h | (0, h*) | (h*, h*) | (h*, ∞) |
O | unstable | stable | glob. asymp. stable |
P+ | stable | stable | − |
P− | − | unstable | − |
A stochastic forest model of young and old age class trees is studied. First, we prove existence, uniqueness and boundedness of global nonnegative solutions. Second, we investigate asymptotic behavior of solutions by giving a sufficient condition for sustainability of the forest. Under this condition, we show existence of a Borel invariant measure. Third, we present several sufficient conditions for decline of the forest. Finally, we give some numerical examples.
Citation: |
Figure 1. Sample trajectories of $u_t$ and $v_t$ of (2) with parameters: $a=2, b=1, c=2.5, f=4, h=1, \rho=5, \sigma=0.5$ and initial value $(u_0, v_0)=(2, 1).$ The left figure illustrates a sample trajectory of $(u_t, v_t)$ in the phase space; the right figure illustrates sample trajectories of $u_t$ and $v_t$ along $t\in [0,100]$
Figure 2. Distribution of $(u_t, v_t)$ of (2) at $t=10^3$. The parameters and initial value are taken as in the legend of Fig. 1
Figure 3. Graphs of $\mathbb Eu$ and $\mathbb Ev$ along $ t\in [0, 20]$. The parameters and initial value are taken as in the legend of Fig. 1
Figure 4. Sample trajectory of two processes $I$ and $J$ defined by $I(t)=\frac{1}{t}\int_0^t u_sds$ and $J(t)=\frac{1}{t}\int_0^t v_sds$ along $ t\in [0,100].$ The parameters and initial value are taken as in the legend of Fig. 1
Figure 5. Graph of probability functions $R$ and $S$ defined by $R(t)=\mathbb P\{(u_t, v_t)\in A; (u_0, v_0)=(2, 1)\}$ and $S(t)=\mathbb P\{(u_t, v_t)\in A; (u_0, v_0)=(3, 4)\}$ along $t\in [50,100], $ where $A=[0.5, 30]\times[0.1, 20]$ and the parameters of (2) are taken as in the legend of Fig. 1. These functions are calculated on the basis of 2000 sample trajectories of $(u_t, v_t)$ corresponding to each initial value
Figure 6. Decline of forest under the effect of noise with large intensity $\sigma$. Here, $a=3, b=4, c=5, f=6, h=2, \rho=7, \sigma=4$ and initial value $(u_0, v_0)=(4, 3)$. The left figure is a sample trajectory of $(u_t, v_t)$ in the phase space; the right figure is a sample trajectory of $u$ and $v$ along $t\in [0, 1]$
Table 1. Stability and instability of stationary solutions of (1)
h | (0, h*) | (h*, h*) | (h*, ∞) |
O | unstable | stable | glob. asymp. stable |
P+ | stable | stable | − |
P− | − | unstable | − |
[1] |
M. Ya. Antonovsky, Impact of the factors of the environment on the dynamics of population (mathematical model), in Proc. Soviet-American Symp. Comprehensive Analysis of the Environment, Tbilisi 1974, Leningrad: Hydromet, (1975), 218-230.
![]() |
[2] |
L. Arnold, Stochastic Differential Equations: Theory and Applications, Wiley, New York, 1972.
![]() ![]() |
[3] |
L. H. Chuan and A. Yagi, Dynamical system for forest kinematic model, Adv. Math. Sci. Appl., 16 (2006), 393-409. ![]() ![]() |
[4] |
L. H. Chuan, T. Tsujikawa and A. Yagi, Asymptotic behavior of solutions for forest kinematic model, Funkcial. Ekvac., 49 (2006), 427-449. doi: 10.1619/fesi.49.427.![]() ![]() ![]() |
[5] |
L. H. Chuan, T. Tsujikawa and A. Yagi, Stationary solutions to forest kinematic model, Glasg. Math. J., 51 (2009), 1-17. doi: 10.1017/S0017089508004485.![]() ![]() ![]() |
[6] |
S. R. Foguel, The ergodic theory of positive operators on continuous functions, Ann. Scuola Norm. Sup. Pisa, 27 (1973), 19-51. ![]() ![]() |
[7] |
A. Friedman, Stochastic Differential Equations and Applications, Academic Press, New York, 1976.
![]() ![]() |
[8] |
N. Ikeda and S. Watanabe, Stochastic Differential Equations and Diffusion Processes, NorthHolland, Tokyo, 1981.
![]() ![]() |
[9] |
I. Karatzas and S. E. Shreve, Brownian Motion and Stochastic Calculus, Springer-Verlag, Berlin, 1991.
doi: 10.1007/978-1-4612-0949-2.![]() ![]() ![]() |
[10] |
P. E. Kloeden, E. Platen and H. Schurz, Numerical Solution of SDE through Computer Experiments, Springer-Verlag, Berlin, 1994.
doi: 10.1007/978-3-642-57913-4.![]() ![]() ![]() |
[11] |
Yu. A. Kuznetsov, M. Ya. Antonovsky, V. N. Biktashev and E. A. Aponina, A cross-diffusion model of forest boundary dynamics, J. Math. Biol., 32 (1994), 219-232. doi: 10.1007/BF00163879.![]() ![]() ![]() |
[12] |
X. Mao, Stochastic Differential Equations and Applications, 2nd edition, Horwood, Chichester, 2008.
doi: 10.1533/9780857099402.![]() ![]() ![]() |
[13] |
L. Michael, Conservative Markov processes on a topological space, Isr. J. Math., 8 (1970), 165-186. doi: 10.1007/BF02771312.![]() ![]() ![]() |
[14] |
L. T. H. Nguyen and T. V. Ta., Dynamics of a stochastic ratio-dependent predator-prey model, Anal. Appl. (Singap.), 9 (2011), 329-344. doi: 10.1142/S0219530511001868.![]() ![]() ![]() |
[15] |
T. Shirai, L. H. Chuan and A. Yagi, Asymptotic behavior of solutions for forest kinematic model under Dirichlet conditions, Sci. Math. Jpn., 66 (2007), 289-301. ![]() ![]() |
[16] |
T. V. Ta., L. T. H. Nguyen and A. Yagi, Flocking and non-flocking behavior in a stochastic Cucker-Smale system, Anal. Appl. (Singap.), 12 (2014), 63-73. ![]() ![]() |
[17] |
A. Yagi, Abstract Parabolic Evolution Equations and their Applications, Springer, Berlin, 2010.
![]() ![]() |
Sample trajectories of $u_t$ and $v_t$ of (2) with parameters: $a=2, b=1, c=2.5, f=4, h=1, \rho=5, \sigma=0.5$ and initial value $(u_0, v_0)=(2, 1).$ The left figure illustrates a sample trajectory of $(u_t, v_t)$ in the phase space; the right figure illustrates sample trajectories of $u_t$ and $v_t$ along $t\in [0,100]$
Distribution of $(u_t, v_t)$ of (2) at $t=10^3$. The parameters and initial value are taken as in the legend of Fig. 1
Graphs of $\mathbb Eu$ and $\mathbb Ev$ along $ t\in [0, 20]$. The parameters and initial value are taken as in the legend of Fig. 1
Sample trajectory of two processes $I$ and $J$ defined by $I(t)=\frac{1}{t}\int_0^t u_sds$ and $J(t)=\frac{1}{t}\int_0^t v_sds$ along $ t\in [0,100].$ The parameters and initial value are taken as in the legend of Fig. 1
Graph of probability functions $R$ and $S$ defined by $R(t)=\mathbb P\{(u_t, v_t)\in A; (u_0, v_0)=(2, 1)\}$ and $S(t)=\mathbb P\{(u_t, v_t)\in A; (u_0, v_0)=(3, 4)\}$ along $t\in [50,100], $ where $A=[0.5, 30]\times[0.1, 20]$ and the parameters of (2) are taken as in the legend of Fig. 1. These functions are calculated on the basis of 2000 sample trajectories of $(u_t, v_t)$ corresponding to each initial value
Decline of forest under the effect of noise with large intensity $\sigma$. Here, $a=3, b=4, c=5, f=6, h=2, \rho=7, \sigma=4$ and initial value $(u_0, v_0)=(4, 3)$. The left figure is a sample trajectory of $(u_t, v_t)$ in the phase space; the right figure is a sample trajectory of $u$ and $v$ along $t\in [0, 1]$
Decline of forest when the mortality $h$ of old trees is large. Here, $a=3, b=4, c=5, f=6, h=3.82, \rho=7, \sigma=0.25$ and initial value $(u_0, v_0)=(4, 3).$ The figure gives a graph of $\mathbb Eu$ and $\mathbb Ev$ along $t\in [0, 10]$