With the continued adoption of passive acoustic monitoring as a tool for rapid and high-resolution ecosystem monitoring, ecologists are increasingly making use of a suite of acoustic indices to summarise the sonic environment. Though these indices are often reported to well represent some aspect of the biology of an ecosystem, the degree to which they are confounded by various extraneous sonic conditions is largely unknown. We conducted an aural inventory across 23 field sites in Okinawa to identify the number of unique animal sounds present in recordings. Using these values of ‘measured richness’, we then examined how the performance of 11 commonly-used acoustic indices varied across a range of sonic conditions (including in the presence and absence of insect stridulations, audible wind or rain, and human-related sounds). Our analysis identified both well- and poor-performing acoustic indices, as well as those that were particularly sensitive to sonic conditions. Only two indices reflected measured richness across the full range of sonic conditions examined. A few indices were relatively insensitive to extraneous sonic conditions, but no index correlated with measured richness when masked by sound from broadband stridulating insects. Our results demonstrate considerable sensitivity of most commonly used acoustic indices to confounding sonic conditions, highlighting the challenges of working with large acoustic datasets collected in the field. We make practical recommendations for acoustic index use based on study design, with the aim of identifying the suite of acoustic indices with greatest utility as indicators for rapid biodiversity monitoring and management of the world’s natural soundscapes.

随着被动声学监测作为一种快速，高分辨率的生态系统监测工具的继续采用，生态学家越来越多地利用一系列声学指数来总结声环境。尽管经常报告这些指数很好地代表了生态系统生物学的某些方面，但是很大程度上不清楚它们与各种无关的声音条件混杂的程度。我们对冲绳的23个现场进行了听觉清点，以查明记录中存在的独特动物声音的数量。然后，使用“测量的丰富度”的这些值，我们检查了11种常用声学指标的性能在各种声波条件下（包括是否存在昆虫鞭id，可闻风或雨以及与人类相关的声音）如何变化）。我们的分析确定了良好的和不良的声学指数，以及对声音条件特别敏感的声学指数。只有两个指数反映了在所检查的整个声波条件下测得的浓度。一些指标对外部声音条件相对不敏感，但是当被宽带刺杀昆虫的声音掩盖时，没有任何指标与测得的丰度相关。我们的结果表明，最常用的声学指标对混杂的声波条件具有相当高的敏感性，突显了使用现场收集的大型声学数据集所面临的挑战。我们会根据研究设计提出一些实用的声学指标建议，