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鱼类发声群落的声学复杂度:现场和受控验证。

Acoustic Complexity of vocal fish communities: a field and controlled validation.

机构信息

Laboratoire de Morphologie Fonctionnelle et Evolutive, Institut de Chimie-B6C, Université de Liège, Liège, Belgium.

MARE, Marine and Environmental Sciences Centre, ISPA - Instituto Universitário, Lisbon, Portugal.

出版信息

Sci Rep. 2018 Jul 12;8(1):10559. doi: 10.1038/s41598-018-28771-6.

DOI:10.1038/s41598-018-28771-6
PMID:30002420
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6043554/
Abstract

The Acoustic Complexity Index (ACI) is increasingly applied to the study of biodiversity in aquatic habitats. However, it remains unknown which types of acoustic information are highlighted by this index in underwater environments. This study explored the robustness of the ACI to fine variations in fish sound abundance (i.e. number of sounds) and sound diversity (i.e. number of sound types) in field recordings and controlled experiments. The ACI was found to be sensitive to variations in both sound abundance and sound diversity, making it difficult to discern between these variables. Furthermore, the ACI was strongly dependent on the settings used for its calculation (i.e. frequency and temporal resolution of the ACI algorithm, amplitude filter). Care should thus be taken when comparing ACI absolute values between studies, or between sites with site-specific characteristics (e.g. species diversity, fish vocal community composition). As the use of ecoacoustic indices presents a promising tool for the monitoring of vulnerable environments, methodological validations like those presented in this paper are of paramount importance in understanding which biologically important information can be gathered by applying acoustic indices to Passive Acoustic Monitoring data.

摘要

声学复杂度指数(ACI)越来越多地应用于水生生物多样性的研究。然而,目前尚不清楚该指数在水下环境中突出了哪种类型的声学信息。本研究通过野外录音和控制实验,探究了 ACI 对鱼类声音丰富度(即声音数量)和声音多样性(即声音类型数量)细微变化的稳健性。结果发现,ACI 对声音丰富度和声音多样性的变化均敏感,因此难以区分这些变量。此外,ACI 强烈依赖于其计算所用的设置(即 ACI 算法的频率和时间分辨率、幅度滤波器)。因此,在比较不同研究或具有特定地点特征(如物种多样性、鱼类发声群落组成)的地点之间的 ACI 绝对值时应谨慎。由于生态声学指数的使用为监测脆弱环境提供了一种有前途的工具,因此,像本文所呈现的方法验证对于理解通过将声学指数应用于被动声学监测数据可以收集哪些具有生物学意义的信息至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/ddb244adf9ff/41598_2018_28771_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/87b7cf7d8cba/41598_2018_28771_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/b6852a06fbb7/41598_2018_28771_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/716ac8be459b/41598_2018_28771_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/f622390ac0f1/41598_2018_28771_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/08a8e27b7c90/41598_2018_28771_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/ddb244adf9ff/41598_2018_28771_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/87b7cf7d8cba/41598_2018_28771_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/b6852a06fbb7/41598_2018_28771_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/716ac8be459b/41598_2018_28771_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/f622390ac0f1/41598_2018_28771_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/08a8e27b7c90/41598_2018_28771_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/07b2/6043554/ddb244adf9ff/41598_2018_28771_Fig6_HTML.jpg

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