GPS radio-collars for spatial dynamics research

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Understanding how organisms use spatially heterogeneous resources and how they live, reproduce, disperse and interact in landscape mosaics have long been goals in ecology. I am proposing to extend my field studies of food-web interactions in the Serengeti ecosystem to test predictive models of movement and spatial interactions by both herbivores and carnivores. In the longer term, I plan to imbed these movement models into spatially-explicit models of food-web interactions to test the impact of adaptive movement behavior on population dynamics and viability of both predators and prey. The only realistic way to gather movement data of this sort on highly mobile, large organisms is to use GPS radio-transmitters. This instrumentation uses satellite global positioning system technology to precisely triangulate spatial position of organisms at frequent intervals. This spatial information is stored for extended periods in a memory bank in the collar, then the information is downloaded either using a remote telemetry link or by retrieving the collar from the study animal. Statistical prediction of movement trajectories will be based on state-space movement models, using mixtures of biased random walks, the parameters of which are estimated using Monte Carlo Markov Chain methods which my research group helped pioneer. Each alternate hypothesis identifies a different mix of parameters incorporated into the movement model, with information-theoretic methods used to assess competing models. In each case, data gathered using GPS radio-collars will be used to parameterize biased random walk models (turn angles and step length distributions), with spatially explicit parameters imposed by local range conditions, habitat cover, and local herbivore or carnivore densities.