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Through the eyes of a wolf: Using non-invasive methods to quantify and classify the facial signalling of wolves (Canis lupus) and domestic dogs (Canis lupus familiaris) [video] Open Access

The morphologies of wild animals typically evolved via natural selection as a result of environmental pressures leading to specific adaptations to cope with life-history challenges, such as foraging, mating and communication. However, many animals, in particular mammals, have been domesticated by humans. As a result of domestication a range of divergent morphological traits are frequently seen in domesticated mammals that separate them from their wild, ancestral counterparts. Many of these diverged traits pertain to cranium morphologies, such as different head shapes and sizes, shorter muzzles, and different ear shapes and positions. To date, there is little research into the potential implications that these diverged morphological traits of domesticated mammals may pose for their behaviour. A model example of diverged cranium morphologies is seen in the domestic dog, the selectively bred descendant of wolves. It is thought that the head and facial feature morphologies of wolves aid the production of facial expressions for communicative purposes. Previous researchers have also speculated on the ability of wolves to convey affective states as well as social status via their facial expressions. Affective states are forms of motivation such as emotions, moods, attitudes, desires, preferences, intentions and dislikes. However, to date there has been no quantitative analyses of these suggested links between facial expressions, affective states and social status in wolves. The relative shape and position of the eyes, ears, forehead, muzzle, nose and lips are the same for all wolves, throughout the world. However, selective breeding has resulted in the main conveyers of facial expressiveness of dogs greatly diverging from those of their wolf ancestors, although, it is still thought that dogs use facial expressions to convey affective states. However, to date there has been little quantitative analyses of the links between domestic dog facial expressions and affective states. This thesis aims to quantify the affective facial expressions of wolves and domestic dogs, and to determine if the various head and facial morphologies found across different dog breeds limits their abilities to successfully produce affective facial expressions like their wolf ancestors. The facial expressions of captive, human-habituated wolves (n = 10) and kennelled rescue dogs (n = 64) were video recorded during social interactions and reactions to ‘emotive’ stimuli. To quantify the facial expressions of wolves and dogs, the video footage was decoded using the Dog Facial Action Coding System (DogFACS). The affective states of focal canids were also quantified and classified from the video footage using independent observers. The quantified facial expressions were then mapped against the reliable classifications of affective states using hierarchical cluster analyses and linear discriminant analyses. Two separate confusion matrices for wolves and dogs were generated from the linear discriminant analyses, which revealed the level of precision (agreement) between the actual and predicted affective facial expressions of wolves and dogs. The research presented in this thesis provides the first quantification of facial expressions in wolves and relates them to reliable classifications of affective states across a range of social contexts. This research also provides the first quantitative, preliminary evidence for wolf facial expressions conveying social status, which has never been shown to exist in any other non-human animal. The affective facial expressions of wolves are shown to be similar to those seen in primates and are discussed in the framework of the social intelligence hypothesis. For the first time, this thesis also shows that the varying head and facial feature morphologies of dogs limit their ability to produce the same range of affective facial expressions as their wolf ancestors. However, this research reveals that dogs have evolved a compensatory way to convey their affective states, via the use of vocalisations.

Descriptions

Resource type

Video

Contributors

Creator: Hobkirk, Elana Rosemary ¹
Contact person: Twiss, Sean David ¹

¹ Durham University

Funder

Grevillea Trust Scholarship, Norman Richardson Postgraduate Research Fund, Thriplow Charitable Trust.

Research methods

Ethical statement: All data collection for this research consisted of non-invasive behavioural observations, therefore, no special requirements to handle study subjects or to enter wolf enclosures or dog kennels was obtained from the UKWCT or Dogs Trust. All observational protocols were approved by Durham University’s Animal Welfare Ethical Review Board (AWERB), and all procedures complied with BIAZA and Dogs Trust ethical guidelines. Video footage was collected at the UK Wolf Conservation Trust (UKWCT, Beenham UK, 51.419491N, -1.153433W), and Dogs Trust Darlington (Sadberge UK, 54.556676N, 1.473808W). UKWCT footage was collected between February 15th 2016 and March 4th 2016, on weekdays between 0900 and 1700 hours (GMT). Dogs Trust Darlington footage was collected between August 9th 2016 and November 11th 2016, on weekdays between 1100 and 1700 hours (BST). Videos were recorded ad-hoc (as and when social interactions or reactions to stimuli occurred) using a hand-held Canon Legria HFR36-D video camera (51x zoom).

Other description

These videos form appendices B, C and D of the following thesis: Hobkirk, Elana, Rosemary (2019). Through the eyes of a wolf: Using non-invasive methods to quantify and classify the facial signalling of wolves (Canis lupus) and domestic dogs (Canis lupus familiaris). Masters thesis, Durham University, UK.

Keyword

Behavioural Ecology
Animal Behaviour
Animal Communication
Animal Affective States
Animal Emotions
Facial Expressions
Facial Signalling
Wolf
Wolves
Canis lupus
Domestic Dog
Dogs
Canis lupus familiaris

Subject

Behavioural Ecology

Location

Language

Cited in

Identifier

ark:/32150/r16q182k15c
doi:10.15128/r16q182k15c

Rights

Creative Commons Attribution 4.0 International (CC BY)

Publisher

Durham University

Date Created

2020-01-31

File Details

Depositor

N. Syrotiuk

Date Uploaded

6 February 2020, 09:02:02

Date Modified

8 February 2020, 09:02:19

Audit Status

Audits have not yet been run on this file.

Characterization

File format: zip (ZIP Format)

Mime type: application/zip

File size: 35938771

Last modified: 2020:02:06 09:21:14+00:00

Filename: Canid_facial_signalling-ERH.zip

Original checksum: 722b658b534d630b57711775ae703c51