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On the evolution of migrating population with two competing species

Magdoń-Maksymowicz M., Maksymowicz A.

Computer Science

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2013

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Vol. 14 (4)

615--627

EN

A computer experiment study of population evolution and its dynamics is presented for two competing species (A and B) which share two habitats (1 and 2) of a limited environmental capacity. The Penna model of biological aging, based on the concept of defective mutation accumulation, was adopted for migrating population. In this paper, we assume and concentrate on the case when only one species (A) is mobile. For isolated habitats and for any initial population, we get at equilibrium spatial population distribution (A, B) in which A occupies location ’1’ only, while B-species is the ultimate winner in ’2’. This is achieved by suitable choice of model parameters so habitat ’1’ is more attractive for species ’A’ while location ’2’ is more advantageous to ’B’. However, population distribution begins to differ when migration between habitats is allowed. Initially stable distribution (A, B), becomes (A, A&B) with a mixed stationary population in location ’2’. For a higher migration rate, initial (A, B) distribution goes to (A, A) distribution, in which A species is dominant also in a less friendly habitat ’2’. However, a further increase in migration rate brings sequence (A, B)b(B, B). In short, for sufficiently high mobility of A-species, they eliminate themselves. Other scenarios not discussed here were also studied. They offer a rich variety of different sequences of population distribution regarding their size as well as other characteristics.

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Simulating the spread of the BSE disease: a cellular automata approach

Magdoń-Maksymowicz M., Maksymowicz A. Z.

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

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2005

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Vol. 9, No 2

179-185

EN

The rules of evolution applied in the cellular automata approach may correspond to the propagation of the mad cow disease. In a computer simulation of the BSE disease's spread both inherited and infectious mechanisms are accounted for. The initial population of items is randomly distributed on a two-dimensional square lattice, Nx × Ny = 1000 × 1000, with a fraction of 1 percent the items already infected. Alternatively, faulty prions may spontaneously develop during the simulation with a very small frequency. Our results indicate a critical probability, pc, of BSE transmission, so that for p below the threshold the population recovers. For p > pc the disease is launched in the population with a dynamic equilibrium between the healthy and infected fractions of the population. The threshold is very sensitive to spatial clustering of the population and the detailed rules for the disease's onset, evolution and propagation.

3

On Penna model of population evolution

Magdoń-Maksymowicz M.

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

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2000

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Vol. 4, No 1

5-18

EN

Computer studies of population evolution are presented. Numerical calculations are based on the Penna model. This model accounts for mutation load of individuals resulting in non-trivial age (a) dependence of the mortality rate q(a) which may be compared with empirical data. The Penna model is also very flexible for suitable modifications of the population evolution process such as hunting, genetic death, migration etc. Here we present some examples of the population growth for different evolution rules. Calculations require about 100 MB memory for 10/sup 6/ population which is necessary to get reliable statistics. The typical running time for 3000 iteration steps is several hours for a HP S2000 machine.