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High-resolution non-invasive animal tracking and reconstruction of local environment in aquatic ecosystems

机译:水生生态系统中当地环境的高分辨率非侵入性动物跟踪和重建

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摘要

Understanding the movement and behaviour of animals in their natural habitats is the ultimate goal of behavioural and movement ecology. By situating our studies in the natural world, we have the potential to uncover processes of selection acting on behaviour in natural populations. The ongoing advance of animal tracking and biologging brings the opportunity to revolutionize not only the scale of data collected from wild systems, but also the types of questions that can subsequently be answered. Incorporating geographical data has already given insights, for example, into the homing behaviour of reef fish, migratory patterns of birds, or the breeding site specificity of sea turtles [1–3]. Great advances in systems biology have further been made through the study of movement ecology, for example understanding the decision-making processes at play within primate groups manoeuvring through difficult terrain or the collective sensing of birds traversing their physical environment [4, 5]. Unravelling these aspects of animal movement can vastly improve management strategies [6, 7], for example in the creation of protected areas that incorporate bird migratory routes [8] or by reducing by-catch with dynamic habitat usage models of marine turtles [9].
机译:了解动物在自然栖息地中的运动和行为是行为和运动生态的最终目标。通过在本自然界中的研究中,我们有可能发现对自然群体行为的选择进程。动物跟踪和生物制度的持续进展使得有机会彻底改变从野生系统中收集的数据规模,而且还可以随后回答的问题类型。例如,纳入地理数据已经熟悉了珊瑚礁鱼,鸟类的迁移模式的归巢行为,或海龟的繁殖现场特异性[1-3]。通过运动生态学进一步研究了系统生物学的巨大进展,例如了解通过困难的地形操纵的灵长类动物组中游戏中的决策过程或穿越其物理环境的鸟类的集体感知[4,5]。揭开动物运动的这些方面可以大大改善管理策略[6,7],例如在创建包含鸟迁移路线的受保护区域[8]或通过海龟的动态栖息地使用模型减少逐个捕获[9] 。

著录项

  • 期刊名称 Movement Ecology
  • 作者单位
  • 年(卷),期 2020(-1),-1
  • 年度 2020
  • 页码 -1
  • 总页数 12
  • 原文格式 PDF
  • 正文语种
  • 中图分类 G804.5;
  • 关键词

    机译:3D跟踪;集体行为;水生生态系统;计算机视觉;从运动中的结构;机器学习;
  • 入库时间 2022-08-21 12:13:40

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