Data from more than 900 vegetation plots surveyed in the evergreen shrublands of southern California were used to develop predictions of the distributions of eight dominant shrub species for a 3880 km2 region. The predictions, based on classification tree (CT) models, were validated using independent field data collected during a vegetation survey conducted in the 1930s. Presence and absence were correctly predicted an average of 75% of the time for the eight species. At the same time, these models minimized false positives, so that presence was predicted in the correct proportion of the cases for most species. The areal proportion of the landscape on which the species were predicted to occur was in the same rank order, and of the same magnitude, as their frequency (proportion of plots in which they occurred) within the field data sets. Predictive maps of species presence were overlaid and combined with an existing regional vegetation map. The shrub species ‘assemblages’ that resulted from this procedure had analogs with vegetation series defined using field data in previous studies. The resulting multiple species map will be used in a landscape simulation model of fire disturbance and succession.
Abbreviations: CT = Classification tree; CCR = Correct classification rate; PPP = Positive predictive power; TMI = Topographic moisture index; USDA = United States Department of Agriculture; VTM = Vegetation type map.
Nomenclature: Hickman (1993).
