Data to: Understanding acoustic indices as multi-taxa biodiversity and habitat quality indicators

Acoustic monitoring captures the sound of nature, revealing biodiversity patterns and underlying drivers. Acoustic indices are increasingly used to analyse obtained recordings, but studies show inconsistent performance of acoustic indices as biodiversity indicators. Here, we develop a conceptual framework on what acoustic indices reflect, including sound sources as well as their direct and indirect drivers. We evaluate our framework using recordings from six land use types and old growth forest sites in north-eastern Madagascar. We found the highest correlation (adj. R² > 0.51) of Acoustic Diversity Index and Acoustic Entropy with endemic multi-taxa species richness, canopy closure, and vegetation density. The results suggest that including multiple taxa strengthens the association between the indices and species richness, potentially accounting for unobserved vocalising taxa, and that acoustic indices indicate habitat quality, reflecting underlying indirect and direct drivers affecting biodiversity. Yet, some acoustic indices are limited by saturation and their sensitivity is too low to detect small changes in biodiversity (i.e., loss of few species).

声学监测捕捉自然之声，揭示生物多样性模式及其潜在驱动因素。声学指数在分析所获录音方面日益受到重视，但研究表明，作为生物多样性指标，声学指数的表现存在不一致性。本研究中，我们构建了一个概念框架，探讨声学指数所反映的内容，包括声源及其直接和间接的驱动因素。我们运用东北马达加斯加六种土地利用类型和原始森林地区的录音数据对这一框架进行了评估。我们发现声学多样性指数和声学熵与特有物种多样性、树冠覆盖度和植被密度之间的相关性最高（校正后的R²值大于0.51）。结果表明，纳入多个物种类别能够加强指数与物种多样性的关联，可能解释了未被观察到的发声物种，同时声学指数能够指示生境质量，反映影响生物多样性的潜在直接和间接驱动因素。然而，某些声学指数因饱和度限制而受限，其灵敏度不足，难以检测生物多样性的微小变化（例如，少数物种的丧失）。