Background: Monitoring the feeding behavior of animals in the wild is key to understanding their energetics and the influence of the environment on their survival. Recently, a novel acceleration transmitter that processes acceleration data onboard and outputs identification results has been developed by AquaSound Inc. (Kobe, Japan) to investigate feeding biology in fish. To date, few attempts have been made to identify the feeding behavior of fish using transmitters, and none of these attempts accomplished classification of alternative feeding behaviors according to prey items. The objective of this study was to develop an algorithm that can be incorporated in the acceleration transmitter and can identify alternative feeding behaviors in fish, using red-spotted grouper (Epinephelus akaara) as a model species. Results: Most of the identification algorithms describing feeding behavior in fish developed in previous studies used a combination of acceleration and angular velocity. In this study, we constructed an algorithm based on three-axis accelerometry data alone, since a gyroscope consumes much more electricity and would shorten the battery life of the transmitter. Acceleration data were obtained in tank experiments. Feeding behaviors, induced by feeding three types of live prey (Trachurus japonicus, Metapenaeus ensis and Hemigrapsus sanguineus), as well as other behaviors (routine and escape movements), were simultaneously recorded at 200 Hz by acceleration data loggers, implanted in the abdominal cavities of fish, and by a video camera. A decision tree, including a three-dimensional lookup table, was constructed to classify the behaviors into four behavior classes: shrimp-eating, fish-eating, crab-eating and other behaviors. The classification accuracy was estimated to be 0.77 (F-measure) for shrimp-eating, 0.73 for fish-eating, 0.71 for crab-eating and 0.78 for other movements, using fivefold cross-validation. Conclusions: The algorithm developed in this study could be incorporated into the transmitter, which would record acceleration data at high frequency (200 Hz), process the data onboard and output classification results of behaviors. This method would reveal more aspects of fish biology, such as individual feeding strategies.

In this study, we investigated the diving behavior of sei whales relative to the vertical distributionoftheirpotentialpreyinthewesternNorthPacificduringthesummerof2013.Acoustic time-depthtransmitterswereattachedtotwoseiwhalesfor10.2and32.0h,respectively.Thevertical distributionanddensity(expressedasthevolumebackscatteringstrength,SV)oftheirpotentialprey were recorded by an echosounder. Diving behavior was classified into two shapes: U-shaped and V-shaped.Forbothindividuals,U-shapeddivingwasassociatedwithhigherSVvaluesthanV-shaped divingandthefrequencyofU-shapeddivingincreasedfromlateafternoonuntilsunset.Duringthe daytime,densescatteringlayers(presumablyzooplankton)weredistributedatapproximately40mand theythenmigratedtowardthesurfacearoundsunset.Thedivingdepthofthewhalesfollowedthediel migrationof thescatteringlayersandthedivingwas concentratedintheselayerswhenthedensity becamehigh.Theresultsofthisstudyindicatethatseiwhaleschangetheirdivingdepthandshapesin responsetothedielverticalmigrationoftheirpotentialprey.

Abstract:In the biological research of fish and marine animals, ultrasonic transmitters (pingers) are used to perform ultrasonic biotelemetry. In this method, the size of the pinger is limited to the size that can be attached to the fish or other marine animal. In such a system, a highly efficient ultrasonic biotelemetry system would be needed for use in the ocean, because there is a high level of underwater ambient noise, especially in temperate and tropical areas. We investigated four parameters that determine the performance of this system with the goal of designing the optimum ultrasonic biotelemetry system. The first parameter, the long distance between the pinger and the receiver, determines the transmitting frequency needed. The second, the battery life, requires an effective transducer and a low power dissipation circuit. The third, minimizing of the pinger size, requires the selection of optimal microelectronics components. The last, a high level of recognition, depends on the signal processing method of the transmitting system. We were able to achieve over 1,000-meter transmission. Using two small battery (SR626SW 32-mAh), the system could operate for 240 days with transmission every 30 seconds. The pinger was 10 mm diameter and 40 mm long. To achieve high signal recognition against the ambient noise and to avoid the collision of the pinger against solid material that might damage it, we used a maximum length (M) sequence signal and correlation processing in the receiving system.The system consisted of the tiny pinger and high-performance receiving equipment including the transducer. The pinger could transmit the pinger identification by M sequence signal and the depth information at each repetition interval. The receiver processed the correlation of the received M sequence signal from the pinger using an FPGA (Field-Programmable Gate Array) chip and calculated the direction of the pinger.

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