Urban soundscapes are increasingly recognized as fundamental for both ecological integrity and human well-being, yet the complex interplay between the vegetation structure, seasonal dynamics, and microclimatic factors in shaping these soundscapes remains poorly understood. This study tests the hypothesis that vegetation structure and seasonally driven biological activity mediate the balance and the quality of the urban acoustic environment. We investigated seasonal and spatial variations in five acoustic indices (NDSI, ACI, AEI, ADI, and BI) within a historical urban garden in Castelfranco Veneto, Italy. Using linear mixed-effects models, we analyzed the effects of season, microclimatic variables, and vegetation characteristics on soundscape composition. Non-parametric tests were used to assess spatial differences in vegetation metrics. Results revealed strong seasonal patterns, with spring showing increased NDSI (+0.17), ADI (+0.22), and BI (+1.15) values relative to winter, likely reflecting bird breeding phenology and enhanced biological productivity. Among microclimatic predictors, temperature (p < 0.001), humidity (p = 0.014), and solar radiation (p = 0.002) showed significant relationships with acoustic indices, confirming their influence on both animal behaviour and sound propagation. Spatial analyses showed significant differences in acoustic patterns across points (Kruskal–Wallis p < 0.01), with vegetation metrics such as tree density and evergreen proportion correlating with elevated biophonic activity. Although the canopy height model did not emerge as a significant predictor in the models, the observed spatial heterogeneity supports the role of vegetation in shaping urban sound environments. By integrating ecoacoustic indices, LiDAR-derived vegetation data, and microclimatic parameters, this study offers novel insights into how vegetational components should be considered to manage urban green areas to support biodiversity and foster acoustically restorative environments, advancing the evidence base for sound-informed urban planning. © 2025 by the authors.

The most commonly used old-growth forest indicators are structural attributes; nevertheless, they do not necessarily represent the biodiversity value of old-growth forests. The aim of this study is to analyse the relationships between species richness data of different taxa and structural indicators of old-growth and to identify taxonomic/functional groups, species and structural attributes that may be used as indicators of old growth. To achieve this goal we sampled forest structure, vascular plants, lichens, bryophytes, fungi, saproxylic beetles and birds in mature and old-growth stands in southern Italy. We calculated Spearman's correlation coefficients between species richness data and structural attributes. Analyses of indicator species, co-occurrences and two-way clusters were performed on the multi-taxonomic list. The group of vascular plants most significantly correlated with other groups in terms of species richness; furthermore, it displays the highest proportion of between-group co-occurrences. The resulting multi-taxonomic list of potential indicators may serve as an effective means of detecting and monitoring forest ecosystems; however, for this goal, structure-based indicators, such as forest structural attributes and vascular plant species composition, are of primary importance. © 2010 Società Botanica Italiana.