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Risso's and Pacific white-sided dolphins in the Southern California Bight : using echolocation clicks to study dolphin ecology

Abstract

This dissertation examines the efficacy of using passive acoustic monitoring of dolphin echolocation clicks to study ecological questions about spatial and temporal distribution patterns and the influence of environmental variability on dolphin activity. First, the groundwork is laid by examining echolocation clicks recorded from concurrent visual and acoustic surveys and testing whether species-specific features exist in the spectral content of clicks recorded in the presence of five delphinid species: short-beaked common dolphins (Delphinus delphis), long- beaked common dolphins (Delphinus capensis), bottlenose dolphins (Tursiops truncatus), Risso's dolphins (Grampus griseus), and Pacific white-sided dolphins (Lagenorhynchus obliquidens). Unique spectral banding patterns are discovered only for Risso's and Pacific white-sided dolphins and two distinct click types are found for Pacific white-sided dolphins. Next, autonomous recordings from six sites are analyzed for the presence of Pacific white-sided and Risso's dolphin click bouts and diel, seasonal, and interannual variability in click activity are described. Risso's dolphins are more vocally active during the night which I suggest is related to foraging on diel vertically migrating squid. Seasonal and interannual variability in Risso's dolphin call activity are high. Comparisons of diel, seasonal and spatial variability of the two Pacific white-sided click types are made and the two click types are shown to exhibit differences in usage patterns. This comparison reveals a southern and northern distribution pattern between the click types adding support to the hypothesis that the two click types represent the two morphologically and genetically distinct populations which overlap in the study area. Finally, the ability to predict variability in click activity is examined with respect to the environment by building generalized additive models. Remotely-sensed environmental variables are modeled with respect to current time and time-lagged data to examine questions about the underlying oceanographic processes which may lead to dolphin occurrence. The inclusion of timelagged environmental data can improve predictive models and allows a realistic time frame for conservation and management mitigation efforts. Passive acoustic monitoring of echolocation clicks has revealed patterns in diel activity and seasonal movements of Risso's and Pacific white-sided dolphins and shows promise for improved predictive habitat models

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