1. Introduction
Very recently, we derived in [
1] the following delayed temporally discrete non-local reaction-diffusion equation
where
denotes the density of the total matured population of a single species at time
, location
,
represents the set of non-negative integers.
is the diffusion rate of matured individuals.
is the Laplacian operator with respect to
,
is a positive integer, which denotes the maturation time for the species.
represents the death rate of matured individuals.
is the survival rate of an individual from birth to maturation.
is the birth function. The integral kernel function
reads as
where
is the diffusion rate of immatured individuals. In particular, we use the convention that if
then
and
.
For the case
,
, i.e., the Dulac
function. Therefore, (
1) is reduced to
Equation (
1) reflects the changes of matured population of a single species in an unbounded habitat with dimension one. It can also be viewed as a non-standard discretization of the following well-known non-local reaction-diffusion equation model with delay,
which was derived in 2001 by So, Wu and Zou [
2]. The model (
4) describes the adult population’s evolution of a single species that have two age classes in an unbounded spatial domain
. In above Equation (
4),
is the diffusion rate of the adult population and
is the death rate of the adult population.
reflects the impact of the death rate of the immature on the matured population.
is the birth function.
is the maturation time of the species.
also reflect the impact of the dispersal rate of the immature on the matured population. The integral kernel function is
. When
approaches to 0, that is, the immature do not disperse, (
4) is reduced to
and the non-local effect disappears.
In our previous paper [
1], we have already given a detailed derivation of Equation (
1). Especially, when
(the immature individuals do not disperse), (
1) becomes
Above equation is a non-standard temporally discrete version of (
5).
It is well known that the continuous-time reaction-diffusion equation has been widely used to describe diffusive phenomena in physics, engineering, chemistry, biology, and so on (see, for example, [
3,
4,
5,
6,
7,
8,
9,
10]). In general, the dynamical behaviors of solutions to a non-linear reaction-diffusion equation are very complicated, and it is often very difficult to find exact solutions. For the sake of understanding the properties of the solutions numerically, we need to study its discrete analogue. However, the basic principle of constructing appropriate discretization of differential equations is to preserve the properties of the corresponding differential equations. Since many classical (standard) discretizations cannot achieve dynamic consistency, non-standard discretizations are usually used to ensure it. Thus, Mickens first introduced the concept of dynamical consistency in [
11,
12] for ordinary differential equations and since then, some dynamical consistent discrete schemes have been constructed. See, for example, Refs. [
13,
14,
15,
16,
17], and references therein.
In [
1], we established the existence of traveling wavefronts of Equation (
6) by using upper and lower solution methods and iterate techniques. We found that (
6) possesses the dynamical consistency with its time continuous counterpart (
5) at least in the sense of the existence of traveling wave solutions. In the sense of propagation, Equation (
6) is also a good approximation of corresponding continuous time model (
5).
From the perspective of mathematical biological modeling, almost all of the data collected are discrete in time because observations are always discontinuous. For example, satellite photographs used for scientific research are usually taken periodically, but the spatial distribution can be seen as continuous. Temporally discrete and spatially continuous diffusion model will be more suitable than its corresponding time continuous diffusion model to study the dynamic behavior of a single species that living in a spatially continuous habitat in population ecology. In 2002, Weinberg, Lewis, and Li in [
18] gave some reasons for studying discrete-time models rather than just reaction diffusion models. They also pointed out the advantage of a discrete-time model over a reaction-diffusion model. We note that in [
18], the authors studied the discrete-time recursion system
where
denotes the population distributions of species and
Q is an operator that models the growth, migration, and interaction of the species.
Although Equations (
1) and (
6) are different from (
7) formally, we have proved in [
1] that the following general non-linear equation
is equivalent to an integral-difference equation as below,
where
. Clearly, (
9) is a special case of (
7) with
As for the general integro-difference equations,
Kot and Schaffer [
19] are the first to apply it modeling temporally discrete and spatially continuous dispersal phenomena, and studying the dispersal of a single species with non-overlapping generations. They showed that, the above model will has more complex dynamic behavior than its corresponding time-continuous one. Moreover, even chaos could occur.
Since the selection of kernel function
plays a key role in the dynamical behavior of (
10), using such a model to describe some biological phenomena will have some uncertainty. Especially, when we discuss dynamical behaviors of populations of some species living in a bounded domain, the choice of suitable integral kernels is very difficult because we may cope with various different boundary value problems.
In contrast with integral difference equations, we found that there is no such problems for temporally discrete reaction diffusion equations like (
8) (or (
1)). Furthermore, from the point of view of the mathematical modeling, (
8) (or (
1)) has the same biological explanations as those for integral difference equations. In fact, in our previous paper [
1], the life cycle of individuals of the population is divided into relatively sedentary and dispersal stages. This coincides with the explanations by Kot and Schaffer [
19] in establishing Equation (
7). To distinguish the difference of dynamical behaviors which occurs at different stages, we assume that the evolution (the relatively sedentary stage) occurs at time
n and dispersal occurs at time
.
For temporally discrete reaction diffusion models, there are only a few results in the literature. In 2006, Lin and Li [
20] studied following equation with delay:
They established the existence of traveling wavefronts and showed that (11) is a good approximation of its continuous time model in the sense of propagation. For more researches on this topic see [
4,
21,
22]. However, we note that in the existing research literature, researchers simply assumed that the non-standard discretizations preserve the dynamical consistency of the continuous-time reaction-diffusion equations, but they do not provide reasonable biological explanations for the modeling process.
Although (
1) has been derived in [
1], the existence of traveling wave solutions is proved without non-local effect, and monotonic condition for birth function is assumed. In order to better understand the dynamical behaviors of (
1) with non-local diffusion caused by immature individuals dispersion, we will study traveling wave solutions whenever the birth function is monotonic or non-monotonic, respectively.
The rest of this paper is organized as follow. In
Section 2, by using the upper-lower solutions and monotone iteration technique, we studied the existence of traveling wavefronts of (
1) for the cases that the birth function
is increasing in
, where
is the unique solution to the equation
. As for the case that birth function
is non-monotone in
, the theory of monotone dynamical system cannot be directly used. By using a similar idea as Ma in [
23,
24], we establish the existence of traveling waves of (
1) in
Section 3. Finally, we give a short discussion in
Section 4.
2. Traveling Wavefronts for the Monotone Case
In this section, we will consider the existence of traveling wavefronts to equation (
1) for monotone case. We are interested in finding traveling waves
of following equation
For this purpose, we will find a solution
to (
12) with
. Clearly,
satisfies the following wave profile equation
Let
and still denote it by
. Then, the above equation becomes
Throughout this section, we always assume that
Hypothesis 1 (H1). , whereis a continuously differentiable function and satisfying, forand;
Hypothesis 2 (H2). andare bounded;
Hypothesis 3 (H3). .
From (H1) and (H3), Equation (
12) has only two constant equilibria
and
, where
is the unique solution of the equation
.
We will study the existence of non-decreasing solutions to Equation (
14) subject to the boundary value conditions
Our approach is similar to that in [
1], which is based on the monotonic iteration techniques combined with upper and lower solution methods that was developed in [
2]. To this end, we further assume that
Hypothesis 4 (H4). is increasing in .
To proceed further, for readers’ convenience, we introduce some results on the following temporally discrete reaction-diffusion equation which will be used later,
where
is assumed to be a continuous function. For detailed proofs on these results, readers can refer to [
1].
Lemma 1 ([
1])
. The initial value problemhas a unique solution andwhere φ is a continuous and absolutely integrable function on satisfying .
In particular, we use the convention that if , then and . The integral kernel function satisfies the following properties.
Proposition 1 - 1.
, for;
- 2.
for;
- 3.
For , , is the solution of equation
Lemma 2 ([
1])
. The function is a solution of (15) if, and only if, it is a solution of following non-linear integro-difference equation For
, define
By (H2) and Proposition 1,
is well defined. Then, Equation (
14) becomes
Let ,
For , for , we say , if . Then from the definition of H and Proposition 1, we can easily obtained the following result.
Lemma 3. Assume that (H4) holds. Then, for every , , and is increasing on Γ, that is, for with .
By direct computations, we have
Lemma 4. For , the equationhas a unique solution satisfyingwhere is defined in (18). Further define the mapping
,
The following theorem is a direct consequence of Lemmas 3 and 4.
Theorem 1. is a solution of Equation (14) if, and only if, it satisfies In other words, φ is a fixed point of mapping F in Γ.
Above theorem shows that the existence of traveling wavefronts of Equation (
12) is equivalent to the existence of fixed points to mapping
. Therefore, in what follows, we will construct upper and lower solutions of (
22) to prove that the mapping
has a unique fixed point in
, as long as
c is greater than a certain constant
.
The linearized equation of (
14) at
is as below.
Then, its characteristic equation is given by
Note that for
,
Since
, we have
By direct computations, we have
In fact, one can give another proof of the equality as follows. By Lemma 1, for
, the initial value problem
has a unique solution
and
On the other hand, one can easily verified that
is a solution to initial value problem (
26). Therefore,
which leads to the equality (
25). Then
and
It is easy to see that for any given
and
,
. Then, for any given
,
strictly increasing in
. Additionally, from
and
, for any
, there exists unique
,
, such that
and
If
, the characteristic Equation (
24) has no positive real roots; If
, the characteristic Equation (
24) has only one positive real root; If
, the characteristic Equation (
24) has exactly two positive real roots.
Lemma 5. There exist a positive constant , such that
- (i)
If , then the characteristic Equation (24) has two positive real roots, ; - (ii)
If , then the characteristic Equation (24) has no positive real roots; - (iii)
If , the characteristic Equation (24) has only one positive real roots.
Proof. Consider the function
. When
and
, due to
, we have
which implies that (
24) will has no positive real roots.
By the continuity of
in
c, for sufficiently small
, (
24) will also have no positive real roots. Otherwise, there will be sequences
and
with
,
and
, such that
, i.e.,
Clearly, there exists a convergent subsequence
, and let
. If
, then,
Contradiction. If
, then
It is also a contradiction.
Next, we consider
for any given
,
Since , , then there exists unique , such that . Denote . Obviously . Moreover, has exactly one positive real root and attains its minimum at the point . This completes the proof. □
In what follows, we will consider the case where
. In this case, the characteristic Equation (
24) has two positive real roots
and
satisfying
and
for
.
Definition 1. A continuous bounded function is called an upper solution of (22) if it satisfies A lower solution of (22) is defined in a similar way by reversing the inequality in (29). Now fixed
and let
. Choose sufficiently large constant
to be determined later, define the functions
and
by
where
,
satisfies
.
Proposition 2. is an upper solution of (
22).
Proof. By the definition of
, for any
,
. Thus, by (H4) and Proposition 1, we achieve
For
, if
, clearly, we have,
If
, that is,
, by (H1) and the definition of
,
The last equality follows from the fact that
is a root of
. Calculate above integral directly,
This proves that
is an upper solution of (
22). □
Proposition 3. For any given , there exist a sufficiently large positive constant , such that is a lower solution of (
22).
Proof. There must exist
, such that
and
, such that
. We know that
is increasing on
and decreasing on
, and
Consequently, , for .
If
,
where
From the proof of Proposition 2, we know
and similar arguments have
Since
,
, we have
For , by (H1), we know . Let , . Then
According to the definition of
,
Based on the above results,
Since
, when
sufficiently large,
That is,
is a lower solution of (
22). This completes the proof. □
We have already obtained an upper and a lower solution of (
22). Using the classical upper and lower solution method together with iteration techniques, we find the following existence result.
Theorem 2. Assume that (H1)–(H4) hold. Then for any , (12) admits a traveling wavefront solution connecting the equilibrium 0 and . 3. Traveling Wave Solution for the Non-Monotone Case
This section is devoted to the existence of traveling wave solutions to (
1) when the birth function
is not increasing in
. Our approach is to construct two auxiliary temporally discrete diffusion equations with birth functions satisfying monotonic conditions. Then, by using a similar method developed in [
23] and applying the results obtained in the
Section 1 to these auxiliary equations, we can prove that (
1) possesses a traveling wave solution connecting equilibrium 0 and
.
Throughout of this section, we suppose that satisfies assumptions (H1)–(H3).
By (H3) and the continuity of at zero, there exists a small constant , such that for any . Then, for any , . For such w, .
On the other hand, when
,
. This means that for
,
. Then
Let
. Then
. For any
,
. Consequently,
Let . Then . Clearly, and for all .
We note that, if
, then
. For sufficiently small
, we define two auxiliary functions
and
as follows.
and
Lemma 6. The following statements hold true:
- (i)
and are continuous on and non-decreasing on ;
- (ii)
for all ;
- (iii)
, and for all ;
- (iv)
, and for all ;
- (v)
.
The proof of Lemma is a direct verification, we omit it.
Now we consider the following two auxiliary temporally discrete diffusion equations
and
Then, the corresponding wave equations of (30) and (31) read as
and
respectively. They are equivalent to the following two integral equations:
Moreover, the traveling wavefronts of (30) and (31) are fixed points of operators
and
, where
By Lemma 6, it is easily to verify that and satisfy all the assumptions (H1)–(H4). Therefore, the results below follow from Theorem 2.
Lemma 7. Assume that (H1)–(H3) hold. Then for each , there exist traveling wavefronts and of (30) and (31), respectively, which satisfy , and . In the sequel, we will always assume . Therefore, there exist two positive roots and with . In order to proceed further, we also need the following assumptions.
Hypothesis 5 (H5). , .
Let us first define
and for given
, denote
Clearly,
is a Banach space. Then, define
and
For any
with
we have
Lemma 8. is nonempty, convex and compact in .
Proof. Firstly, we note that
and
are traveling wavefronts of (
32) and (
33), respectively, and they are obtained by iteration procedures. Set
From the proof of Theorem 2,
and
are upper solutions to (
34) and (
35), respectively. Let
Since
,
, by the monotonicity of
and
on
, we have
and inductively,
Since for , we obtain and . Hence, .
To prove is non-empty, it suffices to show that .
For any
,
Therefore,
. Similarly, we can prove
. Next, we proof that
is convex in
. For any
,
,
Therefore, . Proofs of the other conclusions of Lemma 8 are easy, we omit them. This complete the proof. □
Now, we are in position to state our main result.
Theorem 3. Assume that (H1)–(H3) hold true. Then, there exists , such that for every , (14) admits a traveling wave solution satisfying Furthermore, if (H5) hold, then φ connects the equilibrium 0 and , i.e., , .
Proof. We will use Schauder fixed point theorem to prove that (
14) has a traveling wave solution.
Obviously, for any
,
It follows that
and, hence,
is well defined.
For any
, by the continuity of
on
, we have
where
. Therefore, we have
which yields
where
. Therefore,
is continuous.
In what follows, we verify that
. Note that
is a solution of (
35), i.e.,
Similarly, for all .
For any
and
with
, by the same argument as in the proof Lemma 8, we have
Therefore, we conclude that for all .
Using Schauder’s fixed point theorem, we obtain that
has a fixed point
in
, which satisfies
and
Taking limits
and
in (
43), respectively, we have
and
Then, letting
in the above inequality, we obtain
This finishes the first part of the proof of Theorem 3.
Then . We will verify that .
If this is invalid, then
. It is easy to see that if there exists a large number
, such that
or
on
, then
exists and
, which leads to a contradiction. So there must be a sequence
with
as
, such that
and
as
. It follows from (
14) that
thus
For any
, there exists a sufficiently large constant
, such that
Due to the continuity of
b, we can choose
with
satisfying
For such
, take
, such that
Then choose
, such that
Therefore, for
, we have
It follows from
that
If
, then by (
47), we have
, a contradiction. If
, then (
46) implies that
, also a contradiction. Therefore, we must have
.
Let , such that and . We have the following three cases:
Case (i).
. If
, then
follows from (
46), which is impossible since
. Therefore, we have
and, hence,
which is a contradiction;
Case (ii).
. Using the similar argument that used in (i), we find
and
which is also a contradiction;
Case (iii).
. In this case, we have
and
. Otherwise, we have
which is impossible.
Thus,
, and hence
exists. Using the Lebesgue’s dominated convergence theorem and taking the limit as
in (
42), we have
which yields
, hence
. □
4. Discussion
In this paper, we studied the traveling wave solutions of the temporally discrete reaction-diffusion equation with monotone and non-monotone birth functions, respectively. Now we compare our results with the counterparts for continuous model. In [
2], the authors studied the existence of traveling wavefronts of following equation,
where they took a particular birth function
,
and
are parameters. They showed that if
, then there exists
such that for every
, (
48) admits a traveling wavefront solution connecting the trivial equilibrium
and positive equilibrium
. In [
23], the author established a general existence result of traveling wave solutions for non-local reaction diffusion equation. As a special case, he proved that if
, (
48) still possess a traveling wave solution connecting
and
.
Using the non-standard discretization as the form of (
1), the corresponding temporally discrete reaction diffusion equation reads as
If
, then the assumptions (H1)–(H4) can be easily verified. By Theorem 2, there exists
, such that, for every
, (
49) admits a traveling wavefront with speed
c. When
, by Theorem 3, we can prove that (
49) still possess a traveling wave solution connecting
and
. This implies that in the sense of the existence of traveling wavefronts, (49) is a dynamically persistent discretization.
Now that both (
48) and (
49) have critical propagation speeds
and
, respectively. What is the relationship between the two propagation speeds
and
? To answer this question, we can consider following two functions,
where
. In fact,
and
are characteristic equations of linearizations at zero of wave profile equations corresponding to (
48) and (
49).
By direct computations, we find
which implies that for any given
,
for
.
By the definition of , there exists a unique , such that . Moreover, for . Consequently, for any . It follows that .