Training dataset for Rock ptarmigan

Abstract
Monitoring vulnerable species inhabiting mountain environments is crucial to track population trends and prioritize conservation efforts. However, the challenging nature of these remote areas poses difficulties in implementing effective and consistent monitoring programs. To address these challenges, we examined the potential of passive acoustic monitoring (PAM) on a cryptic high mountain bird species, the Rock Ptarmigan (Lagopus muta). We deployed 38 autonomous recording units spanning the Swiss Alps in areas where the birds are followed by a national monitoring program and built a machine-learning algorithm to automatize song recognition. We focused on studying the daily and seasonal call phenology of the species and relate it to meteorological and climatic data. Our results revealed that Rock Ptarmigans were vocally active from March to July, with a peak of activity occurring between mid-March and late April, one or two months earlier than the conventional count in the second half of May. The calling frequency peaked at dawn before dropping rapidly until sunrise. Daily vocal activity demonstrated a consistent dependency on daily weather and moon phase, while the timing of seasonal vocal activity was dependent on temperature and snow conditions.  We found that the peak of vocal activity occurred when the snowpack was still thick, and snow cover was close to 100% but with a local peak of high temperatures. Between our two study years, the peak of vocal activity occurred with 30 days delay in the colder year, highlighting the species' phenological plasticity in relation to environmental conditions. PAM has the potential to complement conventional acoustic counts of the cryptic birds by highlighting periods of higher detectability of the individuals or following small populations where individuals often remain undetected. Moreover, our case study supports the idea that PAM can provide valuable data over large spatial and temporal scales, allowing it to decrypt hidden ecological patterns and assist conservation efforts.