Models on the distribution of animals are invaluable in understanding how individuals and, ultimately, populations respond to ecological processes. Rarely, have they been applied to conservation issues at a landscape level. We capitalized on the distribution of a previously unavailable novel food resource, found at the juxtaposition of urban and wildland areas, to test the generality of ideal-free distribution (IFD) models using a mammalian carnivore, the black bear (Ursus americanus). The primary question we addressed was whether an increase in the prevalence of individuals in a geographical region reflects a population increase or a landscape level redistribution. Combining spatial and temporal data sets with empirically obtained information spanning 12–15 years, we contrasted demographic, life-history, and reproductive parameters between individuals at urban–wildland interface (experimental) and wildland (control) areas at the interface of the Sierra Nevada Range and Great Basin Desert in western North America. Bears were expected to respond to natural versus artificially clumped resources according to an IFD model. Evidence only partially supported this idea because individuals in urban areas had densities 3 times the historical values from the same area, sex ratios were 4.25 times more skewed toward males, bears had 30% larger body mass, home ranges were reduced by 90% for males and 70% for females, and bears entered dens significantly later than wildland conspecifics. However, females in urban-interface areas gave birth to 3 times the number of cubs, although only half as many dispersed successfully relative to wildland females. Further, urban-interface females had a higher proportion (0.57) of potential reproductive years, in which they had young, compared with wildland females (0.29). We present evidence suggesting that bears in Nevada and in the Lake Tahoe basin conform primarily to an ideal-despotic distribution model. Our findings on population reallocation, rather than demographic increase, reemphasize how knowledge about correlates of individual performance and distribution over time helps to understand the extent to which humans change ecosystems, whether their actions are intentional or not.