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CmaxVideoAnalysis_2018_dutycycled_MW.xlsx

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Mendeley Data2024-01-31 更新2024-06-28 收录
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https://figshare.com/articles/dataset/CmaxVideoAnalysis_2018_dutycycled_MW_xlsx/14837841/1
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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. 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. >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. 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

拖曳式摄像机(Towed cameras)被预设为以1080p分辨率、50帧每秒的规格录制视频数据,直至存储介质耗尽或电力中断。2018年该设备采用连续录制模式,但为延长整体录制时长,2019年启用了每5分钟录制30秒的占空比(duty cycle)录制方案。为此研究人员将2018年的连续视频数据下采样为每5分钟一段的30秒视频序列,以匹配2019年的占空比录制规则。 研究团队还将占空比模式下录制的视频所揭示的栖息地利用模式与行为特征,与2018年采集的连续视频数据进行对比,以明确占空比录制方案下可能遗漏的观测信息。所有视频数据均通过VLC媒体播放器(VLC Media Player,版本3.0.8)完成查看。 初始数据评估环节以2倍原生播放速率遍历每个30秒的视频文件,以获取两类核心信息:(i) 环境光照条件:超过50%的视频数据采集于黑暗环境,该场景被定义为“黑障(blackout)”,并进一步区分为日间与夜间两类;(ii) 海底存在情况与栖息地类型: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。 海底栖息地分类遵循欧洲自然信息系统(European Nature Information System, EUNIS;https://eunis.eea.europa.eu)的栖息地分类体系,同时补充涵盖了海底与海面均不可见时的表层及中层水域游泳场景。 研究人员同时记录了其他行为的发生频率与覆盖范围,包括摄食行为(当鲨鱼口部张开时长超过视频总时长的50%,即超过15秒时)、同类个体及其他物种的出现情况,并将观测物种鉴定至尽可能精细的分类学层级。必要时,会调整播放速率至原生速度或减半速,以准确辨识行为变化或其他特殊事件。 为探究姥鲨(basking sharks)对电子标记的初始响应,研究人员计算了尾拍频率(Tail Beat Frequency, TBF),即视频中可见的鲨鱼侧向摆动次数。基于2018年的连续录制视频数据,TBF以每分钟为间隔进行估算(采用30秒的数据片段进行计算);而对于2019年占空比模式下采集的数据,则在标记后的前30分钟内每5分钟估算一次TBF。此外,研究人员还针对每一段对应表层摄食行为的30秒视频序列单独估算了TBF。
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2024-01-31
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