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Spatiotemporal Patterns and Drivers of Surface Water Quality and Landscape Change in a Semi-Arid, Southern African Savanna

The savannas of southern Africa are a highly variable and globally-important biome supporting rapidly-expanding human populations, along with one of the greatest concentrations of wildlife on the continent. Savannas occupy a fifth of the earth's land surface, yet despite their ecological and economic significance, understanding of the complex couplings and feedbacks that drive spatiotemporal patterns of change are lacking. In Chapter 1 of my dissertation, I discuss some of the different theoretical frameworks used to understand complex and dynamic changes in savanna structure and composition. In Chapter 2, I evaluate spatial drivers of water quality declines in the Chobe River using spatiotemporal and geostatistical modeling of time series data collected along a transect spanning a mosaic of protected, urban, and developing urban land use. Chapter 3 explores the complex couplings and feedbacks that drive spatiotemporal patterns of land cover (LC) change across the Chobe District, with a particular focus on climate, fire, herbivory, and anthropogenic disturbance. In Chapter 4, I evaluated the utility of Distance sampling methods to: 1) derive seasonal fecal loading estimates in national park and unprotected land; 2) provide a simple, standardized method to estimate riparian fecal loading for use in distributed hydrological water quality models; 3) answer questions about complex drivers and patterns of water quality variability in a semi-arid southern African river system. Together, these findings have important implications to land use planning and water conservation in southern Africa's dryland savanna ecosystems. / Ph. D.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/81462
Date08 July 2016
CreatorsFox, John Tyler
ContributorsFisheries and Wildlife Science, Alexander, Kathleen A., Prisley, Stephen P., Frimpong, Emmanuel A., Godrej, Adil N.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeDissertation
FormatETD, application/pdf, application/vnd.openxmlformats-officedocument.wordprocessingml.document
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/

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