Passive acoustic monitoring predicts higher avian diversity metrics than traditional bird surveys across multiple Australian bioregions

Technological advances over the last two decades have seen a large uptake in passive acoustic monitoring (PAM) to supplement traditional biodiversity surveys. To address the growing backlog of acoustic recordings these projects create, multispecies acoustic classifiers are now widely used in favour of manually processing data. Despite the uptake of these technologies, the efficacy of these recognisers needs to be evaluated to ensure they are detecting levels of diversity and community structure similar to traditional surveys. This study compared metrics of avian diversity across eastern Australia, between traditional bird surveys (both dawn, and dawn + nocturnal), and PAM processed using BirdNET, a widely used multi-species classifier. On average, PAM and multi-species classifiers returned higher values for all assessed diversity metrics (Species Richness, Chao2 estimators, Petchey's Functional Diversity, Rao's Q and Phylogenetic Distance), however traditional surveys supplemented with nocturnal surveys returned intermediate values. The efficacy of classifiers varied considerably across the study locations, with the number of incorrect identifications in the tropics substantially higher than those in temperate areas. Both methodologies failed to detect certain taxonomic groups, some threatened species, and detected significantly different avian communities. While these results provide a promising outlook for the future of PAM, it underscores the importance of maintaining traditional surveys as part of biodiversity monitoring, and relying on skilled ornithologists to ensure recorded acoustic data is appropriately interrogated. Furthermore, this study cautions against relying solely on automated classifiers in regions where training data for models is depauperate, such as Australia's tropical and subtropical woodlands. • We compared avian diversity predictions between traditional and PAM surveys. • PAM consistently detected more species sooner than traditional surveys. • BirdNET processed PAM returned higher values for all diversity metrics. • Each survey methods detected unique species, and different community composition. • Combined survey approaches should be considered to maximise species detections.