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Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space

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 stru...

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Autores principales: Hermans, Claire, Koblitz, Jens C., Bartholomeus, Harm, Stilz, Peter, Visser, Marcel E., Spoelstra, Kamiel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131301/
https://www.ncbi.nlm.nih.gov/pubmed/37101233
http://dx.doi.org/10.1186/s40462-023-00387-0
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author Hermans, Claire
Koblitz, Jens C.
Bartholomeus, Harm
Stilz, Peter
Visser, Marcel E.
Spoelstra, Kamiel
author_facet Hermans, Claire
Koblitz, Jens C.
Bartholomeus, Harm
Stilz, Peter
Visser, Marcel E.
Spoelstra, Kamiel
author_sort Hermans, Claire
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-023-00387-0.
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spelling pubmed-101313012023-04-27 Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space Hermans, Claire Koblitz, Jens C. Bartholomeus, Harm Stilz, Peter Visser, Marcel E. Spoelstra, Kamiel Mov Ecol Methodology 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-023-00387-0. BioMed Central 2023-04-26 /pmc/articles/PMC10131301/ /pubmed/37101233 http://dx.doi.org/10.1186/s40462-023-00387-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology
Hermans, Claire
Koblitz, Jens C.
Bartholomeus, Harm
Stilz, Peter
Visser, Marcel E.
Spoelstra, Kamiel
Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space
title Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space
title_full Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space
title_fullStr Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space
title_full_unstemmed Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space
title_short Combining acoustic tracking and LiDAR to study bat flight behaviour in three-dimensional space
title_sort combining acoustic tracking and lidar to study bat flight behaviour in three-dimensional space
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10131301/
https://www.ncbi.nlm.nih.gov/pubmed/37101233
http://dx.doi.org/10.1186/s40462-023-00387-0
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