An acoustic-based method for locating maternity colonies of rare woodland bats

• Published in: PeerJ
• Main Authors: Kieran D. O’Malley, Henry Schofield, Patrick G.R. Wright, Daniel Hargreaves, Tom Kitching, Marina Bollo Palacios, Fiona Mathews
• Format: Article in Journal/Newspaper
• Language: English
• Published: PeerJ Inc. 2023
• Subjects: Barbastella barbastellus; Bats; Citizen science; Passive acoustic monitoring; Woodland; Radio-tracking; Medicine; R; Biology (General); QH301-705.5
• Online Access: https://doi.org/10.7717/peerj.15951; https://doaj.org/article/99b97d652a9046e8b8b4888dc7744f7c

Locating colonies of rare bats can be a time consuming process, as it is often difficult to know where to focus survey effort. However, identifying peaks of bat activity via acoustic monitoring may provide insights into whether a colony is locally present, and help screen out sites with low potential. Using a triage approach, we developed a survey methodology for locating colonies of the woodland-specialist barbastelle bat (Barbastella barbastellus). We investigated whether woodland occupancy by a colony could be predicted by acoustic data, and assessed the influence of survey effort (number of acoustic detectors deployed) on detectability. The methodology was then trialled in citizen science surveys of 77 woodlands, with follow-up radio-tracking surveys by specialists being used to confirm presence or absence. Using Receiver Operating Characteristic (ROC) curve analysis, we found that a threshold of four barbastelle passes recorded by at least one detector within one hour of sunset optimised the balance between the true- and false-positive rates. Subsequently, we found that a minimum survey effort of one detector per 6.25 hectares of woodland was needed to ensure a colony would be detected using this threshold, based on a survey sensitivity of 90%. Radio-tracking surveys in a subset of the woodlands, identified as having a high probability of being occupied by a colony based on acoustic monitoring, confirmed the presence of five previously unknown barbastelle maternity colonies. These results demonstrate that a triage system, in which high probability woodland sites are identified based on acoustic survey data, can be used to prioritise sites for future specialist surveys and conservation action.