Quantifying allo-grooming in wild chacma baboons (Papio ursinus) using tri-axial acceleration data and machine learning. Issue 4 (12th April 2023)
- Record Type:
- Journal Article
- Title:
- Quantifying allo-grooming in wild chacma baboons (Papio ursinus) using tri-axial acceleration data and machine learning. Issue 4 (12th April 2023)
- Main Title:
- Quantifying allo-grooming in wild chacma baboons (Papio ursinus) using tri-axial acceleration data and machine learning
- Authors:
- Christensen, Charlotte
Bracken, Anna M.
O'Riain, M. Justin
Fehlmann, Gaëlle
Holton, Mark
Hopkins, Phillip
King, Andrew J.
Fürtbauer, Ines - Abstract:
- Abstract : Quantification of activity budgets is pivotal for understanding how animals respond to changes in their environment. Social grooming is a key activity that underpins various social processes with consequences for health and fitness. Traditional methods use direct (focal) observations to calculate grooming rates, providing systematic but sparse data. Accelerometers, in contrast, can quantify activity budgets continuously but have not been used to quantify social grooming. We test whether grooming can be accurately identified using machine learning (random forest model) trained on labelled acceleration data from wild chacma baboons ( Papio ursinus ). We successfully identified giving and receiving grooming with high precision (81% and 91%) and recall (87% and 79%). Giving grooming was associated with a distinct rhythmical signal along the surge axis. Receiving grooming had similar acceleration signals to resting, and thus was more difficult to assign. We applied our machine learning model to n = 680 collar data days from n = 12 baboons and found that grooming rates obtained from accelerometers were significantly and positively correlated with direct observation rates for giving but not receiving grooming. The ability to collect continuous grooming data in wild populations will allow researchers to re-examine and expand upon long-standing questions regarding the formation and function of grooming bonds.
- Is Part Of:
- Royal Society open science. Volume 10:Issue 4(2023)
- Journal:
- Royal Society open science
- Issue:
- Volume 10:Issue 4(2023)
- Issue Display:
- Volume 10, Issue 4 (2023)
- Year:
- 2023
- Volume:
- 10
- Issue:
- 4
- Issue Sort Value:
- 2023-0010-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-04-12
- Subjects:
- machine learning -- tri-axial accelerometers -- random forest models -- allo-grooming -- activity budgets -- primates
Science -- Periodicals
500 - Journal URLs:
- https://royalsocietypublishing.org/journal/rsos ↗
- DOI:
- 10.1098/rsos.221103 ↗
- Languages:
- English
- ISSNs:
- 2054-5703
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library STI - ELD Digital store
- Ingest File:
- 26809.xml