In recent years, ecoacoustics has made substantial progress, establishing itself as an autonomous ecological discipline that deepens our understanding of the complex mechanisms governing species, populations, communities, landscapes, and ecosystems (Sueur and Farina, 2015).

Its strength lies in its ability to collect large volumes of acoustic data through autonomous recording systems, which both reduce human disturbance to natural processes and minimize the field effort required of researchers. Moreover, the success of ecoacoustics in ecological research is closely tied to the development of a diverse suite of acoustic indices, which has enabled the extraction of key ecological patterns embedded within complex soundscapes (Harris et al., 2016; Alcocer et al., 2022). Fundamental to this emerging field is the ongoing refinement of a conceptual hierarchical framework grounded in ecology, bioacoustics, and human environmental psychology. Consequently, ecoacoustic theory is being composed from novel concepts to explain ecological phenomena in relation to sounds’ influence on species evolution (Morton 1975; Krause, 1993; Krause, 2015), animal communication (Farina, 2023), physiology and health (Wang et al., 2022), animal movements (Slabbekoorn and Bouton 2008), habitat selection (Mullet et al., 2017), silence and noise (Farina et al., 2023), phenology and climate change (Scarpelli et al., 2023; Mullet et al., 2024), landscape patterns (Farina and Mullet, 2025), human-nature relationships (Miller-Viacava et al., 2025; Mullet and Farina, 2025), and more. This ecoacoustic perspective enables a more precise examination of the biosphere and its emergent properties through the lens of sound.

Nevertheless, much remains to be achieved. The contributions in this second Research Topic on Advances in Ecoacoustics highlight some of the field’s emerging challenges, presenting seven case studies that illustrate how ecoacoustics is advancing scientific understanding and opening new frontiers. The topics explored are particularly timely and include: (1) automatic species recognition, (2) temporal dynamics of acoustic diversity, (3) the influence of forest structural diversity on bird richness and acoustic diversity, (4) acoustic niche dynamics, (5) spatial distribution of sound, (6) sound phenology derived from the close relationship between biophonies and astronomical events, and (7) the complex connections between soundscapes and music.

Although artificial intelligence holds great promise for advancing the processing and analysis of ecoacoustic data (Kitzes et al., 2025), substantial work is still required. The growing availability of large datasets—often collected through citizen participation on digital platforms—opens new avenues for scientific inquiry by enabling the application of increasingly sophisticated algorithms. One such example is the use of BirdNET embeddings to discover novel sound classes from audio recordings (Allen-Ankins et al.). These embeddings are numerical vector representations of audio signals that capture key acoustic features and can be analyzed using machine learning techniques, greatly facilitating the identification of new species or vocalization types. This approach can also be extended to other acoustic models, such as Google Perch (Ghani et al., 2023).

The confirmation that acoustic diversity is closely linked to habitat diversity reinforces the idea that sound is a powerful indicator of environmental complexity and can effectively describe the temporal dynamics of biophonies. Several noteworthy patterns have emerged, including the observation that acoustic diversity declines with increasing levels of forest management (Müller et al.). Acoustic diversity can also be considered an ecosystem service, as it enables people to perceive biodiversity and fosters a positive connection with human well-being. Furthermore, understanding how forest management influences acoustic patterns can support informed decision-making aimed at enhancing forest multifunctionality.

Forest management has been shown to influence biodiversity, and, in particular, acoustic indices have been demonstrated to detect fine structural differences within forest stands, thereby increasing the efficiency of biomonitoring approaches (Shaw et al.). Selecting robust acoustic indices is therefore essential for the effective application of ecoacoustic methods in biodiversity-oriented forest management.

The acoustic complexity found in an environment is not only the result of species adapting to its characteristics, but also the outcome of interspecific interactions aimed at reducing potential competition. This dynamic is well described by the acoustic niche hypothesis (Krause, 1993), which posits that the frequency partitioning of animal signals has evolved as a natural selective advantage (Gasc et al., 2013). However, recent investigations in Hawai’i by Hunt et al. have demonstrated that recordings collected across different habitats show that native and introduced species use similar frequency ranges and do not exhibit a clear partitioning of acoustic space. Comparisons with a null model further indicate that the degree of signal overlap does not differ from what would be expected by chance. This suggests that introduced birds do not strongly influence acoustic partitioning, although additional studies conducted throughout the year are needed.

Acoustic competition can, over long time periods, lead to signal partitioning, but over shorter time scales it may produce ecological consequences such as spatial partitioning—namely, the creation of acoustic spaces or sonotopes. A deeper examination of the spatial characteristics of sound could enrich our understanding of how landscape patterns relate to acoustic sources, thereby opening new pathways for applied conservation, environmental protection, and habitat restoration (Fuller et al., 2015; Müller et al., 2020).

Studying the spatial resolution of a bird community in a mountain beech forest, Farina and Mullet, showed that, despite limited biophony and weak relationships with vegetation, distinct sonotopes emerged across all temporal scales, mainly driven by geophonies below 2000 Hz. These findings suggest that sonoscapes in such forests are shaped primarily by geophysical processes that in many regions are the predominat sonic element.

The intricate acoustic dynamics of species are closely linked to seasonal patterns, revealing the existence of sonophases that align with phenological cycles. Each season is defined by a distinctive acoustic background, largely shaped by climatic conditions that influence the vocal activity of species (Buxton et al., 2016). Consequently, each year produces a unique temporal distribution of sonophases. Seasonal climatic variability determines the acoustic framework within which soniferous species express themselves, establishing dynamic links among species behavior, vocal activity, and climate patterns. This relationship becomes particularly significant during the reproductive season, when climatic factors can either facilitate or constrain behaviors essential for successful breeding. The study conducted by Farina and Mullet demonstrates how soundscapes in a subarctic ecosystem reflect seasonal climate patterns. Ambient sounds were recorded hourly over a three-year period and analyzed using the Acoustic Complexity Index (ACI_tf) in conjunction with weather data. Machine-learning techniques were then used to identify relationships between sonic activity and climatic variables. Distinct sonic phenophases (sonophases) were identified for winter, spring, and summer, corresponding to shifts in daylight, temperature, snow cover, and both animal and human activity. These findings suggest that integrating sonophases with meteorological data offers a multidimensional framework for monitoring ecological responses to climate change.

Sound is not only fundamental to animal communication but also serves as a medium for complex artistic expression. While correspondences between natural sounds and musical elements have long been acknowledged (Gilmurray, 2016; Dyck, 2016), formal validation of these parallels remains relatively rare.

De Bauduin et al. investigate how both ecological and musical approaches analyze soundscapes to understand biodiversity and compositional structure. A central challenge in this interdisciplinary domain is the effective visualization of complex soundscape information for diverse audiences. To address this, the authors introduce the Soundscape Chord Diagram (SCD), a circular similarity visualization based on acoustic β-diversity and clustering methods. Applying the SCD to both ecological and electroacoustic datasets, they demonstrate its ability to highlight key acoustic events and reveal underlying structural patterns. This tool provides a novel interdisciplinary framework for interpreting, communicating, and preserving soundscapes across scientific and artistic fields.

In conclusion, although ecoacoustics still presents many avenues for exploration, it already offers both theoretical and applied insights, as demonstrated by the variety of approaches showcased in this second Research Topic. The ability of ecoacoustics to extract species-level information from extensive acoustic datasets and to characterize acoustic diversity is complemented by its capacity to link climatic variability to the dynamics of acoustic communities and human behavior (Krause and Farina, 2016). Furthermore, ecoacoustics provides a valuable framework for investigating the spatial dimensions of ecosystems—acoustic landscapes—by relating species’ acoustic aggregations to environmental characteristics.

Ecoacoustics has already achieved significant results, and its next major challenge lies in extending research across terrestrial, aquatic, and marine environments. Because sound carries both energy and information, it interacts with and permeates the environment along its propagation path—from emission to dissipation—making it inherently difficult to associate typologically with specific environmental features.

Although its transient and ephemeral nature has often been considered a limitation for its use as a reliable environmental indicator, this intrinsic challenge—arising from the dependence of sound intensity and perception on the spatial relationship between source and listener—is increasingly being addressed through new conceptual and technological approaches. Tools such as the sonotope framework and advanced sonic scanning techniques complement the progressively refined application of ecoacoustic indices.

Spatial ecoacoustics will thus become the next frontier—an area of inquiry with the potential to make a major contribution to applied ecological sciences, which are increasingly focused on designing resilient environments capable of addressing the combined challenges of climate change and land-use transformations. These enduring pressures will continue to test the adaptive responses of species, which are constrained by the inherently slow pace of evolutionary processes.