Search

Introduction: In production forests, management can have cascading effects on biodiversity and ecosystem services. Acoustic diversity reflects the diversity of vocalizing animals and has also considerable recreational value for human well-being, but the relationship between acoustic diversity and forest management remains largely unexplored Method: We recorded acoustic diversity on forest plots along a gradient of silvicultural management intensity (SMI) in three regions of Germany. We explored the diurnal and seasonal temporal dynamics in acoustic diversity index (ADI) from March to July using generalized additive mixed models (GAMMs). We further investigated the interrelation between acoustic diversity and silvicultural management intensity, forest structural diversity, as well as tree diversity, bird species richness and abundance using structural equation modeling (SEM). Results: Silvicultural management intensity had significant effects on the temporal dynamics of ADI in May and June from dawn till dusk, but variance explained by SMI was low. We confirmed our hypothesis that ADI was reduced by SMI due to its cascading effects on forest structural diversity and bird species richness and abundance. Discussion: Acoustic diversity indices can provide valuable insights into how forest management affects the acoustic activity of soniferous communities. We discuss how this can indicate both changes in species diversity as well as their vocal activity. We further address potential implications for forest management. [ABSTRACT FROM AUTHOR]

Given that ecosystems are composed of sounds created by geophysical events (e.g., wind, rain), animal behaviors (e.g., dawn songbird chorus), and human activities (e.g., tourism) that depend on seasonal climate conditions, the phenological patterns of a soundscape could be coupled with long-term weather station data as a complimentary ecological indicator of climate change. We tested whether the seasonality of the soundscape coincided with common weather variables used to monitor climate. We recorded ambient sounds hourly for five minutes (01 January-30 June) over three years (2019-2021) near a weather-station in a subarctic ecosystem in south-central Alaska. We quantified sonic information using the Acoustic Complexity Index (ACItf), coupled with weather data, and used machine learning (TreeNet) to identify sonic-climate relationships. We grouped ACItf according to time periods of prominent seasonal events (e.g., days with temperatures >0°C, no snow cover, green up, dawn biophony, and road-based tourism) and identified distinct sonic phenophases (sonophases) for groups with non-overlapping 95% confidence intervals. In general, sonic activity increased dramatically as winter transitioned to spring and summer. We identified two winter sonophases, a spring sonophase, and a summer sonophase, each coinciding with hours of daylight, temperature, precipitation, snow cover, and the prevalence of animal and human activities. We discuss how sonophases and weather data combined serve as a multidimensional, systems-based approach to understanding the ecological effects of climate change in subarctic environments. [ABSTRACT FROM AUTHOR]

According to the Sonotope Hypothesis, the heterogenous nature of the acoustically sensed, but not yet interpreted, environmental sounds (i.e., sonoscape) is created by the spatial and temporal conformation of sonic patches (sonotopes) as recently been described in a Mediterranean rural landscape. We investigated the Sonotope Hypothesis in a mountain beech forest of the Northern Apennines, Italy that is notoriously poor in soniferous species. Our aim was to test whether sonotopes were temporally distinct over seasonal and astronomical timeframes and spatially configured in relation to vegetation variables. We used the Acoustic Complexity Index (ACItf) to analyze the heterogeneity of sonic information gathered from an array of 11 sound recorders deployed within a lattice of eleven 4-ha hexagonal sample sites distributed throughout a 48-ha managed beech forest. We visualized and described the temporal patterns of ACItf between seasons (May-June and July-August 2021), across six astronomical periods (Night I, Morning Twilight, Morning, Afternoon, Evening Twilight, and Night II), and according to two aggregated frequency classes (<2000 and >2000 Hz). We introduced Spectral Sonic Signature (SSS) calculated from the sequence of ACItf values along frequency bins as a descriptor of the dynamic production of sounds across spatial and temporal scales. We calculated Mean Spectral Dissimilarity to compare SSS values across temporal periods and between sample sites. We identified sonotopes by grouping similar SSS for each sample site generated from cluster analyses and visualized their spatial arrangements. Frequencies <2000 Hz (mainly geophonies from wind and rain) were more prevalent than frequencies >2000 Hz (mainly biophonies from songbirds). Despite there being no strong relationship to vegetation variables and minimal biophony and anthropophony, distinct sonotopes still emerged for every astronomical and seasonal period. This suggests that the sonoscape expresses distinct spatial and temporal sonotope configurations associated with the temporal and spatial patterns of geophysical events that generate geophonies with minimal animal or anthropogenic occurrences. A new strategy based on the reintroduction of indigenous trees and shrubs in managed clearings should be considered for enhancing local biodiversity conservation along with ecoacoustic monitoring based on the Sonotope Hypothesis. [ABSTRACT FROM AUTHOR]