Alpha声学指数效应的meta分析

doi:10.17520/biods.2022369

生物多样性 ›› 2023, Vol. 31 ›› Issue (1): 22369. DOI: 10.17520/biods.2022369

• 中国野生脊椎动物鸣声监测与生物声学研究专题 • 上一篇下一篇

Alpha声学指数效应的meta分析

王言一¹, 张屹美¹, 夏灿玮¹^,^*(), Anders Pape Møller²

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: *E-mail: xiacanwei@bnu.edu.cn
作者简介:*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. 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: *E-mail: xiacanwei@bnu.edu.cn

摘要/Abstract

摘要：

通过声学指数量化声音的特征反映生物的组成和生境信息, 是一种高效率、低干扰的监测方式。该研究领域在近十多年来得到了快速的发展, 不断有新的声学指数被提出, 同时也有大量的实证研究。声学指数可分为反映录音内信息的alpha声学指数和比较不同录音之间差异的beta声学指数, 其中alpha声学指数的实证研究较多。本文在汇总已有研究数据的基础上进行meta分析, 关注alpha声学指数与动物多样性、生境质量、动物活跃性之间关联的方向和程度。基于文献调研, 本文对8个常用的声学指数进行了总结分析: 声学复杂度指数(acoustic complexity index, ACI)、声学熵指数(acoustic entropy index, H)、生物声学指数(bioacoustic index, BI)、标准化声景差异指数(normalized difference soundscape index, NDSI)、声学多样性指数(acoustic diversity index, ADI)、声学均匀度指数(acoustic evenness index, AEI)、声学丰富度指数(acoustic richness index, AR)和频峰数(number of peaks, NP)。其中, ACI是使用频次最高的声学指数, 与动物多样性、生境质量和动物活跃性均存在正相关的关系。ACI与陆地动物活跃性之间的联系最为密切, 总效应量的均值达到0.53。然而, 其他声学指数与动物多样性、生境质量和动物活跃性之间的关联程度普遍不高, 平均解释力不足10%。此外, AEI与生境质量呈显著负相关的关系(相关系数的均值为-0.18, 符号检验P = 0.001), 是本研究发现的唯一显著负相关的联系。本研究结果可为常用alpha声学指数的选用提供参考依据。

关键词: 声学指数, 生物多样性, 动物活跃性, 生境质量, meta分析

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.

Key words: acoustic index, biodiversity, animal activity, habitat quality, meta-analysis

王言一, 张屹美, 夏灿玮, Anders Pape Møller (2023) Alpha声学指数效应的meta分析. 生物多样性, 31, 22369. DOI: 10.17520/biods.2022369.

Yanyi Wang, Yimei Zhang, Canwei Xia, Anders Pape Møller (2023) A meta-analysis of the effects in alpha acoustic indices. Biodiversity Science, 31, 22369. DOI: 10.17520/biods.2022369.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2022369

https://www.biodiversity-science.net/CN/Y2023/V31/I1/22369

图/表 7

表1 常用alpha声学指数介绍

Table 1 Description of the commonly used alpha acoustic indices

声学指数 Acoustic index	计算公式 Computing formula	描述 Description	参考文献 Reference
声学复杂度指数 Acoustic complexity index (ACI)	$D / ∑ ? I k$	相邻频段窗口音量的变化; 相邻频段音量差的累积(D); 各频段的音量(I_k) The difference in amplitude among samples; summary of intensity difference among adjacent frequency bins (D); intensity in a single frequency bin (I_k)	2011
声学多样性指数 Acoustic diversity index (ADI)	Σp_i×logp_i	基于Shannon指数量化音量(p_i)在不同频段的分布 Reflection of spectral complexity based on Shannon index; relative intensity in each frequency bin (p_i)	2011
声学均匀度指数 Acoustic evenness index (AEI)	$G i n i I$	基于Gini指数量化音量(I)在不同频段的分布 Gini coef?cient with intensity (I) at each frequency bin	2011
声学丰富度指数 Acoustic richness index (AR)	[rank(H_t) × rank(M)]/n²	时间熵(H_t)和音量(M)的乘积, 除以频段数量(n) Product of time entropy (H_t) and intensity (M) divided by the number of bins (n)	2012
生物声学指数 Bioacoustic index (BI)	$∑ ? I k$	特定频段音量(I_k)的汇总 The sum of amplitude (I_k) in particular frequency band	2007
声学熵指数 Acoustic entropy index (H)	H_t × H_f	时间熵(H_t)和频谱熵(H_f)的乘积 Product of time entropy (H_t) and spectral entropy (H_f)	2008
标准化声景差异指数 Normalized difference soundscape index (NDSI)	$b ? a b + a$	生物产生音量(b)与人类产生音量(a)的比率 Ratio of amplitude in biophony (b) and anthropophony (a)	2012
频峰数 Number of peaks (NP)	Σf_i	频谱上频峰(f_i)的数量 The number of frequency peaks (f_i) on spectrum	2013

表1 常用alpha声学指数介绍

Table 1 Description of the commonly used alpha acoustic indices

声学指数 Acoustic index	计算公式 Computing formula	描述 Description	参考文献 Reference
声学复杂度指数 Acoustic complexity index (ACI)	$D / ∑ ? I k$	相邻频段窗口音量的变化; 相邻频段音量差的累积(D); 各频段的音量(I_k) The difference in amplitude among samples; summary of intensity difference among adjacent frequency bins (D); intensity in a single frequency bin (I_k)	2011
声学多样性指数 Acoustic diversity index (ADI)	Σp_i×logp_i	基于Shannon指数量化音量(p_i)在不同频段的分布 Reflection of spectral complexity based on Shannon index; relative intensity in each frequency bin (p_i)	2011
声学均匀度指数 Acoustic evenness index (AEI)	$G i n i I$	基于Gini指数量化音量(I)在不同频段的分布 Gini coef?cient with intensity (I) at each frequency bin	2011
声学丰富度指数 Acoustic richness index (AR)	[rank(H_t) × rank(M)]/n²	时间熵(H_t)和音量(M)的乘积, 除以频段数量(n) Product of time entropy (H_t) and intensity (M) divided by the number of bins (n)	2012
生物声学指数 Bioacoustic index (BI)	$∑ ? I k$	特定频段音量(I_k)的汇总 The sum of amplitude (I_k) in particular frequency band	2007
声学熵指数 Acoustic entropy index (H)	H_t × H_f	时间熵(H_t)和频谱熵(H_f)的乘积 Product of time entropy (H_t) and spectral entropy (H_f)	2008
标准化声景差异指数 Normalized difference soundscape index (NDSI)	$b ? a b + a$	生物产生音量(b)与人类产生音量(a)的比率 Ratio of amplitude in biophony (b) and anthropophony (a)	2012
频峰数 Number of peaks (NP)	Σf_i	频谱上频峰(f_i)的数量 The number of frequency peaks (f_i) on spectrum	2013

图1 文献收集、量化和分析的流程图

Fig. 1 Summary of the process used to collect, quantify and analyze the origin research

图2 不同声学指数使用的频次。声学指数的全称见表1。

Fig. 2 Frequency of use of acoustic index. Abbreviations are the same as denoted in Table 1.

表2 声学指数与动物多样性、生境质量、动物活跃性的关联程度

Table 2 The association between acoustic index and animal diversity, habitat quality, animal activity

声学指数与关联变量 Acoustic index and associated variable^*	使用频次 Frequency of use	符号检验的显著性 P value based on sign test	beta分布的参数1 Parameter 1 in beta distribution	beta分布的参数2 Parameter 2 in beta distribution	效应量的均值 ± 标准差 Summary effect, mean ± SD	效应量的中位数 (下、上四分位数) Summary effect, median (lower and upper quartile)
ACI和陆地动物多样性 ACI and terrestrial animal diversity	127	< 0.001	3.14	1.70	0.30 ± 0.39	0.34 (0.02?0.61)
H和陆地动物多样性 H and terrestrial animal diversity	117	0.005	2.29	1.74	0.14 ± 0.44	0.16 (-0.19?0.49)
NDSI和陆地动物多样性 NDSI and terrestrial animal diversity	81	< 0.001	5.97	4.19	0.18 ± 0.29	0.19 (-0.03?0.39)
ADI和陆地动物多样性 ADI and terrestrial animal diversity	73	0.053	2.73	2.17	0.11 ± 0.41	0.13 (-0.19?0.43)
BI和陆地动物多样性 BI and terrestrial animal diversity	69	< 0.001	7.89	5.76	0.16 ± 0.26	0.16 (-0.02?0.34)
AEI和陆地动物多样性 AEI and terrestrial animal diversity	67	0.864	2.52	2.62	-0.02 ± 0.40	-0.02 (-0.32?0.28)
ACI和陆地生境质量 ACI and terrestrial habitat quality	445	0.001	7.92	7.18	0.05 ± 0.25	0.05 (-0.13?0.22)
BI和陆地生境质量 BI and terrestrial habitat quality	119	0.868	5.83	5.94	-0.01 ± 0.28	-0.01 (-0.21?0.19)
NDSI和陆地生境质量 NDSI and terrestrial habitat quality	116	< 0.001	5.37	4.07	0.14 ± 0.31	0.15 (-0.08?0.36)
ADI和陆地生境质量 ADI and terrestrial habitat quality	103	0.005	3.38	2.62	0.13 ± 0.37	0.14 (-0.14?0.41)
AEI和陆地生境质量 AEI and terrestrial habitat quality	82	0.001	2.39	3.41	-0.18 ± 0.38	-0.20 (-0.47?0.09)
H和陆地生境质量 H and terrestrial habitat quality	59	0.052	5.44	4.45	0.10 ± 0.30	0.11 (-0.11?0.32)
ACI和陆地动物活跃程度 ACI and terrestrial animal activity	86	< 0.001	1.95	0.60	0.53 ± 0.45	0.67 (0.26?0.90)
ACI和水生动物多样性 ACI and aquatic animal diversity	51	0.004	6.72	4.96	0.15 ± 0.28	0.16 (-0.04?0.35)
ACI和水生生境质量 ACI and aquatic habitat quality	75	0.035	11.08	9.41	0.08 ± 0.22	0.08 (-0.07?0.23)
ACI和水生动物活跃程度 ACI and aquatic animal activity	87	< 0.001	9.06	5.97	0.20 ± 0.24	0.22 (0.04?0.38)

表2 声学指数与动物多样性、生境质量、动物活跃性的关联程度

Table 2 The association between acoustic index and animal diversity, habitat quality, animal activity

声学指数与关联变量 Acoustic index and associated variable^*	使用频次 Frequency of use	符号检验的显著性 P value based on sign test	beta分布的参数1 Parameter 1 in beta distribution	beta分布的参数2 Parameter 2 in beta distribution	效应量的均值 ± 标准差 Summary effect, mean ± SD	效应量的中位数 (下、上四分位数) Summary effect, median (lower and upper quartile)
ACI和陆地动物多样性 ACI and terrestrial animal diversity	127	< 0.001	3.14	1.70	0.30 ± 0.39	0.34 (0.02?0.61)
H和陆地动物多样性 H and terrestrial animal diversity	117	0.005	2.29	1.74	0.14 ± 0.44	0.16 (-0.19?0.49)
NDSI和陆地动物多样性 NDSI and terrestrial animal diversity	81	< 0.001	5.97	4.19	0.18 ± 0.29	0.19 (-0.03?0.39)
ADI和陆地动物多样性 ADI and terrestrial animal diversity	73	0.053	2.73	2.17	0.11 ± 0.41	0.13 (-0.19?0.43)
BI和陆地动物多样性 BI and terrestrial animal diversity	69	< 0.001	7.89	5.76	0.16 ± 0.26	0.16 (-0.02?0.34)
AEI和陆地动物多样性 AEI and terrestrial animal diversity	67	0.864	2.52	2.62	-0.02 ± 0.40	-0.02 (-0.32?0.28)
ACI和陆地生境质量 ACI and terrestrial habitat quality	445	0.001	7.92	7.18	0.05 ± 0.25	0.05 (-0.13?0.22)
BI和陆地生境质量 BI and terrestrial habitat quality	119	0.868	5.83	5.94	-0.01 ± 0.28	-0.01 (-0.21?0.19)
NDSI和陆地生境质量 NDSI and terrestrial habitat quality	116	< 0.001	5.37	4.07	0.14 ± 0.31	0.15 (-0.08?0.36)
ADI和陆地生境质量 ADI and terrestrial habitat quality	103	0.005	3.38	2.62	0.13 ± 0.37	0.14 (-0.14?0.41)
AEI和陆地生境质量 AEI and terrestrial habitat quality	82	0.001	2.39	3.41	-0.18 ± 0.38	-0.20 (-0.47?0.09)
H和陆地生境质量 H and terrestrial habitat quality	59	0.052	5.44	4.45	0.10 ± 0.30	0.11 (-0.11?0.32)
ACI和陆地动物活跃程度 ACI and terrestrial animal activity	86	< 0.001	1.95	0.60	0.53 ± 0.45	0.67 (0.26?0.90)
ACI和水生动物多样性 ACI and aquatic animal diversity	51	0.004	6.72	4.96	0.15 ± 0.28	0.16 (-0.04?0.35)
ACI和水生生境质量 ACI and aquatic habitat quality	75	0.035	11.08	9.41	0.08 ± 0.22	0.08 (-0.07?0.23)
ACI和水生动物活跃程度 ACI and aquatic animal activity	87	< 0.001	9.06	5.97	0.20 ± 0.24	0.22 (0.04?0.38)

图3 陆地动物多样性与声学指数ACI (A)、H (B)、NDSI (C)、ADI (D)、BI (E)、AEI (F)相关系数的概率密度函数。声学指数的全称见表1。

Fig. 3 Probability density function about the correlation coefficients between terrestrial animal diversity and acoustic index ACI (A), H (B), NDSI (C), ADI (D), BI (E), AEI (F). Abbreviations are the same as denoted in Table 1.

图4 陆地生境质量与声学指数ACI (A)、BI (B)、NDSI (C)、ADI (D)、AEI (E)、H (F)相关系数的概率密度函数。声学指数的全称见表1。

Fig. 4 Probability density function about the correlation coefficients between terrestrial habitat quality and acoustic index ACI (A), BI (B), NDSI (C), ADI (D), AEI (E), H (F). Abbreviations are the same as denoted in Table 1.

图5 声学复杂度指数(ACI)与陆地动物活跃性(A)、水生动物多样性(B)、水生生境质量(C)、水生动物活跃性(D)相关系数的概率密度函数

Fig. 5 Probability density function about the correlation coefficients between acoustic complexity index (ACI) and terrestrial animal activity (A), aquatic animal diversity (B), aquatic habitat quality (C), aquatic animal activity (D)

参考文献 107

[1]	Abrahams C, Desjonquères C, Greenhalgh J (2021) Pond acoustic sampling scheme: A draft protocol for rapid acoustic data collection in small waterbodies. Ecology and Evolution, 11, 7532-7543. DOI PMID
[2]	Afyouni S, Smith SM, Nichols TE (2019) Effective degrees of freedom of the Pearson’s correlation coefficient under autocorrelation. NeuroImage, 199, 609-625. DOI URL
[3]	Arneill GE, Critchley EJ, Wischnewski S, Jessopp MJ, Quinn JL (2020) Acoustic activity across a seabird colony reflects patterns of within‐colony flight rather than nest density. Ibis, 162, 416-428. DOI
[4]	Barbaro L, Sourdril A, Froidevaux JSP, Cauchoix M, Calatayud F, Deconchat M, Gasc A (2022) Linking acoustic diversity to compositional and configurational heterogeneity in mosaic landscapes. Landscape Ecology, 37, 1125-1143. DOI URL
[5]	Benocci R, Brambilla G, Bisceglie A, Zambon G (2020) Eco-acoustic indices to evaluate soundscape degradation due to human intrusion. Sustainability, 12, 10455. DOI URL
[6]	Benocci R, Roman HE, Bisceglie A, Angelini F, Brambilla G, Zambon G (2022) Auto-correlations and long time memory of environment sound: The case of an urban park in the city of Milan (Italy). Ecological Indicators, 134, 108492.
[7]	Bertucci F, Parmentier E, Lecellier G, Hawkins AD, Lecchini D (2016) Acoustic indices provide information on the status of coral reefs: An example from Moorea Island in the South Pacific. Scientific Reports, 6, 33326. DOI PMID
[8]	Bian Q, Wang C, Hao ZZ (2021) Application of ecoacoustic monitoring in the field of biodiversity science. Chinese Journal of Applied Ecology, 32, 1119-1128. (in Chinese with English abstract) DOI
	[边琦, 王成, 郝泽周 (2021) 生物声音监测研究在生物多样性领域的应用. 应用生态学报, 32, 1119-1128.] DOI
[9]	Boelman NT, Asner GP, Hart PJ, Martin RE (2007) Multi-trophic invasion resistance in Hawaii: Bioacoustics, field surveys, and airborne remote sensing. Ecological Applications, 17, 2137-2144. DOI URL
[10]	Bolgan M, Amorim MCP, Fonseca PJ, Di Iorio L, Parmentier E (2018) Acoustic complexity of vocal fish communities: A field and controlled validation. Scientific Reports, 8, 10559. DOI PMID
[11]	Borenstein M, Hedges LV, Higgins JPT, Rothstein HR (2009) Introduction to Meta-analysis. John Wiley & Sons, West Sussex.
[12]	Borker AL, Buxton RT, Jones IL, Major HL, Williams JC, Tershy BR, Croll DA (2020) Do soundscape indices predict landscape-scale restoration outcomes? A comparative study of restored seabird island soundscapes. Restoration Ecology, 28, 252-260. DOI URL
[13]	Boullhesen M, Vaira M, Barquez RM, Akmentins MS (2021) Evaluating the efficacy of visual encounter and automated acoustic survey methods in anuran assemblages of the Yungas Andean forests of Argentina. Ecological Indicators, 127, 107750.
[14]	Bradfer-Lawrence T, Gardner N, Bunnefeld L, Bunnefeld N, Willis SG, Dent DH (2019) Guidelines for the use of acoustic indices in environmental research. Methods in Ecology and Evolution, 10, 1796-1807. DOI
[15]	Brownlie KC, Monash R, Geeson JJ, Fort J, Bustamante P, Arnould JPY (2020) Developing a passive acoustic monitoring technique for Australia's most numerous seabird, the short-tailed shearwater (Ardenna tenuirostris). Emu, 120, 123-134. DOI URL
[16]	Budka M, Jobda M, Szałański P, Piórkowski H (2022) Acoustic approach as an alternative to human-based survey in bird biodiversity monitoring in agricultural meadows. PLoS ONE, 17, e0266557
[17]	Burivalova Z, Purnomo, Orndorff S, Truskinger A, Roe P, Game ET (2021) The sound of logging: Tropical forest soundscape before, during, and after selective timber extraction. Biological Conservation, 254, 108812.
[18]	Buscaino G, Ceraulo M, Pieretti N, Corrias V, Farina A, Filiciotto F, Maccarrone V, Grammauta R, Caruso F, Giuseppe A, Mazzola S (2016) Temporal patterns in the soundscape of the shallow waters of a Mediterranean marine protected area. Scientific Reports, 6, 34230. DOI PMID
[19]	Butler J, Stanley JA, Butler MJIV (2016) Underwater soundscapes in near-shore tropical habitats and the effects of environmental degradation and habitat restoration. Journal of Experimental Marine Biology and Ecology, 479, 89-96. DOI URL
[20]	Cawley GC, Talbot NLC (2010) On over-fitting in model selection and subsequent selection bias in performance evaluation. Journal of Machine Learning Research, 11, 2079-2107.
[21]	Cohen J (1988) Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Lawrence Erlbaum Associates, Hillsdale.
[22]	Davies BFR, Attrill MJ, Holmes L, Rees A, Witt MJ, Sheehan EV (2020) Acoustic complexity index to assess benthic biodiversity of a partially protected area in the southwest of the UK. Ecological Indicators, 111, 106019.
[23]	Decker E, Parker B, Linke S, Capon S, Sheldon F (2020) Singing streams: Describing freshwater soundscapes with the help of acoustic indices. Ecology and Evolution, 10, 4979-4989. DOI PMID
[24]	Denes SL, Miksis-Olds JL, Mellinger DK, Nystuen JA (2014) Assessing the cross platform performance of marine mammal indicators between two collocated acoustic recorders. Ecological Informatics, 21, 74-80. DOI URL
[25]	Deng BC, Yun YH, Liang YZ, Cao DS, Xu QS, Yi LZ, Huang X (2015) A new strategy to prevent over-fitting in partial least squares models based on model population analysis. Analytica Chimica Acta, 880, 32-41. DOI URL
[26]	Depraetere M, Pavoine S, Jiguet F, Gasc A, Duvail S, Sueur J (2012) Monitoring animal diversity using acoustic indices: Implementation in a temperate woodland. Ecological Indicators, 13, 46-54. DOI URL
[27]	Desjonquères C, Rybak F, Depraetere M, Gasc A, Le Viol I, Pavoine S, Sueur J (2015) First description of underwater acoustic diversity in three temperate ponds. PeerJ, 3, e1393.
[28]	Diepstraten J, Kuenbou JK, Willie J (2022) Datasets for assessing the structure and drivers of biological sounds. Data in Brief, 41, 107930.
[29]	Doser JW, Finley AO, Kasten EP, Gage SH (2020) Assessing soundscape disturbance through hierarchical models and acoustic indices: A case study on a shelterwood logged northern Michigan forest. Ecological Indicators, 113, 106244.
[30]	Dröge S, Martin DA, Andriafanomezantsoa R, Burivalova Z, Fulgence TR, Osen K, Rakotomalala E, Schwab D, Wurz A, Richter T, Kreft H (2021) Listening to a changing landscape: Acoustic indices reflect bird species richness and plot-scale vegetation structure across different land-use types in north-eastern Madagascar. Ecological Indicators, 120, 106929.
[31]	Duarte MHL, Sousa-Lima RS, Young RJ, Farina A, Vasconcelos M, Rodrigues M, Pieretti N (2015) The impact of noise from open-cast mining on Atlantic forest biophony. Biological Conservation, 191, 623-631. DOI URL
[32]	Duarte MHL, Sousa-Lima RS, Young RJ, Vasconcelos MF, Bittencourt E, Scarpelli MDA, Farina A, Pieretti N (2021) Changes on soundscapes reveal impacts of wildfires in the fauna of a Brazilian savanna. Science of the Total Environment, 769, 144988.
[33]	Duval S, Tweedie R (2000) Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56, 455-463. DOI PMID
[34]	Ehnes M, Foote JR (2015) Comparison of autonomous and manual recording methods for discrimination of individually distinctive ovenbird songs. Bioacoustics, 24, 111-121. DOI URL
[35]	Farina A (2019) Ecoacoustics: A quantitative approach to investigate the ecological role of environmental sounds. Mathematics, 7, 21. DOI URL
[36]	Farina A, Ceraulo M, Bobryk C, Pieretti N, Quinci E, Lattanzi E (2015) Spatial and temporal variation of bird dawn chorus and successive acoustic morning activity in a Mediterranean landscape. Bioacoustics, 24, 269-288. DOI URL
[37]	Farina A, Pieretti N (2014) Sonic environment and vegetation structure: A methodological approach for a soundscape analysis of a Mediterranean maqui. Ecological Informatics, 21, 120-132. DOI URL
[38]	Farina A, Pieretti N, Piccioli L (2011) The soundscape methodology for long-term bird monitoring: A Mediterranean Europe case-study. Ecological Informatics, 6, 354-363. DOI URL
[39]	Fuller S, Axel AC, Tucker D, Gage SH (2015) Connecting soundscape to landscape: Which acoustic index best describes landscape configuration? Ecological Indicators, 58, 207-215. DOI URL
[40]	Gage SH, Wimmer J, Tarrant T, Grace PR (2017) Acoustic patterns at the samford ecological research facility in South East Queensland, Australia: The peri-urban supersite of the terrestrial ecosystem research network. Ecological Informatics, 38, 62-75. DOI URL
[41]	Gasc A, Francomano D, Dunning JB, Pijanowski BC (2017) Future directions for soundscape ecology: The importance of ornithological contributions. Auk, 134, 215-228. DOI URL
[42]	Gasc A, Gottesman BL, Francomano D, Jung J, Durham M, Mateljak J, Pijanowski BC (2018) Soundscapes reveal disturbance impacts: Biophonic response to wildfire in the Sonoran Desert Sky Islands. Landscape Ecology, 33, 1399-1415. DOI URL
[43]	Gasc A, Sueur J, Pavoine S, Pellens R, Grandcolas P (2013) Biodiversity sampling using a global acoustic approach: Contrasting sites with microendemics in New Caledonia. PLoS ONE, 8, e65311.
[44]	Gottsberger B, Gruber E (2004) Temporal partitioning of reproductive activity in a neotropical anuran community. Journal of Tropical Ecology, 20, 271-280. DOI URL
[45]	Grade AM, Sieving KE (2016) When the birds go unheard: Highway noise disrupts information transfer between bird species. Biology Letters, 12, 20160113.
[46]	Harris SA, Shears NT, Radford CA (2016) Ecoacoustic indices as proxies for biodiversity on temperate reefs. Methods in Ecology and Evolution, 7, 713-724. DOI URL
[47]	Hayashi K, Erwinsyah, Lelyana VD, Yamamura K (2020) Acoustic dissimilarities between an oil palm plantation and surrounding forests: Analysis of index time series for beta-diversity in South Sumatra, Indonesia. Ecological Indicators, 112, 106086.
[48]	Hill AP, Prince P, Covarrubias EP, Doncaster CP, Snaddon JL, Rogers A (2018) AudioMoth: Evaluation of a smart open acoustic device for monitoring biodiversity and the environment. Methods in Ecology and Evolution, 9, 1199-1211.
[49]	Hopson A, de Szalay F (2021) Alteration of above and below-water soundscapes by roads. Wetlands, 41, 2. DOI URL
[50]	Hou YC, Ding N, Xia CW (2015) Patterns evolution of sound characteristic in the Gruidae. Chinese Journal of Zoology, 50, 31-40. (in Chinese with English abstract)
	[侯雨辰, 丁楠, 夏灿玮 (2015) 鹤科鸟类鸣声特征的演化. 动物学杂志, 50, 31-40.]
[51]	Jahn O, Ganchev TD, Marques MI, Schuchmann KL (2017) Automated sound recognition provides insights into the behavioral ecology of a tropical bird. PLoS ONE, 12, e0169041.
[52]	Jennions MD, Møller AP (2002) Relationships fade with time:A meta-analysis of temporal trends in publication in ecology and evolution. Proceedings of the Royal Society of London B: Biological Sciences, 269, 43-48.
[53]	Jennions MD, Møller AP (2003) A survey of the statistical power of research in behavioral ecology and animal behavior. Behavioral Ecology, 14, 438-445. DOI URL
[54]	Jorge FC, Machado CG, da Cunha Nogueira SS, Nogueira-Filho SLG (2018) The effectiveness of acoustic indices for forest monitoring in Atlantic rainforest fragments. Ecological Indicators, 91, 71-76. DOI URL
[55]	Karaconstantis C, Desjonquères C, Gifford T, Linke S (2020) Spatio-temporal heterogeneity in river sounds: Disentangling micro- and macro-variation in a chain of waterholes. Freshwater Biology, 65, 96-106. DOI URL
[56]	Kasten EP, Gage SH, Fox J, Joo W (2012) The remote environmental assessment laboratory’s acoustic library: An archive for studying soundscape ecology. Ecological Informatics, 12, 50-67.
[57]	Krause B (1993) The niche hypothesis. Soundscape Newsletter, 6, 6-10.
[58]	Lamont T, Williams B, Chapuis L, Prasetya M, Seraphim M, Harding H, May E, Janetski N, Jompa J, Smith D, Radford A, Simpson S (2022) The sound of recovery: Coral reef restoration success is detectable in the soundscape. Journal of Applied Ecology, 59, 742-756. DOI URL
[59]	Lawrence BT, Hornberg J, Haselhoff T, Sutcliffe R, Ahmed S, Moebus S, Gruehn D (2022) A widened array of metrics (WAM) approach to characterize the urban acoustic environment: A case comparison of urban mixed-use and forest. Applied Acoustics, 185, 108387.
[60]	Lineros LHM, Chimènes A, Maille A, Dingess K, Rumiz DI, Adret P (2020) Response of Bolivian gray titi monkeys (Plecturocebus donacophilus) to an anthropogenic noise gradient: Behavioral and hormonal correlates. PeerJ, 8, e10417.
[61]	Livio F, Eleonora C, Olivier F, Katrin L, Nicolas M, Lorien P, David R, Marco G (2021) Passive acoustic monitoring of the endangered African penguin (Spheniscus demersus) using autonomous recording units and ecoacoustic indices. Ibis, 163, 1472-1480. DOI URL
[62]	Lun KH, Zhang YY, Xia CW (2017) Bird diversity monitoring based on sound index. Bulletin of Biology, 52(11), 1-5. (in Chinese) DOI URL
	[伦可环, 张雁云, 夏灿玮 (2017) 基于声音指数的鸟类多样性监测. 生物学通报, 52(11), 1-5.]
[63]	Mammides C, Goodale E, Dayananda SK, Kang L, Chen J (2017) Do acoustic indices correlate with bird diversity? Insights from two biodiverse regions in Yunnan Province, south China. Ecological Indicators, 82, 470-477. DOI URL
[64]	Mazaris AD, Kallimanis AS, Chatzigianidis G, Papadimitriou K, Pantis JD (2009) Spatiotemporal analysis of an acoustic environment: Interactions between landscape features and sounds. Landscape Ecology, 24, 817-831. DOI URL
[65]	Minello M, Calado L, Xavier FC (2021) Ecoacoustic indices in marine ecosystems: A review on recent developments, challenges, and future directions. ICES Journal of Marine Science, 78, 3066-3074. DOI URL
[66]	Mitchell S, Bicknell J, Edwards D, Deere N, Bernard H, Davies Z, Struebig M (2020) Spatial replication and habitat context matters for assessments of tropical biodiversity using acoustic indices. Ecological Indicators, 119, 106717.
[67]	Møller AP (2010) Brain size, head size and behaviour of a passerine bird. Journal of Evolutionary Biology, 23, 625-635. DOI PMID
[68]	Møller AP, Jennions MD (2001) Testing and adjusting for publication bias. Trends in Ecology & Evolution, 16, 580-586. DOI URL
[69]	Mooney TA, Di Iorio L, Lammers M, Lin TH, Nedelec SL, Parsons M, Radford C, Urban E, Stanley J (2020) Listening forward: Approaching marine biodiversity assessments using acoustic methods. Royal Society Open Science, 7, 201287.
[70]	Nakagawa S (2004) A farewell to Bonferroni: The problems of low statistical power and publication bias. Behavioral Ecology, 15, 1044-1045. DOI URL
[71]	Nakagawa S, Poulin R, Mengersen K, Reinhold K, Engqvist L, Lagisz M, Senior AM (2015) Meta-analysis of variation: Ecological and evolutionary applications and beyond. Methods in Ecology and Evolution, 6, 143-152. DOI URL
[72]	Ng ML, Butler N, Woods N (2018) Soundscapes as a surrogate measure of vegetation condition for biodiversity values: A pilot study. Ecological Indicators, 93, 1070-1080. DOI URL
[73]	Papin M, Aznar M, Germain E, Guérold F, Pichenot J (2019) Using acoustic indices to estimate wolf pack size. Ecological Indicators, 103, 202-211. DOI
[74]	Pearse WD, Morales-Castilla I, James LS, Farrell M, Boivin F, Davies TJ (2018) Global macroevolution and macroecology of passerine song. Evolution, 72, 944-960. DOI PMID
[75]	Pérez-Granados C, Traba J (2021) Estimating bird density using passive acoustic monitoring: A review of methods and suggestions for further research. Ibis, 163, 765-783. DOI URL
[76]	Perneger TV (1998) What’s wrong with Bonferroni adjustments. British Medical Journal, 316, 1236-1238. DOI URL
[77]	Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L (2007) Performance of the trim and fill method in the presence of publication bias and between-study heterogeneity. Statistics in Medicine, 26, 4544-4562
[78]	Pieretti N, Danovaro R (2020) Acoustic indexes for marine biodiversity trends and ecosystem health. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 375, 20190447.
[79]	Pieretti N, Farina A, Morri D (2011) A new methodology to infer the singing activity of an avian community: The acoustic complexity index (ACI). Ecological Indicators, 11, 868-873. DOI URL
[80]	Planqué R, Britton NF, Slabbekoorn H (2014) On the maintenance of bird song dialects. Journal of Mathematical Biology, 68, 505-531. DOI PMID
[81]	Priyadarshani N, Marsland S, Castro I (2018) Automated birdsong recognition in complex acoustic environments: A review. Journal of Avian Biology, 49, e01447.
[82]	Quinn JE, Schindler AR, Blake L, Schaffer SK, Hyland E (2022) Loss of winter wonderland: Proximity to different road types has variable effects on winter soundscapes. Landscape Ecology, 37, 381-391. DOI URL
[83]	Rice AN, Soldevilla MS, Quinlan JA (2017) Nocturnal patterns in fish chorusing off the coasts of Georgia and eastern Florida. Bulletin of Marine Science, 93, 455-474. DOI URL
[84]	Ríos-Chelén AA, McDonald AN, Berger A, Perry AC, Krakauer AH, Patricelli GL (2017) Do birds vocalize at higher pitch in noise, or is it a matter of measurement? Behavioral Ecology and Sociobiology, 71, 29. DOI URL
[85]	Roca IT, Proulx R (2016) Acoustic assessment of species richness and assembly rules in ensiferan communities from temperate ecosystems. Ecology, 97, 116-123. PMID
[86]	Roca IT, Van Opzeeland I (2020) Using acoustic metrics to characterize underwater acoustic biodiversity in the Southern Ocean. Remote Sensing in Ecology and Conservation, 6, 262-273. DOI URL
[87]	Ross S (2012) A First Course in Probability, 9th edn. Pearson, New York.
[88]	Ross SRPJ, Friedman NR, Dudley KL, Yoshimura M, Yoshida T, Economo EP (2018) Listening to ecosystems: Data-rich acoustic monitoring through landscape-scale sensor networks. Ecological Research, 33, 135-147.
[89]	Sánchez-Giraldo C, Bedoya CL, Morán-Vásquez RA, Isaza CV, Daza JM (2020) Ecoacoustics in the rain: Understanding acoustic indices under the most common geophonic source in tropical rainforests. Remote Sensing in Ecology and Conservation, 6, 248-261. DOI URL
[90]	Scarpelli MDA, Ribeiro MC, Teixeira CP (2021) What does Atlantic forest soundscapes can tell us about landscape? Ecological Indicators, 121, 107050.
[91]	Schwarzer G, Carpenter J, Rücker G (2010) Empirical evaluation suggests Copas selection model preferable to trim-and-fill method for selection bias in meta-analysis. Journal of Clinical Epidemiology, 63, 282-288. DOI PMID
[92]	Shamon H, Paraskevopoulou Z, Kitzes J, Card E, Deichmann JL, Boyce AJ, McShea WJ (2021) Using ecoacoustics metrices to track grassland bird richness across landscape gradients. Ecological Indicators, 120, 106928.
[93]	Siddagangaiah S, Chen CF, Hu WC, Pieretti N (2019) A complexity-entropy based approach for the detection of fish choruses. Entropy, 21, 977 DOI URL
[94]	Sueur J (2018) Sound Analysis and Synthesis with R. Springer. https://link.springer.com/book/10.1007/978-3-319-77647-7.
[95]	Sueur J, Farina A (2015) Ecoacoustics: The ecological investigation and interpretation of environmental sound. Biosemiotics, 8, 493-502. DOI URL
[96]	Sueur J, Farina A, Gasc A, Pieretti N, Pavoine S (2014) Acoustic indices for biodiversity assessment and landscape investigation. Acta Acustica United with Acustica, 100, 772-781. DOI URL
[97]	Sueur J, Pavoine S, Hamerlynck O, Duvail S (2008) Rapid acoustic survey for biodiversity appraisal. PLoS ONE, 3, e4065.
[98]	Torti V, Valente D, De Gregorio C, Comazzi C, Miaretsoa L, Ratsimbazafy J, Giacoma C, Gamba M (2018) Call and be counted! Can we reliably estimate the number of callers in the indri’s (Indri indri) song? PLoS ONE, 13, e0201664.
[99]	Villanueva-Rivera LJ, Pijanowski BC, Doucette J, Pekin B (2011) A primer of acoustic analysis for landscape ecologists. Landscape Ecology, 26, 1233-1246. DOI URL
[100]	Wallace BC, Lajeunesse MJ, Dietz G, Dahabreh IJ, Trikalinos TA, Schmid CH, Gurevitch J (2017) OpenMEE: Intuitive, open-source software for meta-analysis in ecology and evolutionary biology. Methods in Ecology and Evolution, 8, 941-947. DOI URL
[101]	Whittaker RH (1960) Vegetation of the Siskiyou Mountains, Oregon and California. Ecological Monographs, 30, 279-338. DOI URL
[102]	Wiley RH, Richards DG (1978) Physical constraints on acoustic communication in the atmosphere: Implications for the evolution of animal vocalizations. Behavioral Ecology and Sociobiology, 3, 69-94. DOI URL
[103]	Xia CW, Lin XL, Liu W, Lloyd H, Zhang YY (2012) Acoustic identification of individuals within large avian populations: A case study of the brownish-flanked bush warbler, South-Central China. PLoS ONE, 7, e42528.
[104]	Xing XY, Slabbekoorn H, Campbell J, Li F, Ma JZ (2017) Distinct song parts of the endemic marsh grassbird of China vary with latitude and climate among migratory and sedentary populations. Evolutionary Ecology, 31, 63-76. DOI URL
[105]	Zhao Y, Shen XL, Li S, Zhang YY, Peng RH, Ma KP (2020) Progress and outlook for soundscape ecology. Biodiversity Science, 28, 806-820. (in Chinese with English abstract) DOI
	[赵莹, 申小莉, 李晟, 张雁云, 彭任华, 马克平 (2020) 声景生态学研究进展和展望. 生物多样性, 28, 806-820.] DOI
[106]	Zhao YL, Bai ZT, Wang C, Yin LQ, Sun ZK, Zhang C, Sun RL, Xu S, Bian Q, Sun BQ (2021) Urban parks soundscape and its relationship with vegetation structure: A pilot study. Acta Ecologica Sinica, 41, 8040-8051. (in Chinese with English abstract)
	[赵伊琳, 白梓彤, 王成, 殷鲁秦, 孙振凯, 张昶, 孙睿霖, 徐诗, 边琦, 孙宝强 (2021) 城市公园春季声景观与植被结构的关系. 生态学报, 41, 8040-8051.]
[107]	Zwart MC, Baker A, McGowan PJK, Whittingham MJ (2014) The use of automated bioacoustic recorders to replace human wildlife surveys: An example using nightjars. PLoS ONE, 9, e102770.

Alpha声学指数效应的meta分析

A meta-analysis of the effects in alpha acoustic indices

RichHTML

PDF (PC)

补充材料

可视化

摘要/Abstract

引用本文

使用本文

图/表 7

参考文献 107

相关文章 15

编辑推荐

Metrics

本文评价

[1]	何智荣, 吴思雨, 时莹莹, 王雨婷, 江艺欣, 张春娜, 赵娜, 王苏盆. 壶菌及其感染对两栖动物种群影响的研究现状与挑战[J]. 生物多样性, 2024, 32(2): 23274-.
[2]	彭昀月, 靳彤, 张小全. 生物多样性信用的概念、原则、交易和挑战[J]. 生物多样性, 2024, 32(2): 23300-.
[3]	吴相獐, 雷富民, 单壹壹, 于晶. 上海城市公园苔藓植物多样性分布格局及其环境影响因子[J]. 生物多样性, 2024, 32(2): 23364-0.
[4]	张飞飞, 杨天凤, 陈莉荣, 刘冬梅, 杨柳园, 杨杜宇, 鞠鹏, 陆露. 被子植物花粉颜色多样性及应用研究进展[J]. 生物多样性, 2024, 32(1): 23346-.
[5]	刘昱齐, 刘晶岚, 樊晓丽, 胡宜深, 郭鸿筱, 薛凡. 鸟鸣多样性感知与声景感知恢复性: 鸟鸣音频和科普的干预[J]. 生物多样性, 2024, 32(1): 23230-.
[6]	韩丽霞, 王永健, 刘宣. 外来物种入侵与本土物种分布区扩张的异同[J]. 生物多样性, 2024, 32(1): 23396-.
[7]	陈进. 《昆明-蒙特利尔全球生物多样性框架》与国家植物园体系建设[J]. 生物多样性, 2023, 31(9): 23257-.
[8]	冯晨, 张洁, 黄宏文. 统筹植物就地保护与迁地保护的解决方案: 植物并地保护(parallel situ conservation)[J]. 生物多样性, 2023, 31(9): 23184-.
[9]	陈慧妹, 李文军, 邱娟, 马占仓, 李波, 杨宗宗, 闻志彬, 孟岩, 曹秋梅, 邱东, 刘丹辉, 金光照. 新疆野生维管植物名录[J]. 生物多样性, 2023, 31(9): 23124-.
[10]	罗正明, 刘晋仙, 张变华, 周妍英, 郝爱华, 杨凯, 柴宝峰. 不同退化阶段亚高山草甸土壤原生生物群落多样性特征及驱动因素[J]. 生物多样性, 2023, 31(8): 23136-.
[11]	邓晶, 李艺, 侯一蕾. 城市生物多样性保护: 基于中欧对比视角下的经验借鉴[J]. 生物多样性, 2023, 31(8): 23070-.
[12]	杜红. “物种”与“个体”: 究竟谁是生物多样性保护的恰当对象?[J]. 生物多样性, 2023, 31(8): 23140-.
[13]	朱旭, 李嘉奇. 全球协同落实《昆明-蒙特利尔全球生物多样性框架》的挑战与出路: 基于SFIC模型的分析[J]. 生物多样性, 2023, 31(8): 23167-.
[14]	邢超, 林依, 周智强, 赵联军, 蒋仕伟, 林蓁蓁, 徐基良, 詹祥江. 基于DNA条形码技术构建王朗国家级自然保护区陆生脊椎动物遗传资源数据库及物种鉴定[J]. 生物多样性, 2023, 31(7): 22661-.
[15]	苏荣菲, 陈睿山, 郭晓娜. 城市社区更新中生物多样性的保护策略: 以上海市长宁区生境花园为例[J]. 生物多样性, 2023, 31(7): 23118-.