . (b) Permanence, periodicity and global attractivity of and . (c) Permanence, periodicity and global attractivity of and . (d) Permanence, periodicity and global attractivity of and . (e) Permanence, periodicity and global attractivity of and .
From the numerical simulations, we find that system (28) is permanent and has a global attractive positive periodic solution.
Remark 2.
Obviously, in system (28), the assumptions of Theorem 3.1 in [21] do not hold. If , then the assumptions of Theorem 3.1 in [21] are satisfied, and the assumptions of Corollary 3 are also satisfied. Therefore, it can be seen that our obtained results are more general than the results in [21].
4. Conclusions
The Lotka–Volterra competitor–competitor–mutualist system is a mathematical model that describes the interactions between two competing species and a mutualistic species. The model assumes that the two competing species compete for a common resource, while the mutualistic species benefits from the presence of both competitors. In this paper, a Lotka–Volterra competitor–competitor–mutualist system with varying time delay is analyzed, and the permanence, global attractivity and periodic solution of the system are studied. By means of the multiple Lyapunov functional, comparison principle and inequality estimation method, we obtained a set of easily verifiable new sufficient conditions on the aforementioned results. Therefore, the results in this paper can be seen as the supplements and extensions of the results in [21] and other relative known results.
Although our study provides a thorough analysis of the dynamical behavior of system (4) in the general case, however, there are several important avenues for future research such as the extensions and improvements of the considered model and obtained results in this paper to more general cases.
Author Contributions
Conceptualization, L.C.; writing—original draft preparation, L.C.; writing—review and editing, A.H.; supervision, A.M. methodology. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the National Natural Science Foundation of Xinjiang, grant number 2021D01C067 and the Open Project of Key Laboratory of Applied Mathematics of Xinjiang Uygur Autonomous Region, grant number 2023D04045.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
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