Boughey Imogen, Hall Evelyn, Bush Russell
Sydney School of Veterinary Science, The University of Sydney, 425 Werombi Road, Camden, NSW 2567, Australia.
Animals (Basel). 2025 Aug 11;15(16):2357. doi: 10.3390/ani15162357.
The Australian alpaca industry is continuing to develop as an alternative fibre industry to the traditional merino or angora industries. This study aimed to investigate herd behaviour in an extensive system in south eastern Australia. Healthy adult female alpacas (Huacaya n = 32, Suri n = 32) over two years old were inducted into the trial and kept together across a 10 month period. A total of 5 animals were removed during the study due to illthrift or death unrelated to the study. GoPro cameras were set up at 5 locations in the paddock for 3 days in the middle of every season (Summer, Autumn, Winter, Spring) to record alpaca behaviour without a human observer present. Visual observations were taken at 0800, 1000, 1100, 1300, 1500 for 60 min. Behaviour observations were taken every 5 min from the videos according to a prepared ethogram. A count of animals exhibiting each behaviour was recorded at each time point within each of the designated 60-minute periods. A generalised linear mixed-effects model (GLMM) was run on binary data for each behaviour. Behaviours that returned a predicted proportion of over 0.10 for all seasons were used in an ordinal logistic regression that was then utilised to determine the effect of the season, time of day, and weather conditions on the number of animals. Season significantly impacted the number of alpacas grazing, resting, and standing ( < 0.0001). Alpacas were more likely to be grazing throughout the day in cooler seasons (autumn, winter) and resting in the warmer parts of the day in summer and spring. The time of day impacted the proportion of alpacas resting and grazing ( < 0.05) but not standing ( = 0.4432). This study highlights that alpacas spend the majority of the daylight hours grazing, with some variability across different seasons, which may impact ideal management practices to optimise production in an extensive system.
澳大利亚羊驼产业作为传统美利奴或安哥拉产业之外的一种替代纤维产业,正在持续发展。本研究旨在调查澳大利亚东南部粗放养殖系统中的畜群行为。两岁以上健康成年雌性羊驼(瓦卡亚羊驼n = 32,苏利羊驼n = 32)被纳入试验,并在10个月的时间里饲养在一起。在研究期间,共有5只动物因发育不良或与研究无关的死亡而被剔除。在每个季节(夏季、秋季、冬季、春季)的中期,在围场的5个地点设置GoPro相机,持续3天,以记录羊驼在无人观察情况下的行为。在08:00、10:00、11:00、13:00、15:00进行60分钟的目视观察。根据预先准备的行为图谱,每隔5分钟从视频中进行行为观察。在每个指定的60分钟时间段内的每个时间点,记录表现出每种行为的动物数量。对每种行为的二元数据运行广义线性混合效应模型(GLMM)。在所有季节中预测比例超过0.10的行为被用于有序逻辑回归,然后用于确定季节、一天中的时间和天气条件对动物数量的影响。季节对羊驼放牧、休息和站立的数量有显著影响(<0.0001)。在较凉爽的季节(秋季、冬季),羊驼全天更有可能在放牧,而在夏季和春季一天中较温暖的时候休息。一天中的时间对羊驼休息和放牧的比例有影响(<0.05),但对站立比例没有影响(=0.4432)。本研究强调,羊驼在白天的大部分时间都在放牧,不同季节存在一些差异,这可能会影响在粗放养殖系统中优化生产的理想管理实践。