北京中心城区公园中生物声对植被三维结构的响应

doi:10.17520/biods.2025218

生物多样性 ›› 2026, Vol. 34 ›› Issue (4): 25218. DOI: 10.17520/biods.2025218 cstr: 32101.14.biods.2025218

• 研究报告: 动物多样性 • 下一篇

北京中心城区公园中生物声对植被三维结构的响应

白梓彤¹^,²(), 王成¹^,²^,^*()(), 齐志勇³()

¹ 中国林业科学研究院林业研究所, 北京 100091
² 国家林业和草原局城市森林研究中心, 北京 100091
³ 北京大学地球与空间科学学院遥感与地理信息系统研究所, 北京 100871

收稿日期:2025-06-10 接受日期:2025-08-29 出版日期:2026-04-20 发布日期:2026-05-28
通讯作者: 王成
基金资助:
中央级公益性科研院所基本科研业务费专项资金(CAFYBB2020ZB008);国家重点研发计划(2021YFE0193200)

Biophony responses to different vegetation structure in urban central parks of Beijing

Zitong Bai¹^,²(), Cheng Wang¹^,²^,^*()(), Zhiyong Qi³()

¹ Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
² Urban Forestry Research Center, National Forestry and Grassland Administration, Beijing 100091, China
³ Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China

Received:2025-06-10 Accepted:2025-08-29 Online:2026-04-20 Published:2026-05-28
Contact: Cheng Wang
Supported by:
National Non-Profit Research Institutions of the Chinese Academy of Forestry(CAFYBB2020ZB008);National Key Research and Development Program of China(2021YFE0193200)

1. 附录.pdf(876KB)

摘要/Abstract

摘要：

植被三维结构显著影响公园绿地中声景的形成与空间分布, 生物声作为声景的重要组成部分, 能够间接反映区域的生物多样性水平及生态系统健康状况。然而, 目前关于城市公园生物声对植被三维结构特征的响应机制仍缺乏系统的研究。本研究于2024年夏季在北京城市中心公园的52个样点中同步采集了声音数据和背包激光雷达植被数据。基于现场录制的声音计算了6个典型声学指数, 并从激光雷达点云中提取了42个植被结构变量。利用主成分分析和XGBoost-SHAP模型, 识别对生物声产生显著影响的关键植被结构变量及其重要性, 并使用广义加性模型(generalized additive model, GAM)量化边际贡献与生物声特征之间的非线性响应关系。主要结果如下: (1)不同生物声频段的功率谱密度(power spectral density, PSD)夏季的日变化模式存在差异, PSD2-4 kHz与PSD4-6 kHz频段表现出相似的日节律特征, 而PSD6-10 kHz则呈现出错峰鸣唱的时间分布。(2)平均胸径、冠层起伏比和粗糙度指数是驱动各频段生物声表达的重要植被结构因子; 而林下植被结构和冠层覆盖度则对声学复杂度指数(acoustic complexity index, ACI)、声学多样性指数(acoustic diversity index, ADI)和生物声多样性指数(bioacoustic index, BIO)的调控起到关键作用。(3)适度疏透的林分结构与中等尺度的林木胸径更有利于鸟鸣声的增加, 冠层表面形态对昆虫声具有显著调控作用, 冠层起伏比的增加普遍促进生物声的表达。(4)林下植被过密, 寡光区体积过大不利于多声源的共存与传播, 会削弱声景的多样性。本研究系统揭示了植被三维结构对生物声的复杂影响机制, 明确了在生物声营造中的关键植被结构因子, 为城市绿地中的声景优化和生物多样性保护提供了科学依据。

关键词: 声景监测, 声学指数, 激光雷达, 城市森林, 公园

Abstract

Aims: The three-dimensional structure of vegetation is crucial for the formation and spatial distribution of soundscapes in green spaces. Biophony, a key component of soundscapes, indirectly reflects regional biodiversity and ecosystem health. However, the complex relationship between vegetation structure and biophony in urban parks is not well understood.
Methods: During the summer of 2024, we simultaneously collected high-resolution acoustic recordings and backpack LiDAR data from 52 sampling sites in central Beijing parks. Six acoustic indices and 42 vegetation structural variables were calculated from these datasets. We used principal component analysis (PCA) and the XGBoost-SHAP model to identify and assess the importance of key vegetation variables influencing biophony. A generalized additive model (GAM) was then used to quantify the nonlinear relationships between these variables and biophony characteristics.
Results: Our key findings are as follows: (1) The power spectral density (PSD) of different biophony frequency bands showed distinct diurnal patterns. PSD at 2-4 kHz and 4-6 kHz exhibited similar circadian rhythms, while the 6-10 kHz band showed a staggered vocalization pattern. (2) Mean diameter at breast height (DBH), canopy relief ratio (CRR), and rumple index (RI) were key drivers of biophony across all frequency bands. Understory structure and canopy cover (CC) were dominant factors in regulating overall soundscape indices (acoustic complexity index, acoustic diversity index, and bioacoustic index). (3) Forest stands with a euphotic volume over 50% and medium-sized trees were more favorable for bird vocal activity. Increased CRR and canopy surface morphology significantly enhanced biophony, particularly insect sounds. (4) Excessive understory density and a large proportion of oligophotic volume were detrimental to the coexistence and propagation of multiple sound sources, which can reduce soundscape diversity.
Conclusions: This study systematically reveals how three-dimensional vegetation structure influences biophony, identifies key structural factors for biophony patterns, and provides a scientific basis for soundscape optimization and biodiversity conservation in urban green spaces.

Key words: soundscape monitoring, acoustic index, LiDAR, urban forest, parks

白梓彤, 王成, 齐志勇 (2026) 北京中心城区公园中生物声对植被三维结构的响应. 生物多样性, 34, 25218. DOI: 10.17520/biods.2025218.

Zitong Bai, Cheng Wang, Zhiyong Qi (2026) Biophony responses to different vegetation structure in urban central parks of Beijing. Biodiversity Science, 34, 25218. DOI: 10.17520/biods.2025218.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2025218

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图/表 9

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生物声指标 Biophony indices		含义 Explanations
平均功率谱密度 Power spectral density (PSD)	PSD2-4	用于表征频率2-4 kHz中声学群落的能量(Watts/kHz), 多集中分布着低频鸟鸣声(Joo et al., 2007; 赵伊琳等, 2021)。与常见鸣禽的活动与数量相关性较强 This metric represents the acoustic energy (Watts/kHz) of sound communities within the 2-4 kHz frequency range, which primarily corresponds to low-frequency bird vocalizations (Joo et al., 2007; Zhao et al., 2021) and is strongly associated with the activity and abundance of common songbird species
	PSD4-6	用于表征频率4-6 kHz中声学群落的能量(Watts/kHz), 主要分布着中频的鸟鸣声和部分昆虫声。往往与更丰富的鸣禽谱系或活跃的宣告或求偶行为相关 This metric represents the acoustic energy (Watts/kHz) of sound communities within the 4-6 kHz frequency range, which is mainly composed of mid-frequency bird vocalizations along with some insect sounds. It is often associated with a richer assemblage of songbird taxa or heightened levels of territorial or courtship vocal activity
	PSD6-10	用于表征频率6-10 kHz中声学群落的能量(Watts/kHz), 在夏秋季多集中分布着高频虫鸣声(Joo et al., 2007; Pijanowski et al., 2011a), 尤其是以蝉鸣为代表的虫鸣声(Bennet-Clark, 1998) This metric represents the acoustic energy (Watts/kHz) of sound communities within the 6-10 kHz frequency range, which during summer and autumn is predominantly characterized by high-frequency insect vocalizations (Joo et al., 2007; Pijanowski et al., 2011a), particularly cicada calls that dominate this acoustic band (Bennet-Clark, 1998)
声学指数 Acoustic index (AIS)	生物声多样性指数 Bioacoustic index (BIO)	基于soundecology包的bioacoustic_index函数, 计算每个频率(Hz)曲线在最小分贝值(dB)以上的区域, 频率阈值设定在2-11 kHz之间(Boelman et al., 2007)。反映生物声活动的总强度, 较高的BIO值通常表示该区域内生物发声活动频繁, 可能与物种丰富度或个体活跃度相关(Bai et al., 2026) Using the bioacoustic_index function in the soundecology package, the area above the minimum decibel threshold (dB) is calculated for each frequency curve, with the frequency range set between 2-11 kHz (Boelman et al., 2007). This index reflects the overall intensity of biophonic activity; higher BIO values generally indicate more frequent biological vocalizations within the area and may be associated with greater species richness or higher levels of individual activity (Bai et al., 2026)
	声学复杂度指数 Acoustic complexity index (ACI)	基于soundecology包中的acoustic_complexity函数, 频率阈值设置在2-11 kHz之间, FFT=1,024, 通过计算声强的变异性来表征声音群落在时间维度的多变性(Pieretti et al., 2011)。反映声音强度的变化, 较高的ACI值通常表示声音活动复杂度更高, 声音强度变化显著 Using the acoustic_complexity function in the soundecology package, with a frequency threshold set between 2-11 kHz and FFT size of 1,024, this index quantifies temporal variability in sound intensity to characterize the dynamism of acoustic communities (Pieretti et al., 2011). Higher ACI values generally indicate greater complexity in acoustic activity and more pronounced fluctuations in sound intensity
	声学多样性指数 Acoustic diversity index (ADI)	基于soundecology包中的acoustic_diversity函数, 通过Shannon指数来计算光谱复杂性(Pekin et al., 2012)。能较好反映多频段占用的情况, 较高的ADI值表示声音在多个频段中分布更均匀, 而较强的单一声源出现时, ADI下降 Using the acoustic_diversity function in the soundecology package, spectral complexity is quantified based on the Shannon index (Pekin et al., 2012). This index effectively reflects the degree of multi-band occupancy, where higher ADI values indicate that sounds are more evenly distributed across multiple frequency bands, whereas the presence of a dominant single sound source leads to a decrease in ADI

生物声指标 Biophony indices		含义 Explanations
平均功率谱密度 Power spectral density (PSD)	PSD2-4	用于表征频率2-4 kHz中声学群落的能量(Watts/kHz), 多集中分布着低频鸟鸣声(Joo et al., 2007; 赵伊琳等, 2021)。与常见鸣禽的活动与数量相关性较强 This metric represents the acoustic energy (Watts/kHz) of sound communities within the 2-4 kHz frequency range, which primarily corresponds to low-frequency bird vocalizations (Joo et al., 2007; Zhao et al., 2021) and is strongly associated with the activity and abundance of common songbird species
	PSD4-6	用于表征频率4-6 kHz中声学群落的能量(Watts/kHz), 主要分布着中频的鸟鸣声和部分昆虫声。往往与更丰富的鸣禽谱系或活跃的宣告或求偶行为相关 This metric represents the acoustic energy (Watts/kHz) of sound communities within the 4-6 kHz frequency range, which is mainly composed of mid-frequency bird vocalizations along with some insect sounds. It is often associated with a richer assemblage of songbird taxa or heightened levels of territorial or courtship vocal activity
	PSD6-10	用于表征频率6-10 kHz中声学群落的能量(Watts/kHz), 在夏秋季多集中分布着高频虫鸣声(Joo et al., 2007; Pijanowski et al., 2011a), 尤其是以蝉鸣为代表的虫鸣声(Bennet-Clark, 1998) This metric represents the acoustic energy (Watts/kHz) of sound communities within the 6-10 kHz frequency range, which during summer and autumn is predominantly characterized by high-frequency insect vocalizations (Joo et al., 2007; Pijanowski et al., 2011a), particularly cicada calls that dominate this acoustic band (Bennet-Clark, 1998)
声学指数 Acoustic index (AIS)	生物声多样性指数 Bioacoustic index (BIO)	基于soundecology包的bioacoustic_index函数, 计算每个频率(Hz)曲线在最小分贝值(dB)以上的区域, 频率阈值设定在2-11 kHz之间(Boelman et al., 2007)。反映生物声活动的总强度, 较高的BIO值通常表示该区域内生物发声活动频繁, 可能与物种丰富度或个体活跃度相关(Bai et al., 2026) Using the bioacoustic_index function in the soundecology package, the area above the minimum decibel threshold (dB) is calculated for each frequency curve, with the frequency range set between 2-11 kHz (Boelman et al., 2007). This index reflects the overall intensity of biophonic activity; higher BIO values generally indicate more frequent biological vocalizations within the area and may be associated with greater species richness or higher levels of individual activity (Bai et al., 2026)
	声学复杂度指数 Acoustic complexity index (ACI)	基于soundecology包中的acoustic_complexity函数, 频率阈值设置在2-11 kHz之间, FFT=1,024, 通过计算声强的变异性来表征声音群落在时间维度的多变性(Pieretti et al., 2011)。反映声音强度的变化, 较高的ACI值通常表示声音活动复杂度更高, 声音强度变化显著 Using the acoustic_complexity function in the soundecology package, with a frequency threshold set between 2-11 kHz and FFT size of 1,024, this index quantifies temporal variability in sound intensity to characterize the dynamism of acoustic communities (Pieretti et al., 2011). Higher ACI values generally indicate greater complexity in acoustic activity and more pronounced fluctuations in sound intensity
	声学多样性指数 Acoustic diversity index (ADI)	基于soundecology包中的acoustic_diversity函数, 通过Shannon指数来计算光谱复杂性(Pekin et al., 2012)。能较好反映多频段占用的情况, 较高的ADI值表示声音在多个频段中分布更均匀, 而较强的单一声源出现时, ADI下降 Using the acoustic_diversity function in the soundecology package, spectral complexity is quantified based on the Shannon index (Pekin et al., 2012). This index effectively reflects the degree of multi-band occupancy, where higher ADI values indicate that sounds are more evenly distributed across multiple frequency bands, whereas the presence of a dominant single sound source leads to a decrease in ADI

主成分 PC	成分1 Component 1	成分2 Component 2	成分3 Component 3	成分4 Component 4	成分5 Component 5	累积方差 Cumulative variance (%)
PC1	H.p80	H.p70	H.p90	H-mean	VCI	30.67
PC2	H-cv	LAI	H.p20	H.p30	CRR	54.38
PC3	Oligo_LA	Eu_LA	Oligo_volume	DBHm	CC	66.43
PC4	Eu_Depth	Eu_volume	CWm	Filled_VR	Empty_VR	75.93
PC5	UN_TCH	UN_RI	UND	RI	H.p10	82.70

主成分 PC	成分1 Component 1	成分2 Component 2	成分3 Component 3	成分4 Component 4	成分5 Component 5	累积方差 Cumulative variance (%)
PC1	H.p80	H.p70	H.p90	H-mean	VCI	30.67
PC2	H-cv	LAI	H.p20	H.p30	CRR	54.38
PC3	Oligo_LA	Eu_LA	Oligo_volume	DBHm	CC	66.43
PC4	Eu_Depth	Eu_volume	CWm	Filled_VR	Empty_VR	75.93
PC5	UN_TCH	UN_RI	UND	RI	H.p10	82.70

声景指标Soundscape indices	决定系数 Coefficient of determination (R²)	相对均方根误差 Relative root mean square error (rRMSE, %)	相对平均绝对误差 Relative mean absolute error (rMAE, %)
PSD2-4	0.82	8.39	6.13
PSD4-6	0.83	10.25	7.45
PSD6-10	0.88	10.69	7.76
ACI	0.69	19.25	14.10
ADI	0.77	20.37	15.72
BIO	0.78	19.74	25.93

北京中心城区公园中生物声对植被三维结构的响应

Biophony responses to different vegetation structure in urban central parks of Beijing

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