Data from: Using advanced tri-axial accelerometer data to improve behavioral time budgets and bioenergetic estimates of wintering Lesser Scaup

Wildlife 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 is collected using diurnal scan sampling
techniques 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-hr 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-hr 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.