Dissertation (Ph.D.)--Auburn University, 2006. / Abstract. Includes bibliographic references.

Sound production is a widespread phenomenon in fishes; however, the importance of acoustic signals and their potential to influence reproduction has not been determined. This dissertation examines fish acoustic courtship signals to investigate whether sound has a role in reproductive success. The pre-spawning sounds of several fishes were recorded and analyzed. The male advertisement call of two species of Belizean toadfish, Sanopus astrifer and Batrachoides gilberti, were found to significantly differ. These data, coupled with data in the literature suggest an influence of habitat characteristics on the calling behavior of toadfishes. Additionally, acoustic playback experiments were employed to investigate the role of male courtship sounds in the Malawi cichlid species, Tramitichromis intermedius. Playback results indicated that male sounds may initiate egg-laying behavior in females, but may not be behaviorally relevant to conspecific males. A discussion of confounding factors in aquarium playback experiments is presented. Technical aspects of fish sound recording, playback, and analysis were also examined to provide information for future fish bioacoustics studies. It was determined that digital cameras are a useful method of recording fish sounds to describe metric characteristics; however, temporal parameters are more accurately captured by hydrophones, which are optimal for use in scientific description of fish sounds. Underwater speakers commonly used in fish playback experiments were tested for fidelity when producing a low-frequency pulsed fish sound. The Electro-Voice UW30 speaker was found to perform the best playback at low sound pressure levels (<120 dB re 1 μPa) and at short distances (< 15 cm). The Clark Synthesis AQ339 speaker performed the best playback at higher sound pressure levels (>120 dB re 1 μPa) and at greater distances than the UW30. Many fish sounds have been described in the literature; however, there is no standardization of sample size used in species descriptions. A method is presented that can be used to estimate the level of inclusiveness of sound variability in sound descriptions, and to approximate sufficient sample sizes of recordings. The courtship calls of Dascyllus albisella and Batrachoides gilberti were examined to illustrate this method and to provide a benchmark for future sound descriptions.

Red grouper (Epinephelus morio) are long-lived, commercially important, soniferous fish belonging to the family Epinephelidae. Found throughout the western North Atlantic and Gulf of Mexico, they are protogynous hermaphrodites, and peak spawning occurs from March through May. Unlike many grouper species, red grouper do not form large spawning aggregations; rather, they form small polygynous groups, and remain in relatively close proximity to rocky depressions excavated in the sandy bottom by males. This excavation activity creates structure and habitat for a wide variety of species, and as a result, red grouper are a keystone species on the West Florida Shelf. While extensive life-history information exists, largely from fishery catches, little is known about sound production or behavior of red grouper in their natural environment. Passive acoustic recordings combined with simultaneous digital video recordings were used to investigate sonic activity and behavior of red grouper on the Steamboat Lumps and Madison-Swanson marine reserves on the West Florida Shelf. Red grouper were found to produce a unique series of low-frequency (180 Hz peak) pulses, consisting of 1-4 brief (0.15 s) broadband pulses and a 0.5-2 s down-swept "buzz" (i.e., short call); occasionally these were followed by a rapid series of 10-50 broadband pulses (i.e., pulse train). Sound production was observed throughout the day and night, but most sounds occurred between sunrise and sunset, with a noticeable increase during late afternoon. Behaviors associated with sound production included territorial displays and courtship interactions, indicating that sound production is likely related to spawning activity. Thus, monitoring red grouper using passive acoustics could be an effective tool in fisheries management and conservation efforts.

Some fish produce sounds for a variety of reasons, such as to find mates, defend their territory, or maintain cohesion within their group. These sounds could be used to non-intrusively detect the presence of fish and potentially to estimate their number (or density) over large areas and long time periods. However, many fish sounds have not yet been associated to specific species, which limits the usefulness of this approach. While recording fish sounds in tanks is reasonably straightforward, it presents several problems: many fish do not produce sounds in captivity or their behavior and sound production is altered significantly, and the complex acoustic propagation conditions in tanks often leads to distorted measurements. The work presented in this thesis aims to address these issues by providing methodologies to record, detect, and identify species-specific fish sounds in the wild. A set of hardware and software solutions are developed to simultaneously record fish sounds, acoustically localize the fish in three-dimensions, and record video to identify the fish and observe their behavior. Three platforms have been developed and tested in the field. The first platform, referred to as the large array, is composed of six hydrophones connected to an AMAR acoustic recorder and two open-source autonomous video cameras (FishCams) that were developed during this thesis. These instruments are secured to a PVC frame of dimension 2 m x 2 m x 3 m that can be transported and assembled in the field. The hydrophone configuration for this array was defined using a simulated annealing optimization approach that minimized localization uncertainties. This array provides the largest field of view and most accurate acoustic localization, and is well suited to long-term deployments (weeks). The second platform, referred to as the mini array, uses a single FishCam and four hydrophones connected to a SoundTrap acoustic recorder on a one cubic meter PVC frame; this array can be deployed more easily in constrained locations or on rough/uneven seabeds. The third platform, referred to as the mobile array, consists of four hydrophones connected to a SoundTrap recorder and mounted on a tethered Trident underwater drone with built-in video, allowing remote control and real-time positioning in response to observed fish presence, rather than long-term deployments as for the large and mini arrays. For each array, acoustic localization is performed by measuring time-difference of arrivals between hydrophones and estimating the sound-source location using linearized (for the large array) or non-linear (for the mini and mobile arrays) inversion. Fish sounds are automatically detected and localized in three dimensions, and sounds localized within the field of view of the camera(s) are assigned to a fish species by manually reviewing the video recordings. The three platforms were deployed at four locations off the East coast of Vancouver Island, British Columbia, Canada, and allowed the identification of sounds from quillback rockfish (Sebastes maliger), copper rockfish (Sebastes caurinus), and lingcod (Ophiodon elongatus), species that had not been documented previously to produce sounds. While each platform developed during this thesis has its own set of advantages and limitations, using them in coordination helps identify fish sounds over different habitats and with various budget and logistical constraints. In an effort to make passive acoustics a more viable way to monitor fish in the wild, this thesis also investigates the use of automatic detection and classification algorithms to efficiently find fish sounds in large passive acoustic datasets. The proposed approach detects acoustic transients using a measure of spectrogram variance and classifies them as “noise” or “fish sounds” using a binary classifier. Five different classification algorithms were trained and evaluated on a dataset of more than 96,000 manually annotated examples of fish sounds and noise from five locations off Vancouver Island. The classification algorithm that performed best (random forest) has an Fscore of 0.84 (Precision = 0.82,Recall = 0.86) on the test dataset. The analysis of 2.5 months of acoustic data collected in a rockfish conservation area off Vancouver Island shows that the proposed detector can be used to efficiently explore large datasets, formulate hypotheses, and help answer practical conservation questions. / Graduate

The goal of development of sound database for marine fishes in Taiwan not only preserves data, but also wants to provide a common ground of data sharing to increase the efficiency for the study of fish behavior, automatic recognition, localization, and tracking. In order to provide the sound quality in terms of signal-to-noise ratio to users, the fish sound recording will be analyzed before uploading. Because most available data were recorded either in the field or in fish tank, the fish sounds were extracted by using two different automatic detection methods. If fish sound recordings were from the field, the Time Endpoint Detection was applied by the processing a 0.5-s time frame with 50 % overlapping. Then the energy of the time frame was obtained by the sum of square of amplitude and the median of the energy plus a standard deviation was established as the threshold to extract fish sounds. If the recording was made in the fish tank, the Frequency Endpoint Detection was applied by 0.5-s time frame with 50 % overlapping. Then each time frame will be transformed into spectrum and the energy ratio of each frequency will be calculated from the spectrum. Finally the information entropy was obtained from the energy ratio and the detection threshold was set on standard deviation above the median of the information entropy. From two different automatic detection methods, the sound quality was presented in the signal-to-noise ratio, which was the average power of signal divided by average power of the background noise. The fish sound database was a 3-Tier system and developed by PHP and MySQL. In order to reduce the storage size and maintain the integrity of data, the Relational Model was applied. Firstly, the recording data were conceptually represented as Entity-Relationship Diagram(ERD). Secondly, the ERD was transformed to relational schemas. Thirdly, the schemas was normalized by first, second, and third forms. To improve the users¡¦ efficiency the sound database provides three interfaces. One was data uploading, another was data searching according to the keyword of creature name, recording area, and recording time, the other was data comparing by recording number.