Detecting tropical nocturnal birds using automated audio recordings

ABSTRACT Nocturnal bird assemblages are poorly known in most tropical locations, and information about their presence and behavior is often limited to the results of dawn or dusk surveys. We investigated the use of manual‐ and automatic‐detection methods to identify nocturnal birds in acoustic recordings made at Soberania National Park, Republic of Panama. Five nocturnal species were detected in dusk recordings, and a sixth species (Great Potoo, Nyctibius grandis) was detected only after dark. Automatic data template detectors (DTD's) were developed and used to detect Crested Owls (Lophostrix cristata), Black‐and‐White Owls (Ciccaba nigrolineata), Vermiculated Screech‐Owls (Megasops guatemalae), and Great Potoos. Manual analysis of 300 h of overnight recordings allowed us to quantify DTD performance. Sensitivity, the proportion of known calls of target species identified by DTDs, ranged from 0.17 for Black‐and‐White Owls to 0.79 for Vermiculated Screech‐Owls. Positive predictive value, the proportion of detected sounds that corresponded to the target species, ranged from 0.39 for Black‐and‐White Owls to 0.60 for Crested Owls. Our results demonstrate that a combination of manual and automated analysis of audio recordings can provide a verifiable, systematic method to determine the presence of nocturnal birds in tropical forests, investigate temporal activity, and calculate detection probability.