Hazel grouse Bonasa bonasia population dynamics in a fragmented landscape: A metapopulation approach

Abstract

If the deterministic threats of fragmentation can be stopped or reversed, species may find opportunities to disperse between patches and reduce the risk of extinction. In order to realise these opportunities and apply them to conservation programmes, it is necessary to understand the dynamics involved and to estimate which capacity is high enough to sustain a population at the landscape level. In a regional population consisting of several subpopulations, the incidence function model (IFM) is a stochastic, spatially-realistic patch occupancy model which can be applied using few parameters. With this model one can simulate and manipulate a patch network for a species. In IFM, the extinction probability is assumed to be proportional to local population size which in turn is assumed to be proportional to the local patch area. Although, the basic area of patches is of importance, influence from the geometric shape of patches may be equally or more important to determine potential incidence of a species in a particular patch. Basic area measurements might overestimate the probability of occupancy and/or capacity of a certain patch network to sustain a metapopulation. One applicable method to use in dealing with regional dynamics in fragmented landscapes is metapopulation capacity; derived from metapopulation theory, this method can be used to rank different patch networks. In our study, we examine if there is any difference in occupancy level and capacity between four different area scenarios. This allows us to determine if the basic area measurement of patches can result in a biased estimation of population viability in a specific landscape. It is concluded that perimeter-area related measures of patch size combined with capacity could be a more important measure for estimation of population dynamics and impact of landscape changes compared to basic area measurement and occupancy levels. © 2010 Wildlife Biology.