TY - JOUR
T1 - Sampling flying bats with thermal and near-infrared imaging and ultrasound recording
T2 - Hardware and workflow for bat point counts
AU - Darras, Kevin
AU - Yusti, Ellena
AU - Knorr, Andreas
AU - Huang, Joe Chun Chia
AU - Kartono, Agus Priyono
AU - Ilham,
N1 - Publisher Copyright:
© 2022 Darras K et al.
PY - 2022
Y1 - 2022
N2 - Bat communities can usually only be comprehensively monitored by combining ultrasound recording and trapping techniques. Here, we propose bat point counts, a novel, single method to sample all flying bats. We designed a sampling rig that combines a thermal scope to detect flying bats and their flight patterns, an ultrasound recorder to identify echolocating bat calls, and a near-infrared camera and LED illuminator to photograph bat morphology. We evaluated the usefulness of the flight pattern information, echolocation call recordings, and near-infrared photographs produced by our sampling rig to determine a workflow to process these heterogenous data types. We present a conservative workflow to enable taxonomic discrimination and identification of bat detections. Our sampling rig and workflow allowed us to detect both echolocating and non-echolocating bats and we could assign 84% of the detections to a guild. Subsequent identification can be carried out with established methods such as taxonomic keys and call libraries, based on the visible morphological features and echolocation calls. Currently, a higher near-infrared picture quality is required to resolve more detailed diagnostic morphology, but there is considerable potential to extract more information with higher-intensity illumination. This is the first proof-of-concept for bat point counts, a method that can passively sample all flying bats in their natural environment.
AB - Bat communities can usually only be comprehensively monitored by combining ultrasound recording and trapping techniques. Here, we propose bat point counts, a novel, single method to sample all flying bats. We designed a sampling rig that combines a thermal scope to detect flying bats and their flight patterns, an ultrasound recorder to identify echolocating bat calls, and a near-infrared camera and LED illuminator to photograph bat morphology. We evaluated the usefulness of the flight pattern information, echolocation call recordings, and near-infrared photographs produced by our sampling rig to determine a workflow to process these heterogenous data types. We present a conservative workflow to enable taxonomic discrimination and identification of bat detections. Our sampling rig and workflow allowed us to detect both echolocating and non-echolocating bats and we could assign 84% of the detections to a guild. Subsequent identification can be carried out with established methods such as taxonomic keys and call libraries, based on the visible morphological features and echolocation calls. Currently, a higher near-infrared picture quality is required to resolve more detailed diagnostic morphology, but there is considerable potential to extract more information with higher-intensity illumination. This is the first proof-of-concept for bat point counts, a method that can passively sample all flying bats in their natural environment.
KW - Bat
KW - Ecoacoustics
KW - Ecology
KW - Near-infrared
KW - Night vision
KW - Point count
KW - Thermal imaging
UR - http://www.scopus.com/inward/record.url?scp=85120177701&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85120177701&partnerID=8YFLogxK
U2 - 10.12688/f1000research.51195.2
DO - 10.12688/f1000research.51195.2
M3 - Article
C2 - 35436082
AN - SCOPUS:85120177701
SN - 2046-1402
VL - 10
JO - F1000Research
JF - F1000Research
M1 - 189
ER -