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Parks, S. E.

Publications and source records attributed to Parks, S. E..

2 recordsLinked to original sources

Caller identification and characterization of individual humpback whale acoustic behavior

Acoustic recording tags are biologging tools that provide fine scale data linking acoustic signaling with individual behavior; however, when an animal is in a group, it is challenging to tease apart calls of other conspecifics and identify which individuals produce each call. This, in turn, prohibits robust assessment of individual acoustic behavior including call rates and silent periods, call bout production within and between individuals, and caller location. To overcome this challenge, we simultaneously instrumented small groups of humpback whales on a western North Atlantic feeding ground with sound and movement recording tags. This simultaneous tagging approach enabled us to compare the relative amplitude of each call across individuals and infer caller identity though amplitude differences. Focusing on periods when the tagged animals were isolated from other conspecifics, we were able to assign caller ID for 97% of calls in this dataset. From these labeled calls, we found that humpback whale individual call rates are highly variable across individuals and groups (0-89 calls/h), with calls produced throughout the water column and in bouts with short inter-call intervals (ICI = 2.2 s). Most calls received a likely response from a conspecific within 100 s. These results are important for modelling signal detection range for passive acoustic monitoring and density estimation. Future studies can expand on these methods for caller identification and further investigate the nature of sequence production and counter-calling in humpback whale social calls. Finally, this approach can be helpful for understanding intra-group communication in social groups across other taxa. Summary statementTagging entire humpback whale social groups with sound and movement recording tags allows us to for the first time parse out call behavior within groups and understand individual acoustic behavior.

animal behavior and cognition↗

Pose-gait analysis for cetaceans with biologging tags

Biologging tags are a key enabling tool for investigating cetacean behavior and locomotion in their natural habitat. Identifying and then parameterizing gait from movement sensor data is critical for these investigations. But how best to characterize gait from tag data remains an open question. Further, the location and orientation of the tag on an animal in the field are variable and can change multiple times during deployment. As a result, the relative orientation of the tag with respect to (wrt) the animal must be determined before a wide variety of further analyses. Currently, custom scripts that involve specific manual heuristics methods tend to be used in the literature. These methods require a level of knowledge and experience that can affect the reliability and repeatability of the analysis. The authors of this work argue that an animals gait is composed of a sequence of body poses observed by the tag, demonstrating a specific spatial pattern in the data that can be utilized for different purposes. This work presents an automated data processing pipeline (and software) that takes advantage of the common characteristics of pose and gait of the animal to 1) Identify time instances associated with occurrences of relative motion between the tag and animal; 2) Identify the relative orientation of tag wrt the animals body for a given data segment; and 3) Extract gait parameters that are invariant to pose and tag orientation. The authors included biologging tag data from bottlenose dolphins, humpback whales, and beluga whales in this work to validate and demonstrate the approach. Results show that the average relative orientation error of the tag wrt the dolphins body after processing was within 11 degrees in roll, pitch, and yaw directions. The average precision and recall for identifying relative tag motion were 0.87 and 0.89, respectively. Examples of the resulting pose and gait analysis demonstrate the potential of this approach to enhance studies that use tag data to investigate movement and behavior. MATLAB source code and data presented in the paper were made available to the public (https://github.com/ding-z/cetacean-pose-gait-analysis.git), with suggestions related to tag data processing practices provided in this paper. The proposed analysis approach will facilitate the use of biologging tags to study cetacean locomotion and behavior.

animal behavior and cognition↗