A geometric method for asymptotic properties of the stochastic Lotka-Volterra model

Abstract In this paper, we use a geometric method to analyze the asymptotic properties of the stochastic Lokta–Volterra model, which mainly include two aspects: uniformly ultimate boundedness and almost sure permanence. The geometric method demonstrates that there exists a bounded region that lies in the interior of the first quadrant such that solutions of the stochastic model starting from the exterior of the region will almost surely go into the interior of it in finite time, meanwhile, solutions which start from the interior of the region will almost surely not leave the interior of it in any finite time. Firstly, we show that the stochastic competition, predator-prey and mutualism model are uniformly ultimately bounded and almost surely permanent by the geometric structures of invariant sets. Secondly we give numerical simulations to illustrate the geometric method as well as the conclusions.

[1]  Ke Wang,et al.  Almost sure permanence of stochastic single species models , 2015 .

[2]  Hong Liu,et al.  The ergodic property and positive recurrence of a multi-group Lotka-Volterra mutualistic system with regime switching , 2013, Syst. Control. Lett..

[3]  Ke Wang,et al.  Persistence and extinction in stochastic non-autonomous logistic systems , 2011 .

[4]  T. Gard,et al.  Stability for multispecies population models in random environments , 1986 .

[5]  Sanling Yuan,et al.  Survival and Stationary Distribution Analysis of a Stochastic Competitive Model of Three Species in a Polluted Environment , 2015, Bulletin of mathematical biology.

[6]  R. May,et al.  Stability and Complexity in Model Ecosystems , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  Partha Sarathi Mandal,et al.  Stochastic persistence and stationary distribution in a Holling–Tanner type prey–predator model , 2012 .

[8]  Desmond J. Higham,et al.  An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations , 2001, SIAM Rev..

[9]  Xiaoling Zou,et al.  Stationary distribution and stochastic Hopf bifurcation for a predator-prey system with noises , 2013 .

[10]  Gang George Yin,et al.  Stabilization and destabilization of hybrid systems of stochastic differential equations , 2007, Autom..

[11]  Daqing Jiang,et al.  Analysis of a predator-prey model with modified Leslie-Gower and Holling-type II schemes with stochastic perturbation , 2009 .

[12]  Daqing Jiang,et al.  Persistence and non-persistence of a mutualism systemwith stochastic perturbation , 2011 .

[13]  G. Yin,et al.  Logistic models with regime switching: Permanence and ergodicity , 2016 .

[14]  Xiaoling Zou,et al.  A new idea on almost sure permanence and uniform boundedness for a stochastic predator-prey model , 2017, J. Frankl. Inst..

[15]  Daqing Jiang,et al.  Global stability and stochastic permanence of a non-autonomous logistic equation with random perturbation☆ , 2008 .

[16]  Adel Settati,et al.  On stochastic Gilpin-Ayala population model with Markovian switching , 2015, Biosyst..

[17]  Qun Liu,et al.  Dynamics of stochastic predator-prey models with Holling II functional response , 2016, Commun. Nonlinear Sci. Numer. Simul..

[18]  Stationary distribution and pathwise estimation of n-species mutualism system with stochastic perturbation , 2016 .

[19]  Nguyen Huu Du,et al.  Existence of stationary distributions for Kolmogorov systems of competitive type under telegraph noise , 2014 .

[20]  J. Bao,et al.  The stationary distribution of the facultative population model with a degenerate noise , 2013 .

[21]  Xuerong Mao,et al.  Stationary distribution of stochastic population systems , 2011, Syst. Control. Lett..

[22]  Adel Settati,et al.  Stationary distribution of stochastic population systems under regime switching , 2014, Appl. Math. Comput..

[23]  Thomas C. Gard Persistence in stochastic food web models , 1984 .