Speaker
Description
Large-scale, standardized biodiversity monitoring is critical for assessing ecosystem responses to climate change and increasing anthropogenic pressures in protected areas. The KI-Nationalpark project establishes a nationwide biodiversity monitoring network across 13 national parks and two wilderness areas in Germany. Combining camera trapping with passive acoustic monitoring over a 13-month period starting in October 2025, the project enables standardized assessments of biodiversity and human-induced pressures to support adaptive management.This contribution focuses on the acoustic monitoring component, comprising 304 recording positions across 11 study regions, each equipped with paired AudioMoth devices for simultaneous recording of bird vocalizations and bat echolocation. Within the first three months of monitoring, more than 38 TB of acoustic data were collected, highlighting the scale of the approach.Acoustic data are processed with AI-based pipelines to classify species and anthropogenic noise. For bats, Kaleidoscope Pro, a non-AI template-matching tool, provided a first pass to flag files with bat calls and classifications; validated detections will train a dedicated AI classifier. We show spatial and temporal activity patterns: detection rates declined steadily from about 1.7% of recordings in October to below 0.1% in January, reflecting hibernation phenology. At a conservative match-ratio threshold (>=0.95), 21 species were detected, though one (Nyctalus lasiopterus) is not established in Germany and likely reflects call confusion, requiring expert verification. Notably, eight of eleven regions already hold winter recordings, with confirmed activity of nine species despite very low call rates.This project is funded by the BMUKN as part of the Action Programme for Natural Climate Protection under the AI Lighthouses funding scheme.