Developing a passive acoustic monitoring network for harbor porpoise in California

Assessing the abundance of and trends in whale, dolphin, and porpoise (cetacean) populations using traditional visual methods can be challenging due primarily to their limited availability at the surface of the ocean. As a result, researchers are increasingly interested in incorporating non-visual a...

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Bibliographic Details
Main Author: Jacobson, Eiren Kate
Format: Doctoral or Postdoctoral Thesis
Language:English
Published: eScholarship, University of California 2017
Subjects:
Online Access:http://www.escholarship.org/uc/item/9dc5108w
Description
Summary:Assessing the abundance of and trends in whale, dolphin, and porpoise (cetacean) populations using traditional visual methods can be challenging due primarily to their limited availability at the surface of the ocean. As a result, researchers are increasingly interested in incorporating non-visual and remote observations to improve cetacean population assessments. Passive acoustic monitoring (PAM) can complement or replace visual surveys for cetaceans that produce echolocation clicks, whistles, and other vocalizations. My doctoral dissertation is focused on developing methods to improve PAM of cetaceans. I used the Monterey Bay population of harbor porpoise (Phocoena phocoena) as a case study for methods development. In Chapter 2, I used passive acoustic data to document that harbor porpoises avoid bottlenose dolphins (Tursiops truncatus) in nearshore Monterey Bay. In Chapter 3, I investigated whether different passive acoustic instruments could be used to monitor harbor porpoise. I recorded harbor porpoise echolocation clicks simultaneously on two different passive acoustic instruments and compared the number and peak frequency of echolocation signals recorded on the two instruments. I found that the number of echolocation clicks was highly correlated between instruments but that the peak frequency of echolocation clicks was not well-correlated, suggesting that some instruments may not be capable of discriminating harbor porpoise echolocation clicks in regions where multiple species with similar echolocation signals are present. In Chapter 4, I used paired visual and passive acoustic surveys to estimate the effective detection area of the passive acoustic sensors in a Bayesian framework. This approach resulted in a posterior distribution of the effective detection area that was consistent with previously published values. In Chapter 5, I used aerial survey and passive acoustic data in a simulation framework to investigate the statistical power of different passive acoustic network designs and hypothetical changes in harbor porpoise abundance. As a whole, this dissertation used an applied approach to methods development to advance the use of PAM for cetaceans.