Diversity and Distributions

Connectivity is critical to sustaining endangered carnivores in speciose yet fragmented landscapes such as in the global south. Corridors to mitigate fragmentation are designed based on charismatic species or habitat-based approaches, but their multispecies effectiveness for maintaining functional connectivity remains poorly tested. We combined landscape genetic analyses across five sympatric carnivores - Panthera tigris, Panthera pardus, Prionailurus viverrinus, Felis chaus, and Melursus ursinus, to evaluate how landscape features shape functional connectivity in a globally important felid landscape. We then assessed the efficiency of existing tiger corridors and single-species surrogates for maintaining multispecies functional connectivity. Species exhibited contrasting responses to landscape variables, producing distinct resistance surfaces and connectivity corridors. Spatial similarity of connectivity between species pairs was highly variable (r = 0.14-0.93), but no single species effectively captured connectivity patterns of the broader carnivore community (maximum mean overlap of <0.7 across species). Moreover, genetically optimized corridors were at least 70% more efficient in capturing connectivity compared to existing tiger corridors, demonstrating mismatches between structural and functional connectivity. Our results highlight limitations of surrogate-based corridor planning and demonstrate that integrating multispecies functional connectivity can substantially improve conservation planning in human-dominated landscapes.

Understanding how habitat connectivity shapes biodiversity remains a major ecological challenge. In particular, the roles of connectivity and ecological heterogeneity on co-variation in plant species diversity and intraspecific genetic diversity is not understood. We combined species distribution modelling, resistance-to-movement mapping, landscape connectivity analysis and population genomics to investigate diversity patterns in three wet meadow herbs, Scorzonera humilis, Oenanthe peucedanifolia and Lychnis flos-cuculi, and their surrounding plant communities. Genetic diversity patterns differed strongly among co-occurring species. Connectivity metrics explained genetic diversity only in O. peucedanifolia, and environmental drivers of genetic diversity were highly species specific. Importantly, genetic diversity changed with the presence of some species in the community, but it was consistently unrelated to indicators of local plant community diversity. Overall, the processes shaping within-species biodiversity may differ fundamentally from those structuring habitat connectivity and plant species communities, with important implications for conservation.

Global plant biodiversity and associated ecosystem services are being severely threatened by human activities and land-use change. This has led to an immense effort to assess the extinction risk of individual species and associated drivers to inform conservation actions and priorities. However, we lack a more general understanding of the processes that determine variation in vulnerability and resilience among plant taxa facing the same threats in the same or similar ecological conditions and geographic regions. This research helps identify these generalities and determines species and traits that are at disproportionate risk of extinction. Given Floridas high levels of biodiversity and endemism, coupled with ongoing rapid and extensive human development, we use the states native flora as our model system. By combining data on extinction risk, human-induced threats, and plant functional traits, our results show that species threatened with extinction cluster within trait space, with smaller herbaceous species at greater risk than larger woody species. We also find that all categories of threat considered in our study (Development and Infrastructure; Environmental Change and Modification; Natural Hazards and Climate Change; and Resource Extraction) increase extinction risk except for the Invasive Species, Pests, and Diseases threat category. Generalised linear mixed-effect models show differing responses of species to environmental change, habitat loss, and fragmentation, driven by differences in life-history strategies and dispersal capabilities and mechanisms. The varied responses of species facing the same threats uncovered here highlight that plant functional traits in the context of regional ecosystem processes can be used to predict species-specific responses to threats and land-use change, providing a valuable resource for conservation management and prioritisation. Article impact statementPlant functional traits can be used to estimate species-specific responses to human-induced threats and predict overall extinction risk.

Aim: To forecast near-future arrivals of non-native terrestrial and freshwater vertebrates at the regional level. Location: Global (geopolitical regions worldwide, including countries and main administrative divisions). Methods: We compiled first regional record data and assembled functional and macroecological variables for 1,931 non-native vertebrate species. For each region, we identified recently arrived non-native species using retrospective windows of thirty and twenty years ending in 2015 (1986-2015; 1996-2015). We then fitted region-specific random-forest models classifying recently arrived species versus those not yet arrived using as predictors: (i) harmonised species traits (e.g., habitat, diet, body size and native-range attributes) and (ii) spread history, capturing time since first record elsewhere. Predictive performance was evaluated using leave-one-out cross-validation, comparing full models with trait-only and spread-only variants. We also assessed relationships between predictive accuracy, predictor importance, and the geographic positioning and trade connectedness of regions. Finally, we predicted region-specific probabilities of arrival for species not yet recorded. Results: Forecasting accuracy was consistently high across regions and taxa, with AUC values above 0.9 in more than half of the focal regions. Full models substantially outperformed models using either predictor set alone, and spread-history-only models typically exceeded trait-only models. Relative importance of spread-history predictors declined with geographic distance to the focal region, whereas predictability was lower in highly trade-connected regions. Predicted near-future high-risk arrivals were dominated by birds and freshwater fishes and showed strong regional structuring. A small set of species ranked highly across many regions (e.g., birds: Phasianus colchicus, Acridotheres tristis, Amandava amandava, Colinus virginianus, Corvus splendens and Lonchura malacca; fishes: Coregonus peled and Oreochromis mossambicus; mammal: Oryctolagus cuniculus), suggesting substantial unrealised spread potential. Main conclusions: Near-future regional arrivals of non-native vertebrates are predictable from spread history and species traits. This enables scalable, updateable regional watchlists to support prevention, early detection and horizon scanning.

Effective conservation depends on demographic metrics that reliably reflect species status, particularly population abundance. For elusive species occurring at low densities, however, such metrics remain difficult to obtain. Spatial capture-recapture (SCR) models are the standardized approach for estimating density in marked populations, but their data requirements, especially the need for multiple spatial recaptures across individuals, often limit applicability in small or data-poor populations. This constraint has resulted in knowledge gaps for some of the most vulnerable species, undermining evidence-based conservation planning and management. Using camera-trap data and SCR-derived density estimates from data-rich populations, we evaluated alternative, less data-demanding metrics and tested the hypothesis: Space to Event (STE), Mean Local Abundance (MLA), and Relative Abundance Index (RAI) exhibit predictable relationships with SCR-derived density; if supported, these metrics can reliably estimate density in populations where SCR models cannot be implemented. We applied this framework to the European wildcat (Felis silvestris), an elusive small felid with highly fragmented populations across Europe, for which density estimates are largely lacking despite growing conservation concern. Across 21 study areas spanning most of the species' range, our results indicate that European wildcats generally occur at lower densities than previously reported. SCR-derived estimates (n=10) averaged 10.32 {+/-} 11.56 inds/100km2, while STE enabled density estimation in five additional data-poor areas (mean 5.52 {+/-} 5.33 inds/100km2). STE showed a strong linear relationship with SCR-derived density (R2=0.98), supporting its use as a viable alternative when SCR is infeasible, although it tended to underestimate compared to SCR, especially at higher densities. In contrast, MLA and RAI showed weaker and non-linear relationships with SCR-derived density (R2=0.65), indicating substantially lower explanatory power and suggesting their estimates are more strongly influenced by confounding processes. By explicitly calibrating alternative metrics across a wide density gradient throughout most of the species' distribution, this study provides a transferable methodological framework for estimating density in low-density wildlife populations and the first continent-wide, standardized density assessment of a carnivore species. From a management perspective, our findings identify populations that may be most vulnerable, particularly those with the lowest densities, and highlight the need to prioritize absolute abundance monitoring.

AimsHistorical land use has shaped plant diversity in Central Europe for centuries, and many plant communities of high conservation value have been maintained by long-term traditional management. This study assesses how changes in land use over the past century have affected plant community composition and vegetation-based ecological indicator values in the management-dependent mire community Primulo-Schoenetum ferruginei. LocationSouth-western Germany. MethodsWe conducted repeated vegetation surveys at multiple sites, comparing historical records with recent surveys spanning up to 97 years. Changes in species composition were analysed using multivariate approaches, and shifts in habitat conditions were assessed using indicator values for nutrients, temperature, light and mowing frequency. Information on historical management was compiled from original vegetation sources, while current management data were obtained from responsible conservation authorities and regional administration. ResultsFen communities showed pronounced temporal changes in species composition. Community turnover was significantly associated with shrub encroachment, mowing frequency, hay transfer and early mowing. In addition, species-based indicator values suggested increasing nutrient availability and temperature affinity of the vegetation, alongside decreasing light availability. Disturbance indicators pointed towards less frequent but more severe disturbance regimes in contemporary compared to historical vegetation. ConclusionsOur results demonstrate that management-dependent fen communities are highly sensitive to changes in land-use regimes, i.e. disturbance frequency and severity that is indicated to have significantly changed in the protected areas in this study. These findings highlight the importance of maintaining traditional land management practices when aiming to maintain biodiversity in calcareous fens.

Aims: Species' distributions are determined by the interplay between ecological niche and dispersal ability, constrained by biogeographical barriers. Bald-headed uakaris (Cacajao spp.) are highly specialized primates often associated with seasonally flooded forests. In this study, we used ecological niche models to assess changes in habitat suitability and geographic distribution of uakari species under future scenarios. Location: Western Amazonia. Methods: We integrated ecological niche models, current deforestation data, and dispersal ability to estimate habitat suitability under two Shared Socioeconomic Pathway (SSP) scenarios: intermediate (SSP2-4.5) and very high (SSP5-8.5) greenhouse gas (GHG) emissions. Results: Our models project shifts in suitable conditions for all species. Three of the five species are projected to experience substantial reductions ([&ge;]62%) in suitable habitat conditions within their current ranges by 2050 under both future scenarios. Across the western Amazonia, up to 219,189 km2 and 211,276 km2 of land are projected to be unsuitable within the uakari ranges under the intermediate and very high emissions scenarios, respectively. This is particularly relevant for C. calvus, C. rubicundus, and C. ucayalii. At the species level, the uakaris may lose between 343 km2 and 84,531 km2 of their ranges in the intermediate scenario and 858 km2 and 76,216 km2 in the very high scenario. Shifts in suitability due to climate change are expected to vary from 6 to 191 km in the intermediate scenario and from 5 to 168 km in the very high scenario. Furthermore, the uakaris may lose between 0.5% and 8% of their current ranges due to deforestation in all scenarios. Main conclusions: Our findings reveal a high sensitivity of the uakaris to climate change impacts. It is projected that all species may experience contractions in the suitable areas and spatial suitability within their ranges by 2050, underscoring climate change as a relevant threat to these taxa.

iNaturalist has rapidly grown to become one of the largest contributors of global biodiversity data, being widely used in academic research, to support and inform applied conservation, and to help develop policy indicators for decision makers. However, the availability of iNaturalist data varies based on the digital platform it is accessed from. Here, we assess whether the pathway used to access iNaturalist data from three commonly available biodiversity data sources: iNaturalist, the Global Biodiversity Information Facility (GBIF) and ESRIs ArcGIS Online, alters occurrence record availability and downstream analyses for ecological inference. First, we investigate iNaturalist data availability on ArcGIS Online and find that the reduced field metadata for record location and obscuration information can lead to biased assumptions in the spatial ranges of sensitive species. Second, when assessing iNaturalist records available through GBIF, we find that restrictive Creative Commons observation licenses prevent an average of 26.1% of iNaturalist Research Grade records from being exported to GBIF, and this can lead to differences in environmental niche analysis when compared to datasets including all available research grade records. Understanding differences in platform licensing when integrating across biodiversity data repositories is another consideration for researchers and practitioners when conducting biodiversity assessments. Our results show that the pathway through which iNaturalist data are accessed can function as a methodological filter, potentially altering spatial coverage, the climatic conditions represented by occurrence datasets, and downstream ecological analysis.

Many rare saproxylic (deadwood-dwelling) beetles are among Europes most threatened insects, yet the relative importance of local microhabitat quality versus broad-scale landscape connectivity in shaping their genetic integrity remains poorly understood. We evaluated environmental drivers for 13 saproxylic beetle species--rare old-growth specialists, common taxa, and economically significant pests--across eight major forest complexes in Poland, using double digest restriction-site associated DNA sequencing (ddRAD-seq) paired with plot-level structural inventories and estimated effective migration surfaces (EEMS) modelling. A beta generalized linear mixed model identified deadwood diversity as the only significant within-species predictor of observed heterozygosity ({beta} = 0.041, 95% CI 0.0227-0.0586, p < 10-); total deadwood volume, forest age, time since logging, stump density, and veteran tree density were not significant. Management-category contrasts in observed heterozygosity (Ho) and the inbreeding coefficient (Fis) were non-significant after Tukey adjustment. Predictor x ecological-tier interactions did not differ detectably between rare and common species for five of six structural predictors; time since last logging was the exception ({chi}{superscript 2} = 4.56, p = 0.033). EEMS patterns differed among species and fell into three broad groups: regional lineage barriers, asymmetrical corridors, and surfaces close to isolation- by-distance expectations. These results associate plot-level heterozygosity with deadwood diversity and show that regional gene-flow patterns cannot be generalised across saproxylic beetles. Conservation planning should therefore combine local deadwood restoration with species-specific assessment of landscape connectivity.

Ectomycorrhizal (EM) fungi are vital to forest ecosystems, supporting tree growth and survival. However, their inclusion in conservation policy and action remains limited and little is known about the status of their genetic diversity, which is essential for their long-term survival and adaptation. The Global Biodiversity Framework adopted a genetic indicator based on the effective population size, Ne, to monitor genetic diversity in all species. To date, it is still uncertain how Ne, a key parameter, can be reliably assessed in species with complex life history traits. Ectomycorrhizal fungi are a highly diverse group of taxa displaying haplodiplontic life cycles with partially clonal reproduction. Here, we review the literature to understand how these life history traits might affect Ne and its estimation in six species of EM fungi. We estimated Ne in 19 populations using eight genetic and genomic datasets from selected studies. We compared Ne estimates using Linkage Disequilibrium (LD) and Sibship Frequency (SF) methods. We tested how Ne estimates change due to partial clonality and genetic structure gradients and whether the number of genetic markers influence the precision of the estimates. We show a systematic bias in Ne estimations when large clones are present and when populations are not correctly delimited. We found both methods are not robust to these factors, which makes them unreliable for conservation assessment purposes in EM fungi. This study provides new perspectives for further research into the links between life history traits and the effective population size of ectomycorrhizal fungi.

Understanding the ecological determinants of species ranges is a central goal of ecology. Novel tools like global datasets and machine learning models allow us to describe species ranges with increasing scope and accuracy, and to develop and test ecological hypotheses about their determinants. Here, I focus on the widespread nuisance mosquito and dog heartworm vector Aedes sierrensis, a tree hole-breeding mosquito that is widespread and abundance within its native range in western North America, and develop species distribution models (SDMs) to characterize the species range and its environmental determinants. I find that the species range is highly predictable from long-term average bioclimatic variables. Temperature and precipitation were the primary determinants: suitability was highest at wet-season average temperatures of 0 - 10{degrees}C, minimum temperatures of -5 - 5{degrees}C, and summer temperatures of 8 - 22{degrees}C in environments with adequate seasonal rainfall concentrated in the winter. After accounting for climate, land cover variables showed minimal importance for prediction, but suitability was higher in forests and outside of urban areas. The results are consistent with ecological knowledge of the Ae. sierrensis life cycle from field observations and previous laboratory experiments, suggesting that individual physiological constraints scale up to determine species distributional limits.

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.

Commonly shared patterns of introduction and spread into new environmental conditions are often poorly understood, even though a better understanding of invasion history and niche dynamics among closely related invasive species could give practitioners valuable information to prevent and mitigate the impact of biological invasions. For this study, we investigate the invasion history and niche patterns among congeneric invasive species. We synthesize public occurrence data for five invasive alien anurans (Eleutherodactylus coqui, E. planirostris, E. johnstonei, E. antillensis, and E. martinicensis) to reconstruct their historic introductions and evaluate evidence for climatic niche shifts between their native and established non-native ranges. By pairing these data with current and future climate projections, we compare patterns of range shifts under future climate scenarios. Our results highlight different temporal and geographic introduction histories in invasive Eleutherodactylus, but a strong signal of colonizing broader invasive climatic niches, specifically into colder environmental conditions. Under future climate scenarios, suitable habitats for most of the non-native regions are likely to increase, although this increase is restricted under scenarios with high greenhouse gas emissions. Our results reveal that despite different invasion histories, the ability to spread into colder regions may be a conserved trait among the most widespread Eleutherodactylus anurans. This study ultimately shows that commonalities among closely related invasive species can provide clues about their ability to expand into areas with particular abiotic conditions, a pattern likely to be widespread, offering a potentially valuable opportunity to deploy targeted prevention strategies.

The biodiversity crisis is exacerbated by persistent gaps in taxonomic, geographic, and conservation knowledge. This study provides a comprehensive assessment of Linnean, Wallacean, and conservation shortfalls in Rivulidae (Cyprinodontiformes), one of the most diverse families of Neotropical freshwater fishes. To this end, an extensive dataset was compiled, comprising 494 valid species, 51 synonyms, 3,419 occurrence records, and information on life cycle, distribution, and conservation status. The Linnean shortfall remains open: after 1975, the rate of species description increased sharply, and estimates indicate that 103 species remain undescribed (95% CI: 53-212). The year of species description was influenced by detectability and accessibility factors, with larger species, more widely distributed species, and species occurring in more densely populated areas being described earlier. The Wallacean shortfall was broad and spatially uneven: only 5.34% of the region was considered adequately sampled. The conservation shortfall was also substantial: 179 species are threatened with extinction, 69 species remain Not Evaluated, and 62 are Data Deficient. The mean time between taxonomic description and first IUCN extinction-risk assessment was 25.7 years. Moreover, 59.9% of species have no records within protected areas, including 69.3% of threatened species. These findings synthesize an urgent challenge: biodiversity knowledge and conservation shortfalls must be overcome simultaneously to protect species that are still being discovered, remain poorly documented spatially, and are restricted to habitats under intense anthropogenic pressure. The conservation of Rivulidae cannot wait for complete knowledge; action amid uncertainty is necessary to prevent both known and unknown species from disappearing.

Invasive plants pose a major environmental problem, threatening biodiversity, altering ecosystem functions, and causing economic loss. Climate change is altering environmental conditions, potentially facilitating the spread of invasive plant species, posing challenges for ecosystem management and biodiversity conservation. Accurate predictions of invasive species distributions are therefore essential for effective monitoring and early intervention. Species distribution models (SDMs) have become an important tool for predicting species habitats, but many studies rely on traditional machine learning approaches, focus on single-species predictions and overlook uncertainty associated with future climate scenarios. This study aims to evaluate the performance of a deep learning-based SDM framework, Deepbiosphere, for predicting both native and invasive plant species distributions on a regional scale, the US state of Michigan, and to assess how climate scenario uncertainty influences spatial predictions of invasive species risk particularly on two focal invasive species. Results show that Deepbiosphere outcompeted other baseline models by on average of 10.98% with a mean AUC-ROC of 0.79 across 1553 vascular plant species. For two invasive species Rhamnus cathartica and Ailanthus altissima, Deepbiosphere respectively improved modeling accuracy by an average of 56.41% and 74.99%, suggesting its enhanced predictive capability for invasive species. Current predictions indicated that R. cathartica is already broadly suitable across much of Michigan, whereas A. altissima is currently more restricted to southern regions. Under future climate scenarios, both species were projected to expand northward, with a particularly strong expansion signal for A. altissima. Prediction uncertainty was spatially heterogeneous, where general circulation models (GCMs) were the dominant source of uncertainty across most of the state. By integrating citizen science, remote sensing, and deep learning, we produced high-resolution risk-uncertainty maps for key invasive species and highlighted the importance of explicitly mapping uncertainty to support more informed invasive species management under climate change.

Protected areas cannot halt biodiversity loss in isolation; integrating them with surrounding human-dominated landscapes is critical. However, this integration is challenged by substantial landscape heterogeneity at their borders, hindering our understanding of cross-border changes in ecosystem service provision. We introduce a novel framework for characterizing these dynamics by analyzing ecosystem service gradients along protected area borders. For 16 protected areas in the French Alps, we assessed 12 ecosystem services using a mix of established biophysical models and novel connectivity-based models for mobile species. These were aggregated into three stakeholder-driven domains reflecting respectively rural, cultural, and urban management priorities. Automated polynomial regression analysis classified borders into five gradient types. The most common were 'Decreasing Gradients', representing a decline in ecosystem services outside the protected area, and 'Increasing Gradients', with the opposite pattern. Our analysis reveals these patterns are driven by specific landscape configurations, uncovering frequent trade-offs between the three management priorities, where, for instance, landscapes supporting rural priorities often degrade cultural and urban ones. We also identify key opportunities for synergies, by identifying areas where ecosystem services for all three priority domains increase simultaneously outside the protected area. This spatially explicit typology provides a powerful diagnostic tool for designing targeted interventions, such as prioritizing habitat restoration where ecosystem services decline or managing agricultural landscapes to mitigate conflicts across management priorities, supporting a more effective integration of protected areas into the wider landscape.

AimBiodiversity-rich regions often lack the scientific infrastructure needed to document and curate their own biodiversity, creating inequalities in access to taxonomic reference material. We investigated how biological, institutional, and geopolitical factors shape the retention, extraction, and appropriation of reptile holotypes, the name-bearing specimens upon which species descriptions are based. LocationGlobal. TaxonReptiles. MethodsWe compiled a historical dataset of reptile holotype origins and destinations spanning 1758-2024 to reconstruct long-term patterns of retention and international specimen flows. We then quantified species-level holotype retention, holotype flows between country pairs, and country-level patterns of retention, appropriation, and network centrality for the period 1990-2024, and used generalised linear mixed models to assess the biological, institutional, and geopolitical determinants of these contemporary circulation processes. ResultsAlthough nearly 90% of reptile species described originated in the Global South, less than a quarter of their holotypes remain housed there. Historically, exported holotypes consistently outnumbered retained holotypes on a decadal basis until the early twenty-first century. Retention was promoted by local scientific capacity, institutional infrastructure, collector involvement in species descriptions, and environmental governance. In contrast, extraction was concentrated in highly endemic regions with limited scientific infrastructure and was associated with taxonomic revisions, socioeconomic interest, and disparities in political stability and colonial history. Appropriation of foreign holotypes was greatest in countries with high research investment, strong environmental governance, and historical geopolitical influence. Main conclusionsGlobal patterns of holotype circulation reflect a persistent geography of scientific inequality. The distribution of taxonomic reference material emerges from the interaction of retention, extraction, and appropriation processes, linking local biodiversity discovery to uneven global scientific capacity. Reducing these inequalities will require investments in taxonomic expertise, institutional infrastructure, and governance frameworks that promote more equitable stewardship of biodiversity knowledge and its material foundations.

A majority of stream restoration efforts in central Europe focus on streams that are less than five meters wide. Restoration aims to increase structural complexity, thereby enhancing habitat heterogeneity, promoting biodiversity, and reestablishing aquatic-terrestrial linkages that can drive responses in adjacent terrestrial communities. However, the effects of small stream restoration on terrestrial biodiversity remain poorly understood because research focuses mainly on large rivers. Here, we investigated the effects of restoration on the structural complexity of the stream channel as well as the terrestrial habitat and plant diversity on a local and landscape scale across 55 small streams in an agricultural landscape. We compared restored stream sections with non-restored ones that were similar to the conditions before restoration. We also assessed how restored sections changed over time since restoration. Restored stream sections showed a higher stream structural complexity and habitat diversity, both of which are targets of active restoration measures. Restoration also increased riparian plant diversity, both directly and indirectly through structural complexity and habitat diversity. Although time since restoration did not influence structural complexity, it drove successional changes in plant communities that became increasingly associated with wetland habitat conditions. Our results demonstrate that small stream restoration effectively increases floodplain habitat and plant diversity in agricultural landscapes, primarily by enhancing water availability in the floodplain. Restoration actions on small streams support biodiversity if they improve stream channel complexity, connect the stream with its floodplain, and create floodplain habitats.

1. Ruby-throated hummingbirds (Archilochus colubris) exhibit flower preferences and readily visit human subsidies like feeders. However, foraging behavior and plant-animal interactions may vary across spatial, temporal, and landscape gradients. Despite the popularity and ubiquity of Ruby-throated Hummingbirds in the eastern U.S., there has never been a quantitative assessment of their flower preferences or feeder use across broad scales. 2. We investigated how feeder visitation, flower visitation, and flower trait preferences vary by latitude, season, and land use in the northeastern United States using over 6 million occurrence records of Ruby-throated Hummingbirds and flowering plants, >2,100 annotated hummingbird-flower interactions, and >2,700 feeder visit occurrences. 3. We found that hummingbird feeder use declined over the year, increased with latitude, and was higher in developed landscapes. Flower visitation increased over the year across all latitudes, with higher visitation in developed landscapes. Finally, we found that native plant use diverged between landscapes, such that the probability of visiting a native flower increased over time in non-developed land uses but declined over time in developed ones, demonstrating that hummingbirds track the advancement of native floral phenology and use non-native, cultivated flowers as a human subsidy due to either availability or preferences. 4. Our preference and network models revealed that while hummingbird-plant network structure was similar across landscapes, the composition of important taxa shifted from native, wild species like Monarda and Impatiens to non-native, cultivated species like Salvia. 5. Using trait-based models of flower visitation, we found that hummingbirds preferred native, tubular, and red/orange flowers fitting the hummingbird pollination syndrome despite visiting >260 different plant species. Red and orange flowers were preferred across all seasons, suggesting color may be a reliable signal of nectar availability across species and contexts. Native and tubular flowers were strongly preferred during the breeding season; however, preferences relaxed during spring and fall migration. 6. These findings reveal the consistent preferences of Ruby-throated Hummingbirds for native, tubular, and red/orange flowers, and underscore how spatial and temporal factors reshape foraging behavior and trait preferences. Our results also highlight the value of community-collected data in characterizing plant-pollinator interactions across broad spatial and temporal scales.

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.