Hermans Claire, Koblitz Jens C, Bartholomeus Harm, Stilz Peter, Visser Marcel E, Spoelstra Kamiel
Department of Animal Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, The Netherlands.
Max Planck Institute of Animal Behavior, Constance, Germany.
Mov Ecol. 2023 Apr 26;11(1):25. doi: 10.1186/s40462-023-00387-0.
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.
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.
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.
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.
栖息地结构强烈影响生态位分化，有助于躲避捕食者，并驱动蝙蝠特定物种的觅食策略。植被结构也是回声定位叫声特征的重要驱动因素。对蝙蝠在其自然栖息地中如何利用此类结构进行精细尺度评估，有助于理解栖息地组成如何塑造飞行和声学行为。然而，在实地研究它们的物种与栖息地关系非常困难。
在此，我们描述了一种结合激光雷达（LiDAR）来表征三维植被结构和声学跟踪来绘制蝙蝠行为的方法。这使得研究蝙蝠对栖息地的精细尺度利用成为可能，而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，并通过自动识别将蝙蝠叫声分类到蝙蝠类群。我们在森林边缘栖息地的多个激光雷达扫描植被地块中进行了此项研究。将数据集进行空间对齐，以计算蝙蝠位置与植被结构之间的距离。
我们的结果证明了将激光雷达与声学跟踪相结合的概念。尽管将大量精细尺度的蝙蝠运动和植被信息相结合存在挑战，但我们通过两个案例研究展示了这两种方法结合的可行性和潜力。第一个案例展示了伏翼围绕树干的刻板飞行模式，而第二个案例呈现了在有人造光的情况下蝙蝠与植被保持的距离。
通过将蝙蝠类群特定的空间行为与植被结构的精确信息相结合，可以非常详细地研究蝙蝠类群对栖息地特征的特定反应。这为解决关于蝙蝠行为尚未解答的问题开辟了可能性，例如生态位隔离或与自然植被相互作用时对非生物因素的反应。这种技术组合也可以为将其他发声动物的运动模式与三维空间重建相联系的其他应用铺平道路。
