Search

Abstract 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. Conclusion 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.

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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

Artificial light at night (ALAN) is considered as a major threat to biodiversity, especially to nocturnal species, as it reduces availability, quality and functionality of habitats. However, its effects on the way species use landscape elements such as rivers are still largely understudied, especially the effect of crossing infrastructure lighting on bridges. These elements are nevertheless key commuting and foraging habitats in heavily urbanised landscapes for several taxa such as bats that are particularly affected by ALAN. We studied the effects of the illumination of facades and undersides of bridges on the relative abundance of pipistrelle bats, on their 3D distribution and their behavioural response (i.e. flight speed) close to bridges. We set‐up an innovative approach based on a microphone‐array to reconstruct positions and flight trajectories in 3D. We studied the effect of lighting on bats in the close proximity of six similar bridges, mostly differentiated by the presence or absence of lighting (3 lit and 3 unlit). All bridges cross the same waterway, within a uniformly and highly urbanized agglomeration (Toulouse, France). We found that bat activity was 1.7 times lower in lit sites. Bats tended to keep a larger distance, and to fly faster close to illuminated bridges. These results suggest that bridge lighting strongly reduces habitat availability and likely connectivity for bats. In that case, results call for switching off the illumination of such bridges crossing riverine ecosystems to preserve their functionality as habitats and corridors for bats. [ABSTRACT FROM AUTHOR]