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歌唱的溪流:借助声学指标描述淡水声景

Singing streams: Describing freshwater soundscapes with the help of acoustic indices.

作者信息

Decker Emilia, Parker Brett, Linke Simon, Capon Samantha, Sheldon Fran

机构信息

Australian Rivers Institute Griffith University Nathan Queensland Australia.

出版信息

Ecol Evol. 2020 Apr 16;10(11):4979-4989. doi: 10.1002/ece3.6251. eCollection 2020 Jun.

Abstract

Understanding soundscapes, that is, the totality of sounds within a location, helps to assess nature in a more holistic way, providing a novel approach to investigating ecosystems. To date, very few studies have investigated freshwater soundscapes in their entirety and none across a broad spatial scale.In this study, we recorded 12 freshwater streams in South East Queensland continuously for three days and calculated three acoustic indices for each minute in each stream. We then used principal component analysis of summary statistics for all three acoustic indices to investigate acoustic properties of each stream and spatial variation in their soundscapes.All streams had a unique soundscape with most exhibiting diurnal variation in acoustic patterns. Across these sites, we identified five distinct groups with similar acoustic characteristics. We found that we could use summary statistics of AIs to describe daytimes across streams as well. Most difference in stream soundscapes was observed during the daytime with significant variation in soundscapes both between hours and among sites. We demonstrate how to characterize stream soundscapes by using simple summary statistics of complex acoustic indices. This technique allows simple and rapid investigation of streams with similar acoustic properties and the capacity to characterize them in a holistic and universal way. While we developed this technique for freshwater streams, it is also applicable to terrestrial and marine soundscapes.

摘要

了解声景,即一个地点内声音的总和,有助于以更全面的方式评估自然,为研究生态系统提供一种新方法。迄今为止,很少有研究对淡水声景进行全面调查,且没有一项研究是在广泛的空间尺度上进行的。在本研究中,我们在昆士兰东南部连续三天记录了12条淡水溪流,并为每条溪流中的每分钟计算了三个声学指标。然后,我们对所有三个声学指标的汇总统计数据进行主成分分析,以研究每条溪流的声学特性及其声景的空间变化。所有溪流都有独特的声景,大多数在声学模式上表现出昼夜变化。在这些地点中,我们识别出了五个具有相似声学特征的不同组。我们发现,我们也可以使用声学指标的汇总统计数据来描述不同溪流的白天情况。溪流声景的最大差异出现在白天,在不同小时之间和不同地点之间的声景都有显著变化。我们展示了如何通过使用复杂声学指标的简单汇总统计数据来表征溪流声景。这项技术允许对具有相似声学特性的溪流进行简单快速的调查,并能够以整体和通用的方式对它们进行表征。虽然我们是为淡水溪流开发这项技术的,但它也适用于陆地和海洋声景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/889b/7297790/366bc6da054f/ECE3-10-4979-g001.jpg

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