Despite the prevalence of forest disturbances, their effects on bird abundance are poorly understood on a continental scale. Near future harvest rates and natural disturbances will likely increase, thus quantifying the influence of disturbances on biodiversity is increasingly important to plan conservation. We studied the influence of forest disturbances on the abundance of 107 bird species across 25 European countries between 2000 and 2022. We explored the response of birds associated with different habitats, the influence of forest cover and time since the disturbance, comparing results at continental and regional scales. 95 species responded significantly to disturbances, mostly negatively. Forest-associated birds responded mostly negatively, while shrub and edge birds showed a higher proportion of positive responses. Open habitat birds had few statistically significant responses with mixed directions. Forest cover negatively influenced the effect of disturbance on abundance. Responses varied among regions, reflecting differences in community composition and landscape characteristics. Importantly, for 21% of species the response direction changed between region and/or forest cover. These findings suggest that forest disturbances, dominated by clear-cut harvesting, exert a mostly negative influence on birds across Europe, requiring adaptive forest management strategies for avian conservation.

The United Nations and European Union have set ambitious conservation goals to halt and reverse declines in biodiversity by protecting 30% of land and sea areas by 2030. Effective conservation planning requires evidence-based spatial prioritization to maximize the coverage of species within designated protected areas. Based on a pan-European database for occurrence and abundance of breeding birds collected in the 2010s, we applied the Zonation algorithm to identify key areas that would maximize the protection of ranges and populations for 435 species of breeding birds across Europe using either continental or national prioritization targets. When 30% of Europe's highest priority terrestrial areas were selected by the algorithm, 49% of species' ranges and 63% of species' populations were protected. When 10% and 30% of the highest priority lands were selected, compared with prioritization using occurrence data, prioritization using abundance data resulted in a higher percentage of species' populations, especially rare and range-restricted species, being represented for protected area coverage. Stratifying prioritization by habitat criteria greatly enhanced habitat-specific conservation efficiency, enabling coverage of over 80% of breeding bird species' populations in tundra, Mediterranean, and coastal habitats with a selection of 10% of the highest priority areas for each. Our prioritization supports international targets adopted under the Kunming-Montreal Global Biodiversity Framework by identifying key areas and providing a roadmap to guide optimal site protection and conservation planning in Europe.

The Natura 2000 (N2K) network combines biodiversity protection and socioeconomic targets. Human activities, such as agricultural practices, can affect biodiversity in N2K sites in diverse ways. Limiting activities with negative impacts while enforcing land management that supports biodiversity is crucial for effective conservation. Yet, site-level information on how this is addressed in N2K sites is lacking. To fill this knowledge gap, we conducted a European Union-wide survey among N2K site managers. We aimed to assess the implemented conservation measures, their funding sources, and the extent to which different threats are addressed. Of the 341 responses, 61.8% reported the implementation of conservation measures linked to agricultural practices, such as adapting mowing and grazing at levels suitable for the conservation of grassland habitats and species. Sites with management tied to agricultural practices relied more on EU funding, such as the Common Agricultural Policy (CAP), whereas other sites depended more on national funding. Threats not addressed by conservation measures were reported by 63.8% of respondents, suggesting that overall management funding may be insufficient or ineffectively allocated. Most of these unaddressed threats resulted from intensive agricultural practices, such as the use of agrochemicals (reported as a threat in 13% of sites). These findings provide insight into how traditional agricultural practices, mostly related to low-intensity grazing and mowing, are frequently used as conservation tools, whereas intensive agriculture is a prominent source of unmitigated threats. Thus, achieving N2K conservation goals requires avoiding intensive agricultural practices and strengthening effective conservation measures in protected areas.

Resource pulses associated with forest disturbances can significantly influence biological communities, with interacting and sometimes lagged effects on species numbers. Among the most common disturbances in temperate forests are bark beetle outbreaks, which represent a resource pulse and initiate additional resource pulses of other insects and of deadwood. Moreover, bark beetle outbreaks are often followed by changes in habitat conditions due to canopy cover loss or salvage logging that can have contrasting effects on co-occurring forest species. However, the effects of this multi-resource pulse on forest species have rarely been quantified simultaneously. Here, we investigated if and to what extent changes in woodpecker population density were related to resource pulses, specifically spruce bark beetle and standing dead wood of Norway spruce. We used data from long-term monitoring projects collected across Switzerland from 1984 to 2020 to build a network model that estimated relationships among species and resources. We built a semi-mechanistic model that included structured equations of parameters of interest. The equations modelled Norway spruce standing deadwood volume, bark beetle density and density of three woodpecker species as a function of their interactions, as well as climatic, environmental and management variables. The model allowed both same-year and 1-year lagged effects. We found weak relationships between bark beetle outbreaks and woodpecker densities, and strong positive relationships between deadwood amount and woodpecker densities. In turn, standing deadwood was strongly linked to bark beetle outbreaks, highlighting the indirect role of bark beetles in promoting woodpecker populations by means of providing deadwood for foraging and nesting. Salvage logging, that is, the removal of trees infested by bark beetles, had only minor effects on bark beetles. Bark beetle outbreaks contributed to the generation of deadwood that ensured the continuity of its associated ecosystem functions, which benefited woodpeckers and, potentially, forest biodiversity as a whole. Large-scale consequences of these multi-resource pulses were reflected by species populations over longer time periods than the pulses.

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.

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.

Species respond dynamically to climate change and exhibit time lags. Consequently, species may not occupy their full climatic niche during range shifting. Here, we assessed climate niche tracking during recent range shifts of European and United States (US) birds. Using data from two European bird atlases and from the North American Breeding Bird Survey between the 1980s and 2010s, we analysed range overlap and climate niche overlap based on kernel density estimation. Phylogenetic multiple regression was used to assess the effect of species morphological, ecological and biogeographic traits on range and niche metrics. European birds shifted their ranges north and north-eastwards, US birds westwards. Range unfilling was lower than expected by null models, and niche expansion was more common than niche unfilling. Also, climate niche tracking was generally lower in US birds and poorly explained by species traits. Overall, our results suggest that dispersal limitations were minor in range shifting birds in Europe and the USA while delayed extinctions from unfavourable areas seem more important. Regional differences could be related to differences in land use history and monitoring schemes. Comparative analyses of range and niche shifts provide a useful screening approach for identifying the importance of transient dynamics and time-lagged responses to climate change. This article is part of the theme issue ‘Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere’.

Rising temperatures are leading to increased prevalence of warm-affinity species in ecosystems, known as thermophilisation. However, factors influencing variation in thermophilisation rates among taxa and ecosystems, particularly freshwater communities with high diversity and high population decline, remain unclear. We analysed compositional change over time in 7123 freshwater and 6201 terrestrial, mostly temperate communities from multiple taxonomic groups. Overall, temperature change was positively linked to thermophilisation in both realms. Extirpated species had lower thermal affinities in terrestrial communities but higher affinities in freshwater communities compared to those persisting over time. Temperature change’s impact on thermophilisation varied with community body size, thermal niche breadth, species richness and baseline temperature; these interactive effects were idiosyncratic in the direction and magnitude of their impacts on thermophilisation, both across realms and taxonomic groups. While our findings emphasise the challenges in predicting the consequences of temperature change across communities, conservation strategies should consider these variable responses when attempting to mitigate climate-induced biodiversity loss.

Climate change has been associated with both latitudinal and elevational shifts in species’ ranges. The extent, however, to which climate change has driven recent range shifts alongside other putative drivers remains uncertain. Here, we use the changing distributions of 378 European breeding bird species over 30 years to explore the putative drivers of recent range dynamics, considering the effects of climate, land cover, other environmental variables, and species’ traits on the probability of local colonisation and extinction. On average, species shifted their ranges by 2.4 km/year. These shifts, however, were significantly different from expectations due to changing climate and land cover. We found that local colonisation and extinction events were influenced primarily by initial climate conditions and by species’ range traits. By contrast, changes in climate suitability over the period were less important. This highlights the limitations of using only climate and land cover when projecting future changes in species’ ranges and emphasises the need for integrative, multi-predictor approaches for more robust forecasting.

Modelling distributions of species and communities is a key task for modern ecological research and conservation planning. Modelling mountain birds has specific challenges: mountain environments are characterized by steep gradients, where conditions in terms of climate, topography and habitat change markedly over relatively small scales. Moreover, mountain bird species are often less comprehensively monitored than lowland species, resulting in a general paucity of information for many species. We review the approaches to deal with these challenges in order to increase model accuracy to enhance ecological research and to improve conservation planning in mountain environments. We discuss how consistency between species occurrence and climate is tested, and what approaches help to assess distribution dynamics. We assess the current strategies to model microclimate and microhabitat, and how they could be incorporated in distribution modelling over increasingly larger extents. We discuss the pros and cons of (and the potential options for) modelling multiple species vs. community traits to get broad scale multi-species projections which are useful to evaluate the general persistence and resilience of mountain bird communities. Finally, the opportunities presented by Citizen Science data to contribute to monitoring and modelling mountain bird populations are assessed.

Cities can host significant biological diversity. Yet, urbanisation leads to the loss of habitats, species, and functional groups. Understanding how multiple taxa respond to urbanisation globally is essential to promote and conserve biodiversity in cities. Using a dataset encompassing six terrestrial faunal taxa (amphibians, bats, bees, birds, carabid beetles and reptiles) across 379 cities on 6 continents, we show that urbanisation produces taxon-specific changes in trait composition, with traits related to reproductive strategy showing the strongest response. Our findings suggest that urbanisation results in four trait syndromes (mobile generalists, site specialists, central place foragers, and mobile specialists), with resources associated with reproduction and diet likely driving patterns in traits associated with mobility and body size. Functional diversity measures showed varied responses, leading to shifts in trait space likely driven by critical resource distribution and abundance, and taxon-specific trait syndromes. Maximising opportunities to support taxa with different urban trait syndromes should be pivotal in conservation and management programmes within and among cities. This will reduce the likelihood of biotic homogenisation and helps ensure that urban environments have the capacity to respond to future challenges. These actions are critical to reframe the role of cities in global biodiversity loss.

This chapter summaries what is known about population trends of mountain birds, especially in Europe and North America. A European mountain bird indicator, which summaries the population trends of 44 alpine species, suggests an overall slightly increasing mountain bird population during 2002–2020. Regional North American indicators, based on up to seven alpine species showed either stable or declining trends during 1968–2020. In European mountains, cold-dwelling species had on average less favourable regional population trends than warm-dwelling species, and long-distance migrants tended to have more negative trends than short-distance migrants and residents. There were also spatial differences in trends of the indicators in Europe: mountain birds in general increased in the Alps but decreased in the UK. A comparison between two European breeding bird atlases showed that the distribution area of mountain birds has generally decreased since the 1980s, and mountain specialists have lost more of their range than mountain generalists. Monitoring alpine species presents many challenges which has led to poor coverage in surveys even in areas with well organised bird monitoring programmes at low elevation. The necessary future improvements needed for successful bird population monitoring in mountain areas will, in many instances, require strong financial support.

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.

1. Acoustic monitoring is an effective and scalable way to assess the health of important bioindicators like bats in the wild. However, the large amounts of resulting noisy data requires accurate tools for automatically determining the presence of different species of interest. Machine learning-based solutions offer the potential to reliably perform this task, but can require expertise in order to train and deploy. 2. We propose BatDetect2, a novel deep learning-based pipeline for jointly detecting and classifying bat species from acoustic data. Distinct from existing deep learning-based acoustic methods, BatDetect2’s outputs are interpretable as they directly indicate at what time and frequency a predicted echolocation call occurs. BatDetect2 also makes use of surrounding temporal information in order to improve its predictions, while still remaining computationally efficient at deployment time. 3. We present experiments on five challenging datasets, from four distinct geographical regions (UK, Mexico, Australia, and Brazil). BatDetect2 results in a mean average precision of 0.88 for a dataset containing 17 bat species from the UK. This is significantly better than the 0.71 obtained by a traditional call parameter extraction baseline method. 4. We show that the same pipeline, without any modifications, can be applied to acoustic data from different regions with different species compositions. The data annotation, model training, and evaluation tools proposed will enable practitioners to easily develop and deploy their own models. BatDetect2 lowers the barrier to entry preventing researchers from availing of effective deep learning bat acoustic classifiers. Open source software is provided at: ### Competing Interest Statement The authors have declared no competing interest.

Identifying climate refugia is key to effective biodiversity conservation under a changing climate, especially for mountain-specialist species adapted to cold conditions and highly threatened by climate warming. We combined species distribution models (SDMs) with climate forecasts to identify climate refugia for high-elevation bird species (Lagopus muta, Anthus spinoletta, Prunella collaris, Montifringilla nivalis) in the European Alps, where the ecological effects of climate changes are particularly evident and predicted to intensify. We considered future (2041-2070) conditions (SSP585 scenario, four climate models) and identified three types of refugia: (1) in-situ refugia potentially suitable under both current and future climate conditions, ex-situ refugia suitable (2) only in the future according to all future conditions, or (3) under at least three out of four future conditions. SDMs were based on a very large, high-resolution occurrence dataset (2901-12,601 independent records for each species) collected by citizen scientists. SDMs were fitted using different algorithms, balancing statistical accuracy, ecological realism and predictive/extrapolation ability. We selected the most reliable ones based on consistency between training and testing data and extrapolation over distant areas. Future predictions revealed that all species (with the partial exception of A. spinoletta) will undergo a range contraction towards higher elevations, losing 17%-59% of their current range (larger losses in L. muta). We identified ~15,000 km2 of the Alpine region as in-situ refugia for at least three species, of which 44% are currently designated as protected areas (PAs; 18%-66% among countries). Our findings highlight the usefulness of spatially accurate data collected by citizen scientists, and the importance of model testing by extrapolating over independent areas. Climate refugia, which are only partly included within the current PAs system, should be priority sites for the conservation of Alpine high-elevation species and habitats, where habitat degradation/alteration by human activities should be prevented to ensure future suitability for alpine species.

Global change in climate and land use have profound effects on species’ geographic and elevational distributions. In European birds, while species are predicted to track their climatic niches upslope, lowland agricultural intensification and high elevation land abandonment can drive elevational shifts. Species traits that can predict response to change in climate and land use can inform conservation, but thorough examination of their relationships with elevational shifts in European birds are lacking. We estimate change in the elevational distributions of 71 species from 1996 to 2016 in a region of the western Palearctic with wide elevational gradients (approximately 3,000 m) and large changes in temperature. We model the relationships between elevational shifts and species traits associated with resource preference and adaptive capacity at five reference points including the cool edge, warm edge, and the core of species’ elevational distributions. When intermediate reference points were removed changes to the results were negligible, indicating that three reference points are likely sufficient. We found significant upslope and downslope shifts in 56% and 23% of our study species, respectively. Asymmetric rates of shifts in the cool and warm edges caused significant contractions in elevational extent in 30% of our study species. The effect of elevational preference (i.e. midpoint elevation) was habitat dependent. Movement in alpine birds was unidirectionally upslope, with nearly half displaying significant or apparent elevational range contractions. In woodland birds, asymmetries of shifts in reference points led to expansions in extent in low elevation species and contractions in high elevation species. Generally, migrants, species with smaller mass, smaller relative brain size, smaller hand-wing index, and generalists in diet, habitat, and elevation had greater upslope shifts. While elevational shifts in European birds were heterogenous and species-specific, many were rapid, and species traits associated with resource preference and adaptive capacity were associated with common patterns of elevation.

Multi-species indices (MSI) are widely used as ecological indicators and as instruments to inform environmental policies. Many of these indices combine species-specific estimates of relative population sizes using the geometric mean. Because the geometric mean is not defined when values of zero occur, usually only commoner species are included in MSIs and zero values are replaced by a small non-zero value. The latter can exhibit an arbitrary influence on the geometric mean MSI. Here, we show how the compound Poisson and the negative binomial model can be used in such cases to obtain an MSI that has similar features to the geometric mean, including weighting halving and doubling of a species’ population equally. In contrast to the geometric mean, these two statistical models can handle zero values in population sizes and thus accommodate newly occurring and temporarily or permanently disappearing species in the MSI. We compare the MSIs obtained by the two statistical models with the geometric mean MSI and measure sensitivity to changes in evenness and to population trends in rare and abundant species. Additionally, we outline sources of uncertainty and discuss how to measure them. We found that, in contrast to the geometric mean and the negative binomial MSI, the compound Poisson MSI is less sensitive to changes in evenness when total abundance is constant. Further, we found that the compound Poisson model can be influenced more than the other two methods by trends of species showing a low interannual variance. The negative binomial MSI is less sensitive to trends in rare species compared with the other two methods, and similarly sensitive to trends in abundant species as the geometric mean. While the two new MSIs have the advantage that they are not arbitrarily influenced by rare, newly appearing and disappearing species, both do not weight all species equally. We recommend replacing the geometric mean MSI with either compound Poisson or negative binomial when there are species with a population size of zero in some years having a strong influence on the geometric mean MSI. Further, we recommend providing additional information alongside the MSIs. For example, it is particularly important to give an evenness index in addition to the compound Poisson MSI and to indicate the number of disappearing and newly occurring species alongside the negative binomial MSI.

Abstract Global change in climate and land use has profound effects on species' geographic and elevational distributions. In European birds, while species are predicted to track their climatic niches upslope, lowland agricultural intensification and high‐elevation land abandonment can drive elevational shifts. Species traits that can predict response to change in climate and land use can inform conservation, but a thorough examination of their relationships with elevational shifts in European birds is lacking. We estimate the change in the elevational distributions of 71 species from 1996 to 2016 in a region of the western Palearctic with wide elevational gradients (approximately 3000 m) and large changes in temperature. We model the relationships between elevational shifts and species traits associated with resource preference and adaptive capacity at five reference points including the cool edge, warm edge, and the core of species' elevational distributions. When intermediate reference points were removed, changes to the results were negligible, indicating that three reference points are likely sufficient. We found significant upslope and downslope shifts in 56% and 23% of our study species, respectively. Asymmetric rates of shifts in the cool and warm edges caused significant contractions in elevational extent in 30% of our study species. The effect of elevational preference (i.e., midpoint elevation) was habitat dependent. Movement in alpine birds was unidirectionally upslope, with nearly half displaying significant or apparent elevational range contractions. In woodland birds, asymmetries of shifts in reference points led to expansions in extent in low‐elevation species and contractions in high‐elevation species. Generally, migrants, species with smaller mass, smaller relative brain size, smaller hand‐wing index, and generalists in diet, habitat, and elevation had greater upslope shifts. While elevational shifts in European birds were heterogenous and species‐specific, many were rapid, and species traits associated with resource preference and adaptive capacity were associated with common patterns of elevation.

Aim: In biodiversity monitoring, observational data are often collected in multiple, disparate schemes with greatly varying degrees of standardization and possibly at different spatial and temporal scales. Technical advances also change the type of data over time. The resulting heterogeneous data sets are often deemed to be incompatible. Consequently, many available data sets may be ignored in practical analyses. Here, we propose a more efficient use of disparate biodiversity data to assess species distributions and population trends. Location: Switzerland (Europe) Taxon: Birds Methods: We developed an integrated, hierarchical species distribution model with a joint likelihood for all data sets using a shared state process (e.g., latent species abundance or occurrence), but distinct observation process for each data set. We show how the abundance submodel of a binomial N-mixture model can fuse four different data types (count, detection/non-detection, presence-only, and absence-only data) and enable improved inferences about spatio-temporal patterns in abundance. As case studies, we use data from multiple avian biodiversity monitoring schemes. In the first, the goal is estimating abundance-based species distribution maps. In the second, we infer trends in population abundance across time. Results: Accuracy and precision of abundance estimates increased when combining data from different sources compared to using a single data source alone. This is particularly valuable when data from each single data source is too sparse for reliable parameter estimation. Main conclusions: We show that exploiting the complementary nature of "cheap", but abundant, citizen-science data and less abundant, but more information-rich, data from structured monitoring programs might be ideal to estimate distribution and population trends more accurately, especially for rare species. Joint likelihoods allow to include a wide variety of different data sets to (1) combine all the available information and to (2) mitigate weaknesses of one by the strength of another.

The merging of community ecology and phylogenetic biology allows us to link broader evolutionary processes to local ecological processes, thereby increasing our understanding of community assembly. A recurrent way to test how species assemblages respond to different abiotic conditions and evaluate the role of evolutionary constraints in community assembly is through using environmental gradients as natural treatments. Here, we combine phylogenetic and trait-based methods to evaluate how the phylogenetic diversity and composition of bird assemblages and their community-weighted traits vary along an elevational gradient in the Swiss Alps. For this purpose, we used four life-history traits considered to be key indicators of individual species response to environmental changes: clutch size, number of breeding attempts, dispersal capacity and lifespan. Controlling for phylogeny, we determined whether environmental filters (elevation, habitat type) act on these traits independently of the level of relatedness among species. We found that phylogenetic dispersion decreases with elevation, but the signature of phylogenetic clustering was weak. Phylogenetic fuzzy weighting showed that the distribution of bird species across plots was related to the two environmental gradients; nonetheless, such influence was not determined by the phylogenetic relationships in either case. That is, there are no specific clades associated with particular elevation or habitat types. We also found that high elevation communities around the treeline were composed of species with lower reproductive rates, reduced lifespan, and lower dispersal capacity, which would make them less resilient to environmental change. Although traits showed moderate phylogenetic signal, only the lifespan was phylogenetically structured. In the remaining cases, the trait-environment association was not mediated by the phylogenetic relationships among taxa. Our study indicates that evolutionary constraints do not represent a significant driver of community assembly in Alpine bird communities and support the notion that phylogeny may often not be a good proxy for traits subject to environmental filtering.