Impact of human-animal interaction on the behavioural expression of cats (Felis catus) and dogs (Canine lupus familiaris) : a thesis presented in partial fulfilment of the requirements for the degree of MSc (Animal Science), Massey University, Palmerston North, New Zealand

Abstract

Cats and dogs perceive and interpret the world differently from humans and the two species, which influences their behaviours and should be considered in the context of human animal interactions to prevent problem behaviours and increase welfare. The common ancestors of both species had different hunting strategies, which is reflected in differences of their physical structure. Visual capacities also differ, and affect vision in the dark, movement detection capabilities, and acuity. Both have whiskers to provide information and utilise smell for gathering information. They have a wide range of hearing frequencies, which helps intra- and interspecies social communication. Cats and dogs are both affected by their social environment and genetics, which can influence their fear of humans and personality traits. Animal behaviour is a broad field of study, with ethograms used as a tool to distinguish individual behaviours in cats and dogs. Behaviours that can be studied include active, inactive, and maintenance behaviours in cats and dogs. Traditional behavioural research has utilised observation by the owner or researcher. However, to examine animal activity and behaviour in a more natural setting, wearable technologies such as animal-borne cameras, pedometers, and accelerometers can be used. Triaxial accelerometers measure acceleration along three axes which can be correlated with observed activity and behaviour in both cats and dogs. Human-animal relationships exist as psychological and physical bonds, which are influenced by humans (personality and attention), and the animal itself. Research into human interactions with cats and dogs has examined how human health can be affected either positively or negatively. Further research has examined how cats and dogs are affected physically and psychologically by this interaction. There have been multiple studies on problem behaviours and prevention strategies. However, little is known of the effects of human-animal interactions on the behaviour and welfare of cats and dogs themselves. Stress responses are commonly used as indicators of cat and dog welfare. Behavioural and physiological indicators of stress included changes in behaviours and/or non-specific markers such as blood pressure, heart and respiratory rates, or specific markers that include activity of the hypothalamic-pituitary-adrenal (HPA) axis and glucocorticoid levels. A minimally invasive method to determine HPA function in cats and dogs was to measure faecal glucocorticoid metabolite (FGM) concentrations over an extended period. Knowledge of the effects of human-animal interaction on pet behaviour can be used to improve husbandry practices, resulting in better management practices and technology. The main objectives of this thesis were to determine if changes in the total duration and frequency of human-animal interaction had an impact on the activity levels and behavioural expressions of cats and dogs. A secondary objective was to assess FGMs as a tool to measure changes in stress levels within these animals. Behaviours assessed were classified using previously validated random forest (RF) machine learning (ML) models developed with ActiGraph wGT3X-BT triaxial accelerometers in colony cats and dogs, which all fell under the broad behaviour categories of active, inactive, or maintenance behaviours. For cats the specific behaviours assessed included locomotion, eating, grooming, littering, lying, scratching, sitting, and standing over 28 days. For dogs these included barking, drinking, eating, locomotion, scratching, sniffing, lateral recumbency, lying head-down, lying head-up, sitting, and standing over 35 days. All animals were kept under normal colony conditions, with two additional sessions of human-animal interaction time at specified times (Monday, Friday) and during the respective study periods. Weather data and faecal sample collection occurred concurrently to the study. Data analysis was conducted primarily using general linear mixed models (GLMM) in R (R Studio). Comparisons between groups and study period were examined to determine any effect of treatment. Additional human-animal interaction resulted in significantly increased overall dynamic body acceleration (ODBA) in both species. Similarly, locomotive behaviour increased significantly throughout the trial in both cats and dogs. Among the cats, changes were observed only in the treatment group. However, changes occurred in both groups of dogs, indicating that the additional presence of the researcher could have also affected the control animals. Species specific changes included a significant decrease of scratching behaviour in cats, a trend of increased barking behaviour in dogs, and a significant decrease of sniffing among dogs. Faecal glucocorticoid metabolite (FGM) concentrations were analysed using a faecal cortisol enzyme linked immune-sorbent assay (ELISA) and showed a decrease in glucocorticoid concentrations in both cats and dogs. This showed that additional interaction had the potential to increase welfare in colony cats and dogs, which may extend to the home setting.