Thc development and application of predictive models which assess the probability of prehistoric archaeological sites occurring across the landscape have greatly increased in reccnt years (Allen et al. 1 990 ; Brandt et al. 1 992; Carr 1 985 ; Judge and Sebastian I ns ; Kohler and Parker 1 986 ; Kvamme 1 983 , 1 986 . i 990, 1 992 ; Ncumann 1 992; Phi llips and Duncan 1 993) . Thc driving force behind tbis growth in predictive model development has bcen the need for the identification, protection, and management of increasingly threatened cultural resources in a cost-e ffective and useful manner. The basis of such models is that the spatial distribution of cultural remains, which are often represented as archaeological sites, is the result of human decision­ making activities within the possibilities and conditions presented by the environment. The development of most contemporary predictive models involves the considcration of multiple thematic layers of inforn1ation relating to past environmental and/or cultural conditions . Interpreting the interplay between these multiple thematic layers and their various pennutations may reveal identifiable patterns that reflect actual human behavioral patterns and choices (Kincaid I 9��) .