Stochastic matrix metapopulation models with fast migration: Re-scaling survival to the fast scale

•Reduction methods simplify the analysis of stochastic matrix metapopulation models.•By considering time scales one can make use of specific reduction methods.•It is crucial to associate the proper time scale to each of the processes involved.•Re-scaling certain processes helps obtain the appropriate time scale association. In this work we address the analysis of discrete-time models of structured metapopulations subject to environmental stochasticity. Previous works on these models made use of the fact that migrations between the patches can be considered fast with respect to demography (maturation, survival, reproduction) in the population. It was assumed that, within each time step of the model, there are many fast migration steps followed by one slow demographic event. This assumption allowed one to apply approximate reduction techniques that eased the model analysis. It is however a questionable issue in some cases since, in particular, individuals can die at any moment of the time step. We propose new non-equivalent models in which we re-scale survival to consider its effect on the fast scale. We propose a more general formulation of the approximate reduction techniques so that they also apply to the proposed new models. We prove that the main asymptotic elements in this kind of stochastic models, the Stochastic Growth Rate (SGR)11Stochastic Growth Rate (SGR). Scaled Logarithmic Variance (SLV). and the Scaled Logarithmic Variance (SLV), can be related between the original and the reduced systems, so that the analysis of the latter allows us to ascertain the population fate in the first. Then we go on to considering some cases where we illustrate the reduction technique and show the differences between both modelling options. In some cases using one option represents exponential growth, whereas the other yields extinction.