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Investigation of the spatial distribution of biodiversity among communities or across habitats (beta diversity) is often hampered by a scarcity of biological survey data. This is particularly the case in communities of high floristic diversity, such as the subtropical rainforests of eastern Australia. In contrast, there is excellent spatial coverage of environmental data for this region, such as geology, elevation and climate data. Generalized dissimilarity modelling was used in this study to combine biological survey data and environmental data grids for the investigation and prediction of floristic turnover among vegetation communities at a regional scale. Generalized dissimilarity modelling identified four environmental predictors of floristic turnover in the study region, all of which are linked with moisture stress: radiation of the driest quarter, precipitation of the driest period of the year, slope and aspect. Ten land classes representing largely homogeneous floristics and environment were identified and mapped for the region, allowing significantly greater discrimination than currently available mapping for this region. With increases in evapotranspiration and moisture stress predicted as a result of climate change, these results may allow future floristic shifts to be assessed in relation to regional-scale gradients in floristic turnover. [ABSTRACT FROM AUTHOR]