Spatial dynamics of soundscapes and biodiversity in a semi-arid landscape

Context Semi-arid landscapes are naturally heterogeneous with several factors influencing this variation. Fauna responses and adaptations vary in xeric environments, and the scale of observation is important. Biodiversity monitoring at several scales can be challenging, and acoustics are an alternative to this issue. Objectives We investigated how audible biodiversity is influenced by environmental factors (e.g.: vegetation metrics, climatic variables, etc.) across a fine spatial scale, aiming to provide a better understanding of the variation in audible species across recording locations placed close together. These results will improve the current knowledge on ecoacoustics as a tool for measuring ecological processes in this biome, and better inform conservation plans. Methods We collected data in the semi-arid region in Queensland, Australia placing 24 recorders 200 m apart for 48 h. We also sampled environmental attributes (e.g.: temperature and vegetation structure metrics) and used acoustic indices in a time-series algorithm to categorise sound into classes. Bird species and feeding guilds were also identified. Results We found significant differences between proximate sensors, demonstrating that soundscape differences occur across fine spatial scales. Birds and insects were the predominant biophonic sound observed and both groups were associated with shrub cover and subcanopy height. Environments with higher shrub and subcanopy cover had a higher percentage of all birds’ feeding guilds and insects. Sixty-three bird species were identified, including a threatened bird species in Queensland. Conclusion We show biodiversity is influenced by vegetation heterogeneity across fine spatial scales in semi-arid regions, identifying which attributes sustain higher levels of biodiversity activity. Our study reveals the practicality of acoustic surveys for this biodiversity monitoring by covering a large area in 48 h. However, we caution that scale is an important consideration when designing surveys.