McGowan Natasha E, Marks Nikki J, Maule Aaron G, Schmidt-Küntzel Anne, Marker Laurie L, Scantlebury David M
School of Biological Sciences, Queen's University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, UK.
Cheetah Conservation Fund, PO Box 1755, Otjiwarongo, Namibia.
Mov Ecol. 2022 Feb 5;10(1):7. doi: 10.1186/s40462-022-00305-w.
Extinction is one of the greatest threats to the living world, endangering organisms globally, advancing conservation to the forefront of species research. To maximise the efficacy of conservation efforts, understanding the ecological, physiological, and behavioural requirements of vulnerable species is vital. Technological advances, particularly in remote sensing, enable researchers to continuously monitor movement and behaviours of multiple individuals simultaneously with minimal human intervention. Cheetahs, Acinonyx jubatus, constitute a "vulnerable" species for which only coarse behaviours have been elucidated. The aims of this study were to use animal-attached accelerometers to (1) determine fine-scale behaviours in cheetahs, (2) compare the performances of different devices in behaviour categorisation, and (3) provide a behavioural categorisation framework.
Two different accelerometer devices (CEFAS, frequency: 30 Hz, maximum capacity: ~ 2 g; GCDC, frequency: 50 Hz, maximum capacity: ~ 8 g) were mounted onto collars, fitted to five individual captive cheetahs. The cheetahs chased a lure around a track, during which time their behaviours were videoed. Accelerometer data were temporally aligned with corresponding video footage and labelled with one of 17 behaviours. Six separate random forest models were run (three per device type) to determine the categorisation accuracy for behaviours at a fine, medium, and coarse resolution.
Fine- and medium-scale models had an overall categorisation accuracy of 83-86% and 84-88% respectively. Non-locomotory behaviours were best categorised on both loggers with GCDC outperforming CEFAS devices overall. On a coarse scale, both devices performed well when categorising activity (86.9% (CEFAS) vs. 89.3% (GCDC) accuracy) and inactivity (95.5% (CEFAS) vs. 95.0% (GCDC) accuracy). This study defined cheetah behaviour beyond three categories and accurately determined stalking behaviours by remote sensing. We also show that device specification and configuration may affect categorisation accuracy, so we recommend deploying several different loggers simultaneously on the same individual.
The results of this study will be useful in determining wild cheetah behaviour. The methods used here allowed broad-scale (active/inactive) as well as fine-scale (e.g. stalking) behaviours to be categorised remotely. These findings and methodological approaches will be useful in monitoring the behaviour of wild cheetahs and other species of conservation interest.
物种灭绝是对生物世界最大的威胁之一，危及全球的生物，使保护工作成为物种研究的前沿重点。为了最大限度地提高保护工作的成效，了解濒危物种的生态、生理和行为需求至关重要。技术进步，特别是在遥感方面，使研究人员能够在最少的人为干预下，同时持续监测多个个体的活动和行为。猎豹（Acinonyx jubatus）是一种“易危”物种，目前仅对其粗略行为有所了解。本研究的目的是使用动物佩戴式加速度计：（1）确定猎豹的精细行为；（2）比较不同设备在行为分类中的表现；（3）提供一个行为分类框架。
将两种不同的加速度计设备（CEFAS，频率：30Hz，最大容量：约2g；GCDC，频率：50Hz，最大容量：约8g）安装在项圈上，给五只圈养猎豹佩戴。猎豹在跑道上追逐诱饵，在此期间对它们的行为进行录像。加速度计数据与相应的视频片段在时间上对齐，并标记为17种行为之一。运行六个独立的随机森林模型（每种设备类型三个），以确定在精细、中等和粗略分辨率下行为的分类准确率。
精细和中等尺度模型的总体分类准确率分别为83 - 86%和84 - 88%。两种记录仪对非运动行为的分类效果最佳，总体上GCDC设备优于CEFAS设备。在粗略尺度上，两种设备在对活动（准确率86.9%（CEFAS）对89.3%（GCDC））和不活动（准确率95.5%（CEFAS）对95.0%（GCDC））进行分类时表现良好。本研究定义了猎豹除三类行为之外的行为，并通过遥感准确确定了跟踪行为。我们还表明，设备规格和配置可能会影响分类准确率，因此建议在同一个体上同时部署几种不同的记录仪。
本研究结果将有助于确定野生猎豹的行为。这里使用的方法能够对广泛的（活跃/不活跃）以及精细的（例如跟踪）行为进行远程分类。这些发现和方法将有助于监测野生猎豹和其他具有保护意义的物种的行为。
