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探究声学指标与生态系统功能之间的潜在关系:以昆虫食草为检验案例。

Exploring potential relationships between acoustic indices and ecosystem functions: a test on insect herbivory.

机构信息

Botany Department, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland.

State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.

出版信息

Oecologia. 2024 Apr;204(4):875-883. doi: 10.1007/s00442-024-05536-9. Epub 2024 Apr 6.

Abstract

Biodiversity loss is a global concern. Current technological advances allow the development of novel tools that can monitor biodiversity remotely with minimal disturbance. One example is passive acoustic monitoring (PAM), which involves recording the soundscape of an area using autonomous recording units, and processing these data using acoustic indices, for example, to estimate the diversity of various vocal animal groups. We explored the hypothesis that data obtained through PAM could also be used to study ecosystem functions. Specifically, we investigated the potential relationship between seven commonly used acoustic indices and insect leaf herbivory, measured as total leaf damage and as the damage from three major insect feeding guilds. Herbivory was quantified on seedlings in 13 plots in four subtropical forests in south China, and acoustic data, representing insect acoustic complexity, were obtained by recording the evening soundscapes in those same locations. Herbivory levels correlated positively with the acoustic entropy index, commonly reported as one of the best-performing indices, whose high values indicate higher acoustic complexity, likely due to greater insect diversity. Relationships for specific feeding guilds were moderately stronger for chewers, indicating that the acoustic indices capture some insect groups more than others (e.g., chewers include soniferous taxa such as crickets, whereas miners are mostly silent). Our findings suggest that the use of PAM to monitor ecosystem functions deserves to be explored further, as this is a research field with unexplored potential. Well-designed targeted studies could help us better understand how to best use novel technologies to monitor ecosystem functions.

摘要

生物多样性的丧失是一个全球性的问题。当前的技术进步使得开发新型工具成为可能,这些工具可以在最小干扰的情况下远程监测生物多样性。一个例子是被动声学监测(PAM),它涉及使用自主录音单元记录一个区域的声音景观,并使用声学指数对这些数据进行处理,例如,估计各种发声动物群体的多样性。

我们探讨了这样一个假设,即通过 PAM 获得的数据也可以用于研究生态系统功能。具体来说,我们调查了七个常用声学指数与昆虫叶片取食之间的潜在关系,通过测量三种主要昆虫取食类群的总叶片损伤和叶片损伤来进行量化。在中国南方的四个亚热带森林中的 13 个样地中,对幼苗进行了取食,通过在同一地点记录傍晚的声音景观,获得了代表昆虫声音复杂性的声学数据。取食水平与声学熵指数呈正相关,该指数通常被报告为表现最好的指数之一,其高值表明更高的声学复杂性,可能是由于昆虫多样性更高。对于咀嚼者来说,特定取食类群的关系更为强烈,这表明声学指数比其他指数更能捕捉某些昆虫群体(例如,咀嚼者包括蟋蟀等发声类群,而矿工则大多是沉默的)。

我们的研究结果表明,使用 PAM 监测生态系统功能值得进一步探索,因为这是一个具有未开发潜力的研究领域。精心设计的有针对性的研究可以帮助我们更好地理解如何最好地利用新技术来监测生态系统功能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b83b/11062954/12fdceaa9a1e/442_2024_5536_Fig1_HTML.jpg

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