Wildlife-habitat models are an important tool in wildlife management toda?,
and by far the majority of these predict aspects of species distribution (
abundance or presence) as a proxy measure of habitat quality. Unfortunately
, few are tested on independent data, and of those that are, few show usefu
l predictive st;ill. We demonstrate that six critical assumptions underlie
distribution based wildlife-habitat models, all of which must be valid for
the model to predict habitat quality. We outline these assumptions in a met
e-model, and discuss methods for their validation. Even where all sis assum
ptions show a high level of validity, there is still a strong likelihood th
at the model will not predict habitat quality. However, the meta-model does
suggest habitat quality can be predicted more accurately if distributional
data are ignored, and variables more indicative of habitat quality are mod
elled instead.