How to optimize passive acoustic monitoring of forest birds to support rapid biodiversity assessments?

Stockholm

2024

2105

Bandaufführung

40005292

Biodiversity in forests include an overwhelming number of species and their composition is driven by a multitude of factors. To support effective management decisions, conservation efforts and restoration strategies, many research projects are dedicated to developing rapid biodiversity assessment methods that yield reliable data. These projects aim to identify key indicator species, including various bird species as they provide ecosystem services or exhibit a pronounced habitat association with specific forest characteristics. Acoustic monitoring techniques are generally more important in forest bird surveys than visual identification, but the courtship of some migratory species is comparably short and their detection is limited to only a few weeks before incubation. Due to time and budget constraints for field work, such behavior can result in data deficiencies. These methodological challenges are especially pronounced in remote areas with low infrastructure such as close-to-nature forests in mountainous regions. Recent advancements in conservation technology facilitate research at those sites as they enable simultaneous data collection and open up the possibility to increase sample size. Our study encompasses a network of 40 forest sites located as stepping stones and sites in two national parks aimed to be connected. Throughout the entire breeding season, we deployed autonomous recording units at these sites. Target species were cavity-breeders with particular emphasis on three long-distant migratory species belonging to the genus Ficedula, all of which breed in forests and co-occur within our study area. Naturally, these species compete with other nonmigratory species from the family Paridae for cavities and their occurrence indicate a sufficient number of such breeding sites in forests. In fact, the inclusion of Ficedula parva in the Austrian woodland bird index highlights its significance as a reliable indicator for species richness. Occurrence data is however insufficient in some regions, underscoring the need for further research to enhance monitoring effectiveness. We used hierarchical modeling to analyze parameters that potentially influence the detection probability of selected species, including environmental and methodological factors. Our study aimed to propose an optimized workflow for passive acoustic monitoring of forest birds and to provide insights towards the integration of this method within rapid biodiversity assessments.