Demographic, morphological and coat factors in dogs after exercise at a fast course ability test (FCAT) trial

Domestic dogs are a widely diverse species of endothermic mammals that show a positive correlation between body mass and whole-animal metabolic rate, but a negative correlation between body mass and lifespan, making them an interesting system for determining thermoregulatory patterns in relation to...

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Veröffentlicht in:Veterinary research communications 2025-02, Vol.49 (1), p.25-25, Article 25
Hauptverfasser: Jiménez, Ana Gabriela, Russel, William Andrew, Paul, Kailey Diane, McQuillen, Alta, Ay, Ahmet Ali
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Sprache:eng
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Zusammenfassung:Domestic dogs are a widely diverse species of endothermic mammals that show a positive correlation between body mass and whole-animal metabolic rate, but a negative correlation between body mass and lifespan, making them an interesting system for determining thermoregulatory patterns in relation to body mass, body morphology, and age within a single mammalian species. Though previous work has found differences in thermoregulation across seasons and with training in dogs of different sizes, we now seek to determine (1) whether sampling event-related temperature differences remained when dogs exercised intensely and acutely outdoors and (2) whether thermal differences were also expressed in short-term burst exercise in athletic dogs compared to long-term exercise in non-athletic dogs, as previously found. Here, we measured tympanic membrane temperature (T ear ) as a correlate of core or internal body temperature (T b ). We also measured changes in body temperature across different body surfaces using thermal imaging (T eye , T nose , and T mouth ) in dogs after exercise during Fast Course Agility Trial (FCAT) competitions between spring and summer months in Central New York State, USA ( N  = 20, July and August N  = 26). We correlated these data to each dog’s body mass (average(± standard error) = 29.97(± 0.24) lbs.), age (5.99(± 0.78) years), and various aspects of body part measurements and coat characteristics, such as length, type, and color. First, in our overall dataset, being sampled in May was the most significant predictor of temperature slope ( p  
ISSN:0165-7380
1573-7446
1573-7446
DOI:10.1007/s11259-024-10578-8