Visualizing Wildlife Conservation and Development in Southern Africa: A Multi-Optic Approach

Part I of the dissertation engages a long-standing debate about community-based natural resource management (CBNRM), which together with protected areas has been one the core conservation strategies across countries in southern Africa. Since the advent of CBNRM in the mid-1980s, scholars and practitioners have sought to explain the uneven performance of CBNRM programs. Most CBNRM assessments examine the underlying principles of community-based conservation, the local social and ecological contexts, and connections with larger political and historical patterns. I argue that analysis of the potential and pitfalls of CBNRM also requires an understanding of the institutional history and internal dynamics of projects that implement CBNRM reforms. Drawing upon theory and methods from development ethnography and public policy, I examine the rise and fall of CONASA, a second-generation CBNRM project in Zambia that operated in the early 2000s. CONASA was constituted from a merger of organizations and discourses to create continuity with previous projects. Its ambitious suite of activities included support for household livelihoods, community-based resource management, policy analysis, advocacy, and conservation enterprises at local, national, and transboundary levels. While individual activities were largely successful, CONASA's hybrid origins and logframe-centric management created fissures between its holistic design and daily operations, and hindered its ability to develop a broader narrative and maintain key alliances. This study illustrates the importance of understanding the interplay between project design and operational context in order to fully appreciate the possibilities and limitations of project-mode conservation.;While a ground's eye view highlights context and nuances of process, the bird's eye view reveals pattern and emergent behavior across scales. In Part II, I present a new spatial modeling method for location data from orbiting satellites to analyze the spatiotemporal patterns in movement data. Advances in GPS technology have created both opportunities in ecology as well as a need for analytical tools that can deal with the growing volume of data and ancillary variables associated with each location. Time Local Convex Hull (T-LoCoH), is a home range construction algorithm that incorporates time into the construction and aggregation of local kernels. Time is integrated with Euclidean space using an adaptive scaling of the individual's characteristic velocity, enabling the construction of utilization distributions that capture temporal partitions of space as well as contours that differentiate internal space based on movement phase and time-use metrics. I test T-LoCoH against a simulated dataset and provide illustrative examples from a GPS dataset from springbok in Namibia. The incorporation of time into home range construction expands the concept of utilization distributions beyond the traditional density gradient to spatial models of movement and time, opening the door to new applications in movement ecology.;Hulls also provide a means for characterization of the interactions between individuals, which are central to many aspects of population biology, including competition, predation, reproduction, resource optimization, and disease transmission. Classic measures of association are based on the intersection of static home range estimates and counts of matched locations, but the advances in GPS technology have created new possibilities for characterizing dynamic spatiotemporal properties of association. Hull metrics of association for both spatially and temporally overlapping hulls reveal the intensity of interaction both in raw terms as well as corrected for revisitation, as well as time lags. Similarly, a metric for the proportion of enclosed points constructed from the combined set of locations reveal the distribution of sharing across space and time for the entire time period. Illustrative examples of the methodology are provided using elephant tracking data from Tembe Elephant Park in South Africa. Plotting association metrics on a map, over time, and against other hull properties reveal novel patterns that can be basis for further study. Local hulls offer a promising approach for characterizing the spatiotemporal properties of association and exploring their covariates. (Abstract shortened by UMI.).