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Habitat relationships between a sympatric mule and white-tailed deer population in South-Central Texas

Josh T. Avey

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Abstract

My objective was to determine landscape and ecological parameters that serve as spatial separators between desert mule deer and white-tailed deer. My goal was to develop recommendations that landowners could use to manage habitats for both deer species. \n \nI separated the analysis into two separate chapters. Chapter II investigates landscape separation considering ecological parameters that serve as spatial separators between desert mule deer and white-tailed deer. The predictions I tested were as follows: (1) mule deer use steeper slopes than white-tailed deer; (2) desert mule deer occur at higher elevations than white-tailed deer; (3) there were no differences between topography selected by desert mule deer and white-tailed deer; and (4) habitats used b> white-tailed deer had greater shrub densities (plants >1 m) than habitats used by desert mule deer. \n \nChapter III considers landscape separation based on signature classifications of satellite imagery. I tested two predictions with classified data. First, areas with different vegetation structure will project different pixel signatures. Second, habitat used by desert mule deer will possess different pixel signatures than the habitat used by white- tailed deer.

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My objective was to determine landscape and ecological parameters that serve as spatial separators between desert mule deer and white-tailed deer. My goal was to develop recommendations that landowners could use to manage habitats for both deer species. \n \nI separated the analysis into two separate chapters. Chapter II investigates landscape separation considering ecological parameters that serve as spatial separators between desert mule deer and white-tailed deer. The predictions I tested were as follows: (1) mule deer use steeper slopes than white-tailed deer; (2) desert mule deer occur at higher elevations than white-tailed deer; (3) there were no differences between topography selected by desert mule deer and white-tailed deer; and (4) habitats used b> white-tailed deer had greater shrub densities (plants >1 m) than habitats used by desert mule deer. \n \nChapter III considers landscape separation based on signature classifications of satellite imagery. I tested two predictions with classified data. First, areas with different vegetation structure will project different pixel signatures. Second, habitat used by desert mule deer will possess different pixel signatures than the habitat used by white- tailed deer.

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Available abstract

My objective was to determine landscape and ecological parameters that serve as spatial separators between desert mule deer and white-tailed deer. My goal was to develop recommendations that landowners could use to manage habitats for both deer species. \n \nI separated the analysis into two separate chapters. Chapter II investigates landscape separation considering ecological parameters that serve as spatial separators between desert mule deer and white-tailed deer. The predictions I tested were as follows: (1) mule deer use steeper slopes than white-tailed deer; (2) desert mule deer occur at higher elevations than white-tailed deer; (3) there were no differences between topography selected by desert mule deer and white-tailed deer; and (4) habitats used b> white-tailed deer had greater shrub densities (plants >1 m) than habitats used by desert mule deer. \n \nChapter III considers landscape separation based on signature classifications of satellite imagery. I tested two predictions with classified data. First, areas with different vegetation structure will project different pixel signatures. Second, habitat used by desert mule deer will possess different pixel signatures than the habitat used by white- tailed deer.

Key concepts: Sympatric speciation, Habitat, Geography, White (mutation), Population, Ecology, Biology, Demography

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Habitat relationships between a sympatric mule and white-tailed deer population in South-Central Texas — Research Paper | ScholarLens