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The influence of habitat quality and population density on occupancy dynamics may surpass that of traditional metrics of area and isolation, but often this is not considered explicitly in studies of spatially structured populations. In landscapes that are not easily characterized as binary habitat/non-habitat (e.g. variegated landscapes), this influence may be even more important and occur at both local and landscape levels. It follows that occupancy dynamics may be driven by disparate processes depending on how extinction or colonization relate to habitat quality and population density. We examined the relative influence of area, structural isolation, habitat quality, local population density, and neighborhood population density (i.e. population density in the landscape around a site) on the probability of extinction and colonization of snowshoe hare Lepus americanus across an expansive forest mosaic landscape (encompassing the northern third of Idaho). Habitat quality and population density were highly influential in determining extinction and colonization, whereas patch area and isolation were much less important. Sites with heavier vegetative cover at the site or landscape-level were more likely to be colonized and less likely to go extinct, and sites with greater local population density in the previous time step had lower probability of extinction. Sites embedded in high density neighborhoods also were less likely to go extinct, but not more likely to be colonized. We found a significant interaction between local and neighborhood population density on extinction in 1 yr, suggesting that the strength of demographic rescue may vary dependent on local site densities. Our results add to a growing literature showing that factors outside of structural metrics of area and isolation are important drivers of occupancy dynamics. Given the multi-scaled influence of habitat quality and population density on occupancy dynamics, our work also indicates that research on snowshoe hare must extend beyond simply assessing local factors to understand the spatial dynamics of populations.