Predicting bird diversity through acoustic indices within the Atlantic Forest biodiversity hotspot

L. P. Gaspar, Marina D. A. Scarpelli, Eliziane G. Oliveira, Rafael Souza Cruz Alves, Arthur Monteiro Gomes, Rafaela Wolf, Rafaela Vitti Ferneda, Silvia Harumi Kamazuka, C. Gussoni, Milton Cezar Ribeiro
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Abstract

The increasing conversion of natural areas for anthropic land use has been a major cause of habitat loss, destabilizing ecosystems and leading to a biodiversity crisis. Passive acoustic sensors open the possibility of remotely sensing fauna on large spatial and temporal scales, improving our understanding of the current state of biodiversity and the effects of human influences. Acoustic indices have been widely used and tested in recent years, with an aim towards understanding the relationship between indices and the acoustic activity of several taxa in different types of environments. However, studies have shown divergent relationships between acoustic indices and the vocal activity of most soniferous taxa. A combination of indices has, in turn, been reported as a promising tool for representing biodiversity in different contexts. We used uni- and bivariate models to test different combinations of 8 common indices in relation to bird assemblage metrics. We recorded twenty-two study sites in Brazil’s Atlantic Forest and three different types of environments in each site (forest, pasture, and swamp). Our results showed that 1) the best acoustic indices for explaining bird richness, abundance, and diversity were Bioacoustic and Acoustic Complexity; 2) the type of environment (forest, pasture, and swamp) influenced the performance of acoustic indices in explaining bird biodiversity, with the highest score model (biggest R2 value) being a combination between Acoustic Diversity and Bioacoustic indices. Our results do support the use of acoustic indices in monitoring the acoustic activity of birds, but combining indices is encouraged since it provided the best results. However, given the divergence we found across environments, we recommend that sets of indices are tested to determine which of them best describe the biodiversity pattern models for a specific habitat. Based on our results, we propose that biodiversity patterns can be predicted through acoustic patterns. However, the level of confidence will depend on the acoustic index used and on focal taxa of interest (i.e., birds, amphibians, insects, and mammals).
通过声学指数预测大西洋森林生物多样性热点地区的鸟类多样性
越来越多的自然地区转为人为土地利用是生境丧失、生态系统不稳定和导致生物多样性危机的一个主要原因。被动声传感器开启了在大空间和时间尺度上遥感动物的可能性,提高了我们对生物多样性现状和人类影响影响的理解。近年来,声学指数得到了广泛的应用和测试,目的是了解不同类型环境中几种分类群的声学活动与指数之间的关系。然而,研究表明声学指标与大多数声科分类群的声乐活动之间存在不同的关系。反过来,指数组合也被报道为在不同背景下代表生物多样性的一种很有前途的工具。我们使用单变量和双变量模型来测试8种常见指数与鸟类组合指标的不同组合。我们在巴西的大西洋森林中记录了22个研究地点,并在每个地点记录了三种不同类型的环境(森林、牧场和沼泽)。结果表明:1)生物声学(Bioacoustic)和声学复杂性(acoustic Complexity)是解释鸟类丰富度、丰度和多样性的最佳声学指标;2)环境类型(森林、牧场和沼泽)对声学指数解释鸟类生物多样性的表现有影响,其中声学多样性与生物声学指数组合的模型得分最高(R2值最大)。我们的研究结果确实支持使用声学指标来监测鸟类的声学活动,但由于它提供了最好的结果,因此鼓励结合指数。然而,考虑到我们在不同环境中发现的差异,我们建议对一系列指标进行测试,以确定哪些指标最能描述特定栖息地的生物多样性模式模型。基于我们的研究结果,我们提出生物多样性模式可以通过声学模式来预测。然而,置信水平将取决于所使用的声学指数和感兴趣的焦点分类群(即鸟类,两栖动物,昆虫和哺乳动物)。
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