Knowing the displacement capacity and mobility patterns of industrially exploited (i.e., fished) marine resources is key to establishing effective conservation management strategies in human-impacted marine ecosystems. Acquiring accurate behavioral information of deep-sea fished ecosystems is necessary to establish the sizes of marine protected areas within the framework of large international societal programs (e.g., European Community H2020, as part of the Blue Growth economic strategy). However, such information is currently scarce, and high-frequency and prolonged data collection is rarely available. Here, we report the implementation of autonomous underwater vehicles and remotely operated vehicles as an aid for acoustic long-baseline localization systems for autonomous tracking of Norway lobster (Nephrops norvegicus), one of the key living resources exploited in European waters. In combination with seafloor moored acoustic receivers, we detected and tracked the movements of 33 tagged lobsters at 400-m depth for more than 3 months. We also identified the best procedures to localize both the acoustic receivers and the tagged lobsters, based on algorithms designed for off-the-shelf acoustic tags identification. Autonomous mobile platforms that deliver data on animal behavior beyond traditional fixed platform capabilities represent an advance for prolonged, in situ monitoring of deep-sea benthic animal behavior at meter spatial scales.

了解工业化开发（即捕鱼）海洋资源的位移能力和迁移方式对于在人类影响的海洋生态系统中建立有效的保护管理策略至关重要。为了在大型国际社会计划（例如，欧洲共同体H2020，作为“蓝色增长”经济战略的一部分）的框架内确定海洋保护区的规模，必须获取准确的深海捕鱼生态系统行为信息。但是，此类信息目前很稀少，而且很少有高频和长时间的数据收集。在这里，我们报告了自动水下航行器和远程操纵车辆的实施情况，以作为对挪威龙虾（Nephrops norvegicus的自动跟踪）的声学长基线定位系统的帮助），这是在欧洲水域开发的重要生物资源之一。结合海底系泊声接收器，我们检测并跟踪了400米深度的33个带标签龙虾的运动，历时超过3个月。我们还基于为现成的声波标签识别设计的算法，确定了定位声波接收器和加标签龙虾的最佳程序。在传统的固定平台功能之外提供动物行为数据的自主移动平台代表了在米级空间范围内长期，原位监测深海底栖动物行为的进步。