Edge effects, abiotic and biotic changes associated with habitat boundaries, are key drivers of community change in fragmented landscapes. Their influence is heavily modulated by matrix composition. With over half of the world’s tropical forests predicted to become forest edge by the end of the century, it is paramount that conservationists gain a better understanding of how tropical biota is impacted by edge gradients. Bats comprise a large fraction of tropical mammalian fauna and are demonstrably sensitive to habitat modification. Yet, knowledge about how bat assemblages are affected by edge effects remains scarce. Capitalizing on a whole-ecosystem manipulation in the Central Amazon, the aims of this study were to i) assess the consequences of edge effects for twelve aerial insectivorous bat species across the interface of primary and secondary forests and ii) investigate if the activity levels of these species differed between the understory and canopy and if they were modulated by distance from the edge. Acoustic surveys were conducted along four 2-km transects each traversing equal parts of primary and ca. 30-year-old secondary forest. Five models were used to assess the changes in the relative activity of forest specialists (three species), flexible forest foragers (three species), and edge foragers (six species). Modelling results revealed limited evidence of edge effects, except for forest specialists in the understory. No significant differences in activity were found between the secondary and primary forest but almost all species exhibited pronounced vertical stratification. Previously defined bat guilds appear to hold here as our study highlights that forest bats are more edge-sensitive than edge-foraging bats. The absence of pronounced edge effects and the comparable activity levels between primary and old secondary forests indicate that old secondary forests can help ameliorate the consequences of fragmentation on tropical aerial insectivorous bats.

Acoustic recordings were collected from the Central Brazilian Amazon, 80 km north of Manaus, at the Biological Dynamics of Forest Fragments Project (BDFFP; 2024’26’’S, 59043’40’’W). Two static detectors (SM2Bat+, Wildlife Acoustics) with omnidirectional microphones (SMX-US Ultrasonic Microphone) were placed in the understory and canopy of 164 sample points. These sample points were spaced 50 m apart along four 2 km transects. Transects were located across two spatially independent sites to reduce site bias. Each transect extended through 1 km of secondary forest and then continued 1 km into the neighbouring primary forest. Surveys were conducted in the dry season of 2013 and the wet season of 2014 to minimise seasonal bias, equating to eight transect visits in total. The understory was defined as extending from the ground to a height of approximately 10 m and the canopy was defined as approximately 30 m from ground level. To ensure the understory and canopy samples were independent, plastic dividers were attached to the detectors to create discrete directional microphones. Additionally, sample points were rotationally sampled so that actively recording detectors were always 250 m apart. Each active detector was programmed to record for 12 hours (18:00-06:00) for three consecutive nights, amounting to 11,808 recording hours. Detectors recorded at 384 kHz sampling rate in full spectrum with 16-bit resolution. The high pass filter was set at 12 kHz (fs/32), with a trigger level of 18SNR. Recordings were split into five-second fragments with at least two distinguishable pulses to define a bat pass which was used as the surrogate measure of bat activity.

Bat passes were automatically classified into species using the classifier for Amazonian bats, developed by López-Baucells et al. (2019). Bat passes that were automatically classified with an accuracy above the 60% threshold were subjected to manual post-validation. The data has been limited to species where additional analysis showed no significant difference in the performance of the acoustic classifier and manual identification of the calls.