首页> 外文会议>OCEANS 2016 MTS/IEEE Monterey >Tracking whales on the Scotian Shelf using passive acoustic monitoring on ocean gliders
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Tracking whales on the Scotian Shelf using passive acoustic monitoring on ocean gliders

机译:使用大洋滑翔机的无源声波监测在斯科蒂架上追踪鲸鱼

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Expanded marine shipping and industrial activity has increased the risk of harmful effects on marine mammals. Quantitative estimates of marine mammal time and space distributions are essential for developing mitigation strategies designed to reduce the risks. Seasonal distributions of key marine mammals can be estimated by deploying passive acoustic monitoring (PAM) hydrophone systems and using the acoustic data to monitor, detect and identify species presence, often in near real-time. Most contemporary PAM deployments in the ocean are stationary and archive the acoustic data for post-recovery analyses after some extended period and are thus not ideal for addressing risk dynamics in near real-time. Substantive expansions of fixed PAM arrays over large ocean expanses can be economically and on-time limiting. Mobile autonomous vehicles now offer the economy of collecting the necessary acoustic and oceanographic data over extended periods and across large swaths of the ocean. They can operate with a high degree of spatial sampling flexibility in near real-time that cannot be easily achieved using fixed PAM arrays. The Whale Habitat and Listening Experiment (WHaLE), funded by the Marine Environmental Observation Prediction And Response Network (MEOPAR) at Dalhousie University, and using Ocean Tracking Network (OTN) autonomous vehicles, is searching for whale habitats and monitoring the distributional patterns of the endangered North Atlantic right whale and other at-risk baleen whales across the shelf waters of Atlantic Canada. This is being achieved through fixed PAM array deployments involving several research partners, as well as the deployment of profiling and surface gliders (autonomous vehicles) equipped with PAM systems capable of detecting and identifying baleen whales that produce sounds in the 10 - 2000 Hz frequency range. When fitted with onboard, automated detection and identification algorithms, the gliders can become powerful tools for near real-time monitoring of the at-risk whales and thus risk mitigation.
机译:扩大的海洋运输和工业活动增加了对海洋哺乳动物产生有害影响的风险。海洋哺乳动物时间和空间分布的定量估计对于制定旨在降低风险的缓解策略至关重要。可以通过部署被动声学监测(PAM)水听器系统并使用声学数据来监视,检测和识别物种的存在(通常是近实时)来估计关键海洋哺乳动物的季节性分布。在海洋中,大多数当代PAM部署都是固定的,并在一段较长的时间后将声学数据存档以进行恢复后的分析,因此对于近实时处理风险动态而言不是理想的选择。固定PAM阵列在大洋中的大量扩张在经济和时间上都可能受到限制。现在,自动驾驶无人驾驶汽车可提供经济的经济效益,可在较长时期内以及大片海洋中收集必要的声学和海洋学数据。它们可以以近乎实时的高度空间采样灵活性进行操作,而使用固定PAM阵列则无法轻松实现。由Dalhousie大学海洋环境观测预测和响应网络(MEOPAR)资助并使用海洋跟踪网络(OTN)自主车辆的鲸鱼栖息地和听力实验(WHaLE)正在寻找鲸鱼栖息地,并监测鲸鱼的栖息地。在大西洋沿岸的加拿大大西洋沿岸,濒临灭绝的北大西洋右鲸和其他有风险的须鲸。这是通过固定的PAM阵列部署(涉及多个研究合作伙伴)以及配备有PAM系统的轮廓和表面滑翔机(自动驾驶汽车)的部署来实现的,该PAM系统能够检测和识别在10-2000 Hz频率范围内产生声音的须鲸。 。配备机载,自动检测和识别算法后,滑翔机将成为强大的工具,可用于对濒危鲸鱼进行近实时监控,从而降低风险。

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