| It has long been recognized that organisms exist in environments peculiar to taxa. Climate is thought to be of primary importance in determining the natural geographic distribution of species. Growing concern over climate change and its potential consequences to biodiversity has prompted the rapid development of numerous analytical techniques to correlate quantifiable environmental characteristics with the known location of species. Ecological niche modelling focuses primarily on determining the dimensions of the niche space of species as a means of predicting their geographic distributions. Recently, many alarming predictions have emerged ranging from the mass extinction of taxa over the next century, to, at the very least, their partial redistribution. Regardless of consequence, however, these predictions indicate a deep and gnawing uncertainty.;A central assumption underpinning research into the potential future habitat of terrestrial biota is that species are presently in equilibrium with their environments and that quantitative climate models adequately represent the distribution of species. The second study examines the effect of the assumption of species/climate equilibrium upon projected distributions using different historic and future data sets. Distributional models were developed for 24 Salix (willow) species occurring in the province of Ontario, Canada, using three historical climate data sets. Although historical data very accurately represented the distributions of willows, the inherent variability within the models of species based on different periods greatly influenced the direction and magnitude of projected distributional change. Even large-scale models of the climatic niche dimensions of species are temporally variable. These findings imply that many of the recent predictions of the potential consequences of climate change to terrestrial biota may be unrealistic.;Keywords: Salix (willow), climate change, continuous/discontinuous data, BIOCLIM, logistic regression, model validation, species/climate equilibrium, uncertainty.;To explore some of the fundamental sources of uncertainty with respect to niche modelling two studies were undertaken. In the first, simple correlative models were developed for Salix (willow) species occurring in Ontario, Canada, to determine the algorithmic sensitivity of logistic regression to extreme cases of distributional and environmental data sets. Provincial distribution models were developed for 30 willow species to examine (i) the predictive ability of logistic regression analysis, and (ii) the effects of using different distributional and environmental data sets. Two original measures of model accuracy and over-prediction were employed and evaluated using independent data. Models based on unique combinations of monthly climate data, rather than a fixed selection of annual and seasonal variables, predicted distributions most accurately for all species. Models based on a fixed set of variables, while generating the highest average probabilities of occurrence for certain species with limited ranges, resulted in the greatest under- and overestimates of willow distributions. Regardless of distributional and environmental data input, no algorithm maximized model performance for all species. Individual species models require individual approaches; i.e., the variable selection technique, the set of environmental factors used as predictors, and the nature of species distributional data must be carefully matched to the intended application. |
