CmaxVideoAnalysis_2018_continuous_MW.xlsx

Towed cameras were programmed to record video data at 1080p resolution at 50 frames per second until either the memory or power were exhausted. Video recording was continuous in 2018, but a duty cycle of 30 seconds of recording every 5 minutes was used in 2019 to extend the recording duration. The 2018 continuous video data were therefore sub-sampled to 30-second video sequences every 5 minutes to match the duty cycling used in 2019. We also compared habitat use and behaviours revealed using the duty-cycled video with the continuous video data (collected in 2018), to understand what may have been missed in the duty-cycled data.<br>All video data were observed in VLC Media Player (Version 3.0.8). Initial assessment of all data was undertaken by viewing each 30-second video file at twice the native speed to ascertain information on the following: (i) ambient lighting conditions (more than 50% of video data gathered in dark conditions, termed ‘blackout’, separated into day and night) and (ii) seabed presence and habitat type (whether seabed was visible in more than 50% of data and dominant habitat type). Seabed habitats were classified following the European Nature Information System (EUNIS; https://eunis.eea.europa.eu) habitat classification system, and also included surface and mid-water swimming where neither the seabed nor surface were visible. The frequency and extent of other behaviours, including feeding behaviour (when the shark’s mouths was open for more than 50% of the video duration, i.e. &gt;15 seconds), presence of conspecifics and other species were recorded, and species were identified to the finest possible taxonomic level. Where necessary, video data were watched at native or slowed to half speed to ascertain behaviour changes or other events.<br><br>To investigate the initial responses of basking sharks to tagging, Tail Beat Frequency (TBF) was calculated as the number of lateral undulatory movements visible in the video data. Using data collected in 2018, where video recording was continuous, TBF was estimated every minute (using 30 second of data), and every five minutes for the 2019 duty cycled data for the first 30 minutes following tagging. TBF was also estimated for each 30-second video sequence of surface feeding behaviour

拖曳式摄像头（Towed cameras）被预设为以1080p分辨率、50帧每秒的规格录制视频数据，直至存储容量耗尽或电力中断。2018年采用全程连续录制模式，而2019年为延长总录制时长，采用了每5分钟录制30秒的占空比录制策略。因此，我们将2018年的连续视频数据按每5分钟截取一段30秒视频序列的方式进行二次采样，以匹配2019年的占空比录制方案。此外，我们将占空比录制模式下获取的视频所揭示的栖息地利用与行为数据，与2018年采集的连续视频数据进行对比，以明确占空比录制模式下可能遗漏的信息。<br>所有视频数据均通过VLC媒体播放器（VLC Media Player，版本3.0.8）进行查看。首先以2倍原生速率播放每段30秒的视频文件，完成对所有数据的初步评估，以获取两类核心信息：(i) 环境光照条件：若超过50%的采集视频数据处于黑暗环境，则记为‘黑障（blackout）’，并进一步划分为日间与夜间；(ii) 海底存在性与栖息地类型：判断海底是否在超过50%的视频片段中可见，并确定该场景下的优势栖息地类型。海底栖息地参照欧洲自然信息系统（European Nature Information System, EUNIS；https://eunis.eea.europa.eu）的栖息地分类体系进行划分，同时涵盖海底与海面均不可见时的表层及中层水域游泳场景。我们还记录了其他行为的发生频率与覆盖范围，包括摄食行为（当鲨鱼嘴巴张开时长超过视频总时长的50%，即＞15秒时）、同物种个体及其他物种的出现情况，并尽可能将物种鉴定至最精细的分类学层级。必要时，我们会以原生速率或减半速率播放视频，以准确识别行为变化或其他异常事件。<br><br>为研究姥鲨（basking sharks）对标记操作的初始响应，我们通过视频数据计算尾拍频率（Tail Beat Frequency, TBF），即视频中可见的侧向摆动动作总次数。基于2018年的连续录制视频数据，我们每分钟估算一次TBF（采用30秒时长的视频片段进行计算）；而针对2019年占空比录制的数据，我们在标记后的前30分钟内每5分钟估算一次TBF。此外，我们还针对每一段涉及表层摄食行为的30秒视频序列估算了TBF。