Data from: Insectivorous bats respond to vegetation complexity in urban green spaces

Structural complexity is known to determine habitat quality for insectivorous bats, but how bats respond to habitat complexity in highly modified areas such as urban green spaces has been little explored. Furthermore, it is uncertain whether a recently developed measure of structural complexity is as effective as field-based surveys when applied to urban environments. We assessed whether image-derived structural complexity (MIG) was as/more effective than field-based descriptors in this environment, and evaluated the response of insectivorous bats to structural complexity in urban green spaces. Bat activity and species richness were assessed with ultrasonic devices at 180 locations within green spaces in Vienna, Austria. Vegetation complexity was assessed using 17 field-based descriptors and by calculating the mean information gain (MIG) using digital images. Total bat activity and species richness decreased with increasing structural complexity of canopy cover, suggesting maneuverability and echolocation (sensorial) challenges for bat species using the canopy for flight and foraging. The negative response of functional groups to increased complexity was stronger for open space foragers than for edge space foragers. Nyctalus noctula, a species foraging in open space, showed a negative response to structural complexity, whereas Pipistrellus pygmaeus, an edge space forager, was positively influenced by the number of trees. Our results show that MIG is a useful, time- and cost-effective tool to measure habitat complexity that complemented field-based descriptors. Response of bats to structural complexity was group- and species-specific, which highlights the need for manifold management strategies (e.g., increasing or reinstating the extent of ground vegetation cover) to fulfill different species’ requirements, and to conserve insectivorous bats in urban green spaces.

众所周知，结构复杂度是决定食虫蝙蝠栖息地质量的关键因素，但针对城市绿地等高度人工改造区域内蝙蝠对栖息地结构复杂度的响应模式，目前相关研究仍较为匮乏。此外，新近开发的结构复杂度测量手段在城市环境中是否能与传统野外调查法具备同等效用，目前尚无定论。本研究旨在评估图像衍生的结构复杂度指标——平均信息增益（mean information gain, MIG）在该场景下是否不劣于乃至优于野外描述指标，并探究城市绿地中食虫蝙蝠对栖息地结构复杂度的响应规律。研究团队于奥地利维也纳的绿地内180个采样点，利用超声波声学监测设备对蝙蝠活动频次与物种丰富度开展了调查；植被复杂度的评估同时采用两种方式：一是基于17项野外描述指标，二是通过数码图像计算平均信息增益（MIG）。研究发现，蝙蝠总活动频次与物种丰富度均随林冠覆盖结构复杂度的提升而下降，这表明依赖林冠进行飞行与觅食的蝙蝠类群可能面临飞行机动性与回声定位感知层面的双重挑战。不同功能群对复杂度提升的负向响应存在显著差异：开阔空间觅食类群的负向响应强度显著高于边缘空间觅食类群。其中，开阔空间觅食的普通夜蝠（Nyctalus noctula）对结构复杂度呈现负向响应，而边缘空间觅食的侏伏翼（Pipistrellus pygmaeus）则受树木数量的正向影响。本研究结果证实，MIG是一种兼具实用性、省时性与成本效益的栖息地复杂度测量工具，可作为野外描述指标的有效补充。蝙蝠对结构复杂度的响应存在类群与物种特异性，这凸显出需制定多元管理策略（例如增加或恢复地面植被覆盖范围）以满足不同物种的生存需求，进而在城市绿地中实现食虫蝙蝠的生物多样性保护。