  We propose the use of finite mixtures of continuous distributions in
modelling the process by which new individuals, that arrive in groups, become
part of a wildlife population. We demonstrate this approach using a data set of
migrating semipalmated sandpipers (Calidris pussila) for which we extend
existing stopover models to allow for individuals to have different behaviour
in terms of their stopover duration at the site. We demonstrate the use of
reversible jump MCMC methods to derive posterior distributions for the model
parameters and the models, simultaneously. The algorithm moves between models
with different numbers of arrival groups as well as between models with
different numbers of behavioural groups. The approach is shown to provide new
ecological insights about the stopover behaviour of semipalmated sandpipers but
is generally applicable to any population in which animals arrive in groups and
potentially exhibit heterogeneity in terms of one or more other processes.
