Detecting surface‐feeding behavior by rorqual whales in accelerometer data

Owen, Kylie; Dunlop, Rebecca A.; Monty, Jason; Chung, Daniel; Noad, Michael J.; Donnelly, David; Goldizen, Anne W.; Mackenzie, Thomas B.

doi:10.1111/mms.12271

Cited by 22 publications

(38 citation statements)

References 48 publications

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“…The depth at which each lunge occurred was also determined. Due to the impact that wave drag can have on the whale and on the accelerometer signals expected during lunge feeding at the surface [39], any potential lunges shallower than 10 m were excluded from the analysis.…”

Section: Identifying Lunge Feeding Behaviormentioning

confidence: 99%

A week in the life of a pygmy blue whale: migratory dive depth overlaps with large vessel drafts

Owen

Jenner

et al. 2016

Anim Biotelemetry

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Background:The use of multi-sensor tags is increasingly providing insights into the behavior of whales. However, due to limitations in tag attachment duration and the transmission bandwidth of the Argos system, little is known about fine-scale diving behavior over time or the reliability of assigning behavioral states based on horizontal movement data for whale species. How whales use the water column while migrating has not been closely examined, yet the strategy used is likely to influence the vulnerability of whales to ship strike. Here we present information from a rare week long multi-sensor tag deployment on a pygmy blue whale (Balaenoptera musculus brevicauda) that provided a great opportunity to examine the fine-scale diving behavior of a migrating whale and to compare the occurrence of feeding lunges with assigned behavioral states. Results:The depth of migratory dives was highly consistent over time and unrelated to local bathymetry. The mean depth of migratory dives (~13 m when corrected for the tag position on the whale) was just below the threshold depth (12 m) that blue whales are predicted to travel below to remove the influence of wave drag at the surface. The whale spent 94 % of observed time and completed 99 % of observed migratory dives within the range of large container ship drafts (<24 m). Areas of high residence identified using the horizontal movement data (FastLoc GPS) did not reflect where lunge feeding occurred. Conclusions:The lack of correspondence between areas of high residence inferred from horizontal movement data and the locations where the whale performed feeding lunges highlights the need for further research to determine whether movement models can accurately detect whale feeding areas or only areas of prey searching. While migrating, the whale made dives to a depth that is likely to allow it to avoid wave drag and maximize horizontal movement. Although this strategy may reduce energy expenditure during migration, it also placed the whale at greater risk of ship strike for a much longer period than currently thought. If other whales have similar diving behavior to this animal during migration, many whale species may spend much longer periods than currently estimated within the parts of the water column where the risk of ship strike is high.

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Section: Identifying Lunge Feeding Behaviormentioning

confidence: 99%

A week in the life of a pygmy blue whale: migratory dive depth overlaps with large vessel drafts

Owen

Jenner

et al. 2016

Anim Biotelemetry

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“…; Owen et al. ). The rapid acceleration of a whale toward a prey patch, and then deceleration as it opens its jaws, is represented in the tag data as an increase and then subsequent drop in flow noise, a sharp spike and then drop in the jerk signal, and often a significant roll (Goldbogen et al.…”

Section: Methodsmentioning

confidence: 97%

“…; Owen et al. ). At varying levels of complexity, decision tree methods are being used across a wide variety of taxa as a simple, easily implemented method of automated activity detection.…”

Section: Introductionmentioning

confidence: 97%

“…; Owen et al. ). One group of animals that has had proven success in the identification of foraging behavior from tag data are the rorqual whales, which feed by a stereotyped, extremely large kinematic event that is identifiable in tag sensor data (Goldbogen et al.…”

Section: Introductionmentioning

confidence: 97%

“…For more challenging behavioral identification, Owen et al. () calculated a novel parameter and combined it with a clear series of linear decision rules to identify the timing of feeding events in large whales. All of these methods require a detailed knowledge of the study species, and the use of skilled observers to confirm the automated method behavioral identification (Lagarde et al.…”

Section: Introductionmentioning

confidence: 99%

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Development of an automated method of detecting stereotyped feeding events in multisensor data from tagged rorqual whales

Allen

Goldbogen

Friedlaender

et al. 2016

Ecology and Evolution

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The introduction of animal‐borne, multisensor tags has opened up many opportunities for ecological research, making previously inaccessible species and behaviors observable. The advancement of tag technology and the increasingly widespread use of bio‐logging tags are leading to large volumes of sometimes extremely detailed data. With the increasing quantity and duration of tag deployments, a set of tools needs to be developed to aid in facilitating and standardizing the analysis of movement sensor data. Here, we developed an observation‐based decision tree method to detect feeding events in data from multisensor movement tags attached to fin whales (Balaenoptera physalus). Fin whales exhibit an energetically costly and kinematically complex foraging behavior called lunge feeding, an intermittent ram filtration mechanism. Using this automated system, we identified feeding lunges in 19 fin whales tagged with multisensor tags, during a total of over 100 h of continuously sampled data. Using movement sensor and hydrophone data, the automated lunge detector correctly identified an average of 92.8% of all lunges, with a false‐positive rate of 9.5%. The strong performance of our automated feeding detector demonstrates an effective, straightforward method of activity identification in animal‐borne movement tag data. Our method employs a detection algorithm that utilizes a hierarchy of simple thresholds based on knowledge of observed features of feeding behavior, a technique that is readily modifiable to fit a variety of species and behaviors. Using automated methods to detect behavioral events in tag records will significantly decrease data analysis time and aid in standardizing analysis methods, crucial objectives with the rapidly increasing quantity and variety of on‐animal tag data. Furthermore, our results have implications for next‐generation tag design, especially long‐term tags that can be outfitted with on‐board processing algorithms that automatically detect kinematic events and transmit ethograms via acoustic or satellite telemetry.

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First evidence of bubble‐net feeding and the formation of ‘super‐groups’ by the east Australian population of humpback whales during their southward migration

Pirotta

Owen

Donnelly³

et al. 2021

Aquatic Conservation

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The recovery of overexploited populations is likely to reveal behaviours that may have been present prior to harvest but are only now reappearing as the population size increases. The east Australian humpback whale (Megaptera novaeangliae) population (group V, stock E1) has recovered well from past exploitation and is now estimated to be close to the pre‐whaling population size. Humpback whales were thought to follow a ‘feast and famine’ model historically, feeding intensively in high‐latitude feeding grounds and then fasting while migrating and in calving grounds; however, there is growing evidence that animals may feed outside of known foraging grounds. This short article reports on the first photographically documented evidence of bubble‐net feeding by humpback whales in Australian coastal waters (n = 10 groups observed) and provides the first evidence of a second site in the southern hemisphere for the formation of ‘super‐groups’ (n = 6 super‐groups at discrete locations). The formation of super‐groups may be linked to changes in the type or density of prey available, either along the migratory route or in the feeding grounds of the previous summer. It is also possible that the increased population size following recovery make large group sizes while feeding more common. These findings strongly support evidence that feeding behaviour is not restricted to high‐latitude foraging grounds in the Southern Ocean, and that prey consumption prior to leaving the coastal waters of Australia may be a significant component of the migratory ecology of this population. Understanding how environmental variation influences the extent to which humpback whales depend on foraging opportunities along their migratory route, and where feeding occurs, will help to predict how future changes in the ocean will influence whale populations. This will also allow for more effective management measures to reduce the impact of threats during this important period of energy consumption.

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Detecting surface‐feeding behavior by rorqual whales in accelerometer data

Cited by 22 publications

References 48 publications

A week in the life of a pygmy blue whale: migratory dive depth overlaps with large vessel drafts

A week in the life of a pygmy blue whale: migratory dive depth overlaps with large vessel drafts

Development of an automated method of detecting stereotyped feeding events in multisensor data from tagged rorqual whales

First evidence of bubble‐net feeding and the formation of ‘super‐groups’ by the east Australian population of humpback whales during their southward migration

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