Parameter Estimation - Part I

In all the previous Units we used as a reference metapopulation presence/absence data obtained by simulations from a IFM at equilibrium with parameters A0 = 0.0004, x = 0.05 and y = 0.005. Here we deal with the problem of estimating the unknown parameters of an IFM on the basis of one or more snapshots of presence/absence data.

As mentioned at the end of Unit 1, we will assume that the species behaves as a metapopulation in the fragmented area where it has been observed, and that an IFM is suitable to model the metapopulation dynamics. Then, we will not discuss how to check whether a metapopulation approach is suitable or not.

In particular, we limit ourselves to the case of the basic IFM, with and without the rescue effect and we will not discuss parameter estimation for the time-dependent model. For the basic IFM approach, the maximum likelihood estimation method will be used. A slight variation of this method also applies to the time-dependent IFM. However, in this case a lot of technicalities are required, going beyond the aim of this course. Interested people can refer to Moilanen (1999).