Metapopulation dynamics have received much attention in conservation a
nd population biology, but the standard approach has also been critici
zed for being too restrictive, as it is based on the effects of habita
t patch area and isolation only. Here we demonstrate how the effects o
f habitat quality (extra environmental factors) and detailed landscape
structure (described with GIS [Geographical Information System]) can
be included in a spatially realistic metapopulation model, the inciden
ce function model. Expanded models are tested with a large data set on
the Glanville fritillary butterfly (Melitaea cinxia). The incidence f
unction model supplemented with additional environmental factors revea
led some new and confirmed some previously known interactions between
M. cinxia and its environment. However, the ability of the additional
environmental factors to explain the error in the fit of the basic mod
el was generally low (less than or equal to 15%). In the second varian
t of the basic model, landscape structure was used to modify effective
patch isolations. This approach, though biologically appealing, faile
d to improve significantly the fit of the incidence function model. Th
ere are several possible reasons for this failure, including inaccurat
e satellite data, problems with habitat classification, and most impor
tantly, generic problems in the modeling of migration. Our results dem
onstrate that additional complexity beyond the effects of habitat patc
h area and isolation does not necessarily improve the predictive power
of a metapopulation model.