Diversity and Distributions

Evidence is accumulating that global change is altering species distributions. Yet, detailed knowledge is missing about the relative and joint contribution of different drivers to observed species responses. Here, we implemented an impact attribution framework based on counterfactual simulations to assess the impact of climate and land use change on occupancy dynamics of North American breeding birds. We used a Bayesian framework to fit process-explicit dynamic occupancy models to long-term survey data for 159 species from 1995 to 2019, and quantified predictive performance using spatial and temporal cross-validation. We then assessed the relative importance and effect direction of climate and land use change while accounting for model predictive accuracy. Results indicate that climate change negatively affected 90 % of the species and land use change negatively impacted 96 %. Climate change emerged as more important than land use change for driving changes in occupancy across species. Remarkably, the effects of both drivers were mostly antagonistic rather than acting additively or synergistically. Climate was the most important driver for bird communities in the western USA, while land use change dominated in the southeast, and combined climate and land use change in the northeast. Our analysis demonstrates that recent changes in North American bird distributions are shaped by multiple global change drivers acting in concert. The effect of recent climate and land use change were mostly antagonistic, and thus trends in bird occupancy dynamics could not be understood by studying the impact of those drivers in isolation. By disentangling the effects of climate and land use change on biodiversity trends, impact attribution approaches can improve our understanding of global change impacts and can support conservation planning and more accurate and realistic projections of biodiversity response to global change.

Rosa gallica L., the French rose, is a perennial, tetraploid, heterozygous species that naturally propagates by seed and sucker. It occurs in the wild, primarily in Europe, and also exists as cultivated varieties. R. gallica cultivars were extensively bred and cultivated in France at the beginning of the 19th century. Although several hypotheses have been proposed regarding the species expansion based on historical records, none have been assessed using molecular data. Indeed, its genetic diversity has so far been investigated only at local or regional scales, hindering the identification of the evolutionary factors shaping its present-day distribution. Using 29 sequenced microsatellites, we genotyped a comprehensive sample of 1618 individuals, including wild R. gallica from 219 sites across the species range, rose cultivars, and specimens from other Rosa species. We then detected clonal lineages and characterized the range-wide genetic diversity and structure, aiming to disentangle the roles of natural and human factors in shaping the distribution of R. gallica, with particular focus on France. French diversity appears particularly structured compared to the rest of the range, suggesting multiple origins within France. Populations in South Alps, Central Eastern Europe, and Eastern France appear to have recolonized naturally from a single southern glacial refugium. In contrast, populations in the western part of France likely resulted from more recent natural or human-mediated dispersal. Finally, clonal lineages containing both wild and cultivated individuals were predominantly found in France, highlighting the role of human-mediated dispersal in 28 of the 98 French sites studied. These findings show that the present-day natural range of R. gallica was shaped primarily by post-glacial recolonization, but also reveal a contribution of human activities to its recent dispersal, particularly in France, where cultivated varieties were intensively bred and exchanged.

Retrospective ecological niche modeling (rENM) combines historical species occurrence records with historical environmental data to reconstruct the spatio-temporal dynamics of species-environment relationships under changing conditions. Despite growing recognition that those relationships can be nonstationary, time-series approaches to ecological niche modeling remain uncommon, and the tools to support them at scale are limited. Here, we describe the rENM Framework, an experimental, open-source suite of R packages that automates a complete rENM workflow spanning data preparation, ensemble time-series construction, trend analysis, AI interpretation, and report generation. The framework integrates eBird occurrence records with environmental variables derived from NASAs MERRA-2 reanalysis across a 45-year study period (1980-2024) and executes a complete analysis for any species with eBird data through a single function call. By treating climatic suitability as a dynamic ecological response surface rather than a static baseline, the framework produces the following analytical products that complement conventional ecological niche modeling approaches: suitability time series, long-term trend and acceleration maps, centroid displacement estimates, bioclimatic velocity metrics, variable contribution trajectories, and hotspot analyses identifying areas of accelerating suitability decline. We illustrate the frameworks outputs with a representative run for Cassins Sparrow (Peucaea cassinii), a grassland species of conservation concern in the arid southwestern United States and the focal species throughout our development work. The frameworks automated, unsupervised pipeline makes systematic application across large numbers of species tractable, with direct implications for conservation assessments, such as State Wildlife Action Plans, where species-specific analytical capacity is often limited by available resources. The rENM Framework is openly available on GitHub and archived on Zenodo.

Social wasps (family: Vespidae) are increasingly concerning invaders and have been subject to increased detections and a growing number of invasive populations in the last few decades. As established invasive populations are challenging to eradicate, preventing introductions and prioritizing early interventions are the most cost-effective management solutions to mitigate these effects. A current challenge to this approach is that species distribution data is limited for many social wasp species, hindering our ability to accurately predict novel habitats with high suitability. To address this gap, we used MAXENT to create species distribution models (SDM) for 299 species of social vespid. We identified existing invasive populations of social wasps and incorporated their current invasive ranges to improve the transferability of our models in predicting habitat suitability in new environments. Current range sizes and habitat suitability varied widely among species and genera. We identified new species of high invasive concern, particularly in the genus Vespa. We also identified previously unrecognized regions that may be at high risk of future invasion primarily in Central Africa and the Indo-Australian Archipelago. Combining current and suitable ranges, we calculated an "Invasion Risk Score" to compare the relative likelihood of each species establishing a new invasive population based upon habitat suitability. To assess invasion risk in the future, we projected habitat suitability under four Shared Socioeconomic Pathway (SSP) climate change scenarios. Under all scenarios, species faced significant changes in habitat suitability for current native ranges. Habitat suitability generally shrank and shifted towards the poles, leaving equatorial species at highest risk of habitat loss. Notably, Vespa was the only genus whose suitable habitat expanded under these climate scenarios. Our framework demonstrates how multi-species SDMs can be applied to risk management of invasive populations.

Protected areas are vital to the recovery of endangered species. Of the 24 remaining endemic passerines in Hawaii, 16 species are endangered or critically endangered. Yet protected areas in the archipelago are changing as a result of climate change and biological invasions. For example, the non-native southern house mosquito (Culex quinquefasciatus), the primary vector of avian malaria (Plasmodium relictum), has been encroaching upward as higher elevations warm. How the ranges of endemic birds have also shifted their range upward in the Ka[u] Rainforest, the largest native forest on the Island of Hawaii, is not well understood. We used hierarchical distance sampling to characterize how population density has changed from 2002 to 2024 for eight endemic bird species in the Ka[u] Rainforest. For five species, the most parsimonious model included an interaction between year and a quadratic elevation effect. Species that were most common at lower elevations in 2002, e.g., Apapane (Himatione sanguinea), tended to be most common at mid-elevations by 2024. Species that were already most common at higher elevations, such as Iiwi (Drepanis coccinea) and Hawaii [A]kepa (Loxops coccineus), tended to decline in density. For example, Iiwi density at 1,530 m declined from 3.31 birds per ha (95% confidence interval [CI]: 2.67-4.11) to 1.34 birds per ha (95% CI: 1.05-1.71), and Hawaii [A]kepa were completely extirpated from elevations below 1,530 m by 2024. Our results demonstrate how the elevational ranges of endemic species have shifted in response to climate change, biological invasions, and habitat degradation. Translating these results into conservation measures may require a more thorough investigation of the causal mechanisms of these range shifts with finer scale habitat data, under the same hierarchical modeling framework.

Citizen science observations are abundant, but conservation requires turning uneven records into reliable predictions and directing new surveys to where information is missing. We developed a biodiversity platform for Japan that is updated monthly and integrates 2.32 million records to predict 8,297 species across seven taxonomic groups. Shared representation models outperformed species-specific models in four groups and extended predictions to species with few records. Five independent datasets, including structured monitoring, environmental DNA and complete forest inventories, confirmed that the models ranked observed species and occupied sites above alternatives, with median AUCs of 0.724 to 0.894 across sites and 0.650 to 0.841 across species. For any user-selected area, the platform returns candidate species, distribution predictions, a biodiversity map corrected for uneven observation effort, a conservation priority map for native species and a map recommending where to survey next. This map highlights places where species with few records are predicted to occur despite limited sampling. Independent observations showed that areas ranked highly by this predicted potential contained many such species, indicating that model predictions can help direct surveys toward knowledge gaps. New observations are incorporated into monthly updates, creating a national feedback system connecting citizen science, local conservation decisions and future surveys.

Long-lived plants facing anthropogenic disturbance often exhibit recruitment failure despite persistent reproductive adults, generating extinction debt masked by longevity. However, whether adult presence reliably reflects environmental suitability for recruitment remains unclear. Here, we examine ontogenetic niche differentiation and its consequences for recruitment in Jubaea chilensis, an endangered long-lived Mediterranean palm with an aging population. We assigned individuals within the largest known population to four ontogenetic stages and characterized their environmental niches using climatic, edaphic, topographic, and vegetation variables. We then applied spatial and multivariate analyses, including Random Forest models to evaluate environmental segregation and identify predictors of seedling establishment. Age classes occupied significantly different environmental niches, with the greatest differentiation between seedlings and reproductive adults. Saplings and adult differentiation reflected mainly topographic variables at landscape scale, whereas seedling establishment was primarily predicted by microhabitat conditions (vegetation cover heterogeneity, east-facing slope orientation, and soil texture). This pattern is consistent with niche reconfiguring throughout the life cycle, suggesting that adult occurrence and recruitment suitability respond to distinct environmental conditions. Over one-fifth of sampled individuals occupied high-suitability sites without recruitment, suggesting that ontogenetic niche shifts are associated with a spatial decoupling between adult persistence and recruitment, consistent with demographic collapse independent of habitat degradation. This failure is likely mediated by insufficient effective seed dispersal, as the sole disperser (Octodon degus) preys on most seeds before dispersal. Conservation strategies based solely on adult distribution may therefore overestimate effective habitat and underestimate extinction risk in long-lived species.

AimSpecies in mountain ecosystems often experience upslope distribution shifts in response to climate change. However, elevational range dynamics exhibit substantial complexity around this general trend, with varying magnitude and direction of shifts observed among studies. We tested whether factors other than temperature, such as habitat size and land use, are also responsible for observed elevational shifts in a cold adapted species. LocationHokkaido, Japan MethodsWe resurveyed 61 historical (1963-2007) occurrence sites covering a wide elevational range (60-2,210 m) within the distribution range of the northern pika (Ochotona hyperborea). We assessed the existence of elevational shifts using quantile regression and the relative importance of temperature, habitat size, and land use on the shift using occupancy analysis. ResultsWe detected presence of the northern pika at 41 sites, suggesting extirpations at 20 sites (32.8%) across a wide elevational range of 60-1,550 m. The concentration of extirpation sites at low to mid elevations resulted in a significant upslope shift of the distribution centroid, although the shift was nonsignificant at lower and upper portions of the range. The occupancy analysis revealed a negative effect of long-term mean of summer maximum temperature and a stronger positive effect of habitat size. ConclusionsThis highlights the susceptibility of the northern pika to heat stress and the importance of larger habitats and thus habitat heterogeneity for persistence of local populations. Given the possibility that the observed shift represents a precursor of elevational contraction, continuous monitoring of the local populations is highly needed to evaluate their long-term viability.

Understanding the spatial patterns of biodiversity and their environmental determinants is fundamental to ecology and conservation, particularly in mountainous transitional zones where species assemblages can shift rapidly. Amphibians, as highly sensitive organisms, are excellent indicators of environmental change, yet quantitative assessments of their diversity in the Huangshan Mountains-a biodiversity hotspot at the junction of the Palaearctic and Oriental realms in southern Anhui, China-remain limited. We conducted systematic line-transect surveys across 200 grids (5 km x 5 km) during the spring and autumn of 2023 and 2024, recording a total of 10,342 individuals belonging to 23 species, 20 genera, 9 families, and 2 orders. Three species (Fejervarya multistriata, Microhyla fissipes, and Bufo gargarizans) were identified as dominant, and two nationally protected species (Hoplobatrachus chinensis and Andrias davidianus) were detected. Inter-annual alpha diversity did not differ significantly, but pronounced seasonal variation was observed, with spring supporting higher Shannon-Wiener and Pielou evenness than autumn in both years. Using generalized additive models and model averaging, we found that annual precipitation and the normalized difference vegetation index (NDVI) were consistently the strongest positive predictors of Shannon-Wiener diversity, Simpson dominance, and species richness, while species richness also declined significantly with increasing human footprint. Total beta diversity (Soerensen dissimilarity) was very high (0.981) and overwhelmingly driven by species turnover (97.86%) rather than nestedness. Partial Mantel tests and distance-based redundancy analysis further revealed that environmental distances-particularly annual precipitation-significantly shaped overall beta diversity and its turnover component after accounting for geographic distance. These results highlight the predominant role of climatic and vegetation gradients in structuring amphibian assemblages in this subtropical mountainous region, providing baseline data to inform local conservation strategies.

Conserving migratory birds effectively requires full annual cycle strategies that identify where on-the-ground efforts can have the greatest impact. Here, we present a hemispheric spatial framework to identify priority areas for 112 migratory bird species across the Americas. Building on full annual cycle prioritizations, we defined finer-scale spatial planning units that reflect differences in migratory and congregational behaviors between shorebirds and landbirds. We compiled population data for each planning unit and focal species and applied conservation planning tools to design area-efficient portfolios of sites and landscapes that secure 10% of each species population within the Americas flyways. The resulting minimum area portfolios include 175 shorebird sites and 80 landbird landscapes optimized to meet the species-specific 10% representation targets across breeding, non-breeding, and passage seasons. We also identified a broader set of complementary solutions, ranked by an importance score, to provide decision-makers with flexible options for strategic resource allocation. This framework provides the scientific foundation for the Americas Flyways Initiative (AFI), which aims to catalyze investment in nature-based solutions and bird-friendly infrastructure to enhance the conservation of migratory birds and strengthen the resilience of the Americas flyways by 2050.

Reliable population estimates are essential for wildlife management, yet monitoring schemes often do not match the administrative scale at which decisions are made. We illustrate this challenge using the Eurasian lynx in the canton of Valais, Switzerland, where official state monitoring is fragmented across three reference areas surveyed in different years. We analyzed three winters (2023-2026) of independent, canton-wide camera trap data, recording 899 independent lynx captures (27, 31 and 34 adults per winter). Lynx distribution and reproduction concentrated in the Northwest and connected to the thriving Pre-alpine populations. Density modelling for 2025/2026 estimated 37 independent lynx (95% CI: 26-52) on the whole cantonal territory, corresponding to a density of 1.09 (0.77-1.56) individuals per 100 km2. These estimates are substantially below the figures improperly extrapolated from a cross-cantonal reference area and conveyed by political authorities. Future lynx management decisions should be rooted in scientifically sound, scale-relevant information.

AimHere we aim to disentangle species-specific bioclimatic drivers of forest site productivity and project their future dynamics, providing a spatially explicit basis for anticipating climate-driven shifts in productivity and their implications for forest carbon sequestration. LocationIberian Peninsula. Time period1985-2014 (calibration); 2071-2100 (projected under CMIP6 scenarios). Major taxa studied21 Iberian tree species. MethodsWe used Site Form (SF) maps derived from the Third Spanish National Forest Inventory, spatially interpolating plot-level SF estimates as a continuous productivity index and relating them to 25 bioclimatic variables. Multiple linear regression models were selected via complementary stepwise and subset regression and validated on independent hold-out data (80%/20% split). ResultsValidated [Formula] ranged from 0.46 (Quercus faginea) to 0.97 (Pinus pinaster); 17 of 21 species reached [Formula]. BI013 precipitation of the wettest month), not BI014, was the most frequently retained predictor (15/17); BI014 was retained in only (11/17 models with a near-even sign split. Combining projected changes in mean productivity and habitat extent under SSP5-8.5, fifteen of sixteen applicable species lose total productivity by 2071-2100, six -- including Fagus sylvatica and Betula alba -- collapsing to below 1% of their reference-period value; only Pinus pinaster gains, and only under the lowest-emission pathway (up to 175%) -- under SSP5-8.5 it too loses productivity, albeit less than any other species (35% of its reference-period value retained). Limiting warming to SSP1-2.6 spares Mediterranean pine and oak species but not Euro-Siberian and montane ones. Main conclusionsThese validated, extrapolation-aware models reveal a near-universal, climate-driven collapse in Iberian forest site productivity, with direct implications for the carbon-sink potential currently attributed to these forest types, and provide a route to dynamic, climate-aware carbon-uptake estimates for the region.

1. Migration is a widespread phenomenon across taxa, yet the ecological mechanisms underlying its evolution and maintenance, particularly whether migratory behaviors are primarily driven by access to spatially restricted breeding sites or by seasonal tracking of trophic resources, remain poorly documented outside birds and large mammals. Despite increasing evidence that reptiles perform seasonal migrations, the ecological mechanisms underlying these movements have rarely been formally tested. 2. The critically endangered Galapagos pink land iguana (Conolophus marthae), endemic to Wolf Volcano, Isabela Island, exhibits partial migration along a steep altitudinal gradient, providing an opportunity to disentangle the relative roles of breeding-site availability, trophic resource dynamics, and thermoregulatory conditions as drivers of migration. 3. We used GPS tracking data from 22 individuals (7 males, 15 females) monitored between 2019 and 2023, combined with high-resolution spatio-temporal models of vegetation productivity and air temperature across the species' altitudinal range, to characterize population-level movement patterns and evaluate competing hypotheses explaining the evolution of this migratory behavior. 4. Movement models revealed a clear pattern of partial migration: 16 out of 22 tracked individuals performed seasonal altitudinal movements between a restricted high-elevation mating area and a larger dispersal area at lower elevation, with males reaching the mating area approximately 48 days earlier than females. The dispersal area remained consistently more productive than the mating area throughout the year, rejecting the prediction that individuals should track the shifting trophic resource peaks. Instead, the mating season coincided with the local productivity peak within the mating area, whereas temperature differences between areas were small (ca. 2{degrees}C) and did not explain migration timing. 5. These results support a site-dependent hypothesis of partial migration over a resource-tracking hypothesis, indicating that access to spatially restricted breeding sites is the primary driver of migration in this species, with local trophic resource dynamics fine-tuning reproductive timing. Providing empirical evidence for the ecological mechanisms underlying migration in a large terrestrial reptile, our results extend site-dependent theories of migration beyond birds and mammals and identify breeding-site availability as a key ecological driver of migratory behaviors across taxa.

The accelerated loss of biodiversity in sub-Saharan Africa threatens the functioning of tropical ecosystems. In Cote dIvoire, the Comoe National Park (PNCOMOE), a Sudano-Guinean savannah, and the Tai National Park (PNTAI), a dense rainforest, both UNESCO World Heritage Sites, are home to fauna assemblages of global importance, whose long-term resilience remains insufficiently quantified. This study assesses and compares, over a decade (2014-2025), the functional stability of vertebrate communities in these two contrasting ecosystems, using nine metrics covering resistance, invariance, persistence, interspecific synchrony, Tilmans stability, Jacobian resilience and a Composite Stability Index (CSI). Abundance data for 107 vertebrate species were collected via foot transects at PNTAI and aerial surveys at PNCOMOE. The stability metrics were calculated using the R package estar, integrated with an alpha diversity analysis (Shannon H', species richness S, Pielous evenness J') and a Jacobian spectral analysis within a multidimensional ecological assessment. PNTAI (0.708) exhibits significantly higher alpha diversity (H' = 2.82; S = 55.7 taxa) and community resilience 4.6 times higher than in the PNCOMOE (0.153). Its interspecific asynchrony index (0.504) reveals a strong portfolio effect, absent in the PNCOMOE (0.232). In contrast, PNCOMOE exhibits higher temporal invariance (0.382 versus 0.116) and Tilman stability (0.276 versus 0.152), reflecting more predictable dynamics. The overall ICS favours the PNTAI (0.484) and (0.370). The Jacobian analysis detects local instability in both parks (Re({lambda}max) = 5.58 at the PNTAI; 3.73 at the PNCOMOE). The two parks exhibit distinct yet complementary stability architectures: PNTAI relies on dynamic stability based on resilience and interspecific compensation, whilst PNCOMOE demonstrates conservative stability through temporal regularity. The absence of calculable resilience at PNCOMOE suggests a potential crossing of a functional degradation threshold, arguing for urgent restoration interventions and differentiated conservation strategies, tailored to the resilience mechanisms specific to each ecosystem.

Managers must make decisions in the face of uncertainty, especially when available resources are limiting. Identifying thresholds when certain conditions are met or exceeded enable the potential to mitigate risks. In 2005, sustainable harvest levels of willow ptarmigan were identified to avoid harvest efforts exceeding three hunter days km2. Here we evaluate these recommendations by analyzing line transect counts and harvest data from six areas forming three open/closed pairs in a region of state managed willow ptarmigan harvest. We developed three sets of Bayesian hierarchical models, one static distance model, and two dynamics models. One mechanistic hazard model and a Gompertz phenomenological model. Adult and juvenile density showed pronounced year-to-year variation that was largely synchronous across all six sites regardless of hunting status. The harvest effort parameter shows a striking difference between the two models. In the Hazard model, is positive, and excludes zero with near certainty, but in the Gompertz model, the parameter is highly uncertain. However, the two models do not contradict each other but answer complementary questions with different sensitivity to the harvest signal, harvest mortality is additive at the individual level, but this additive mortality is masked at the level of population abundance. The demographic cost of harvest is therefore real and quantifiable through the survival chain, but bounded in the long run by the stabilizing dynamics. A fixed limit anchored to monitored effort and bag is not a crude substitute for adaptive management but the appropriate design under the information commonly at hand. It will be a precautionary instrument grounded in the one relationship this study establishes firmly, the translation of hunter effort into harvest mortality.

The ecological and economic threat posed by invasive pests demands proactive mitigation. Species distribution models (SDMs) are widely used in efforts to predict where invasive species might spread after introduction, though such models face several limitations. Among these is the unrealistic assumption of niche uniformity throughout a species' range. This has led to interest in developing SDMs that explicitly account for local adaptation, though few methods have achieved this in a way that confidently separates local adaptation from population structure. Here we develop and implement a sequential SDM approach that incorporates experimentally verified associations between genotype, phenotype, and environment to forecast establishment risk in a major agricultural pest. We leverage genomic data from 738 individuals to characterize the geographic distribution of alleles at a major-effect locus for cold tolerance (tret1) in Helicoverpa armigera, an invasive crop pest of major economic concern in North America. We demonstrate that a recently detected North American population carries a cold-adapted tret1 allele, which has likely contributed to its persistence. We quantify the contribution of cold-adapted tret1 to the potential invasive range of H. armigera in North America under current and future climate scenarios. We find that cold-adapted tret1 may dramatically expand the potential range of H. armigera, and that potential future range expansion is likely to be driven primarily by cold-adapted individuals. Our results highlight the importance of accounting for intraspecific variation in invasive species risk assessments and management strategies.

1. Natal dispersal is a key process in population ecology because it links local demographic processes to broader-scale population dynamics by redistributing individuals. When using capture-recapture data, multistate capture-recapture models using discrete spatial units as states are the gold standard for estimating natal dispersal among spatial units while accounting for spatial variation in survival, recruitment and imperfect detection. However, because their computational cost increases rapidly with the number of spatial units, applications have been limited to a small number of units. Therefore, in practice, these models cannot provide spatially detailed inference on natal dispersal across large landscapes. 2. We develop a computationally efficient Bayesian capture-recapture model, called the efficient natal dispersal (END) model, to estimate natal dispersal among discrete spatial units jointly with spatial variation in demographic parameters and detection probabilities. The END model relies on two key structural features: juveniles and breeders are separated into two arrays, and resightings outside the natal spatial unit are aggregated over time for individuals released as juveniles. 3. Using simulations, we show that the END model is considerably (up to 30 times) more computationally efficient than a conventional multistate model, while maintaining comparable parameter accuracy. We then apply the END model to white stork (Ciconia ciconia) capture-recapture data from Germany across 101 hexagonal spatial units, a spatial resolution at which a conventional multistate model is computationally infeasible. We estimate natal dispersal among units jointly with spatial variation in survival and recruitment. This allows us to identify areas of lower or higher survival, earlier or delayed recruitment, and dispersal probabilities among all units. By combining estimated dispersal probabilities with existing data on the number of juveniles born in each spatial unit, we estimate natal dispersal in terms of numbers of individuals and identify units with positive or negative net migration, sources and sinks. 4. Overall, our approach moves capture-recapture analyses from estimating natal dispersal among a few spatial units to inferring dispersal networks and assessing their demographic consequences across large domains. Our approach is applicable to many spatially structured capture-recapture datasets, opening new opportunities for studying spatial population dynamics.

Understanding how contemporary population declines affect the genomic diversity and structure of threatened species is important for effective conservation. The Eurasian curlew (Numenius arquata) is experiencing severe population declines across Europe, with Ireland among the most extreme, showing declines exceeding 90% over 40 years. Genomic data are increasingly incorporated into policy and used to assess conservation status by estimating genetic diversity, differentiation, inbreeding, effective population size, and adaptive divergence. Such data for curlew is scarce, and the population structure among northern and north-western European breeding populations remains unclear. To address this, we generated whole-genome resequencing data for 56 curlews across Ireland, Britain and Sweden. Irish and British populations showed minimal interpopulation differentiation, but both were substantially differentiated from Sweden. This was apparent from principal component analysis, and admixture and FST analyses. Measures of genetic diversity (nucleotide diversity, heterozygosity, Watterson's{theta} ) were similar across populations. A slightly elevated Tajima's D in Ireland, along with elevated FROH in Ireland and Britain relative to Sweden, may be the early genomic signs of recent population declines. We identified locally selected candidate genes. These had putative roles in metabolic processes, the immune response, and were potentially associated with distinct migratory behaviours and environmental conditions. We find a potential lag in genomic effects of decline being detectable following population contraction. We also show highly migratory species can exhibit differentiation in ecologically relevant traits, potentially driven by high site fidelity. These findings warrant consideration in translocation planning and broader conservation strategies.

Biodiversity loss is driven by unsustainable human activities, yet the contextual conditions and underlying drivers of threats remain poorly understood. We assessed how protected areas, socioeconomic conditions, and biophysical factors explain global patterns of threat probabilities across six major threat types and four vertebrate taxa. We identified key explanatory variables and their associations with threats using Extreme Gradient Boosting (XGBoost) and SHapley Additive exPlanations (SHAP). Socioeconomic conditions, specifically human development and income inequality, were the strongest predictors. Their associations were complex and non-linear: notably, high human development index (HDI) was associated with both higher and lower threat probabilities, depending on inequality and regional context. Second, land cover and biophysical variables, such as shrubland cover, tree cover, and elevation range, explained additional, but taxon-specific variation. Finally, protected areas showed limited ability to explain threat patterns. By linking threat probabilities to their contextual and socioecological conditions, we aim to build a better understanding of the systemic drivers of biodiversity loss.

The number of species introduced outside of their historical ranges by human activity continues to rise. A subset of these species establishes, form self-sustaining populations, and some (invasive alien species) go on to cause substantial harm to biodiversity and ecosystems. Preventing new invasive alien species from establishing is the key focus of interventions, because post-establishment management is costly and often fails. However, it remains unclear how effective multilateral efforts have been in curbing the rise. Here we show that the emergence of new invasive alien species across countries is slowing, and trends are similarly negative across geographically diverse countries. Using data and modelling advances, we find a 35% reduction in the establishment of new invasive alien species over a policy-relevant 50-year time frame. The findings directly inform the assessment of progress for the invasive alien species target of the Kunming-Montreal Global Biodiversity Framework, and provide a global baseline for monitoring rates of invasive alien species establishment. Furthermore, the slowdown suggests that policy and investment over recent decades to prevent invasive alien species from entering and establishing in countries have had a positive effect.