Optimizing tropical forest bird surveys using passive acoustic monitoring and high temporal resolution sampling

Estimation of avian biodiversity is a cornerstone measure ecosystem condition. Surveys conducted using autonomous recorders are often more efficient at estimating diversity than traditional point-count surveys. However, there limited research into the optimal temporal resolution for sampling—the trade-off between number samples and sample duration when sampling survey window with fixed effort—despite allowing easy repeat compared to methods. We assess whether additional coverage from high (HTR) sampling, consisting 240 15-s spread randomly across detects higher alpha gamma low (LTR) four 15-min same locations. do so an acoustic dataset collected 29 locations in region very biodiversity—the eastern Brazilian Amazon. find HTR outperforms LTR every metric considered, predicted detect approximately 50% diversity, 10% diversity. This effect primarily driven by increased variation detectability morning, earliest period containing distinct community that under sampled sampling. produced almost times as many false absences species presence. Additionally, incorrectly found 70 (34%) only single forest type they were fact present multiple types, while use reduced this just two (0.9%). When considering independent detections species, detected three uncommon conclude passive-acoustic monitoring-based surveys should be considered primary method richness bird communities tropical forests.