• 中国野生脊椎动物鸣声监测与生物声学研究专题 •

### Alpha声学指数效应的meta分析

1. 1.生物多样性与生态工程教育部重点实验室, 北京师范大学生命科学学院, 北京 100875, 中国
2.巴黎萨克雷大学, 法国科学院, 巴黎高科生命与环境工程学院, 系统、生态与进化实验室, 91190, 法国
• 收稿日期:2022-06-30 接受日期:2022-10-10 出版日期:2023-01-20 发布日期:2022-10-13
• 通讯作者: *夏灿玮, E-mail: xiacanwei@bnu.edu.cn
• 基金资助:
国家自然科学基金(32170491)

### A meta-analysis of the effects in alpha acoustic indices

Yanyi Wang1, Yimei Zhang1, Canwei Xia1,*(), Anders Pape Møller2

1. 1. Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing 100875, China
2. Université Paris-Saclay, CNRS, AgroParisTech, Ecologie Systématique et Evolution, Gif-sur-Yvette 91190, France
• Received:2022-06-30 Accepted:2022-10-10 Online:2023-01-20 Published:2022-10-13
• Contact: *Canwei Xia, E-mail: xiacanwei@bnu.edu.cn

Abstract

Background: Many animals such as mammals, birds, amphibians, fishes and arthropods, produce sounds when moving, communicating or sensing their environment. Building upon the rich legacies of bioacoustics and animal communication, the acoustic properties from soundscape are used to monitor and assess the changes in animal communities and related environments. During the past decade, many acoustic indices have been developed and can be divided into two categories, namely alpha acoustic indices and beta acoustic indices. Alpha acoustic indices reflect the information in the recording while beta acoustic indices focus on comparison of differences between different recordings. There are far more empirical studies of the application of alpha acoustic indices than beta acoustic indices. However, patterns in alpha acoustic indices have been contradictory. Before alpha indices can be applied widely, it is necessary to understand better how well they reflect the communities and the environments to be monitored.

Aims: To make general inferences from the mixed evidence, associations between alpha acoustic indices and animal diversity, habitat quality, animal activity were quantitatively reviewed based on the meta-analytic approach.

Methods: Both key word searches and cross-reference searches were conducted, and 2,845 pairs of data related to alpha acoustic indices and other variables were collected from 136 references. For the alpha acoustic indices which were used more than 50 times, the direction of their associations was tested by sign test. Then, the maximum likelihood method was employed to estimate the probability density function of the summary effect (i.e., the correlation coefficient between the alpha acoustic index and other variable). Lastly, the correlation coefficients were calculated based on the probability density function.

Results & Conclusion: Eight commonly used alpha acoustic indices were involved in the study, namely acoustic complexity index (ACI), acoustic entropy index (H) (including two closely related indices: temporal entropy and spectral entropy index), bioacoustic index (BI), normalized difference soundscape index (NDSI), acoustic diversity index (ADI), acoustic evenness index (AEI), acoustic richness index (AR), and number of peaks (NP). Among these acoustic indices, ACI was the most frequently used and positively related with animal diversity, habitat quality, and animal activity. The highest association coefficient appeared at the relationship between ACI and terrestrial animal activity, with the mean effect size 0.53. Besides, the correlation coefficients in other acoustic indices were always trivial, with the effect sizes generally less than 0.30. The only significantly negative relationship occurred between AEI and terrestrial habitat quality, with the mean effect size ‒0.18. The robustness of the main results was thoroughly analyzed, and the strengths and weaknesses of acoustic monitoring through acoustic indices were also discussed. This study is expected to provide a guideline for the selection of alpha acoustic indices in future research.