Luc Barbaro

Aim: Treeline ecotones are key indicators of environmental change, yet their responses to climate warming vary markedly across landscapes. This study investigates how elevation and local environmental contexts moderate warming effects on treeline dynamics. Location: French Pyrenees. Time Period: 1950s to 2015. Major Taxa Studied: Montane and alpine treeline ecotones are dominated, respectively, by Fagus sylvatica and Pinus uncinata . Methods: We analysed 626 treelines using two metrics of long‐term ecotone dynamics: elevational shift and forest infilling. We tested three hypotheses: (i) whether elevation moderates warming effects on treeline dynamics; (ii) whether treeline responses remain spatially heterogeneous within elevational zones; and (iii) whether local environmental factors explain this heterogeneity. Climate change was quantified as absolute maximum temperature change (Δ T _max ) between 1950–1984 and 1985–2020. Sites were objectively stratified into montane treeline ecotones (MTE; < 1942 m) and alpine treeline ecotones (ATE; ≥ 1942 m). Results: Elevation strongly moderated climate change effects, with (i) montane treelines showing larger elevational shifts but weaker relationships with warming, likely reflecting forest rebound following pastoral abandonment, while (ii) alpine treelines showed smaller shifts but stronger warming relationships, likely constrained by slow demographic processes near tree physiological limits. We also found support for spatial heterogeneity persistence within both montane and alpine belts. Local environmental factors largely explained this heterogeneity, with well‐drained, steep sites exhibiting positive warming responses and poorly‐drained sites and crystalline substrates showing negative or neutral responses. Main Conclusions: Treeline responses to warming are context‐dependent, with local environmental conditions moderating and even reversing climate effects. The spatial heterogeneity observed reconciles apparently contradictory patterns in global treeline literature by demonstrating that warming effects interact with local filters to produce heterogeneous outcomes even within elevational zones. These findings highlight the need for spatially explicit models of treeline dynamics that integrate local environmental contexts, improving our ability to monitor and conserve these sensitive ecosystems.

Emerging evidence shows that responses to deforestation can differ both across species and among populations of the same species. The reasons underlying these complex patterns are unclear, and this lack of clarity is a barrier to accurate monitoring and prediction of biodiversity change. Using data from 2,262 bird species across 7,326 sites from all forested continents, we show that between-species and within-species variations in responses to forest cover are mediated by temperature. Populations in warmer macroclimates tend to decline in incidence in deforested landscapes because hotter microclimates push them closer to their species’ realized upper thermal tolerance limits. By contrast, populations in cooler macroclimates tend to be less affected by or even benefit from deforestation, as microclimatic temperatures are pushed closer to more optimal temperatures. Our findings offer an empirically grounded framework for biodiversity models that move beyond fixed species responses and incorporate interactions between temperature and land-use change.

In the French countryside, the succession of silent springs associated with the erosion of rural biodiversity has brought sound-related issues to the forefront as an essential approach enabling researchers (in life and territorial sciences) to characterize the state of landscapes and ecosystems in a context of global change. Anthropologists, for their part, can show how local communities perceive their territories through their immediate sound environments, at a time when profound transformations are affecting both their societies and their environment. In this article, we revisit a multidisciplinary research programme entitled Sonates (Ecouter les SONs de la NATurE pour comprendre les changements environnementaux – funded by the LabEx DynamiTe, 2018–2022). This project brought together anthropology, geography, ecology, and ecoacoustics, and was conducted in a CNRS Long-Term Socio-Ecological Research Area south of Toulouse (ZA Pygar), in the Bas-Comminges region, a field site studied by our team for more than twenty years. Through investigations conducted in our field sites combining acoustic recordings and sensory ethnography (participant observation, semi-structured interviews, and commented walks), we seek to understand how the environment is heard by local communities and how sounds contribute to the construction of local diagnoses of environmental change. We explore the coexistence, within a single territory, of different types of ecological knowledge (local, expert, scientific, etc.), and thus potential variations in the perception of sounds. This article also provides an opportunity to reflect on questions of convergence or discrepancy between the definitions of sounds adopted by the different researchers involved in the project (for example, what is anthrophony, and should it be considered a component of soundscapes or a form of pollution to be removed from recordings?), as well as on the methodological and conceptual issues raised by these questions, which allow us to further develop our shared understanding of sounds.

Boreal-subarctic forests, and the biodiversity they host, are among the most threatened ecosystems worldwide due to the joint pressures of climate warming and intensification of forestry practices. Here, we examined the combined effects of forest management regimes and latitude on bird species and acoustic communities in Finland using passive acoustic monitoring (PAM). We collected acoustic recordings using a replicate design under low, medium and high forest management intensity in three study sites across the North–South latitudinal gradient of Finland. We computed acoustic indices and automated bird species identifications using BirdNet to identify diurnal and phenological patterns in species vocalisations along forest management type and latitudinal gradient. While bird species identification revealed greater diversity of vocalising species in high and medium management compared to low management forests, forest indicator birds predominantly occurred under low-intensive management. Further analysis dividing forest indicator species into a forest specialist group and old-growth species group showed an even more significant impact of forest management on their detection. Random forest models were used to assess the predictive value of spatial data (land cover diversity, dead wood availability, forest quality) and acoustic indices on bird species diversity and the presence of forest indicator communities. The challenges and potential of passive acoustic monitoring, especially in Boreal-subarctic landscapes are discussed. Overall, the study demonstrates the potential of PAM monitoring in Finnish forest areas as a complement to existing transect count methods, and how the results can inform decision making as part of the upcoming Nature Restoration Law in Finland.

Mounting evidence points to widespread declines in insect abundance and diversity across European terrestrial ecosystems, highlighting an urgent need for effective large-scale monitoring methods. Passive acoustic monitoring enables the monitoring of sound-producing insects at an unprecedented temporal and spatial scale by remotely capturing sounds such as orthopteran stridulations and cicada timbalizations. However, current automated recognition tools for European insect sounds remain limited, and developing algorithms capable of reliably identifying diverse species requires large, ecologically heterogeneous acoustic datasets. Here we present a dataset of 11,224 recordings covering 193 orthopteran and 24 cicada species from North, Central, and temperate Western Europe. It combines coarsely labeled recordings, for which we can only infer the presence, at some point, of their target species (weak labeling), with finely annotated recordings that specify the time and frequency range of each insect sound (strong labeling). This dataset complements existing online resources and supports the advancement of automated acoustic classification for orthopterans and cicadas, aiding biodiversity monitoring efforts across Europe.

Environmental variation shapes acoustic interactions among birds, creating spatial structures in the sonic signature of local species assemblages. Exploring these patterns at regional scales can reveal processes that segregate acoustic strategies along environmental gradients. Here, we examined how the acoustic trait composition of bird assemblages varies at a regional extent in relation to landscape resolution environmental variation. We used data on 2427 bird assemblages and 15 acoustic traits, quantifying the frequency, complexity, rhythm, and duration of vocalisations for 117 species. We used multivariate ordinations to investigate the distribution of species' acoustic traits along climatic and landscape gradients while accounting for spatial and phylogenetic dependencies. We then assessed whether these relationships resulted in directional shifts in the acoustic trait composition of bird assemblages for three key acoustic traits. Our results show that acoustic traits were phylogenetically and spatially clustered and correlated with regional climatic conditions (e.g. lower complexity and isochronous rhythms under higher precipitation and temperature seasonality). Conversely, we found mixed support for the hypothesis that the acoustic signature of species assemblages is shaped by habitat composition within landscapes. For instance, we found urbanisation to be associated with vocalisations featuring broader spectral bandwidths, likely facilitating their propagation under noise pollution, but also greater complexity, which may hinder transmission in urban landscapes. These regional patterns may reflect differences in the structure of acoustic networks within and among species assemblages. Our results thus form a first step towards a regional‐level assessment of the environmental and anthropogenic factors that structure or disrupt acoustic connectivity in landscapes.

Under the current global biodiversity crisis, there is a need for automated and noninvasive monitoring techniques that can gather large amounts of data cost‐effectively at various ecological scales, from local to large spatial scales. These data can then be analyzed to inform stakeholders and decision‐makers. One such technique is passive acoustic monitoring, which is commonly coupled with automatic identification of animal species based on their sound. Automated sound analyses usually require the training of sound detection and identification algorithms. These algorithms are based on annotated acoustic datasets which mark the occurrence of sounds of species inside sound recordings. However, compiling large annotated acoustic datasets is time‐consuming and requires experts, and therefore, they normally cover reduced spatial, temporal, and taxonomic scales. This data paper presents WABAD, the World Annotated Bird Acoustic Dataset for passive acoustic monitoring. WABAD is designed to provide the public, the research community, and conservation managers with a novel and globally representative annotated acoustic dataset. This database includes 5047 min of audio files annotated to species‐level by local experts with the start and end time and the upper and lower frequencies of each identified bird vocalization in the recordings. The database has a wide taxonomic and spatial coverage, including information on 91,931 vocalizations from 1192 bird species recorded at 72 recording sites in 29 recording locations (mainly countries) and distributed across 13 biomes. WABAD can be used, for example, for developing and/or validating automatic species detection algorithms, answering ecological questions, such as assessing geographical variations on bird vocalizations, or comparing acoustic diversity indices with species‐based diversity indices. The dataset is published under a Creative Commons Attribution 4.0 International license that permits redistribution and reuse on the condition that the original work is properly credited.

BirdNET is a popular machine learning tool for automated recognition of bird sounds. However, evidence on how to optimize its settings for accurate bird monitoring remains limited. Here, we evaluate how BirdNET settings influence model performance in identifying bird vocalizations and characterizing bird communities, using 4224 1‐min recordings from 67 recording locations worldwide. Giving equal importance to recall and precision, a low confidence score threshold (0.1–0.3) appears optimal for detecting bird vocalizations, whereas higher thresholds (around 0.5) are more suitable for characterizing bird communities. Based on our findings, we recommend increasing the Overlap parameter from its default value of 0 to 2 s, as this consistently improves BirdNET performance in detecting both bird vocalizations and species presence. The effect of the Sensitivity parameter varied across regions. However, a value of 0.5 maximizes global performance for community‐level analyses across all confidence thresholds, and a value of 1.5 generally yields better results for vocalization‐level studies, particularly at low confidence thresholds. Our findings offer practical guidance for selecting BirdNET settings in passive acoustic bird surveys, enhancing both the identification of bird vocalizations and the characterization of bird communities.

Bird population estimation over broad spatial and temporal scales is a key objective in ornithology. To date, bird ecologists mainly relied on standard point counts where the number of detected individuals is interpreted as either the true abundance or proportionally related to it. However, providing accurate estimates of species abundance requires modelling the observation process with temporally replicated data, which is not always possible with the increasing use of ever-bigger datasets from citizen science programs. Data integration methods allow combining temporally replicated sampling at coarser spatial grains with data collected over larger spatial extents. Here, we developed an Integrated distance sampling (IDS) to combine national structured and semi-structured citizen-based bird surveys in France to estimate species abundances using observation distances and accounting for availability, i.e. the probability of individuals being detectable during a given sampling visit. While our simulation study showed an overall increase in the accuracy of estimated parameters for both ecological and observation processes, without significant biases, our case study suggests that such model improvements will depend on specific sampling scenarios. Integrated models represent a promising tool for ecological science, permitting the joint use of large unstructured datasets with scale-restricted structured surveys.

Aim: The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean).Location: Worldwide, 12,343 sites, all ecosystem types.Time Period: 1991 to present.Major Taxa Studied: All soniferous taxa.Methods: We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms.Results: Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm²) than aquatic sampling (0.3 and 1.8 sites/Mkm² in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds.Main Conclusions: PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio‐temporal replication in freshwater habitats. Overall, this worldwide PAM network holds promise to support cross‐realm biodiversity research and monitoring efforts.