Forest edges can be important strongholds for biodiversity and play a crucial role in the protection of forest interiors against edge effects. However, their potential to host biodiversity is dependent on the structure of the forest: Abrupt edges often fail to realise this potential. Yet, methods to accurately characterise and quantify forest edge abruptness are currently lacking. Here, we combine three-dimensional forest structural data with biodiversity monitoring to assess the influence of forest edge structure on habitat suitability. We derived several structural metrics to determine forest edge abruptness using terrestrial laser scanning and applied these to six forest edge transects in Belgium. The local soundscapes were captured using audio recording devices (Audiomoths) and quantified using acoustic indices (AIs) (metrics on the soundscape characteristics). In each transect, the dawn choruses were recorded over a period of a week, both at the edge and the interior of the forest. No correlation between the AIs and bird species richness was found. There were clear differences between transects in the structural metrics and the recorded soundscapes. Some possible relations between both were found. In this proof of concept, we demonstrated innovative techniques to semi-automatically classify forest structure and rapidly quantify soundscape characteristics and found a weak effect of forest edge structure on bird biophony.

中文翻译：

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地面激光扫描的森林边缘结构从声学指数解释鸟类的生物特征

森林边缘是生物多样性的重要据点，在保护森林内部免受边缘效应影响方面发挥着至关重要的作用。然而，它们承载生物多样性的潜力取决于森林的结构：陡峭的边缘往往无法实现这种潜力。然而，目前缺乏准确表征和量化森林边缘突变度的方法。在这里，我们将三维森林结构数据与生物多样性监测相结合，评估森林边缘结构对栖息地适宜性的影响。我们使用地面激光扫描得出了几个结构指标来确定森林边缘的突变度，并将其应用于比利时的六个森林边缘样带。使用音频记录设备（Audiomoths）捕获本地音景，并使用声学指数（AI）（音景特征的度量）进行量化。在每个样带中，在森林边缘和内部都记录了一周的黎明合唱。没有发现人工智能与鸟类物种丰富度之间存在相关性。样线之间的结构指标和记录的声景存在明显差异。发现了两者之间的一些可能的关系。在这个概念验证中，我们展示了半自动分类森林结构和快速量化声景特征的创新技术，并发现森林边缘结构对鸟类生物声音的影响微弱。