Exploring the application of frequency-dependent acoustic diversity index in human-dominated areas

doi:10.17520/biods.2024286

Abstract

Abstract:

Background & Aims: As a popular tool for rapid biodiversity assessment using passive acoustic monitoring (PAM), acoustic indices have attracted increasing attention in the field of soundscape ecology in recent years, which can help quantify the level of activity or diversity of biological sounds. However, the impact of complicated anthropogenic noise on the numerical results of acoustic indices and the methods for suppressing it have not been well understood. This deficit in understanding poses a challenge for wider applications of acoustic indices in human-dominated areas such as urban green infrastructure.

Methods: In this paper, we investigated the frequency-dependent acoustic diversity index (FADI), a recently proposed acoustic index that is robust to noise, in relation to its application conditions and performance in human-dominated areas. Specifically, three controlled computational experiments were conducted focusing on three aspects including the lower limit of signal-to-noise ratio (SNR), the spatial coverage for bird vocalization monitoring, and the limitations imposed by different types of interferences.

Results: The results of the controlled simulation experiments show that, (1) FADI was significantly robust to noise within the SNR range from −5 dB to 40 dB. (2) The monitoring area of FADI can be expanded by more than 6 times compared to conventional acoustic diversity index (ADI). (3) FADI can effectively suppress the effects of temporally stationary interference such as sounds from lawn mower, rain, and flowing water, but its performance shows a certain degree of degradation in environments with highly time-varying noise.

Conclusions: FADI has a great potential to serve as a stable and reliable tool for rapid biodiversity assessment in human-dominated areas. Furthermore, the numerical robustness of FADI can be improved by use of the microphone array technology that can provide spatial signal processing capability in addition to current time-frequency processing.

Key words: acoustic indices, rapid biodiversity assessment, passive acoustic monitoring, frequency-dependent acoustic diversity index

Lei Chen, Zhiyong Xu, Pukun Su, Xiaotian Lai, Zhao Zhao. Exploring the application of frequency-dependent acoustic diversity index in human-dominated areas[J]. Biodiv Sci, 2024, 32(10): 24286.

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URL: https://www.biodiversity-science.net/EN/10.17520/biods.2024286

https://www.biodiversity-science.net/EN/Y2024/V32/I10/24286

Figures/Tables 12

Fig. 1 Locations of two passive acoustic recorders in Jiangsu Jiuli Lake National Wetland Park. Site A represents a terrestrial sampling point, and site B is surrounded by a lake.

Table 1 Details of bird species and vocalization segments used in this work

物种 Species	鸟鸣声时频分布结构 Sound unit shape	频率范围 Frequency range (kHz)	鸟鸣声片段数量 Number of segments
长尾山雀 Aegithalos glaucogularis	受频率调制类型 Frequency modulated whistles (FM)	5-7	303
灰喜鹊 Cyanopica cyanus	可变频率分量宽带类型 Broadband with varying frequency components (BVF)	1-8	273
田鹀 Emberiza rustica	宽带脉冲类型 Broadband pulses (BP)	5.5-8	280
游隼 Falco peregrinus	强谐波类型 Strong harmonics (SH)	0.5-8	282
棕头鸦雀 Paradoxornis webbianus	恒定频率类型 Constant frequency (CF)	2-5	275

Fig. 2 Temporal waveform (A) and spectrogram (B) of the 60 s-length background noise recording

Fig. 3 Temporal waveforms and normalized power spectra density (PSD) of six interference sound signals. (A) Ambulance siren; (B) Pile-driving noise; (C) Car horn; (D) Lawn mower sound; (E) Rain sound; (F) Flowing water sound.

Fig. 4 Temporal waveforms and spectrograms of noisy simulated recordings at distances of 1 m (A, C) and 191 m (B, D)

Fig. 5 Comparison of ADI (A) and FADI (B) with SNR under different sound unit shapes. ADI, Acoustic diversity index; FADI, Frequency-dependent acoustic diversity index; FM, Frequency modulated whistles; BVF, Broadband with varying frequency components; BP, Broadband pulse; SH, Strong harmonics; CF, Constant frequency; MIXED, Mixed sound unit shapes.

Fig. 6 Comparison of ADI (A) and FADI (B) with distance under different sound unit shapes. ADI, Acoustic diversity index; FADI, Frequency-dependent acoustic diversity index; FM, Frequency modulated whistles; BVF, Broadband with varying frequency components; BP, Broadband pulse; SH, Strong harmonics; CF, Constant frequency; MIXED, Mixed sound unit shapes.

Fig. 7 The ratio of difference with distance under different sound unit shapes. FM, Frequency modulated whistles; BVF, Broadband with varying frequency components; BP, Broadband pulse; SH, Strong harmonics; CF, Constant frequency; MIXED, Mixed sound unit shapes.

Fig. 8 The proportion of time-frequency bins with a value of 1 in each frequency band (pi) with distance in the calculation of ADI (A) and FADI (B)

Fig. 9 The number of time-frequency bins with a value of 1 in each frequency band (Ni) and their sum (Ntotal) with distance in the calculation of ADI (A) and FADI (B)

Fig. 10 The binary spectrogram of FADI at a high SINR condition (SINR = 30 dB) with different interference backgrounds: (A) Ambulance siren; (B) Pile-driving noise; (C) Car horn; (D) Lawn mower sound; (E) Rain sound; (F) Flowing water sound.

Fig. 11 The binary spectrogram of FADI at a low SINR condition (SINR = -5 dB) with different interference backgrounds: (A) Ambulance siren; (B) Pile-driving noise; (C) Car horn; (D) Lawn mower sound; (E) Rain sound; (F) Flowing water sound.

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