Massey Documents by Type
Permanent URI for this communityhttps://mro.massey.ac.nz/handle/10179/294
Browse
6 results
Search Results
Item Evaluating the Effects of Novel Enrichment Strategies on Dog Behaviour Using Collar-Based Accelerometers(MDPI (Basel, Switzerland), 2025-06-03) Redmond C; Draganova I; Corner-Thomas R; Thomas D; Andrews C; Gaunet FEnvironmental enrichment is crucial to improve welfare, reduce stress, and encourage natural behaviours in dogs housed in confined environments. This study aimed to use accelerometery and machine learning to evaluate the effect of different enrichment types on dog behaviour. Three enrichments (food, olfactory, and tactile) were provided to dogs for five consecutive days, with four days between each treatment. Acceleration data were collected using a collar mounted ActiGraph®. Nine behaviours were classified using a validated machine learning model. Behaviour and activity differed significantly among the dogs. Dogs interacted most with the food enrichment, followed by the olfactory and then tactile enrichments. The dogs were least active during the olfactory enrichment, whereas activity was relatively consistent during the food and tactile enrichments. For all enrichments, dogs exhibited the most exploratory/locomotive behaviour during the first hour of each enrichment period, but this declined over the treatment period indicating habituation. For exploratory and locomotive behaviour, food enrichment was the most stimulating for the dogs with longer daily engagement than for both olfactory and tactile enrichments. These results illustrate that accelerometery and machine learning can be used to evaluate enrichment strategies in dogs, but it is important to consider variation among dogs and habituation.Item Longitudinal Study on the Effect of Season and Weather on the Behaviour of Domestic Cats (Felis catus)(MDPI AG, 2025-02-24) Smit M; Andrews C; Draganova I; Corner-Thomas R; Thomas DItem Development and validation of an LC-MS/MS method for the quantification of oral-sugar probes in plasma to test small intestinal permeability and absorptive capacity in the domestic cat (Felis catus)(Elsevier BV, 2024-07-15) Patterson K; Fraser K; Bernstein D; Bermingham EN; Weidgraaf K; Kate Shoveller A; Thomas DA novel method for quantifying the concentration of lactulose, rhamnose, xylose, and 3-O-methylglucose (3-OMG) in cat plasma using liquid chromatography-mass spectrometry (LC-MS) was developed. Domestic male cats (n = 13) were orally dosed with a solution containing the four sugars to test the permeability and absorptive capacity of their intestinal barrier. Plasma samples were taken 3 h later and were prepared with acetonitrile (ACN), dried under N2, and reconstituted in 90 % ACN with 1 mM ammonium formate. Stable isotope labelled 13C standards for each analyte were used as internal standards. Chromatographic separation was conducted using a Phenomenex Luna NH2 column with a gradient elution system of deionized water and 90 % ACN with 1 mM ammonium formate at 300 µL/min for 13 min total analysis time. Recovery trials were conducted in triplicate over three days with RSD values (%) for each day ranging from 1.2 to 1.4 for lactulose, 5.4 - 6.0 for rhamnose, 3.3 - 5.5 for xylose, and 2.6 - 5.6 for 3-OMG. Inter-day variations for each analyte were not different (p > 0.05). Limit of detection and quantification were 0.2 and 0.7 µg/mL for lactulose, 0.8 and 2.4 µg/mL for rhamnose, 0.6 and 1.8 µg/mL for xylose, and 0.3 and 1.1 µg/mL for 3-OMG, respectively. Plasma sugar concentrations recovered from cats were above the limit of quantification and below the highest calibration standard, validating the use of this method to test intestinal permeability and absorptive capacity in cats.Item The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behavioural Identification in Domestic Dogs (Canis familiaris): A Validation Study(MDPI (Basel, Switzerland), 2024-09-13) Redmond C; Smit M; Draganova I; Corner-Thomas R; Thomas D; Andrews C; Fullwood DT; Bowden AEAssessing the behaviour and physical attributes of domesticated dogs is critical for predicting the suitability of animals for companionship or specific roles such as hunting, military or service. Common methods of behavioural assessment can be time consuming, labour-intensive, and subject to bias, making large-scale and rapid implementation challenging. Objective, practical and time effective behaviour measures may be facilitated by remote and automated devices such as accelerometers. This study, therefore, aimed to validate the ActiGraph® accelerometer as a tool for behavioural classification. This study used a machine learning method that identified nine dog behaviours with an overall accuracy of 74% (range for each behaviour was 54 to 93%). In addition, overall body dynamic acceleration was found to be correlated with the amount of time spent exhibiting active behaviours (barking, locomotion, scratching, sniffing, and standing; R2 = 0.91, p < 0.001). Machine learning was an effective method to build a model to classify behaviours such as barking, defecating, drinking, eating, locomotion, resting-asleep, resting-alert, sniffing, and standing with high overall accuracy whilst maintaining a large behavioural repertoire.Item How Lazy Are Pet Cats Really? Using Machine Learning and Accelerometry to Get a Glimpse into the Behaviour of Privately Owned Cats in Different Households(MDPI (Basel, Switzerland), 2024-04-19) Smit M; Corner-Thomas R; Draganova I; Andrews C; Thomas D; Friedrich CMSurprisingly little is known about how the home environment influences the behaviour of pet cats. This study aimed to determine how factors in the home environment (e.g., with or without outdoor access, urban vs. rural, presence of a child) and the season influences the daily behaviour of cats. Using accelerometer data and a validated machine learning model, behaviours including being active, eating, grooming, littering, lying, scratching, sitting, and standing were quantified for 28 pet cats. Generalized estimating equation models were used to determine the effects of different environmental conditions. Increasing cat age was negatively correlated with time spent active (p < 0.05). Cats with outdoor access (n = 18) were less active in winter than in summer (p < 0.05), but no differences were observed between seasons for indoor-only (n = 10) cats. Cats living in rural areas (n = 7) spent more time eating than cats in urban areas (n = 21; p < 0.05). Cats living in single-cat households (n = 12) spent more time lying but less time sitting than cats living in multi-cat households (n = 16; p < 0.05). Cats in households with at least one child (n = 20) spent more time standing in winter (p < 0.05), and more time lying but less time sitting in summer compared to cats in households with no children (n = 8; p < 0.05). This study clearly shows that the home environment has a major impact on cat behaviour.Item Female song occurs in songbirds with more elaborate female coloration and reduced sexual dichromatism(Frontiers Media, 15/03/2016) Webb W; Brunton DH; Aguirre JDAVID; Thomas D; Valcu M; Dale J; Schausberger, PElaborate plumages and songs in male birds provide classic evidence for Darwinian sexual selection. However, trait elaboration in birds is not gender-restricted: female song has recently been revealed as a taxonomically-widespread trait within the songbirds (oscine Passerines), prompting increased research into likely functions and social/ecological correlates. Here we use phylogenetically-informed comparative analysis to test for an evolutionary association between female song and plumage color elaboration in songbirds. If there is an evolutionary trade-off between signaling modes, we predict a negative correlation between acoustic and visual elaboration. This trade-off hypothesis has been commonly proposed in males but has mixed empirical support. Alternatively, if song and plumage have similar or overlapping functions and evolve under similar selection pressures, we predict a positive correlation between female song and female plumage elaboration. We use published data on female song for 1023 species of songbirds and a novel approach that allows for the reliable and objective comparison of color elaboration between species and genders. Our results reveal a significant positive correlation between female colorfulness and female song presence. In species where females sing, females (but not males) are on average more colorful—with concomitantly reduced average sexual dichromatism. These results suggest that female plumage and female song likely evolved together under similar selection pressures and that their respective functions are reinforcing. We discuss the potential roles of sexual vs. social selection in driving this relationship, and the implications for future research on female signals.