Centre for Research into Ecological and Environmental Modelling, University of St Andrews, The Observatory, Buchanan Gardens, Fife, KY16 9LZ, UK.
Biol Rev Camb Philos Soc. 2013 May;88(2):287-309. doi: 10.1111/brv.12001. Epub 2012 Nov 29.
Reliable estimation of the size or density of wild animal populations is very important for effective wildlife management, conservation and ecology. Currently, the most widely used methods for obtaining such estimates involve either sighting animals from transect lines or some form of capture-recapture on marked or uniquely identifiable individuals. However, many species are difficult to sight, and cannot be easily marked or recaptured. Some of these species produce readily identifiable sounds, providing an opportunity to use passive acoustic data to estimate animal density. In addition, even for species for which other visually based methods are feasible, passive acoustic methods offer the potential for greater detection ranges in some environments (e.g. underwater or in dense forest), and hence potentially better precision. Automated data collection means that surveys can take place at times and in places where it would be too expensive or dangerous to send human observers. Here, we present an overview of animal density estimation using passive acoustic data, a relatively new and fast-developing field. We review the types of data and methodological approaches currently available to researchers and we provide a framework for acoustics-based density estimation, illustrated with examples from real-world case studies. We mention moving sensor platforms (e.g. towed acoustics), but then focus on methods involving sensors at fixed locations, particularly hydrophones to survey marine mammals, as acoustic-based density estimation research to date has been concentrated in this area. Primary among these are methods based on distance sampling and spatially explicit capture-recapture. The methods are also applicable to other aquatic and terrestrial sound-producing taxa. We conclude that, despite being in its infancy, density estimation based on passive acoustic data likely will become an important method for surveying a number of diverse taxa, such as sea mammals, fish, birds, amphibians, and insects, especially in situations where inferences are required over long periods of time. There is considerable work ahead, with several potentially fruitful research areas, including the development of (i) hardware and software for data acquisition, (ii) efficient, calibrated, automated detection and classification systems, and (iii) statistical approaches optimized for this application. Further, survey design will need to be developed, and research is needed on the acoustic behaviour of target species. Fundamental research on vocalization rates and group sizes, and the relation between these and other factors such as season or behaviour state, is critical. Evaluation of the methods under known density scenarios will be important for empirically validating the approaches presented here.
可靠地估计野生动物种群的大小或密度对于有效的野生动物管理、保护和生态学非常重要。目前，获得此类估计值的最广泛使用的方法涉及从横截线上观察动物，或者对标记或可识别个体进行某种形式的捕获再捕获。然而，许多物种难以观察，并且不易标记或重新捕获。其中一些物种产生易于识别的声音，为使用被动声学数据来估计动物密度提供了机会。此外，即使对于其他基于视觉的方法可行的物种，被动声学方法也为在某些环境（例如水下或茂密的森林）中提供更大的检测范围提供了潜力，因此潜在的精度更高。自动化的数据收集意味着可以在人类观察员成本过高或过于危险的时间和地点进行调查。在这里，我们介绍了使用被动声学数据进行动物密度估计的概述，这是一个相对较新且快速发展的领域。我们回顾了当前研究人员可用的数据类型和方法，并提供了基于声学的密度估计框架，并用实际案例研究中的示例进行了说明。我们提到了移动传感器平台（例如拖曳声学），但随后重点介绍了涉及固定位置传感器的方法，特别是用于调查海洋哺乳动物的水听器，因为迄今为止基于声学的密度估计研究主要集中在这一领域。其中主要的方法是基于距离抽样和空间显式捕获再捕获的方法。这些方法也适用于其他水生和陆地发声类群。我们的结论是，尽管处于起步阶段，但基于被动声学数据的密度估计可能会成为一种重要的方法，用于调查许多不同的类群，例如海洋哺乳动物、鱼类、鸟类、两栖动物和昆虫，尤其是在需要长时间推断的情况下。还有很多工作要做，有几个潜在的富有成效的研究领域，包括（i）用于数据采集的硬件和软件的开发，（ii）高效、校准、自动化的检测和分类系统的开发，以及（iii）针对这种应用优化的统计方法的开发。此外，需要开发调查设计，并且需要对目标物种的声学行为进行研究。关于发声率和群体大小的基础研究，以及这些与季节或行为状态等其他因素之间的关系的研究至关重要。在已知密度情况下评估这些方法对于验证本文提出的方法的实证有效性非常重要。
