Into the night : evaluating sleep as a measure of animal welfare

Schork, IG 2020, Into the night : evaluating sleep as a measure of animal welfare , PhD thesis, The University of Salford.

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There is a need for a simple non-invasive measure of animal welfare. In humans, sleep quality correlates strongly with a person’s wellbeing; this suggests that sleep may also prove to be a suitable tool to measure mammals’ welfare. Studies in humans have shown that lack of sleep compromises the health of individuals, causing heart attacks, strokes, diabetes and even cancer. Likewise, research conducted with shift workers demonstrated they are more likely to develop such diseases but are also more susceptible to psychological conditions such as depression. Considering humans and mammals have similar physiology and sleeping patterns, disturbances in mammals’ natural sleeping cycles could have similar outcomes. Our model system to examine this is the domestic dog. This system was chosen because dogs are a well-studied species regarding their physiology and have been used as a model in human sleep studies. They also co-exist with humans which gives us insight on their environment. This thesis presents the results of a multidisciplinary approach to evaluate sleep as a measure of animal welfare in domestic dogs. Firstly, trough behavioural observations, the sleep structure of kenneled dogs was investigated and after finding the dogs had an altered sleep architecture and highly fragmented sleep in the surveyed environment, we then verified the impact of sleep loss in other behaviours. Secondly, using glucocorticoids levels and assessing environmental variables such as temperature, light and sound levels, we evaluated how the environment along with stress responses can further compromise sleep and found important correlations between these measures. Thirdly, using wearable technology, dogs sleep, activity and health parameters (heart rate and respiration rate) were measured and results compared which sleep parameters, demonstrating remote sensing is a reliable technology and can provide further information on the effects of sleep loss in dogs. Lastly, an autonomous system was developed which combines deep leaning techniques (convolutional neural networks) with classical data processing methods to automatically detect and quantify dogs’ sleeping patterns and the results demonstrated it is an efficient tool to measure sleep and a practical solution to common problems associated with welfare research. Keywords: animal welfare, sleep behaviour, sleep quality, domestic dogs.

Item Type: Thesis (PhD)
Contributors: Young, RJ (Supervisor), Boubli, JP (Supervisor) and de Azevedo, CS (Supervisor)
Schools: Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Funders: CNPQ - Comite Nacional de Pesquisa Cientifica
Depositing User: Ivana Schork
Date Deposited: 27 Jul 2020 10:37
Last Modified: 27 Aug 2021 21:38

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