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BOVIDS: A deep learning-based software for pose estimation to evaluate nightly behavior and its application to Common Elands (Tragelaphus oryx) in zoos
  • Jennifer Gübert,
  • Max Hahn-Klimroth,
  • Paul W. Dierkes
Jennifer Gübert
Goethe University Frankfurt

Corresponding Author:[email protected]

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Max Hahn-Klimroth
TU Dortmund University
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Paul W. Dierkes
Goethe-Universitat Frankfurt am Main
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Abstract

Only a few studies on the nocturnal behavior of African ungulates exist so far, with mostly small sample sizes. For a comprehensive understanding of nocturnal behavior, this database needs to be expanded. Zoo animals offer a good opportunity to lay the corresponding foundations. The results can provide clues for the study of wild animals and furthermore contribute to a better understanding of animal welfare and better husbandry conditions in zoos. To tackle this open question, we developed a stand-alone open-source software based on deep learning techniques, named BOVIDS (Behavioral Observations by Videos and Images using a Deep-Learning Software). This software is used to identify ungulates in their enclosure and to determine crucial behavioral poses on video material with an accuracy of 99.4%. A case study on 25 Common Elands (Tragelaphus oryx) out of 5 EAZA zoos with a total of 11,411 hours video material out of 822 nights is conducted, yielding the first detailed description of the nightly behavior of Common Elands. Our results indicate that age and sex are influencing factors on the nocturnal activity budget, the length of behavioral phases as well as the number of phases per behavioral state during the night. Finally, the results suggest the existence of species-specific rhythms that open future research directions.
10 Nov 2021Submitted to Ecology and Evolution
11 Nov 2021Submission Checks Completed
11 Nov 2021Assigned to Editor
18 Nov 2021Reviewer(s) Assigned
04 Dec 2021Review(s) Completed, Editorial Evaluation Pending
13 Dec 2021Editorial Decision: Revise Minor
11 Jan 20221st Revision Received
11 Jan 2022Submission Checks Completed
11 Jan 2022Assigned to Editor
11 Jan 2022Review(s) Completed, Editorial Evaluation Pending
12 Jan 2022Reviewer(s) Assigned
11 Feb 2022Editorial Decision: Revise Minor
13 Feb 20222nd Revision Received
14 Feb 2022Assigned to Editor
14 Feb 2022Submission Checks Completed
14 Feb 2022Review(s) Completed, Editorial Evaluation Pending
18 Feb 2022Editorial Decision: Accept
Mar 2022Published in Ecology and Evolution volume 12 issue 3. 10.1002/ece3.8701