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Research article

Positive periodic solutions for discrete Nicholson system with multiple time-varying delays

  • Received: 06 July 2023 Revised: 10 October 2023 Accepted: 18 October 2023 Published: 31 October 2023
  • Fly communities exhibit rich ecological dynamics, and one of the important influencing factors is the interaction between species. A discrete Nicholson-type system with multiple time varying delays which considers the mutualism relationship between two fly species is investigated in this paper. Sufficient conditions for the existence of positive periodic solutions are elucidated. The result is obtained by the well-known continuation theorem of coincidence degree theory. An example is attached to illustrate our result. Moreover, the actual biological descriptions obtained from our main result are explained.

    Citation: Xinning Niu, Huixin Liu, Dan Li, Yan Yan. Positive periodic solutions for discrete Nicholson system with multiple time-varying delays[J]. Electronic Research Archive, 2023, 31(11): 6982-6999. doi: 10.3934/era.2023354

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  • Fly communities exhibit rich ecological dynamics, and one of the important influencing factors is the interaction between species. A discrete Nicholson-type system with multiple time varying delays which considers the mutualism relationship between two fly species is investigated in this paper. Sufficient conditions for the existence of positive periodic solutions are elucidated. The result is obtained by the well-known continuation theorem of coincidence degree theory. An example is attached to illustrate our result. Moreover, the actual biological descriptions obtained from our main result are explained.



    Flies are complete metamorphosis insects that contain various species, including Muscidae (houseflies), Calliphoridae (blowflflies) Drosophilae (fruitflies) and Scrcophagidae (fleshflies), etc. The life history of flies can be divided into egg, larva, pre-pupa, pupa and adult stages. Although the life span of flies is only about one month, they are very fertile and multiply rapidly in a short period [1]. The feeding habits of flies are very complex. They can feed on a variety of substances, such as human food, animal waste, kitchen scraps and other refuses. It is known to us that flies transmit various pathogens from filth to humans and cause many diseases [2,3,4]. On the other hand, flies are also beneficial to medical research, ecosystem food chain and pollen dispersal. Considering medical research, for example, fruit fly Drosophila is of great significance in studying the pathogenesis and therapy of human diseases. The nervous system of Drosophila is much simpler than that of human beings, but it also exhibits complex behavioral characteristics similar to humans [5,6]. Therefore, studying fly population dynamics is of crucial importance to both nature and human society.

    The study of biological population growth model promotes the development of human society to a great extent. It has important applications in population control, social resource allocation, ecological environment improvement, species protection and human life and health [7,8,9]. To understand the population dynamics of the Australian sheep blowfly, Gurney et al. [10] constructed the autonomous delay differential equation

    x(t)=δx(t)+Px(tτ)eγx(tτ)

    based on experimental data [11,12]. In this model, x is the density of mature blowflies, δ is the daily mortality rate of adult blowflies, P is the maximum daily spawning rate of female blowflies, τ is the time required for a blowfly to mature from an egg to an adult, 1/γ is the blowfly population size at which the production function f(u)=ueγu reaches the maximum value. Subsequently, this model and its modified extensions were continually used to describe rich fly dynamics.

    Environmental changes play an important role in biological systems. The influence of a periodically changing environment on the system is different from that of a constant environment, and it can better facilitate system evolution. Moreover, delay is one of the important factors which can change the dynamical properties and result in more rich and complex dynamics in biological systems [13,14]. Many researchers have assumed periodic coefficients and time delays in the system to combine with the periodic changes of the environment [15,16,17,18]. For related literature, we refer to [19,20]. However, considering the fact that adult flies number is a discrete value that varies daily and the situations where population numbers are small and individual effects are important or dominate, a discrete model would indeed be more realistic to describe the population evolution in discrete time-steps [21,22,23].

    Interactions between different species are extremely important for maintaining ecological balance. Such interactions are typically direct or indirect between multiple species, including positive interactions and negative interactions. Among them, the positive interactions can be divided into three categories according to the degree of action: commensalism, protocooperation and mutualism [24,25]. In the paper [9], a delay differential Nicholson-type system concerning the mutualism effects with constant coefficients was proposed. The existence, global stability and instability of positive equilibrium were obtained. Based on this system, Zhou [26] and Amster [27] considered periodic Nicholson-type system combined with nonlinear harvesting terms. The main research theme is the existence of positive periodic solutions. Recently, Ossandóna et al. [28] presented a Nicholson-type system with nonlinear density-dependent mortality to describe the dynamics of multiple species, the uniqueness and local exponential stability of the periodic solution are established. However, relatively few studies on discrete dynamical systems have explored the mutualism of flies. In this paper, we consider the mutualism relationship between two fly species and establish a two-dimensional discrete Nicholson system with multiple time-varying delays

    {Δx1(k)=a1(k)x1(k)+b1(k)x2(k)+nj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k))Δx2(k)=a2(k)x2(k)+b2(k)x1(k)+nj=1c2j(k)x2(kτ2j(k))eγ2j(k)x2(kτ2j(k)). (1.1)

    We assume that ai:Z(0,1), bi:Z(0,), cij:Z(0,), τij:ZZ+ and γij:Z(0,) are ω-periodic discrete functions for 1i2 and 1jn. The period ω is a positive integer. Moreover, the interaction rate of second fly specie on first fly species and that of first fly specie on second fly species are represented by b1 and b2, respectively.

    Because τij (1i2) have ω-periodicity, we can find the maximum values

    ¯τi=max1jn{max1kωτij(k)}Z+

    of {τi1(k)}, {τi2(k)}, , {τin(k)} for i=1,2. Note that 0<ai(k)<1 for kZ. Then, the solution x(,ϕ)=(x1(,ϕ1),x2(,ϕ2))T of system (1.1) that satisfies the initial condition

    xi(s)=ϕi(s)>0fors[¯τi,0]Z (1.2)

    is a positive solution. The purpose of this paper is to present sufficient conditions for the existence of positive ω-periodic solution of (1.1).

    We discuss the parametric delay difference system

    {Δx1(k)=λa1(k)x1(k)+λb1(k)x2(k)+λnj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k))Δx2(k)=λa2(k)x2(k)+λb2(k)x1(k)+λnj=1c2j(k)x2(kτ2j(k))eγ2j(k)x2(kτ2j(k)) (2.1)

    for each parameter λ(0,1). Let a_i=min1kωai(k) and ¯bi=max1kωbi(k) for i=1,2. Then, an estimation of upper and lower bounds of positive ω-periodic solution of (2.1) can be conducted.

    Proposition 2.1. Suppose that

    a_1a_2¯b1¯b2>0 (2.2)

    and there exists a constant γ>1 such that

    nj=1cij(k)>γai(k)fork=1,2,,ωand1i2. (2.3)

    Then, every positive ω-periodic solution x=(x1,x2)T of (2.1) is bounded. Specifically,

    A1<x1(k)B1andA2<x2(k)B2fork=1,2,,ω,

    where

    A1min{lnγ¯γ1,γB1e¯γ1B1}andB1=a_2(a_1a_2¯b1¯b2)e(nj=1¯c1jγ_1j+¯b1a_2nj=1¯c2jγ_2j),
    A2min{lnγ¯γ2,γB2e¯γ2B2}andB2=a_1(a_1a_2¯b1¯b2)e(nj=1¯c2jγ_2j+¯b2a_1nj=1¯c1jγ_1j),

    in which γ_1j=min1kωγ1j(k), γ_2j=min1kωγ2j(k), ¯c1j=max1kωc1j(k), ¯c2j=max1kωc2j(k), ¯γ1=max1jn{max1kωγ1j(k)} and ¯γ2=max1jn{max1kωγ2j(k)}.

    Remark 1. Note that Ai and Bi are the lower bound and upper bound of xi, respectively. We can verify the fact that Ai<Bi for i=1,2. From the definitions of A1 and A2, we see that

    A1γB1e¯γ1B1γe¯γ1andA2γB2e¯γ2B2γe¯γ2.

    Hence, we obtain

    B1>a_2(a_1a_2¯b1¯b2)enj=1¯c1jγ_1j=1/(1¯b1¯b2a_1a_2)×1a_1enj=1¯c1jγ_1j>nj=1¯c1ja_11e¯γ1>γe¯γ1A1.

    Similarly, it follows that

    B2>a_1(a_1a_2¯b1¯b2)enj=1¯c2jγ_2j>γe¯γ2A2.

    Proof. Let x=(x1,x2)T be arbitrary positive ω-periodic solution of (2.1) under the initial condition (1.2). For i=1,2, we define

    ¯xi=max1kωxi(k)andx_i=min1kωxi(k).

    Then x_ixi(k)¯xi for kZ+. We can rewrite system (2.1) into

    {x1(k+1)=(1λa1(k))x1(k)+λb1(k)x2(k)+λnj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k))x2(k+1)=(1λa2(k))x2(k)+λb2(k)x1(k)+λnj=1c2j(k)x2(kτ2j(k))eγ2j(k)x2(kτ2j(k)). (2.4)

    Taking the maximum on both sides of the first equation of (2.4) in one period, we have

    ¯x1=max1kω{x1(k+1)}max1kω{(1λa1(k))x1(k)}+λmax1kω{b1(k)x2(k)}+λmax1kω{nj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k))}max1kω{(1λa1(k))}max1kω{x1(k)}+λmax1kω{b1(k)}max1kω{x2(k)}+λmax1kω{nj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k))}(1λa_1)¯x1+λ¯b1¯x2+λmax1kω{nj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k))}.

    Similarly, we obtain

    ¯x2(1λa_2)¯x2+λ¯b2¯x1+λmax1kω{nj=1c2j(k)x2(kτ2j(k))eγ2j(k)x2(kτ2j(k))}.

    Hence, it leads to

    ¯x1¯b1a_1¯x2+1a_1max1kω{nj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k))}¯b1a_1¯x2+1a_1enj=1¯c1jγ_1j, (2.5)

    and

    ¯x2¯b2a_2¯x1+1a_2max1kω{nj=1c2j(k)x2(kτ2j(k))eγ2j(k)x2(kτ2j(k))}¯b1a_2¯x1+1a_2enj=1¯c2jγ_2j. (2.6)

    By (2.5) and (2.6), basic computations show that

    ¯x11/(1¯b1¯b2a_1a_2)×(1a_1enj=1¯c1jr_1j+¯b1a_1a_2enj=1¯c2jγ_2j)=a_2(a_1a_2¯b1¯b2)e(nj=1¯c1jγ_1j+¯b1a_2nj=1¯c2jγ_2j)=B1,
    ¯x21/(1¯b1¯b2a_1a_2)×(1a_2enj=1¯c2jr_2j+¯b2a_1a_2enj=1¯c1jγ_1j)=a_1(a_1a_2¯b1¯b2)e(nj=1¯c2jγ_2j+¯b2a_1nj=1¯c1jγ_1j)=B2.

    Note that 1λai(k)>0 for all kZ and i=1,2. Multiplying both sides of the two equation of (2.1) by kr=01/(1λa1(r)) and kr=01/(1λa2(r)) respectively, we have

    x1(k+1)kr=011λa1(r)x1(k)k1r=011λa1(r)λb1(k)x2(k)kr=011λa1(r)=λnj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k))kr=011λa1(r), (2.7)

    and

    x2(k+1)kr=011λa2(r)x2(k)k1r=011λa2(r)λb2(k)x1(k)kr=011λa2(r)=λnj=1c2j(k)x2(kτ2j(k))eγ2j(k)x2(kτ2j(k))kr=011λa2(r). (2.8)

    Choosing natural numbers k1 and k2 such that

    ¯τ1k1¯τ1+ω1andx1(k1)=x_1,
    ¯τ2k2¯τ2+ω1andx2(k2)=x_2.

    Summing both sides of (2.7) and (2.8) over k ranging from k1 to k1+ω1 and k2 to k2+ω1 respectively, by using xi(ki+ω)=xi(ki)=x_i, we obtain

    x_1k11r=011λa1(r)(k1+ω1r=k111λa1(r)1)                =λk1+ω1s=k1((b1(s)x2(s)+nj=1c1j(s)x1(sτ1j(s))eγ1j(s)x1(sτ1j(s)))sr=011λa1(r)),

    and

    x_2k21r=011λa2(r)(k2+ω1r=k211λa2(r)1)                =λk2+ω1s=k2((b2(s)x1(s)+nj=1c2j(s)x2(sτ2j(s))eγ2j(s)x2(sτ2j(s)))sr=011λa2(r)).

    Note that ai (i=1,2) is positive ω-periodic. It follws that

    ki+ω1r=ki(1λai(r))=ω1r=0(1λai(r)). (2.9)

    Hence, we obtain

    x_1=λk1+ω1r=0(1λa1(r))1ω1r=0(1λa1(r))(k1+ω1s=k1(b1(s)x2(s)+nj=1c1j(s)x1(sτ1j(s))eγ1j(s)x1(sτ1j(s)))sr=011λa1(r))=λ1ω1r=0(1λa1(r))k1+ω1s=k1((b1(s)x2(s)+nj=1c1j(s)x1(sτ1j(s))eγ1j(s)x1(sτ1j(s)))k1+ω1r=s+1(1λa1(r))), (2.10)

    and

    x_2=λ1ω1r=0(1λa2(r))k2+ω1s=k2((b2(s)x1(s)+nj=1c2j(s)x1(sτ2j(s))eγ2j(s)x1(sτ2j(s)))k1+ω1r=s+1(1λa2(r))). (2.11)

    Recall that ¯γi=max1jn{max1kω1γij(k)} for i=1,2. We define f1(u)=ue¯γ1u and f2(u)=ue¯γ2u for u0. Since x_ixi(k)¯xi for all kZ+, it turns out that

    xi(sτij(s))eγij(s)xi(sτij(s))min{fi(x_i),fi(¯xi)}fors¯τijfori=1,2.

    Note that k1¯τ1. By using (2.3) and (2.10), we have

    x_1λmin{f1(x_1),f1(¯x1)}1ω1r=0(1λa1(r))k1+ω1s=k1(nj=1c1j(s)k1+ω1r=s+1(1λa1(r)))>λmin{f1(x_1),f1(¯x1)}1ω1r=0(1λa1(r))k1+ω1s=k1(γa1(s)k1+ω1r=s+1(1λa1(r)))=γmin{f1(x_1),f1(¯x1)}1ω1r=0(1λa1(r))k1+ω1s=k1(λa1(s)k1+ω1r=s+1(1λa1(r)))=γmin{f1(x_1),f1(¯x1)}1ω1r=0(1λa1(r))k1+ω1s=k1((1(1λa1(s)))k1+ω1r=s+1(1λa1(r)))=γmin{f1(x_1),f1(¯x1)}1ω1r=0(1λa1(r))k1+ω1s=k1(k1+ω1r=s+1(1λa1(r))k1+ω1r=s(1λa1(r)))=γmin{f1(x_1),f1(¯x1)}1ω1r=0(1λa1(r))(k1+ω1r=k1+ω(1λa1(r))k1+ω1r=k1(1λa1(r))).

    Calculating by the same way, from (2.3) and (2.11), we obtain

    x_2=γmin{f2(x_2),f2(¯x2)}1ω1r=0(1λa2(r))(k2+ω1r=k2+ω(1λa2(r))k2+ω1r=k2(1λa2(r))).

    Then, it follows from (2.9) that

    x_i>γmin{fi(x_i),fi(¯xi)}fori=1,2. (2.12)

    It is natural to divide the argument into two cases: (ⅰ) fi(x_i)fi(¯xi); (ⅱ) fi(x_i)>fi(¯xi).

    Case (ⅰ): It follows from (2.12) that x_i>γfi(x_i). Specifically, we have

    x_1>γf1(x_1)=γx_1e¯γ1x_1andx_2>γf2(x_2)=γx_2e¯γ2x_2,

    which imply that x_1>lnγ/¯γ1 and x_2>lnγ/¯γ2.

    Case (ⅱ): Function fi is unimodal and takes the only peak value at 1/¯γi. Also, fi monotonically increases on [0,1/¯γi] and monotonically decreases on [1/¯γi,). If ¯xi1/1/¯γi, then we see that fi(x_i)fi(¯xi)fi(1/¯γi), which is a contradiction. Hence, it follows that ¯xi>1/¯γi. Note that ¯xiBi. From (2.12), we obtain

    x_1>γf1(¯x1)γf1(B1)=γB1e¯γ1B1

    and

    x_2>γf2(¯x2)γf2(B2)=γB2e¯γ2B2.

    Thus, we estimate

    x_1>min{lnγ¯γ1,γB1e¯γ1B11}A1

    and

    x_2>min{lnγ¯γ2,γB2e¯γ2B22}A2.

    Now, it can be concluded that each positive ω-periodic solution x=(x1,x2)T of (2.1) satisfies

    A1<x_1x1(k)¯x1B1

    and

    A2<x_2x2(k)¯x1B2

    for kZ+. The proof is complete.

    Suppose that X is a Banach space and L:Dom LXX is a linear operator. The operator L is called a Fredholm operator of index zero if

    (i) dim Ker L=codim Im L<+,

    (ii) Im L is closed in X.

    If L is a Fredholm operator of index zero and P, Q:XX are continuous projectors satisfying

    Im P=Ker LandKer Q=Im L=Im (IQ),

    where I is the identity operator from X to X, then the restriction LP:Dom LKer PIm L is invertible and has the inverse KP:Im LDom LKer P.

    Let N:XX be a continuous operator and Ω an open bounded subset of X. The operator N is L-compact on ¯Ω if

    (i) QN(¯Ω) is bounded,

    (ii) KP(IQ)N:¯ΩX is compact.

    We present the continuation theorem of coincidence degree theory (for example, see [29,30]) as follows:

    Lemma 2.2. Let L:Dom LXX be a Fredholm operator of index zero and let N:XX be L-compact on ¯Ω. Suppose that

    (i) every solution x of Lx=λNx satisfies xΩ for λ(0,1);

    (ii) QNx0 for xΩKer L and

    deg{QN,ΩKer L,0}0.

    Then, Lx=Nx has at least one solution in X¯Ω.

    Theorem 3.1. Suppose that (2.2) and (2.3) hold. If

    ωk=1nj=1(cij(k)ωk=1(ai(k)bi(k))>1fori=1,2, (3.1)

    then system (1.1) has at least one positive ω-periodic solution x.

    Proof. Let X be a set of ω-periodic functions x=(x1,x2)T defined on Z+ and denote the maximum norm ||x||=max{max1kω|x1(k)|,max1kω|x2(k)|} for any xX. Then, X is a Banach space. Moreover, we define

    Lx=((Lx)1(k)(Lx)2(k))=(x1(k+1)x1(k)x2(k+1)x2(k)),

    and

    Nx=((Nx)1(k)(Nx)2(k))=( a1(k)x1(k)+b1(k)x2(k)+nj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k)) a2(k)x2(k)+b2(k)x1(k)+nj=1c2j(k)x2(kτ2j(k))eγ2j(k)x2(kτ2j(k))).

    It is not difficult to show that L is a linear operator from X to X and N is a continuous operator from X to X.

    From the definition of L, we see that

                    Ker L={xX:(x1(k),x2(k))T(c1,c2)TR2}and                Im L={xX:ωk=1x1(k)=ωk=1x2(k)=0}.

    It turns out that dim Ker L=2=codim Im L<+ and Im L is closed in X. Thus, L is a Fredholm operator of index zero.

    We define P:XX by

    Px=((Px)1(Px)2)=(1ωωk=1x1(k)1ωωk=1x2(k))

    and let Q=P. Then, P and Q are two continuous projectors such that Im P=Ker L and Ker Q=Im L=Im (IQ).

    It can be shown that the restriction LP:Dom LKer PIm L has the inverse KP:Im LDom LKer P given by

    KPx=((KPx)1(KPx)2)=(k1s=0x1(s)1ωω1s=0sr=0x1(r)k1s=0x2(s)1ωω1s=0sr=0x2(r))

    for x=(x1,x2)TIm L. In fact, for i=1,2, since

    (KPx)i(k+ω)(KPx)i(k)=k+ω1s=0xi(s)1ωω1s=0sr=0xi(r)k1s=0xi(s)+1ωω1s=0sr=0xi(r)=k+ω1s=kxi(s)=ω1s=0xi(s)=0

    for all kZ+, we see that KPxDom L. Moreover, it follows that

    (PKPx)i=1ωωk=1KPxi(k)=1ωωk=1(k1s=0xi(s)1ωω1s=0sr=0xi(r))=1ω(ωk=1k1s=0xi(s)ωωω1s=0sr=0xi(r))=1ω(ωk=1k1s=0xi(s)ωk=1k1r=0xi(r))=0.

    Hence, KPxKer P.

    For any xIm L, one has

    (LPKPx)i=(KPx)i(k+1)(KPx)i(k)=ks=0xi(s)1ωω1s=0sr=0xi(r)k1s=0xi(s)+1ωω1s=0sr=0xi(r)=xi(k)=(Ix)i.

    Furthermore, for any xDom LKer P, one has

    (KPLPx)i=KP(xi(k+1)xi(k))=k1s=0(xi(s+1)xi(s))1ωω1s=0sr=0(xi(r+1)xi(r))=xi(k)xi(0)1ωω1s=0(xi(s+1)xi(0))=xi(k)1ωωs=1xi(s).

    Since xKer P=Ker Q=Im L, we see that ωs=1xi(s)=0. Hence, (KPLPx)i=xi(k)=(Ix)i. We therefore conclude that KP=L1P.

    We define

    Ω={x=(x1,x2)TX:A1<x1(k)<B1+1,A2<x2(k)<B2+1}

    and prove that the operator N defined above is L-compact on ¯Ω. We first check that QN(¯Ω) is bounded.

    Since x1(k)<B1+1 and x2(k)<B2+1 for kZ+, we obtain

    (QNx)1=1ωωk=1( a1(k)x1(k)+b1(k)x2(k)+nj=1c1j(k)x1(kτ1j(k))eγ1j(k)x1(kτ1j(k)))<1ωωk=1(¯b1(B2+1)+1enj=1¯c1jγ_1j)=(¯b1(B2+1)+1enj=1¯c1jγ_1j),

    and

    (QNx)2=1ωωk=1( a2(k)x2(k)+b2(k)x1(k)+nj=1c2j(k)x2(kτ2j(k))eγ2j(k)x2(kτ2j(k)))<1ωωk=1(¯b2(B1+1)+1enj=1¯c2jγ_2j)=(¯b2(B1+1)+1enj=1¯c2jγ_2j)

    for x¯Ω. Hence, the operator QN is bounded on ¯Ω.

    We next show that KP(IQ)N:¯ΩX is compact. From the definitions of N, QN and Kp, we obtain

    (Kp(IQ)Nx)1=k1s=0( a1(s)x1(s)+b1(s)x2(s))+k1s=0(nj=1c1j(s)x1(sτ1j(s))eγ1j(s)x1(sτ1j(s)))(kωω+12ω)ωs=1( a1(s)x1(s)+b1(s)x2(s))(kωω+12ω)ωs=1(nj=1c1j(s)x1(sτ1j(s))eγ1j(s)x1(sτ1j(s)))1ωω1s=0sr=0( a1(r)x1(r)+b1(r)x2(r))1ωω1s=0sr=0(nj=1c1j(r)x1(rτ1j(r))eγ1j(r)x1(rτ1j(r))).

    Meanwhile, we have

    (Kp(IQ)Nx)2=k1s=0( a2(s)x2(s)+b2(s)x1(s))+k1s=0(nj=1c2j(s)x2(sτ2j(s))eγ2j(s)x2(sτ2j(s)))(kωω+12ω)ωs=1( a2(s)x2(s)+b2(s)x1(s))(kωω+12ω)ωs=1(nj=1c2j(s)x2(sτ2j(s))eγ2j(s)x2(sτ2j(s)))1ωω1s=0sr=0( a2(r)x2(r)+b2(r)x1(r))1ωω1s=0sr=0(nj=1c2j(r)x2(rτ2j(r))eγ2j(r)x2(rτ2j(r)))

    for xX. For any bounded subset E¯ΩX, it is a subspace of a finite dimensional Banach space X. Hence, E is closed, and therefore E is compact. By a straightforward calculation, it can be proven that KP(IQ)N(E) is relatively compact.

    An arbitrary ω-periodic solution of (2.1) corresponds one-to-one to a solution of Lx=λNx with parameter λ(0,1). Proposition 2.1 displays that each positive solution x=(x1,x2)T of Lx=λNx satisfies that A1<x1B1 and A2<x2B2. It is obvious that if y=(y1,y2)TΩ, then y is never a solution of Lx=λNx. Hence, the condition (i) of Lemma 2.2 holds. If x=(x1,x2)TΩKer L, then there are four cases to be considered: (1) x=(A1,x2)T, (2) x=(B1+1,x2)T, (3) x=(x1,A2)T, (4) x=(x1,B2+1)T.

    Case (1): It follows from x1A1 that

    (QNx)1=1ωωk=1(A1a1(k)+b1(k)x2(k)+nj=1cij(k)A1eγ1j(k)A1)A1ωωk=1(a1(k)+1eA1¯γ1nj=1cij(k))>A1ωωk=1(a1(k)+γeA1¯γ1a1(k))=A1ω(γeA1¯γ11)ωk=1a1(k).

    Since A1lnγ/¯γ1, we see that eA1¯γ1γ. Hence, (QNx)1>0.

    Case (2): Because of x1B1+1, we have

    (QNx)1=1ωωk=1((B1+1)a1(k)+b1(k)x2(k)+nj=1cij(k)(B1+1)eγ1j(k)(B1+1))1ωωk=1(a_1(B1+1)+¯b1B2+nj=1¯c1jeγ_1j)=a_1(B1+1)+¯b1B2+1enj=1¯c1jγ_1j=a_1a_1a_2(a_1a_2¯b1¯b2)e(nj=1¯c1jγ_1j+¯b1a_2nj=1¯c2jγ_2j)+a_1¯b1(a_1a_2¯b1¯b2)e(nj=1¯c2jγ_2j+¯b2a_1nj=1¯c1jγ_1j)+1enj=1¯c1jγ_1j=a_1<0.

    Similarly, we can show that (QNx)2>0 in Case (3) and (QNx)2<0 in Case (4). We therefore conclude that QNx=((QNx)1,(QNx)2)T0 for each xΩKer L.

    Define a continuous operator H:ΩKer L×[0,1]X by

    H(x,μ)=(H1(x,μ)H2(x,μ))=(μ(Ix1A1+B12)+(1μ)(QNx)1μ(Ix2A2+B22)+(1μ)(QNx)2).

    Recall that the elements of ΩKer L are vectors satisfying x=(A1,x2)T, y=(B1+1,y2)T, z=(z1,A2)T and w=(w1,B2+1)T. For x=(A1,x2)T, we can check that

    H1(x,μ)=μ(A1A1+B12)+(1μ)(QNx)1=μ(A1B12)+(1μ)(QNx)1>0.

    Moreover,

    H1(y,μ)=μ(B1+1A1+B12)+(1μ)(QNy)1=μ(A1B1+22)+(1μ)(QNy)1<0

    for y=(B1+1,y2)T. Hence, H(x,μ)0 and H(y,μ)0. By similar computations, we have H(z,μ)0 and H(w,μ)0. Therefore, we see that H(x,μ)0 for (x,μ)ΩKer L×[0,1]. Thus, H is a homotopic mapping. Using the homotopy invariance, we have

    deg{QN,ΩKer L,0}=deg{(Ix1+A1+B12Ix2+A2+B22),ΩKer L,0}=10.

    Hence, the condition (ⅱ) of Lemma 2.2 holds. Therefore, the equation Lx=Nx has at least one solution located in X¯Ω. Thus, from Lemma 2.2, we obtain that there is a positive ω-periodic solution of system (1.1). The proof is now complete.

    Consider the delay difference system

    {Δx1(k)=a1(k)x1(k)+b1(k)x2(k)+c11(k)x1(k1)eγ11(k)x1(k1)+c12(k)x1(k1)eγ12(k)x1(k1),Δx2(k)=a2(k)x2(k)+b2(k)x1(k)+c21(k)x2(k4)eγ21(k)x2(k4)+c22(k)x2(k4)eγ22(k)x2(k4).

    Here, we assume that

    a1(k)={1/2ifk=1,2/5ifk=2,1/4ifk=3,1/5ifk=4,a2(k)={3/4ifk=1,3/5ifk=2,1/2ifk=3,5/6ifk=4,
    b1(k)={1/5ifk=1,1/4ifk=2,1/7ifk=3,1/6ifk=4,b2(k)={1/20ifk=1,1/12ifk=2,1/24ifk=3,1/18ifk=4,
    c11(k)={1/2ifk=1,3/4ifk=2,1/3ifk=3,2/3ifk=4,c12(k)={5/6ifk=1,4/5ifk=2,2/5ifk=3,1/6ifk=4,c21(k)={7/8ifk=1,4/5ifk=2,2/3ifk=3,6/7ifk=4,c22(k)={1/4ifk=1,1/2ifk=2,1/10ifk=3,20/21ifk=4,
    γ11(k)={3ifk=1,1ifk=2,1.5ifk=3,2ifk=4,γ12(k)={10ifk=1,4ifk=2,3ifk=3,5ifk=4,γ21(k)={5ifk=1,2ifk=2,1ifk=3,2.5ifk=4,γ22(k)={2ifk=1,1.5ifk=2,8ifk=3,3ifk=4.

    In addition, ai(k)=ai(k+4), bi(k)=bi(k+4), cij(k)=cij(k+4) and γij(k)=γij(k+4) for kZ, i=1,2 and j=1,2. Theorem 3.1 shows that the system has at least one positive 4-periodic solution.

    It is clear that ω=4, ai, bi, cij, γij and τij (1i2,1j2) are ω-periodic discrete functions satisfying 0<ai(k)<1, 0<bi(k)<1, cij(k)>0 and γij(k)>0 for kZ+. Since a_1=1/5, a_1=1/2, ¯b1=1/4 and ¯b2=1/12, we see that

    a_1a_1¯b1¯b2=15×1214×112=19240>0.

    Hence, condition (2.2) is satisfied. Let γ=11/10>1. Then, we can easily check condition (2.3)

    (c11(k)+c12(k))>γa1(k)and(c21(k)+c22(k))>γa2(k)

    for k=1,2,3,4. Moreover, it can be calculated that

    4k=1(c11(k)+c12(k))4k=1(a1(k)b1(k))=1869248>1and4k=1(c21(k)+c22(k))4k=1(a2(k)b2(k))=221106181>1.

    Namely, condition (3.1) holds. Therefore, from Theorem 3.1, it turns out that the system has at least one positive 4-periodic solution.

    Figure 1.  Graphs of three arbitrary positive solutions of system. The numerical simulations show that there is a positive 4-periodic solution and this positive 4-periodic solution is locally asymptotically stable.

    A discrete Nicholson system that describles the dynamics of two fly species is studied in this paper. The system considers the mutualism effect between fly species. Continuation theorem of coincidence degree theory is used effectively to seek sufficient conditions for the existence of a positive periodic solution. It is easy to check whether these sufficient conditions hold or not by using coefficients. The positive periodic solution indicates a cycle change in the adult fly populations. From the obtained result, we found that mutualistic interactions between species plays an important role in adult flies populations. But the increase in the flies populations resulting from maximum cumulative mutualism effect only should be less than the death of the flies populations because there is the natural generation of flies populations. Moreover, to avoid species extinction and maintain the coexistence of two fly species in a mutually beneficial environment, we see that (ⅰ) the adult fly population produced by maximum daily spawning should exceed a constant multiple of dead fly population for each fly species, and the multiple is greater than constant 1 and (ⅱ) the total population growth must be maintained more than the population loss for each fly species. In fact, the third sufficient condition (3.1) of Theorem 3.1 can be rewritten into the form

    ωk=1(nj=1(c1j(k)+b1(k))>ωk=1a1(k)andωk=1(nj=1(c2j(k)+b2(k))>ωk=1a2(k).

    The left side of each inequality represents the production of one fly species in a period under the mutualism influence of another, and the right side represents the death of that species in a period. Hence, statement (ⅱ).

    The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

    The paper is supported by College Students Innovations Special Project funded by Northeast Forestry University of China (Grant No. 202210225156) and Fundamental Research Funds for the Central Universities of China (Grant No. 41422003).

    The authors declare that there is no conflicts of interest.



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