Habitat ordinations were performed on 37 sites in forests and woodlands along a latitudinal transect that spanned over 250 km in central Victoria. Australia. Multivariate analyses of these data by using nonmetric. multidimensional scaling (AIDS) were used to generate composite variables. The relationships of these composite variables and densities (by area) of 58 species of forest and woodland birds were assessed by using linear and polynomial regressions. Only seven of the 58 species of birds did not display a significant relationship to one or other of the five composite variables. Approximately 50% of the avian species showed significant relationships with each of the first two composite variables, but lower percentages were observed for the other three variables. About a third of all significant correlations were either of second or third order, ft appears that marked curvilinearities associated with the first composite variable can be interpreted as linear responses with respect to the secondary composite variable. These results suggest that, although composite variables derived from multivariate classifications are statistically independent, there often may be substantial biological dependence between the composite variables. Therefore, for biological interpretation, it would be appropriate to regard composite variables derived from multivariate classifications as suites of related variables. Some authors have traced sharp discontinuities in distributions of species with respect to habitat structure by using presence/absence data alone. This approach appears to be sensitive to sampling of habitat types, and densities should be used wherever possible.
|Number of pages||9|
|Journal||Australian Journal of Ecology|
|Publication status||Published - 1990|