Effective management of small expanding populations is aided by the availability of reliable estimates of distribution, as well as by demographic characteristics such as population density, genetic diversity and sex ratio. The range of the black bear Ursus americanus in the southeastern United States is expanding to include areas from which it has been extirpated for more than a century. Lack of baseline demographic data in recently reoccupied areas leaves little information on which to base emerging management needs.

Predictive logistic regression models are commonly used to make informed decisions related to wildlife management and conservation, such as predicting favourable wildlife habitat for land conservation objectives and predicting vital rates for use in population models. Frequently, models are developed for use in the same population from which sample data were obtained, and thus, they are intended for internal use within the same population. Before predictions from logistic regression models are used to make management decisions, predictive ability should be validated.

Many environmental patterns that may have profound effects on wildlife communities occur at the landscape scale, e.g. habitat fragmentation, human demography and distribution of various resources. In order to understand how alterations of such patterns could influence e.g. wildlife species occurrences and community composition, it is important to first study these relationships empirically and at the appropriate scale. We surveyed the wildlife community in a boreal ecosystem in central Sweden using pellet group counts, while walking ‘‘wildlife triangles’’.