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Alex Genin edited this page Jun 23, 2015 · 1 revision

Description

This model considers three states: predator, prey and empty. For clarity of implementation in the code we use fish and shark instead of predator and prey.

Prey growth

A prey chooses a neighbouring site at random and then gives birth into if the site is empty with probability βf.

Predator growth

A predator inspect its neighbours. If some of them are preys then it chooses one randomly, moves to its cell and eats it. If a predator ate a prey then it reproduces with probability βs. If a predator could not find a prey then it starves to death with probability ẟ.

Mixing

Random mixing occurs: at each time step a pair of neighbours is considered r

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