The Development of Automated Detection Techniques for Passive Acoustic Monitoring as a Tool for Studying Beaked Whale Distribution and Habitat Preferences in the California Current Ecosystem

The objectives of this research were to test available automated detection methods for passive acoustic monitoring and integrate the best available method into standard marine mammal monitoring protocols for ship based surveys.;The goal of the first chapter was to evaluate the performance and utility of PAMGUARD 1.0 Core software for use in automated detection of marine mammal acoustic signals during towed array surveys. Three different detector configurations of PAMGUARD were compared. These automated detection algorithms were evaluated by comparing them to the results of manual detections made by an experienced bio-acoustician (author TMY). This study provides the first detailed comparisons of PAMGUARD automated detection algorithms to manual detection methods. The results of these comparisons clearly illustrate the utility of automated detection methods for odontocete species. Results of this work showed that the majority of whistles and click events can be reliably detected using PAMGUARD software.;The second chapter moves beyond automated detection to examine and test automated classification algorithms for beaked whale species. Beaked whales are notoriously elusive and difficult to study, especially using visual survey methods. The purpose of the second chapter was to test, validate, and compare algorithms for detection of beaked whales in acoustic line-transect survey data.;Using data collected at sea from the PAMGUARD classifier developed in Chapter 2 it was possible to measure the clicks from visually verified Baird's beaked whale encounters and use this data to develop classifiers that could discriminate Baird's beaked whales from other beaked whale species in future work.;Echolocation clicks from Baird's beaked whales, Berardius bairdii, were recorded during combined visual and acoustic shipboard surveys of cetacean populations in the California Current Ecosystem (CCE) and with autonomous, long-term recorders at four different sites in the Southern California Bight (SCB). The preliminary measurement of the visually validated Baird's beaked whale echolocation signals recorded from the ship-based towed array were used as a basis for identifying Baird's signals in the seafloor-mounted autonomous recorder data.;The passive acoustic detection algorithms for beaked whales developed using data from Chapters 2 and 3 were field tested during a three year period to test the reliability of acoustic beaked whale monitoring techniques and to use these methods to describe beaked whale habitat in the SCB. In 2009 and 2010, PAM methods using towed hydrophone arrays were tested. These methods proved highly effective for real-time detection of beaked whales in the SCB and were subsequently implemented in 2011 to successfully detect and track beaked whales during the ongoing Southern California Behavioral Response Study (SOCAL-BRS).;The final step in this research was to utilize the passive acoustic detection techniques developed herin to predictively model beaked whale habitat use and preferences in the CCE. This chapter uses a multifaceted approach to model beaked whale encounter rates in the CCE. Beaked whale acoustic encounters are utilized to inform Generalized Additive Models (GAMs) of encounter rate for beaked whales in the CCE and compare these to visual based models. Acoustic and visual based models were independently developed for a small beaked whale group and Baird's beaked whales. Two models were evaluated for visual and acoustic encounters, one that also included Beaufort sea state as a predictor variable in addition to those listed and one that did not include Beaufort sea state. (Abstract shortened by UMI.).