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We investigate a metapopulation model referring to populations that are spatially structured in colonies. Each colony thrives during a random time until a catastrophe when only a random amount of individuals of that colony survives. These survivors try independently establishing new colonies at neighbour sites, randomly. If the chosen site is occupied, that individual dies, otherwise the individual founds there a new colony. Here we consider this metapopulation model subject to two schemes: (i) Poisson growth, during an exponential time, for each colony and geometric catastrophe, and (ii) Yule growth, during an exponential time, for each colony and binomial catastrophe. We study conditions on the set of parameters for these processes to survive, present relevant bounds for the probability of survival, for the number of vertices that were colonized and for the reach of the colonies compared to the starting point. As a byproduct we study convergence of sequence of branching processes. [ABSTRACT FROM AUTHOR]

We consider stochastic growth models to represent population dynamics subject to geometric catastrophes. We analyze different dispersion schemes after catastrophes, to study how these schemes impact the population viability and comparing them with the scheme where there is no dispersion. In the schemes with dispersion, we consider that each colony, after the catastrophe event, has d new positions to place its survivors. We find out that when d = 2 no type of dispersion considered improves the chance of survival, at best it matches the scheme where there is no dispersion. When d = 3 , based on the survival probability, we conclude that dispersion may be an advantage or not, depending on its type, the rate of colony growth and the probability that an individual will survive when exposed to a catastrophe. [ABSTRACT FROM AUTHOR]

We consider stochastic growth models to represent population subject to catastrophes. We analyze the subject from different set ups considering or not spatial restrictions, whether dispersion is a good strategy to increase the population viability. We find out it strongly depends on the effect of a catastrophic event, the spatial constraints of the environment and the probability that each exposed individual survives when a disaster strikes. [ABSTRACT FROM AUTHOR]