背景:生境结构强烈影响生态位分化,有利于避免捕食者,并推动蝙蝠特定物种的觅食策略。植被结构也是回声定位呼叫特征的强大驱动因素。对蝙蝠如何在其自然栖息地中利用此类结构的精细评估有助于了解栖息地组成如何塑造飞行和声学行为。然而,众所周知,在原地研究它们的物种-栖息地关系是非常困难的。
方法:这里,我们描述了一种结合光检测和测距(LiDAR)来表征三维植被结构和声学跟踪以绘制蝙蝠行为的方法。这使得研究蝙蝠对栖息地的精细利用成为可能,这对于理解蝙蝠的空间生态位隔离至关重要。使用麦克风阵列对蝙蝠进行声学跟踪,并使用自动识别将蝙蝠呼叫分类到蝙蝠行会。我们在森林边缘栖息地的多个LiDAR扫描植被中做到了这一点。数据集在空间上对齐,以计算蝙蝠位置和植被结构之间的距离。
结果:我们的结果证明了将LiDAR与声学跟踪相结合的概念。尽管结合大量的细尺度蝙蝠运动和植被信息会带来挑战,我们通过两个案例研究展示了将这两种方法结合起来的可行性和潜力。第一个显示了树干周围的立体飞行模式,而第二个是在人造光存在的情况下蝙蝠与植被保持的距离。
结论:通过将蝙蝠公会特定的空间行为与植被结构的精确信息相结合,可以详细研究蝙蝠公会对栖息地特征的特定反应。这为解决蝙蝠行为尚未解决的问题提供了可能性,例如生态位隔离或对与自然植被相互作用的非生物因素的响应。这种技术的组合还可以为链接其他发声动物的运动模式和3D空间重建的其他应用铺平道路。
BACKGROUND: Habitat structure strongly influences niche differentiation, facilitates predator avoidance, and drives species-specific foraging strategies of bats. Vegetation structure is also a strong driver of echolocation call characteristics. The fine-scale assessment of how bats utilise such structures in their natural habitat is instrumental in understanding how habitat composition shapes flight- and acoustic behaviour. However, it is notoriously difficult to
study their species-habitat relationship in situ.
METHODS: Here, we describe a methodology combining Light Detection and Ranging (LiDAR) to characterise three-dimensional vegetation structure and acoustic tracking to map bat behaviour. This makes it possible to
study fine-scale use of habitat by bats, which is essential to understand spatial niche segregation in bats. Bats were acoustically tracked with microphone arrays and bat calls were classified to bat guild using automated identification. We did this in multiple LiDAR scanned vegetation plots in forest edge habitat. The datasets were spatially aligned to calculate the distance between bats\' positions and vegetation structures.
RESULTS: Our results are a proof of concept of combining LiDAR with acoustic tracking. Although it entails challenges with combining mass-volumes of fine-scale bat movements and vegetation information, we show the feasibility and potential of combining those two methods through two case studies. The first one shows stereotyped flight patterns of pipistrelles around tree trunks, while the second one presents the distance that bats keep to the vegetation in the presence of artificial light.
CONCLUSIONS: By combining bat guild specific spatial behaviour with precise information on vegetation structure, the bat guild specific response to habitat characteristics can be studied in great detail. This opens up the possibility to address yet unanswered questions on bat behaviour, such as niche segregation or response to abiotic factors in interaction with natural vegetation. This combination of techniques can also pave the way for other applications linking movement patterns of other vocalizing animals and 3D space reconstruction.