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AccelerometerBehavior: R Package for Classifying Ungulate Behaviors Into Three States.

Rachel A Smiley^1,2, Seth T Rankins^1,2, Lindsay Millward³

¹Haub School of the Environment and Natural Resources University of Wyoming Laramie Wyoming USA.

Ecology and Evolution

|December 22, 2025

Summary

This summary is machine-generated.

Researchers developed an R package, AccelerometerBehavior, to classify ungulate behavior using accelerometer data from GPS collars. This tool enhances the use of underutilized movement data for wildlife research.

Keywords:

accelerometer activity budgets activity data bighorn sheep moose mule deer ungulates

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Area of Science:

Wildlife ecology
Animal behavior
Movement ecology

Background:

Technological advancements enable fine-scale animal behavior studies.
Accelerometer data from GPS collars are underutilized for behavioral analysis.
Classifying ungulate behavior from accelerometer data requires robust models.

Purpose of the Study:

To develop and validate models for classifying ungulate behaviors (stationary, foraging, traveling) using accelerometer data.
To create an R package (AccelerometerBehavior) for accessible application of these models.
To compare activity budgets derived from accelerometer data with those from GPS-based Hidden-Markov models.

Main Methods:

Paired accelerometer data with direct behavioral observations for three ungulate species.
Developed random forest models for behavior classification.
Validated models and created a general ungulate model applicable to species lacking observation data.

Main Results:

Achieved high classification accuracy (≥87%) and AUC (≥0.93) for species-specific models.
Developed a general ungulate model with 90% accuracy and 0.95 AUC.
AccelerometerBehavior R package allows direct application of validated models.

Conclusions:

AccelerometerBehavior facilitates the underutilized accelerometer data for ungulate behavior studies.
Method and data resolution significantly impact activity budget estimations.
The R package simplifies behavior classification, expanding research potential.