Over the past 15 years the endangered eastern timber wolf (Canis lupus lycaon) has been slowly recolonizing northern Wisconsin and, more recently, upper Michigan, largely by dispersing from Minnesota (where it is listed as threatened). We have used geographic information systems (GISs) and spatial radiocollar data on recolonizing wolves in northern Wisconsin to assess the importance of factors in defining favorable wolf habitat. We built a multiple logistic regression model applied to the northern Great Lakes states to estimate the amount and spatial distribution of favorable wolf habitat at the regional landscape scale. Our results suggest that areas with high probability of favorable habitat are more extensive than previously estimated in the northern Great Lake States. Several variables were significant in comparing new pack areas in Wisconsin to nonpack areas, including land ownership class, land cover type, road density, human population, and spatial landscape indices such as fractal dimension (land cover patch boundary complexity), land cover type contagion, landscape diversity, and landscape dominance. Road density and fractal dimension were the most important predictor variables in the logistic regression models. The results indicate that public forest land and private industrial forest land are both important in managing for a broad‐ranging animal such as the wolf. Our data portray favorable habitat that is highly fragmented along development corridors in northern Wisconsin, which may be responsible for the slow growth of the wolf population. Upper Michigan, which is just beginning to be colonized by wolves, has very large, contiguous areas of likely habitat approaching the importance of those in northeastern Minnesota. If continuing development or wolf control restrict dispersing wolves from moving from Minnesota to Wisconsin, and Wisconsin habitat becomes more marginal through further fragmentation, Michigan has the potential to maintain a significant wolf population independent of Minnesota and serve as a source population for Wisconsin. However, a simple island/corridor model of wolf habitat in Wisconsin does not seem to apply. Wolves apparently move throughout the landscape, across many unfavorable areas, but establishment success is restricted to higher quality habitat. Source‐sink dynamics may be operating here, and they suggest that reduction of the Minnesota population in the near term may affect recovery in Wisconsin and Michigan. Our analysis is an example of use of long‐term monitoring data and large‐scale cross‐boundary regional analysis that must be done to solve complex spatial questions in resource management and conservation.

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Many carnivore populations escaped extinction during the twentieth century as a result of legal protections, habitat restoration, and changes in public attitudes. However, encounters between carnivores, livestock, and humans are increasing in some areas, raising concerns about the costs of carnivore conservation. We present a method to predict sites of human-carnivore conflicts regionally, using as an example the mixed forest-agriculture landscapes of Wisconsin and Minnesota (U.S.A.). We used a matched-pair analysis of 17 landscape variables in a geographic information system to discriminate affected areas from unaffected areas at two spatial scales (townships and farms). Wolves (Canis lupus) selectively preyed on livestock in townships with high proportions of pasture and high densities of deer (Odocoileus virginianus) combined with low proportions of crop lands, coniferous forest, herbaceous wetlands, and open water. These variables plus road density and farm size also appeared to predict risk for individual farms when we considered Minnesota alone. In Wisconsin only, farm size, crop lands, and road density were associated with the risk of wolf attack on livestock. At the level of townships, we generated two state-wide maps to predict the extent and location of future predation on livestock. Our approach can be applied wherever spatial data are available on sites of conflict between wildlife and humans. Predicción de Conflicto Humano-Carnívoro: un Modelo Espacial Basado en 25 Años de Datos de Depredación de Ganado por Lobos Resumen: Muchas poblaciones de carnívoros lograron evitar la extinción durante el siglo veinte debido a protecciones legales, restauración de hábitat y cambios en las actitudes del público. Sin embargo, los encuentros entre carnívoros, ganado y humanos están incrementando en algunasáreas, lo cual es causa de preocupación en cuanto a los costos de la conservación de carnívoros. Presentamos un método para predecir los sitios de conflictos humanos -carnívoro a nivel regional, utilizando como ejemplo los paisajes mixtos de bosques-agricultura de Wisconsin y Minnesota (E. U. A.). Utilizamos un análisis apareado de 17 variables del paisaje en un sistema § §Current address: Living Landscapes Program, Wildlife Conservation Society, Treves et al. Predicting Human-Carnivore Conflict 115de información geográfica para discriminaráreas afectadas deáreas no afectadas a dos escalas espaciales (municipios y establecimientos). Los lobos (Canis lupus) depredaron selectivamente el ganado en municipios con proporciones altas de pasto y altas densidades de venado (Odocoileus virginianus) combinadas con proporciones bajas de terrenos agrícolas bosques de coníferas, humedales herbáceos y cuerpos de agua abiertos. Estas variables, junto con la densidad de caminos y el tamaño del establecimiento, permitieron además predecir el riesgo para establecimientos individuales cuando analizamos solamente el estado de Minnesota. En Wisconsin, solamente el tamaño del establecimiento, los terrenos agrícolas y la densidad de cam...

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