Using Advanced Tri-Axial Accelerometer Data to Improve Behavioral Time Budgets and Bioenergetic Estimates of Wintering Lesser Scaup

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Author(s)Schley, Hannah L.
Author(s)Williams, Christopher K.
Author(s)Homyack, Josh
Author(s)Harvey, Bill
Author(s)Olsen, Glenn H.
Author(s)Johnson, Sharon
Date Accessioned2026-01-09T19:36:55Z
Date Available2026-01-09T19:36:55Z
Publication Date2026-01-05
DescriptionThis is an open access article under the terms of the Creative Commons Attribution License, https://creativecommons.org/licenses/by/4.0/ which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2025 The Author(s). Ecology and Evolution published by British Ecological Society and John Wiley & Sons Ltd. This article was originally published in Ecology and Evolution . The version of record is available at: https://doi.org/10.1002/ece3.72868
AbstractWildlife behavior studies have provided vital information towards understanding the natural histories of wildlife species and identified crucial components regarding their habitat and metabolic needs. For many species, typical behavioral data are collected using diurnal scans that have limitations in both when and where the data can be collected, ultimately leading to biases in behavioral patterns. With technological and analytical advancements of radiotechnology, behavior data can be collected more often and over larger spatial scales than with traditional methods. This study compares the behavioral time budget estimates between two different observational methods: ground-truthed diurnal scanning observations and 24-h tri-axial accelerometer (ACC) GPS/GSM transmitter data that were classified using machine learning. We used the time budgets produced from the two methodologies and calculated the daily energy expenditure (DEE) for wintering Lesser Scaup (Aythya affinis) to explore the implications of biased behavioral data. We found significantly more feeding and less flight behavior of birds in the ACC data than in the visual scanning data. Using the ACC behavior proportions of the two most energetically demanding behaviors (feeding and flying), we found that feeding occurred 42% more during the day and flying occurred 23% more during the night. Lastly, we identified that the DEE estimated using the diurnal scanning observations produced a significantly lower estimate than with the 24-h ACC data. This advanced way of interpreting wildlife behavior patterns can increase our understanding of wildlife species' natural history and make improved decisions regarding wildlife conservation and management. Incorporating this new technique of wildlife behavioral observations, we provided a new framework to expand our current knowledge of wintering waterfowl behaviors and energetic needs that can be adapted to research the vast intricacies of wildlife behavior.
SponsorFunding for this research came from the Maryland Department of Natural Resources, Ducks Unlimited, The University of Delaware Waterfowl and Upland Gamebird Center, and USDA Hatch (DEL00854). We are especially grateful to Matt Whitbeck and Marcia Pradines of the US Fish and Wildlife Service for providing access to Eastern Neck National Wildlife Refuge, the many biologists and technicians, specifically Nathan Simmons and Amanda Hoyt, of the Maryland Department of Natural Resources who helped during fieldwork, and Dr. Alicia Berlin, Carlyn Caldwell, and the staff of the US Geological Survey—Eastern Ecological Science Center for providing their expertise and facilities. This work was supported by Maryland Department of Natural Resources and Ducks Unlimited. Additional funding was provided by the US Department of Agriculture Hatch (DEL00774) and the University of Delaware Waterfowl and Upland Gamebird Center.
CitationSchley, H. L., C. K. Williams, J. Homyack, B. Harvey, G. H. Olsen, and S. Johnson. 2026. “ Using Advanced Tri-Axial Accelerometer Data to Improve Behavioral Time Budgets and Bioenergetic Estimates of Wintering Lesser Scaup.” Ecology and Evolution 16, no. 1: e72868. https://doi.org/10.1002/ece3.72868
ISSN2045-7758
URLhttps://udspace.udel.edu/handle/19716/36827
Languageen_US
PublisherEcology and Evolution
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
KeywordsAythya affinis
Keywordsdaily energy expenditure
Keywordslesser scaup
Keywordsmachine learning
Keywordsscanning observations
Keywordstime-activity budgets
Keywordstri-axial
Keywordsaccelerometer data
TitleUsing Advanced Tri-Axial Accelerometer Data to Improve Behavioral Time Budgets and Bioenergetic Estimates of Wintering Lesser Scaup
TypeArticle
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