Heart rate (HR) and heart rate variability (HRV) are commonly used physiological measures in animals. While several studies exist on horse HRV, less information is available for donkeys. This scoping review aims to understand the extent and type of published evidence on donkey HR and HRV, their clinical and research applications, the devices used, and the analysis performed. Only quantitative primary studies published in English were considered. Four different databases were queried through the Web of Science platform, with additional evidence identified by citation chasing. After a two-stage screening phase, data were extracted considering study and population characteristics, information on HR/HRV analysis, and applications. The majority of the 87 included articles (about 80%) concerned a sample size of up to 20 individuals and were published since 2011 (about 65%). Forty-one articles employed an electronic device for signal acquisition (mainly electrocardiographs and heart rate monitors), yet only two articles reported HRV parameters. The literature on donkey HRV is lacking, and this gap can be filled by gaining knowledge on donkey characteristics and finding useful tools for welfare assessment. Comparison with what is known about the horse allows a discussion of the technical and interpretative difficulties that can be encountered with donkeys.
Recognizing animal emotions is critical to their welfare and can lead to a better relationship with humans and the environment, especially in a widespread species like the donkey, which is often prone to welfare issues. This study aims to assess the emotional response of donkeys through an operant conditioning task with two presumed different emotional contents. Specifically, a within-subject design including positive and negative conditions was conducted, collecting behavioural and physiological (heart rate variability and HRV) parameters. Facial expressions, postures, and movements were analysed by principal component analysis and behavioural diversity indexes (frequencies, activity budgets, richness, Shannon and Gini-Simpson). During the positive condition, both ears were held high and sideways (left: r = −0.793, p < 0.0001; right: r = −0.585, p = 0.011), while the ears were frontally erected (left: r = 0.924, p < 0.0001; right: r = 0.946, p < 0.0001) during the negative one. The latter was also associated with an increased tendency to walk (r = 0.709, p = 0.001), walk away (r = 0.578, p = 0.012), more frequent changes in the body position (VBody position = 0, p = 0.022), and greater behavioural complexity (VGini-Simpson Index = 4, p = 0.027). As for HRV analysis, the root mean square of successive beat-to-beat differences (rMSSD) was significantly lower after the negative condition. These non-invasive parameters could be considered as possible indicators of donkeys’ emotional state.
Surveys of harbor seals to assess pup production inDenmark are conducted at the assumed breeding season peak between 9 and 15 hr at winds <10 m/s, with no precipitation at least 6 hr before observations and at low tide in areas with a significant tidal range. Harbor seal pups can swim immediately after birth, so the fraction available for counting likely varies according to conditions. In the Limfjord, a separate harbor seal population is living in a large inlet in northern Denmark where >95% of pups are born at two haul-out sites situated 4 km apart. Drone surveys of these two haul-outs were conducted throughout the breeding seasons during 2017-2019. The effects of weather conditions and timing of surveys on counts were analyzed by generalized additive mixed models. The bestperforming model included date and wind speed. Pup counts grew from the onset of the observation period and were predicted to peak on June 22. Wind speed had a linear relationship with pup counts and > 50% more pups were counted at 5 m/s than at 1 m/s. To achieve representative pup counts careful consideration of survey conditions and possibly correction for these effects are necessary.
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