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

PeerJ. 2023 Oct 3:11:e15951. doi: 10.7717/peerj.15951. eCollection 2023.

Abstract

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.

Keywords: Barbastella barbastellus; Barbastelle; Bats; Citizen science; Maternity colonies; Passive acoustic monitoring; ROC curve analysis; Radio-tracking; Survey effort; Woodland.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acoustics
  • Animals
  • Chiroptera*
  • Female
  • Forests
  • Humans
  • Pregnancy

Grants and funding

This work was conducted as part of a PhD funded by the University of Sussex and Vincent Wildlife Trust. Former and current staff of Vincent Wildlife Trust provided support in data collection. Kieran D. O’Malley is a PhD student joint supervised by Prof Fiona Mathews (main supervisor) and Dr. Henry Schofield (secondary supervisor), both of whom contributed to study design and/or data collection.