Earth and Environmental Sciences

Oceanic islands are global biodiversity hotspots, yet they face disproportionate risks of species extinction. The Azores archipelago holds a unique flora composed of 94 endemic vascular plant taxa (species and subspecies) that are strictly endemic to the Azores, which represents about 32% of the native vascular flora. Here, we present the first comprehensive IUCN Red List assessment of the Azorean endemic vascular flora, based on more than 10,600 curated occurrence records, herbaria specimens, and recent field surveys. We found that nearly 60% of assessed taxa are threatened with extinction, Endangered being the most frequent IUCN category. Two species are confirmed Extinct, and 12 taxa remain Data Deficient due to unresolved taxonomy. The Red List Index (RLI) for Azorean endemics was calculated at 0.602, indicating a concerning level of extinction risk and, importantly, providing a reference point for monitoring future changes in conservation status. Spatial analysis revealed that endemic taxa richness is highly uneven, with most areas hosting few or no endemics. Notably, 12 hotspots occur outside the current protected area network, leaving key refuges for endemic taxa unprotected. These findings underscore the urgent need to expand legal protection, prioritise the management of invasive taxa, restore degraded habitats, and integrate newly described taxa into conservation frameworks. By establishing a baseline for monitoring extinction risk, this study provides a critical tool to guide conservation action in the Azores, and contributes to broader efforts to safeguard the unique natural heritage of oceanic islands.

Heavy metal (HM) accumulation is a significant environmental concern that endangers human health and the ecosystem due to increasing natural and anthropogenic activities. This study assessed the toxicity of fourteen different HMs in the soil samples taken from the agricultural sites situated along the national highways in Bilaspur, Chhattisgarh, India. Using a range of soil indices, such as contamination factor (CF), pollution load index (PLI), geo-accumulation index (Igeo), ecological risk assessment (ERA), and risk index (RI), the study examined the risk associated with the HMs such as boron, aluminum, vanadium, chromium, manganese, iron, cobalt, nickel, copper, zinc, arsenic, molybdenum, cadmium, and lead. Their potential sources of origin were assessed using multivariate statistical techniques, coupled with positive matrix factorization (PMF) and self-organizing map (SOM). The CF and Igeo results showed that 4.80% of the soil sites were extremely polluted and 54.0% were moderately polluted. Comprehensive multivariate analysis combining PMF and SOM identified both geogenic and mixed anthropogenic sources, with vehicular pollution and agricultural activities emerging as the major contributors to health risk. This study advances the knowledge of HM contamination in agroecosystems and helps in developing the future strategies to reduce HM exposure in the environment.

Common rats (Rattus rattus and Rattus norvegicus) and the house mouse (Mus musculus) are globally distributed synanthropic rodents, yet their tolerance to high altitude has never been assessed at a global scale. We combined worldwide occurrence records with climatic and elevational data to compare their observed and potential altitudinal ranges. Using more than 200,000 curated Global Biodiversity Information Facility (GBIF) records, we assigned elevation to each occurrence and built MaxEnt species distribution models incorporating elevation and four bioclimatic variables. Rats and mice overlapped broadly at low and mid elevations; however, both rat species showed a sharp and consistent decline in occurrence above ~ 2,500 m. Only 2.3-2.7% of rat records occurred above this threshold, compared with ~ 10% for M. musculus. Species distribution models corroborated this pattern, predicting high-altitude regions, including the Andean and Tibetan plateaus, and major mountain ranges in North America and Asia, as largely unsuitable for rats but suitable for mice. Minimum and maximum temperature were the strongest predictors of habitat suitability for all species, yet elevation exerted a markedly stronger negative effect on rats than on mice. These findings identify elevation as a major global constraint on the biogeography of common rats but not house mice, likely reflecting species-specific physiological limits related to hypoxia tolerance.

Under the dual pressures of global climate change and intensive human activities, the degradation of ecosystem services has become a critical challenge for regional sustainable development. This study aims to investigate the spatiotemporal evolution and driving mechanisms of water yield and carbon storage in the middle reaches of the Yellow River. By integrating the land use transfer matrix, InVEST, PLUS, GeoDetector, and spatial autocorrelation analysis, we assessed the impacts of land use change on water yield and carbon storage from 1985 to 2023. The results indicate that cropland area declined by approximately 15%, while construction land expanded rapidly during the study period, intensifying land use conflicts. Water yield exhibited a pronounced fluctuation-recovery pattern, with a sharp decline of nearly 70% in the early stage followed by a gradual recovery in recent years, reflecting the combined influence of climate variability and human activities. In contrast, carbon storage showed a steady increasing trend associated with vegetation restoration, rising by about 2% over the study period. Driving factor analysis revealed that interactions between vegetation conditions (NDVI) and human activity indicators played a dominant role in shaping ecosystem service dynamics (q > 0.85). A clear trade-off relationship was observed between water yield and carbon storage, indicating the tension between vegetation restoration and regional water availability. Based on these results, this study recommends implementing zonal management strategies, strengthening vegetation restoration in ecologically fragile areas, and optimizing land use structures in urban expansion zones to promote the coordinated enhancement of ecosystem services, thereby ensuring ecological protection and high-quality development in the Yellow River Basin.

Amid rapid urbanization, urban plants measurably contribute to climate change mitigation by carbon sink and storage, rather than constituting a singular dominant solution. This necessitates a robust, standardized framework for method evaluation and selection. This study adopts the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation as its methodological core, developing a multi-level evaluation model with 9 specific indicators based on 3 primary criteria: Accuracy, Generality, and Advancement. The model was applied to systematically compare and comprehensively assess 8 prevalent methods used to estimate urban plants' carbon sink and storage. Consistency checks (CR < 0.10) for all judgment matrices confirmed the statistical robustness of the evaluation data. The results revealed that among the evaluation criteria, Advancement carried the highest weight (52.00%), highlighting the importance of methodological innovation in the face of rapid technological progress. Accuracy ranked second (28.90%), while Generality was assigned the lowest weight (19.10%). In terms of comprehensive performance scores, the Optical Remote Sensing Method (Score: 97/100) outperformed others in carbon sink estimation. Similarly, the Remote Sensing Estimation Method (Score: 82/100) led the field in carbon storage measurement. In contrast, the Average Biomass Method received the lowest score (48/100), indicating significant performance disparities in addressing urban environmental complexity.

Coral reefs are experiencing severe decline due to anthropogenic stressors and natural disturbances, necessitating innovative restoration strategies. Micro-fragmentation is a method used for accelerating coral growth and enhancing reef rehabilitation. This study investigates the use of micro-fragments to cover an artificial three-dimensional bottomless cube structure designed to increase space efficiency, structural complexity, and scalability for coral restoration. We examined four Hexacorallia species, Cyphastrea microphthalma, Galaxea fascicularis, Pocillopora favosa and Stylophora pistillata to evaluate species-specific and source colony-specific survival and growth rates. Over 204 days, micro-fragments demonstrated both tissue growth and fusion, at varying degrees, with G. fascicularis exhibiting the highest survival and growth rates. Corals grew and fused over the surfaces of the test structures and fused across corners. Our results demonstrate variation in fragment survival and fusion potential among species and colonies, highlighting the importance of source colony and species selection in restoration efforts. Notably, we found that coral fragments could successfully fuse after six months of separation. This approach has broad applications in reef restoration and the ornamental coral trade, offering a scalable solution to lessen the impact of coral harvesting on natural ecosystems. Our findings highlight the potential of designed 3D structures to support efficient coral restoration in degraded reef environments.

In response to the urgent need for water environment protection, this study proposes an improved algorithm for detecting floating objects on the surface of water: You Only Look Once version 8-water surface floating object detection (YOLOv8-WSFOD). This algorithm aims to address the impacts of illumination variations and water surface distortion on floating object detection, as well as missed and false small object detections in complex aquatic scenarios. The improvements provided by YOLOv8-WSFOD include the design of a spatial pyramid pooling fusion-large separable kernel attention (SPPF-LSKA) module to evolve the SPPF module, which possesses long-range dependence and adaptive capabilities to mitigate the interference caused by noise factors such as water surface fluctuations, strong illumination, and high-contrast weather conditions. Then, the model focuses more on important feature areas and effectively reduces the impact of noise on floating object detection. Additionally, the normalized Wasserstein distance (NWD) regression loss function is introduced and combined with the original complete intersection-over-union (CIoU) loss function through weighted integration, resulting in a novel comprehensive regression loss function that significantly enhances the small object detection performance and accuracy of the model. Finally, the adaptive moment estimation (Adam) optimizer in the original algorithm was replaced with the second-order clipped stochastic optimization (Sophia) optimizer to improve the generalizability of the model. Experimental results demonstrate that YOLOv8-WSFOD achieves significant WSFOD improvements, with a 3.4% mean average precision (mAP)@0.5 increase and a 3.4% mAP@0.5:0.95 increase. In multiclass detection tasks, mAP@0.5 improves by 8.6%, and the detection accuracies achieved across all categories is significantly enhanced. The performance of the developed algorithm demonstrates its great feasibility for deployment in unmanned cleaning vessels, offering high accuracy and efficiency in WSFOD scenarios.

Under the combined pressures of extreme rainfall and rapid urbanization, urban waterlogging has become increasingly severe. As high-density and low-income settlements, urban villages are particularly vulnerable. Taking the "9·7" extreme rainstorm event in Shenzhen as a case, this study analyzes 623 urban-village study units across the Longgang River and Shenzhen River basins to identify urban-form-related factors and empirical thresholds associated with waterlogging risk under an extreme rainfall scenario. Specifically, we focus on the dominant role of the topographic low-lying effect and the amplifying effect of street-canyon characteristics on the vulnerability of urban villages. By integrating multi-source data and constructing a multi-scale buffer analysis framework, we quantify the spatial contrasts between urban villages and their surrounding environments. An XGBoost model, combined with SHAP analysis and partial dependence plots (PDPs), is used to interpret the contribution of each factor, nonlinear thresholds, and interaction effects. The results show that: (1) the topographic low-lying effect exhibits the strongest explanatory contribution and presents a clear threshold-switch pattern, with absolute elevation as the leading factor; (2) within a 0-400 m range, urban villages form significant morphological contrasts with their surroundings, constituting a risk "vulnerability ring"; (3) street-canyon indicators are more informative than traditional density indicators, highlighting the critical role of micro-scale urban form in regulating runoff pathways; and (4) maintaining the sky view factor (SVF) within the range of 0.3-0.55 is associated with lower waterlogging risk. Overall, this study identifies urban-form-related factors, nonlinear response patterns, and empirical risk thresholds of urban-village waterlogging, providing a scientific basis for targeted resilience enhancement.

, respectively. Compared to the current scenario, future projections indicate a significant increase in suitable areas. Furthermore, except for SSP245, the distribution centroid is projected to move southwestward then northward under other climate scenarios. These findings suggest that climate change may broadly benefit the expansion of E. ferox, offering critical insights for the formulation of regional conservation and cultivation strategies.

Centennial-scale changes in Atlantic Meridional Overturning Circulation (AMOC) strength might disturb global climate by altering interhemispheric heat transport and CO2 partitioning between the ocean and the atmosphere. Due to the short instrumental record and lack of high-resolution paleo records that so far only resolve millennial-scale changes, centennial-scale changes remain elusive. Here we use radiocarbon ventilation ages from a western equatorial Atlantic sediment core with a remarkably high sedimentation rate to reconstruct AMOC variability during the last deglaciation, with a focus on Heinrich Stadial 1 (HS1; 17.8-14.8 ka). Results from model simulations indicate that ventilation ages serve as a sensitive proxy for AMOC variability under weak overturning conditions (i.e., during HS1) at our study location. Notably, within an overall weakened AMOC condition during HS1, our record shows two centennial-scale AMOC intensifications: one from 16.5 to 15.8 ka and another at ~15.4 ka. These centennial-scale episodes of intensified AMOC briefly revitalized Atlantic interhemispheric heat transport during HS1, resulting in decreased precipitation over northeastern Brazil and short-lived but intense changes in climate elsewhere. These episodes of AMOC intensification likely transported substantial volumes of CO2-rich water from the mid-depth Atlantic to the Southern Ocean, where the CO2 was rapidly outgassed to the atmosphere. Using radiocarbon ages from Atlantic sediments, AMOC variability during Heinrich Stadial 1 is reconstructed, revealing brief intensifications that altered heat transport, reduced rainfall over northeastern Brazil, and likely enhanced atmospheric CO2.

Abstract Iran’s long history of climate-related crises, primarily driven by droughts, has been intensified by ongoing climate change, placing forest ecosystems under increasing hydroclimatic stress. In recent decades, prolonged droughts combined with elevated atmospheric moisture deficits have reduced ecosystem resilience and increased vulnerability to degradation. To better understand long-term drought dynamics and their ecological impacts, we developed two 200-year chronologies (1821–2020) of tree-ring width (TRW) and stable oxygen isotope variations (δ 1 ⁸O) from Juniperus polycarpos in the Hezar Masjed Mountains, northeastern Iran. The δ 1 ⁸O record served as a proxy for atmospheric moisture conditions and was used to reconstruct growing-season (March–September) vapor pressure deficit (VPD). When combined with TRW in a multiple regression framework, this dual-parameter approach enabled reconstruction of the Standardized Precipitation-Evapotranspiration Index (SPEI07), representing cumulative growing-season hydroclimatic conditions related to soil moisture availability. This allows the differentiation of atmospheric and soil drought impacts on tree growth over two centuries. By classifying drought years into VPD-only, SPEI-only, and combined drought events, we found that drought conditions associated with reduced soil moisture availability (SPEI) exerted the strongest constraint on radial growth. Tree growth declined most strongly during severe SPEI droughts, followed by severe combined drought (COMB-D) years, whereas atmospheric drought alone (VPD-D) had a weaker and more transient effect. Growth typically recovered within two years following drought events. Analysis of long-term drought classifications (1821–2020) revealed a shift towards more intense droughts in recent decades, particularly in the frequency of severe VPD and combined drought years. Our findings highlight that tree growth in semi-arid mountain ecosystems is primarily limited by soil moisture availability, with atmospheric drought acting as an additional stressor when coinciding with soil moisture deficits. This study demonstrates the value of combining multiple tree-ring proxies to disentangle drought mechanisms and improve understanding of forest responses to climate change.

This study collected 287 samples from nine boreholes in the Sanjiang Plain and analyzed the contents of rare earth elements (REEs), major elements, pH, and organic matter. The study summarizes the vertical distribution characteristics and influencing factors of REEs in the sediments of the Sanjiang Plain. The results show that the vertical distribution of REEs in the sediments of the Sanjiang Plain exhibits a strong grain size effect. Sediments with a particle size < 165.11 μm show higher concentrations of Eu depletion, and lower (La/Lu)NASC and (Nd/Yb)NASC ratios; while sediments with a particle size > 165.11 μm show lower concentrations of Eu enrichment, and higher (La/Lu)NASC and (Nd/Yb)NASC ratios. The fundamental reason for this phenomenon is the varying weathering intensities of the sediments. Coarse-grained sediments are less affected by weather, primarily reflecting the REE characteristics of the source area; fine-grained sediments are more strongly affected by weathering, with feldspar weathering producing clay minerals. Meanwhile, primary minerals release Fe2+ and Mn2+ during weathering, some of which precipitate as Fe and Mn oxides1, adsorbing REEs and increasing overall concentrations of fine-grained sediments. Additionally, the weathering of feldspar minerals also causes Eu depletion. The REE characteristics of some coarse-grained sediments near the surface are similar to those of fine-grained sediments, likely because human activities increase the organic matter content in surface soil, which adsorbs REEs.

We theoretically investigate the structural stability, electronic property, and superconductivity of the hydrogen-rich compound Li[Formula: see text]CuH[Formula: see text] in its face-centered cubic phase. First-principles calculations show that Li[Formula: see text]CuH[Formula: see text] is thermodynamically metastable at ambient pressure but dynamically stable. Moreover, ab initio molecular dynamics (AIMD) simulation at 300 K further confirms that Li[Formula: see text]CuH[Formula: see text] remains structurally intact without decomposition. These results suggest that the material may be synthesized under high pressure and retained after decompression. Although thermodynamically metastable at ambient conditions, its dynamic stability supports its persistence after pressure release. Moreover, Li[Formula: see text]CuH[Formula: see text] exhibits metallic behavior with a flat band and van Hove singularity (vHS) near the Fermi level and Fermi-surface states dominated by Cu-d and H-s orbitals. Phonon calculations further indicate that hydrogen vibrations dominate the phonon contribution, while the electronic states near the Fermi level govern the coupling strength, resulting in a large electron-phonon coupling constant. Insights into the superconducting temperature ([Formula: see text]) are obtained using various theoretical approaches, which estimate [Formula: see text] to be in the range of 93-152 K. Bonding analysis further indicates mixed covalent-ionic character within Cu-H octahedra. These results highlight Li[Formula: see text]CuH[Formula: see text] as a promising hydrogen-based metastable superconductor for future experimental exploration.

Marine heatwaves can interact across ocean basins through atmospheric teleconnections, but such inter-basin links remain poorly understood. Here we show that boreal spring and summer marine heatwaves in the Caribbean Sea are significantly connected to marine heatwaves in the Indian Ocean during the preceding winter. Using observational data and climate model simulations, we identify that boreal winter Indian Ocean marine heatwaves trigger atmospheric convection, generating an eastward-propagating Indo-Pacific-Atlantic Rossby wave train. This wave train alters the regional Hadley circulation and renders the overlying atmosphere warm, moist, and stable over the Caribbean Sea, reducing latent heat loss from the ocean, driving sea surface warming and promoting the intensification of marine heatwaves. These findings reveal a robust teleconnection pathway that allows climate signals from one basin to amplify marine heatwaves in another. Winter marine heatwaves in the Indian Ocean can intensify spring and summer marine heatwaves in the Caribbean Sea through an atmospheric bridge. An eastward propagating wave train alters the regional Hadley circulation, reducing latent heat loss from the ocean and driving sea surface warming.

Climate extremes increasingly threaten energy infrastructure, yet whether disparities in energy resilience persist within cities under comparable hazard exposure and how distributed energy resources may reshape them remain largely unquantified. By integrating climate and energy projections, socio-demographic data, and an optimization-based power outage metric that captures initial outages, recovery, and distributed energy resource support, this study reveals evident energy resilience disparities shaped by intersectionality across income, race, and ethnicity in New York City. These disparities are projected to be exacerbated under future climates. Middle-income households exhibit the lowest levels of energy resilience, with their outage risk increasing by 1.5-2 times compared to the wealthiest households under severe events. Low- and middle-income Asian and high-income Black households experience up to twice the average outage risk increase compared to others within the same income groups. While distributed energy resources can partially mitigate disparities, their impact remains limited under business-as-usual growth. Our findings identify climate-vulnerable communities and inform efforts to promote energy justice in a changing climate.

Microbes, as the planet’s most abundant and diverse organisms, drive soil functions globally and are vulnerable to environmental stressors triggered by global change. Yet, knowledge regarding the impacts of multiple environmental stressors on their functional profiles as well as the consequences for soil functionality largely remains unknown. Here, we analyze two global-scale datasets including information on soil metagenomics and multiple environmental stressors. We find that across terrestrial ecosystems worldwide, up to 60% of all functional genes significantly shift when soil microbes experience the high-level of concurrent stressors. In this regard, the relative abundances of genes involved in microbial growth are negatively linked to the increasing number of stressors. Conversely, those genes linked to stress resistance and energy production exhibit positive responses. Taken together, our findings highlight a significant restructuring of global soil functional microbiomes in response to multiple environmental stressors. Consequently, such restructuring drives community-level shifts in matter and energy reallocations, thereby impacting the maintenance of soil functionality under the projected global change. Soil microbes drive ecosystem functions but are vulnerable to environmental stressors triggered by global change. This study reveals that multiple environmental stressors drive community-level restructuring of soil functional microbiomes globally.

Energy-sector decarbonisation requires large-scale investment in low-carbon technologies, yet only a limited share flows to low- and middle-income countries, partly due to higher financing costs and perceived risks. Most modelling exercises do not fully account for how the cost of capital may vary across regions and technologies, potentially influencing policy insights. We examine how plausible, expert-informed long-term trends in de-risking clean energy and increasing risks for fossil fuels could shape decarbonisation pathways, using an empirical dataset differentiated by country and technology. We also evaluate a "corrective justice" policy that taxes corporate windfall profits and redistributes revenues to support low-carbon investments in higher-risk regions. Results suggest that incorporating differentiated cost-of-capital trajectories may improve mitigation outcomes and help narrow the gap between current commitments and long-term climate targets, while indicating potential underestimation of risks associated with bioenergy-based negative emissions technologies in mitigation scenarios for high-income nations.

While research has largely focused on boreal fires, here we show a significant increase in spring fire activity across continental tropical Asia between 2001 and 2020, characterized by two prominent hotspots. We further show that this upward trend in fire activity is driven by distinct regional mechanisms. In the Indian Peninsula hotspot, anthropogenic agricultural burning across expanding cropland has amplified fire activity. In contrast, the Indo-China Peninsula hotspot is dominated by wildfires linked to reduced precipitation driven by internal climate variability. Large ensemble climate simulations identify Pacific decadal variability as a key driver of this regional drying, beyond what can be explained by anthropogenic forcing alone. These findings highlight an overlooked increase in tropical fire activity and reveal distinct regional drivers shaping the overall upward fire trend across continental tropical Asia. Policymakers should account for these factors to design effective climate mitigation and fire risk management strategies for the region. This study shows a pronounced increase in spring fire activity across continental tropical Asia since 2001, driven by human activity and natural climate variability, with distinct regional drivers shaping the fire trends.

Abstract Estimates of carbon emissions budgets to limit global warming to 1.5 °C or 2 °C rely on the near-linear relationship between global temperature change and total CO 2 emitted, known as the Transient Climate Response to cumulative CO 2 Emissions (TCRE). The TCRE is determined from Earth System Models (ESMs) and is therefore sensitive to the physical and biogeochemical processes represented within them. Here we use an ESM (UKESM) to explore the sensitivity of TCRE to six Earth system processes in isolation. Four processes increase TCRE: fire-vegetation interactions by 14.6%; nitrogen limitation of vegetation by 9.7%; diffuse radiation effects on vegetation by 8.5%; and interactive emissions of methane from wetlands by 5.1%. Conversely, two processes marginally reduce TCRE: allowing the vegetation distribution to adapt to changing climate and CO 2 lowers TCRE by 1.5%, and climate impacts from the emission of biogenic volatile organic compounds reduce it by 1.4%. We demonstrate the extent to which each process changes TCRE via its influence on the climate and on the global carbon cycle, and discuss underlying mechanisms. Our results highlight the substantial process-dependence of model-derived estimates of TCRE, with implications for remaining carbon budgets to future warming targets calculated from them.

Abstract Tidal wetlands are critical ecosystems for coastal sustainability, yet despite growing regulatory protection, they continue to decline globally. Their long-term resilience to interacting chronic stressors and extreme events remains uncertain, in part because comprehensive, high-frequency monitoring has been lacking. While direct land-use conversion has been substantially restricted in the United States, the true trajectory of these protected habitats has remained unclear. Here, we use four decades of high-resolution satellite records to analyze the shifting dynamics of US tidal wetlands. We reveal a widespread and previously unquantified acceleration in the rate of tidal wetland loss, amounting to a net loss of −1640 km 2 at the rate of −40.53 km 2 year −1 , accelerating by −0.73 km 2 year −2 , of which tidal marsh contributed the majority of this loss with a cumulative decline of 1567 km 2 . Furthermore, we show that the drivers of this decline are shifting: while chronic stressors like relative sea level rise have caused the largest cumulative loss (~60% of the total area loss), acute shocks from extreme weather now dominate (1.4 times that of the chronic stressors) the acceleration of that loss. By contrast, direct human activities were a minor driver, accounting for only 4% of total observed losses. These findings indicate that the resilience of these protected ecosystems is declining. It provides an urgent warning that existing conservation strategies, initially concerned with direct human impacts and increasingly focused on relative sea level rise as a slow-moving pressure, are ill-equipped for a future of increasing extreme weather events and highlights the need to redesign adaptation policies.

Abstract Coral reefs face a perilous future due to global climate change compounded by the increasing prevalence of local stressors. Prominent among these is nutrient pollution, particularly nitrate eutrophication, which disrupts the coral-algal symbiosis and escalates reef degradation. While microbial denitrification is hypothesized to mitigate nitrate stress, the mechanisms underlying coral resilience remain unknown. Studying Hong Kong’s coral “reef oases” that persist under chronic hyper-eutrophication, we discovered that resilience is not mediated by diversity or abundance shifts in denitrifier genera but by the association with specific, hyper-efficient denitrifying populations within the dominant denitrifier genus Ruegeria . By integrating population genomics, subspecies-resolution metabarcoding (resolving both the entire Ruegeria community and the denitrifying sub-community), and direct isotope-based activity assays, we identified and validated putative denitrifying “specialist” populations. These specialists were significantly enriched in corals from high-nitrate waters and exhibited 10-fold higher denitrification rates in low-oxygen incubations, converting nitrate to inert N 2 with superior efficiency compared to non-specialists. Our findings reveal that critical ecosystem-scale adaptations to anthropogenic change can occur through a unique association with specialized sub-genus populations, which may be missed in conventional microbiome surveys. As such, our work sheds light into why dominant denitrifying genera are ubiquitous, yet only certain corals thrive in eutrophic conditions. It also provides a framework for future studies delineating ecologically important host-associated microbes.

Many viral proteins self-assemble into capsid structures, often using their genetic material as a template for assembly. To date, de novo designed capsid-like proteins do not require genetic material as a template for assembly, which can be both an advantage and a disadvantage depending on the use case. Templates are indispensable, for example, in the assembly of linear structures with well-defined lengths. As a first step towards fully de novo designed templated assembly, here we redesign proteins from the Transcription activator-like effector (TALE) family of transcriptional regulators to polymerize on double-stranded DNA (dsDNA) templates. Starting from natural TALE protein sequences, we create idealized repeat proteins with sequence-independent DNA binding properties that self-assemble to form linear protein-DNA complexes with template-controlled lengths. We use high-resolution atomic force microscopy (AFM) and cryo electron microscopy (cryo-EM) to characterize the three-dimensional structures of the DNA-protein hybrid complexes. In these structures, a protein filament helically wraps around the dsDNA similar to natural TALE proteins. As an example application of these materials, we show the system can be used for repetitive peptide antigen display at precisely controlled repeat distances, and that such immunogens elicit robust antigen-specific antibodies in mice.

Marine phytoplankton monitoring has long relied on microscopy, but DNA metabarcoding has recently emerged as a complementary approach. This study assessed the applicability of DNA metabarcoding of the 18S ribosomal RNA gene in marine monitoring and compared its results with conventional microscopy. We analyzed data from 232 surface water samples from 17 monitoring stations in the Baltic Sea, Kattegat, and Skagerrak. Metabarcoding detected more orders, genera, and species than microscopy, with a 43% overlap in the most common genera identified by both methods. Despite attempts to normalize sequence reads to spike-in DNA or DNA concentrations, the correlations between abundances derived from the two methods were weak, though varied considerably between taxonomic groups and geographical areas. Correlations were consistently stronger when using carbon and biovolume concentrations than cell abundances. Our results highlight the potential of metabarcoding to expand biodiversity assessments and advance our understanding of microbial biodiversity in marine ecosystems. As a complement to microscopy, it can enhance existing monitoring efforts. Future improvements in reference database completeness, adoption of long-read sequencing technologies, and better characterization of gene copy number variability per cell are needed to further extend the applicability of metabarcoding for quantitative analyses.

Leaf hyperspectral reflectance (HSR) data have gained increasing attention due to their usage in predicting a range of leaf physiological, biochemical, structural, and photosynthetic traits using machine learning (ML) models. The PROSPECT family of models offers a complementary, mechanistic means to estimate leaf traits from HSR data using model inversion. However, a comprehensive evaluation of the accuracy and transferability of the PROSPECT model across a large set of species is hindered by the limited availability of ground truth data sets. Here, we employed a combination of inversion and forward simulation of the PROSPECT-D model across a broad range of species and identified four narrow wavebands linked to environmental effects. We also introduced a novel framework using partial least squares regression to enable the analysis of the transferability of the machine learning models trained base on the PROSPECT-D across species. This analysis revealed trait-specific patterns of transferability for the machine learning surrogate based on the PROSPECT-D forward model. We then extended this analysis to PROSPECT-D inversion using neural networks and developed a fast, accurate deep-learning-based surrogate inversion approach to estimate leaf traits from measured HSR data. Our data-driven framework paves the way for improving the accuracy of PROSPECT and similar mechanistic models.

Phenol is a water-soluble contaminant frequently detected in sediments, yet sediment-specific toxicity data are scarce. To address this data gap, we evaluated the use of water-based toxicity data for sediment ecological risk assessment (ERA) by combining the equilibrium partitioning method (EPM) with species sensitivity distributions (SSDs). Acute and chronic toxicity data from laboratory and artificial-stream tests using native aquatic species were compiled and converted to sediment-equivalent values for SSD construction. We quantified how species origin (native vs. foreign), habitat type (benthic vs. non-benthic), taxonomic composition, and sample size affect SSD-derived hazardous concentration for 5% of species (HC5). Inclusion of benthic taxa, including early life-stage amphibians classified as benthic, was associated with lower HC5 estimates; sensitivity differences across groups were generally < one order of magnitude. At least 8 species were needed for stable SSD performance. Applying an assessment factor to the HC5 yielded a PNECsediment of 0.81 µg/g dry weight. Using this value, phenol concentrations from 23 monitoring sites indicate that 87% of locations would be categorized as moderate to high risk. As a phenol case study, the EPM–SSD framework demonstrates a pragmatic, transparent route to sediment ERA for moderately hydrophilic substances under data-limited conditions.