Publications by authors named "Adam D Baer"
Understanding the influences of forest management practices on wildfire severity is critical in fire-prone ecosystems of the western United States. Newly available geospatial data sets characterizing vegetation, fuels, topography, and burn severity offer new opportunities for studying fuel treatment effectiveness at regional to national scales. In this study, we used ordinary least-squares (OLS) regression and sequential autoregression (SAR) to analyze fuel treatment effects on burn severity for three recent wildfires: the Camp 32 fire in western Montana, the School fire in southeastern Washington, and the Warm fire in northern Arizona.
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- Disease maps are vital in health sciences for tracking infectious diseases but often rely on limited data samples.
- The study compared various spatial modeling techniques for predicting the ranges of two tick-borne pathogens, highlighting the role of spatial autocorrelation and spatial heterogeneity in improving prediction accuracy.
- Results showed that models integrating these spatial factors significantly outperformed traditional logistic regression, with unique methods favoring each pathogen's distribution characteristics.