Summary Land-use changes are considered one of the main drivers of biodiversity loss. Agricultural intensification, pastoral abandonment, and changes in forest management have led to the homogenisation of landscapes. In particular, the encroachment of grasslands and the densification of forests that are no longer pastured threaten species that require multiple habitats to nest and forage, such as the European Nightjar Caprimulgus europaeus. Whereas previous studies have focused on understanding factors influencing the decrease of nightjars at regional or national scales, here, we aimed to assess fine-scaled habitat selection by nightjars within nesting and foraging sites based on high-resolution GPS tracking data. Vegetation structure and composition were quantified in the field. In the nesting habitat, nightjars prefer open forests with a low percentage of trees and where the ground is not covered by more than 40% of grass and crawling bushes (dwarf bushes such as Juniperus species). In contrast, when foraging, nightjars select open grasslands and biodiversity-friendly managed vineyards, both richly structured, i.e. interspersed or surrounded by other land-use types such as hedges or isolated trees. Both the nesting and foraging habitats are currently threatened, either by the abandonment of forest management, which makes stands denser and more homogeneous, or through agricultural intensification, which reduces land-use diversity. Clear habitat-specific management recommendations and political incentives are needed to simultaneously preserve and/or restore these critical habitats, which are important for nightjars that use complementary resources for nesting and foraging.

Human‐induced alterations in natural water flow have seriously impaired the integrity of riverine ecosystems. Nonetheless, even in human‐altered riverine and adjacent terrestrial habitats, there is considerable potential for the protection of rare species if management practices prioritize biodiversity conservation. However, the management of such areas often presents complex challenges. On the one hand, efforts to mitigate natural hazards frequently overshadow biodiversity conservation objectives. On the other hand, high‐resolution maps of forest structures are often lacking but could be very useful for spatial prioritization of conservation efforts, especially as vegetation structure can be directly managed through local restoration activities. Here, we used an airborne LiDAR‐derived vegetation structure along an 80 km stretch of the Rhône River (Valais, Switzerland) to assess the habitat characteristics that best explain the presence of a flagship species, the common nightingale Luscinia megarhynchos, a species that historically thrived along this river system but has experienced a drastic population decline over the past decades. Nightingales showed a preference for dense vegetation in the lower strata above ground (3–6 m), as opposed to an open and sparsely vegetated ground level (0–1 m). The preferred habitats were predominantly located within forested regions, as indicated by a preference for taller canopies. These findings align surprisingly well with prior field research on the species, demonstrating the capability of high‐resolution LiDAR to upscale locally derived habitat preferences across very large areas. Based on LiDAR outputs, we proposed management recommendations for the whole river. Such spatially detailed information furthers our understanding of local habitat preferences of endangered species, thus facilitating the formulation of conservation recommendations at the scale of entire populations.

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-Mkm(2)) than aquatic sampling (0.3 and 1.8 sites/Mkm(2) 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.

The urgent need for remote, reliable, and scalable biodiversity monitoring amidst mounting human pressures on ecosystems and changing climate has sparked interest in Passive Acoustic Monitoring (PAM) worldwide. PAM holds potential for supporting global sustainability goals by aiding conservation efforts, but so far, there is no comprehensive overview of its coverage. Here we present metadata from 293 PAM datasets recorded since 1991 in the first global synthesis of ecoacoustic sampling coverage across spatial, temporal, and ecological scales. We report data on sampling sites, deployment schedules, focal taxa, and recording parameters, and quantify biological, anthropogenic, and geophysical soundscape components across nine terrestrial and aquatic ecosystems. We found that terrestrial sampling is spatially denser (33 sites/Mkm2) compared to aquatic realms, with significant data gaps in subterranean realms. While diel and lunar cycles are well-sampled, seasonal coverage is lacking in freshwater and terrestrial ecosystems, while 57% of marine datasets cover all seasons. Opportunities for improvement include broader taxonomic sampling on land, expanding coverage in the high seas, and increasing spatial replication in freshwater environments. Additionally, we highlight nine case studies showcasing how PAM-based soundscape ecology can contribute to macroecology, conservation, and phenology studies, illustrating its potential to support global sustainability efforts both on land and underwater.### Competing Interest StatementThe authors have declared no competing interest.

Monitoring vulnerable species inhabiting mountain environments is crucial to track population trends and prioritize conservation efforts. However, the challenging nature of these remote areas poses difficulties in implementing effective and consistent monitoring programmes. To address these challenges, we examined the potential of passive acoustic monitoring of a cryptic high mountain bird species, the Rock Ptarmigan Lagopus muta . For 5 months in each of two consecutive years, we deployed 38 autonomous recording units in 10 areas of the Swiss Alps where the species is monitored by a national count monitoring programme. Once the recordings were collected, we built a machine‐learning algorithm to automate call recognition. We focused on studying the species' daily and seasonal calling phenology and relating these to meteorological and climatic data. Rock Ptarmigans were vocally active from March to July, with a peak of activity occurring between mid‐March and late April, 1 or 2 months earlier than the second half of May when the counts of the monitoring programme take place. The calling rate peaked at dawn before dropping rapidly until sunrise. Daily vocal activity demonstrated a consistent association with weather conditions and moon phase, whereas the timing of seasonal vocal activity varied with temperature and snow conditions. We found that the peak of vocal activity occurred when the snowpack was still thick and snow cover was close to 100% but with a local peak of high temperatures. Between our two study years, the peak of vocal activity occurred 30 days later in the colder year, suggesting phenological plasticity in relation to environmental conditions. Passive acoustic monitoring has the potential to complement conventional acoustic counts of cryptic birds by highlighting periods of higher detectability of individuals, and to survey small populations that often remain undetected during single visits. Moreover, our study supports the idea that passive acoustic monitoring can provide valuable data over large spatial and temporal scales, allowing decryption of hidden ecological patterns and assisting in conservation efforts.

Artificial light at night significantly alters the predictability of the natural light cycles that most animals use as an essential Zeitgeber for daily activity. Direct light has well-documented local impacts on activity patterns of diurnal and nocturnal organisms. However, artificial light at night also contributes to an indirect illumination of the night sky, called skyglow, which is rapidly increasing. The consequences of this wide-spread form of artificial night light on the behaviour of animals remain poorly understood, with only a few studies performed under controlled (laboratory) conditions. Using animal-borne activity loggers, we investigated daily and seasonal flight activity of a free-living crepuscular bird species in response to nocturnal light conditions at sites differing dramatically in exposure to skyglow. We find that flight activity of European Nightjars (Caprimulgus europaeus) during moonless periods of the night is four times higher in Belgium (high skyglow exposure) than in sub-tropical Africa and two times higher than in Mongolia (near-pristine skies). Moreover, clouds darken the sky under natural conditions, but skyglow can strongly increase local sky brightness on overcast nights. As a result, we find that nightjars' response to cloud cover is reversed between Belgium and sub-tropical Africa and between Belgium and Mongolia. This supports the hypothesis that cloudy nights reduce individual flight activity in a pristine environment, but increase it when the sky is artificially lit. Our study shows that in the absence of direct light pollution, anthropogenic changes in sky brightness relieve nightjars from visual constraints on being active. Individuals adapt daily activities to artificial night-sky brightness, allowing them more time to fly than conspecifics living under natural light cycles. This modification of the nocturnal timescape likely affects behavioural processes of most crepuscular and nocturnal species, but its implications for population dynamics and interspecific interactions remain to be investigated.

The fasta file countains custom partial COI sequences from alpine orthopternans used to recontruct orthopteran phylogeny.

Monitoring vulnerable species inhabiting mountain environments is crucial to track population trends and prioritize conservation efforts. However, the challenging nature of these remote areas poses difficulties in implementing effective and consistent monitoring programs. To address these challenges, we examined the potential of passive acoustic monitoring (PAM) on a cryptic high mountain bird species, the Rock Ptarmigan (Lagopus muta). We deployed 38 autonomous recording units spanning the Swiss Alps in areas where the birds are followed by a national monitoring program and built a machine-learning algorithm to automatize song recognition. We focused on studying the daily and seasonal call phenology of the species and relate it to meteorological and climatic data. Our results revealed that Rock Ptarmigans were vocally active from March to July, with a peak of activity occurring between mid-March and late April, one or two months earlier than the conventional count in the second half of May. The calling frequency peaked at dawn before dropping rapidly until sunrise. Daily vocal activity demonstrated a consistent dependency on daily weather and moon phase, while the timing of seasonal vocal activity was dependent on temperature and snow conditions. We found that the peak of vocal activity occurred when the snowpack was still thick, and snow cover was close to 100% but with a local peak of high temperatures. Between our two study years, the peak of vocal activity occurred with 30 days delay in the colder year, highlighting the species' phenological plasticity in relation to environmental conditions. PAM has the potential to complement conventional acoustic counts of the cryptic birds by highlighting periods of higher detectability of the individuals or following small populations where individuals often remain undetected. Moreover, our case study supports the idea that PAM can provide valuable data over large spatial and temporal scales, allowing it to decrypt hidden ecological patterns and assist conservation efforts.

In Europe, agricultural practices have progressively evolved towards high productivity leading either to the intensification of productive and accessible areas or to the abandonment of less profitable sites. Both processes have led to the degradation of semi‐natural habitats like extensive grasslands, threatening species such as the Eurasian Scops Owl Otus scops that rely on extensively managed agricultural landscapes. In this work, we aimed to assess the habitat preferences of the Scops Owl using habitat suitability models combined with a multi‐scale approach. We generated a set of multi‐scale predictors, considering both biotic and abiotic variables, built on two newly developed vegetation management and orthopteran abundance models. To select the variables to incorporate in a ‘best multi‐scale model’, we chose the best spatial scale for each variable using univariate models and by calculating their relative importance through multi‐model inference. Next, we built ensembles of small models (ESMs) at 10 different scales from 50 to 1000 m, and an additional model with each variable at its best scale (‘best multi‐scale model’). The latter performed better than most of the other ESMs and allowed the creation of a high‐resolution habitat suitability map for the species. Scops Owls showed a preference for dry sites with extensive and well‐structured habitats with 30–40% bush cover, and relied strongly on semi‐extensive grasslands covering at least 30% of the surface within 300 m of the territory centre and with high orthopteran availability near the centre (50‐m radius), revealing a need for good foraging grounds near the nest. At a larger spatial scale within a radius of 1000 m, the habitat suitability of Scops Owls was negatively related to forest cover. The resulting ESM predictions provide valuable tools for conservation planning, highlighting sites in need of particular conservation efforts together with offering estimates of the percentage of habitat types and necessary prey abundance that could be used as targets in future management plans to ensure the persistence of the population.

Abstract To acquire a fundamental understanding of animal communication, continuous observations in a natural setting and at an individual level are required. Whereas the use of animal‐borne acoustic recorders in vocal studies remains challenging, light‐weight accelerometers can potentially register individuals’ vocal output when this coincides with body vibrations. We collected one‐dimensional accelerometer data using light‐weight tags on a free‐living, crepuscular bird species, the European Nightjar (Caprimulgus europaeus). We developed a classification model to identify four behaviors (rest, sing, fly, and leap) from accelerometer data and, for the purpose of this study, validated the classification of song behavior. Male nightjars produce a distinctive “churring” song while they rest on a stationary song post. We expected churring to be associated with body vibrations (i.e., medium‐amplitude body acceleration), which we assumed would be easy to distinguish from resting (i.e., low‐amplitude body acceleration). We validated the classification of song behavior using simultaneous GPS tracking data (i.e., information on individuals’ movement and proximity to audio recorders) and vocal recordings from stationary audio recorders at known song posts of one tracked individual. Song activity was detected by the classification model with an accuracy of 92%. Beyond a threshold of 20 m from the audio recorders, only 8% of the classified song bouts were recorded. The duration of the detected song activity (i.e., acceleration data) was highly correlated with the duration of the simultaneously recorded song bouts (correlation coefficient = 0.87, N = 10, S = 21.7, p = .001). We show that accelerometer‐based identification of vocalizations could serve as a promising tool to study communication in free‐living, small‐sized birds and demonstrate possible limitations of audio recorders to investigate individual‐based variation in song behavior.

Spatial autocorrelation (SAC) is a common feature of ecological data where observations tend to be more similar at some geographic distance(s) than expected by chance. Despite the implications of SAC for data dependencies, its impact on the performance of species distribution models (SDMs) remains controversial, with reports of both strong and negligible impacts on inference. Yet, no study has comprehensively assessed the prevalence and the strength of SAC in the residuals of SDMs over entire geographic areas. Here, we used a large‐scale spatial inventory in the western Swiss Alps to provide a thorough assessment of the importance of SAC for (1) 850 species belonging to nine taxonomic groups, (2) six predictors commonly used for modeling species distributions, and (3) residuals obtained from SDMs fitted with two algorithms with the six predictors included as covariates. We used various statistical tools to evaluate (1) the global level of SAC, (2) the spatial pattern and spatial extent of SAC, and (3) whether local clusters of SAC can be detected. We further investigated the effect of the sampling design on SAC levels. Overall, while environmental predictors expectedly displayed high SAC levels, SAC in biodiversity data was rather low overall and vanished rapidly at a distance of ~5–10 km. We found low evidence for the existence of local clusters of SAC. Most importantly, model residuals were not spatially autocorrelated, suggesting that inferences derived from SDMs are unlikely to be affected by SAC. Further, our results suggest that the influence of SAC can be reduced by a careful sampling design. Overall, our results suggest that SAC is not a major concern for rugged mountain landscapes.

Knowledge on species' ecological requirements is the key to an effective evidence-based conservation. An adaptive approach can refine management recommendations following the outcomes of previous actions or as improved scientific knowledge about a species' ecology becomes available. Following severe population declines the majority of the Swiss European Nightjar (Caprimulgus europaeus)population is now restricted to a small core area in the canton of Valais, despite the local application of evidence-based restoration measures to the breeding habitats. The habitat use of this crepuscular bird species is presumed to be restricted to semi-open oak-pine scrublands and rocky steppe. By deploying miniature GPS loggers we assessed the spatial and habitat selection of 42 individuals (25 individuals in 2018 and 30 individuals in 2019; comprising 13 redeployments between years) in five study sites in the canton Valais. We highlight the importance of using fine-scaled movement data to obtain insight into complex multi-scale habitat requirements of a species. Nightjars used multiple habitats, indicating the importance of complementary resources to breed (e.g. open forest and shrub) and to forage (e.g. semi-extensive grasslands and vineyards). The connectivity between these resources was influenced by habitat configuration and composition. Given these new insights for future conservation strategies, our results also suggest that national-level land use changes, mainly due to agricultural intensification processes, have contributed to the long-term population declines in Switzerland. We therefore consider our result in the context of knowledge gaps for species that exploit complementary habitats and the potential shortcomings for conservation planning on discrete species showing complex ecological requirements.

AbstractA growing food demand and advanced agricultural techniques increasingly affect farmland ecosystems, threatening invertebrate populations with cascading effects along the food chain upon insectivorous vertebrates. Supporting farmland biodiversity thus optimally requires the delineation of species hotspots at multiple trophic levels to prioritize conservation management. The goal of this study was to investigate the links between grassland management intensity and orthopteran density at the field scale and to upscale this information to the landscape in order to guide management action at landscape scale. More specifically, we investigated the relationships between grassland management intensity, floral indicator species, and orthopteran abundance in grasslands with different land use in the SW Swiss Alps. Field vegetation surveys of indicator plant species were used to generate a management intensity proxy, to which field assessments of orthopterans were related. Orthopteran abundance showed a hump‐shaped response to management intensity, with low values in intensified, nutrient‐rich grasslands and in nutrient‐poor, xeric grasslands, while it peaked in middle‐intensity grasslands. Combined with remote‐sensed data about grassland gross primary productivity, the above proxy was used to build landscape‐wide, spatially explicit projections of the potential distribution of orthopteran‐rich grasslands as possible foraging grounds for insectivorous vertebrates. This spatially explicit multitrophic approach enables the delineation of focal farmland areas in order to prioritize conservation action.

As anthropogenic degradation of biodiversity and ecosystems increases, so does the potential threat to the supply of ecosystem services, a key contribution of nature to people. Biodiversity has often been used in spatial conservation planning and has been regarded as one among multiple services delivered by ecosystems. Hence, biodiversity conservation planning should be integrated in a framework of prioritizing services in order to inform decision-making. Here, we propose a prioritization approach based on scenarios maximising both the provision of ecosystem services and the conservation of biodiversity hotspots. Different weighting scenarios for the alpha-diversity in four taxonomic groups and 10 mapped ecosystem services were used to simulate varying priorities of policymakers in a mountain region. Our results illustrate how increasing priorities to ecosystem services can be disadvantageous to biodiversity. Moreover, the analysis to identify priority areas that best compromise the conservation of alpha-diversity and ecosystem services are predominantly not located within the current protected area network. Our analyses stress the need for an appropriate weighting of biodiversity within decision making that seek to integrate multiple ecosystem services. Our study paves the way toward further integration of multiple biodiversity groups and components, ecosystem services and various socio-economic scenarios, ultimately fuelling the development of more informed, evidence-based spatial planning decisions for conservation.

Venomous animals use venom, a complex biofluid composed of unique mixtures of proteins and peptides, for either predation or defense. Bumblebees, which occur in various habitats due to their unique thermoregulatory properties, mainly use venom for defense. Herein, we conducted an exploratory analysis of the venom composition of a bumblebee species (Bombus pascuorum) along an elevation gradient in the western Swiss Alps using shot-gun proteomic approaches to assess whether their defense mechanism varies along the gradient. The gradient was characterized by high temperatures and low humidity at low elevations and low temperatures and high humidity at high elevations. Venom composition is changing along the elevation gradient, with proteomic variation in the abundances of pain-inducing and allergenic proteins. In particular, the abundance of phospholipase A2-like, the main component of bumblebee venom, gradually decreases toward higher elevation (lower temperature), suggesting venom alteration and thus a decrease in bumblebee defense towards harsher environments. Larger datasets may complement this study to validate the observed novel trends.

When using these datasets, please cite the following reference:Descombes, P., Marchon, J., Pradervand, J.-N., Bilat, J., Guisan, A., Rasmann, S., & Pellissier, L. (2017). Community-level plant palatability increases with elevation as insect herbivore abundance declines. Journal of Ecology, 105, 142–151. https://doi.org/10.1111/1365-2745.12664Details on the data sampling are fully described in the aforementioned reference.DataOrtho.txt: This dataset contains the richness and abundance of 175 orthopteran (Ensifera and Caelifera) communities sampled along an elevation gradient in the Swiss Alps (only above 1000m).DataOrtho_Total.txt: This dataset contains the richness and abundance of 190 orthopteran (Ensifera and Caelifera) communities sampled along an elevation gradient in the Swiss Alps.DataTrait_Species.txt: This dataset contains the leaf traits (SLA, LDMC, C:N, leaf palatability) collected for 287 species along an elevation gradient in the Swiss Alps.DataTrait_CWM.txt: This dataset contains the community weighted mean of the traits (SLA, LDMC, C:N, leaf palatability) calculated for 307 plant communities along an elevation gradient in the Swiss Alps.

Venomous animals use venom, a complex biofluid composed of unique mixtures of proteins and peptides, for either predation or defense. Bumblebees, which occur in various habitats due to their unique thermoregulatory properties, mainly use venom for defense. Herein, we conducted an exploratory analysis of the venom composition of a bumblebee species (Bombus pascuorum) along an elevation gradient in the western Swiss Alps using shot-gun proteomic approaches to assess whether their defense mechanism varies along the gradient. The gradient was characterized by high temperatures and low humidity at low elevations and low temperatures and high humidity at high elevations. Venom composition is changing along the elevation gradient, with proteomic variation in the abundances of pain-inducing and allergenic proteins. In particular, the abundance of phospholipase A2-like, the main component of bumblebee venom, gradually decreases toward higher elevation (lower temperature), suggesting venom alteration and thus a decrease in bumblebee defense towards harsher environments. Larger datasets may complement this study to validate the observed novel trends.

Protected areas (PAs) play a critical role in conserving biodiversity and maintaining viable populations of threatened species. Yet, as global change could reduce the future effectiveness of existing PAs in covering high species richness, updating the boundaries of existing PAs or creating new ones might become necessary to uphold conservation goals. Modelling tools are increasingly used by policymakers to support the spatial prioritization of biodiversity conservation, enabling the inclusion of scenarios of environmental changes to achieve specific targets. Here, using the Western Swiss Alps as a case study, we show how integrating species richness derived from species distribution model predictions for four taxonomic groups under present and future climate and land-use conditions into two conservation prioritization schemes can help optimize extant and future PAs. The first scheme, the “Priority Scores Method” identified priority areas for the expansion of the existing PA network. The second scheme, using the zonation software, allowed identifying priority conservation areas while incorporating global change scenarios and political costs. We found that existing mountain PAs are currently not situated in the most environmentally nor politically suitable locations when maximizing alpha diversity for the studied taxonomic groups and that current PAs could become even less optimum under the future climate and land-use change scenarios. This analysis has focused on general areas of high species richness or species of conservation concern and did not account for special habitats or functional groups that could have been used to create the existing network. We conclude that such an integrated framework could support more effective conservation planning and could be similarly applied to other landscapes or other biodiversity conservation indices.