Changes in avian communities following wildfires in Mediterranean pine forest: A passive acoustic monitoring approach across temporal and seasonal gradients

Wildfires are major modifiers of Mediterranean forest ecosystems, with long-term impacts on biodiversity and ecological resilience. However, how fire-history contrasts and seasonal dynamics jointly relate to avian community structure remain insufficiently understood in Mediterranean pine forests. To address this gap, we assessed how avian communities vary across sites with different time since fire using passive acoustic monitoring (PAM) across four Pinus halepensis forests in northern Greece representing a post-fire chronosequence: unburned for at least 40 years and burned in 2001, 2009, and 2018. At each site, autonomous AudioMoth recorders captured 10-min soundscape samples every 30 min for ten consecutive days per season. Bird vocalizations within each sample were identified to species level using BirdNET (v2.4) followed by expert validation of a subset of detections to reduce misclassification. We used Non-metric Multidimensional Scaling (NMDS) to visualize how bird community composition varied among sites and seasons, and Bray–Curtis dissimilarities to describe differences in species composition. We detected 43 species and found that both seasonality and fire history significantly structured avian assemblages, with seasonal variation explaining the largest portion of community differences. Burned sites were dominated by generalist and shrubland species, while unburned forests supported mature-forest specialists. Indicator species analysis identified 13 taxa associated with different successional stages. Overall bird communities showed variation across sites with contrasting fire histories, reflecting potential changes in habitat structure across successional stages, although these patterns should be interpreted cautiously given the limited number of fire-history categories. Our findings highlight the importance of integrating fire history and seasonal dynamics in biodiversity monitoring, and support PAM as a scalable tool for evaluating ecological recovery in fire-affected Mediterranean landscapes.