The FLEBEFA project investigated how adaptive, motion‑activated lighting on a regional cycle path influences the behaviour of local bat species. The study ran from 1 May 2022 to 31 March 2023 and was organised into four work packages. Work package 1 (AP 1) focused on bioacoustic monitoring, AP 2 (AP 2) on three‑dimensional flight‑path reconstruction, AP 3 (AP 3) on radiometric quantification of light exposure, and AP 4 (AP 4) produced the final report and a dissemination event. The project was carried out by a consortium of academic and technical partners, including specialists in bat ecology, thermal imaging, UAV photometry, and optical simulation, and was funded through a German research grant.

In AP 1, continuous acoustic recordings were analysed to determine how bats responded to the motion‑activated LED lighting. The statistical analysis revealed significant differences between full models and null models, with p‑values ranging from 0.043 to 0.441 for various interaction terms. The results showed that the frequent use of the cycle path by cyclists produced near‑continuous illumination during evening and morning hours, yet bats tolerated this lighting better than at later night times. Guild‑specific responses were evident: open‑space hunters avoided illuminated areas despite being generally light‑tolerant, edge‑foragers were more active in darkness than when lights were on, and forest specialists displayed a comparatively weaker avoidance. The data suggest that the LED system triggers a guild‑specific avoidance reaction that could be mitigated by shortening illumination intervals.

AP 2 employed a dual‑camera thermal imaging system (FLIR Tau 2 LWIR) coupled with a thermal capture module and synchronized with an ultrasonic bat detector (BATLOGGER A+). Over two nights in July and October 2022, the cameras recorded 12 distinct flight paths—nine on the first night and three on the second—when the lights were dark. Three‑dimensional positions were reconstructed using DLTdv5 and MATLAB, while the relative positions of the cameras were calibrated with a 50 cm LED‑equipped rod. Although species identification was not possible due to overlapping echolocation calls, the most common local species, Pipistrellus pipistrellus, was inferred to dominate the dataset. The flight‑path analysis confirmed that bats remained close to the lampposts only when the lights were off, indicating a strong avoidance of illuminated zones.

In AP 3, the light environment was quantified using calibrated Canon 6D and DJI Mini 2 SE UAV cameras. The IQ‑Luminance software converted raw RGB data into luminance values, producing detailed light‑density maps of the study area. These empirical measurements were then incorporated into a virtual lighting landscape created with OpenSCAD and analysed with TracePro’s Monte‑Carlo ray‑tracing engine. By parameterising the model with field data collected on 11 January 2023, the simulation could predict bat exposure to light at arbitrary positions within the environment. This approach provided a comprehensive, spatially explicit assessment of how adaptive lighting alters bat illumination compared to static illumination.

Overall, the project demonstrated that motion‑activated lighting can reduce bat exposure to artificial light, but guild‑specific avoidance behaviours persist. The combination of acoustic monitoring, thermal flight‑path reconstruction, and radiometric modelling offers a robust framework for evaluating wildlife impacts of adaptive lighting systems. The findings will inform future design guidelines for cycle‑path illumination that balance human safety with conservation objectives.