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Spatial variation in drivers of bird species richness. Jones, Kingsford*,1, Hansen, Andrew1, 1 Montana State University, Bozeman, Montana ABSTRACT- Landscape-level analyses of drivers of species richness have historically been limited by the relatively course scale of available data, and confounded by spatial variation in predictors of diversity. Limiting our research to the data-rich forested portions of western Montana, we investigated variation in predictors across the region, and within ecological subsections. We used mixed models to determine strength of linear relations of biotic and abiotic predictors of diversity while controlling for spatial autocorrelation. Consistently, elevation was negatively correlated with bird richness, while June and July temperature indices were positively correlated. Richness was higher in the lower, wetter ecosections, and within these sections the interaction of temperature and precipitation was significant. The influence of vegetation type and structure appeared to vary randomly across the landscape. The resolution of the data used to build our mixed models allowed us to examine variation in trends of drivers of diversity at a finer scale than was previously possible. Such models can serve as important tools for conservation planning and for advancing biogeographic theory. KEY WORDS: biodiversity, landscape ecology, mixed models |