Communications Earth & Environment

Understanding how animals respond to their physical environment requires environmental observations at the scale at which behavioural decisions are made. For soaring birds, the coarse resolution of weather products has long hindered the analysis of their behavioural response to fine-scale atmospheric dynamics, forcing uplift sources to be inferred largely from behaviour itself. Here, we combined high-resolution movement data from 24 golden eagles with the kilometre-scale COSMO weather model. We first classified thermal, orographic, and gravity-wave uplifts using independent atmospheric predictors and then quantified the birds' use of each uplift type and their fine-scale behavioural responses. Eagles relied predominantly on thermals, but opportunistically adjusted their use of uplift sources seasonally. The birds' flight behaviour could not reliably indicate which uplift type was primarily used, and thus suggests that both atmospheric processes and behavioural responses are better described as continua than discrete categories. Finally, we compared vertical wind velocities derived from eagles soaring behaviour with those modelled by the COSMO weather model, showing that most of the thermals exploited by eagles remain unresolved at kilometre-scale model resolution. Our results demonstrate how high-resolution weather models provide new insights into bird movement decisions, while also highlighting the potential of soaring birds as biologically embedded atmospheric sensors that could help closing the resolution gap in atmospheric models.

A direct empirical relationship between gross primary productivity (GPP) estimated by the eddy covariance method and satellite vegetation indices (VIs) has been widely observed across diverse ecosystems globally. Building on this observed covariation, VIs are frequently utilized as critical parameters - such as the fraction of absorbed photosynthetically active radiation (fPAR) - within light use efficiency (LUE) and greenness-based models for carbon cycle monitoring. However, actual canopy carbon assimilation is jointly governed by slowly evolving structural parameters and highly dynamic functional traits, such as physiological efficiency. The extent to which the macro-scale VI-GPP covariance is driven by structural scaffolding, and how this structural signal decouples from physiological function under environmental stress, remains to be systematically quantified. Here, we synthesized half-hourly eddy covariance measurements from 328 globally distributed sites and paired them with a rigorously angle-normalized Enhanced Vegetation Index (nadir view and fixed solar zenith angle at 30 degrees, EVI_SZA30). By applying a nonlinear light-response curve model across 54,720 high-frequency temporal windows, we mechanistically disentangled observed actual GPP (GPP_EC) into baseline photosynthetic capacity (P_c) and intrinsic quantum yield (alpha). Our results demonstrate that the macroscopic covariance between EVI_SZA30 and GPP_EC (R^2=0.554) is primarily driven by the index's robust ability to track structural capacity (P_c, R^2=0.538). In contrast, EVI_SZA30 exhibits limited sensitivity to high-frequency variations in functional traits like physiological efficiency (alpha, R^2=0.038). Particularly in water-limited biomes (e.g., open shrublands and woody savannas), intense environmental stress triggers rapid stomatal regulation while the physical canopy structure remains relatively stable. Consequently, the correlation between EVI and P_c becomes notably stronger than its correlation with actual GPP_EC, highlighting a pronounced structural-physiological decoupling. Because discrete overpasses by sun-synchronous polar-orbiting satellites face intrinsic temporal constraints in capturing sub-daily physiological down-regulation (e.g., midday photosynthetic depression), future monitoring paradigms could greatly benefit from the continuous, high-frequency observations provided by next-generation geostationary (GEO) satellites to bridge the gap between structural parameters and transient ecosystem function.

Current planetary protection approaches rely heavily on spore-based tests developed for Mars missions and may not adequately assess contamination risks for icy ocean worlds such as Europa. We developed a genome-based framework combining deep shotgun metagenomics and supervised machine learning to predict survival-relevant microbial traits in ESA JUICE launch-site cleanrooms. From 183 genome bins, 25 representative genomes were analyzed for traits including cryotolerance, desiccation tolerance, salt resilience, anaerobic metabolism, autotrophy, and sporulation. Several skin-associated microbes carried multiple relevant traits, and some appeared actively replicating. A broader meta-analysis of 1,868 genomes showed that trait profiles vary strongly within taxa, demonstrating that taxonomy alone is insufficient for risk assessment. This framework complements current planetary protection assays, helps to predict how microbes would survive in a new biotope, and supports functional, risk-informed contamination monitoring for future space missions.

Marine diatoms contribute to about 20% of global primary production. We present the first basin-scale, multiyear assessment of diatom communities in the North Pacific, combining taxonomically high-resolution RuBisCO large subunit gene (rbcL) metabarcoding with concurrent environmental measurements. Using a nine-year time series of daily samples resolved at the species level via ~500 bp rbcL fragments, we performed multivariate analyses across biogeographic provinces, identifying significant correlations between community structure and environmental drivers such as temperature and macronutrient availability. We report the prevalence of a previously overlooked centric diatom species in the North Pacific, Eunotogramma lunatum, which appears to be near-dominant even in subarctic high-nitrate, low-chlorophyll waters where pennate diatoms are typically favored. These results demonstrate the power of rbcL for large-scale ocean monitoring and provide a critical baseline for future studies of diatom population dynamics, climate change impacts, and ecosystem resilience in a key marine region.

Aerobiological studies have largely focused on near-surface sampling and horizontal biogeographic patterns, while vertical structuring of airborne microbial communities within the atmospheric boundary layer (ABL) remains poorly understood. Here, we investigated microbial communities across the lower and upper ABL in a low-orography coastal site on the Antarctic Peninsula, representative of the Southern Ocean marine ABL and with low direct human influence. Airborne microorganisms were sampled simultaneously using ground-based and aerial platforms on five occasions. Community composition, abundance, and cell morphometry were assessed using metabarcoding and epifluorescence microscopy and interpreted alongside atmospheric observations. Airborne bacterial and eukaryotic communities showed consistent vertical stratification, although partial taxonomic overlap indicates vertical connectivity between atmospheric layers. Lower ABL communities were more diverse than upper ABL counterpart, compositionally homogeneous, and dominated by marine-associated taxa, reflecting strong influence from local sources and turbulent mixing. In contrast, upper ABL communities were less diverse but more heterogeneous among sampling events, enriched in stress-tolerant, terrestrial and plant-associated taxa, consistent with atmospheric filtering, selective upward transport, and long-range atmospheric inputs. Upper-layer samples also exhibited higher microbial abundance and greater prevalence of elongated cell morphologies, suggesting particle accumulation aloft and aerodynamic selection permanence. Together, these findings identify the Southern Ocean ABL as a vertically structured microbial habitat organized into two partially decoupled sublayers, in which atmospheric dynamics regulate microbial dispersal, ecosystem connectivity, and biogeographic patterns.

Antarctica represents a significant, unresolved, and unstable source of methane to the atmosphere. To advance our understanding of the biological filter of methane in Antarctica, here we identify the taxa and functional genes present during methane oxidation in an Antarctic Methane Seep. Methane oxidation was present in all sediments, including in a non seep control site. Using 16S rRNA analysis alongside metagenomics, we found that ANaerobic MEthane oxidizing (ANME) archaea coupled to Sulfate-Reducing Bacteria (SRB), documented as the most important marine methane sink in other locations, were not present. Instead, we observed the presence of denitrification-dependent methane oxidizers, including the anaerobic genus Candidatus Methylomirabilis, alongside the nitrate reducing archaea Candidatus Methanoperedens through short-read metagenomic classification. In addition, we note the presence of multiple aerobic methanotrophs, with a particularly high abundance of the Methylobacter, Methylomonas, and Methyloprofundus genera. Our results support denitrification-mediated methane oxidation and aerobic methanotrophy as the primary potential methane sinks in the Ross Sea. The widespread methane oxidation, including in control sediment, combined with the possibility of anaerobic methane oxidation linked to denitrification rather than sulfate reduction highlights the ubiquity and uniqueness of the Antarctic methane cycle.

Sequential hurricane-heatwave events threaten forest resilience via understudied legacy effects. Using Bayesian Structural Time Series, piecewise Structural Equation Modeling, and a 21-event global synthesis, we quantify how structural degradation non-linearly amplifies productivity loss during subsequent heatwaves. Our Hurricane Michael (2018) case study reveals significant negative GPP legacy effects during the 2019 heatwave. Intact, tall and diverse canopies buffer microclimates and moderate thermal sensitivity. Hurricane-induced structural simplification removes this protection, exposing temperature-sensitive shaded leaves to extreme stress. We identified a context-dependent hydraulic trade-off: structural complexity provides shading but exacerbates forest sensitivity to water deficits during peak heat, the vulnerability of which reverses during the recovery phase. Globally, these legacy effects are triggered by heatwave intensity and modulated by soil type, with loamy-soil forests most vulnerable. These findings highlight the critical role of forest structure in forest responses to compound disturbances. Neglecting structural legacies in Earth System Models likely underestimates risks to global carbon sinks.

The picocyanobacterium Prochlorococcus is a fundamental contributor to ocean primary productivity. While its free-living population has been extensively studied, primarily using flow cytometric analyses, the size and distribution of its particle-associated population is not well understood. Using filter fractionated samples from cruises in the Pacific Ocean, Atlantic Ocean, and Mediterranean Sea, we generated metagenomic data using internal standards, yielding absolute genome equivalent counts of Prochlorococcus cells in different size fractions. We used these data to model a relationship between relative and absolute genome equivalent counts, yielding a correction factor that we validated using published datasets. We then applied the correction factor to size-fractionated global metagenomic data from the TARA Oceans Project, which has widespread Prochlorococcus cells in size fractions >1.6 m throughout the transects, to calculate the fraction of the total Prochlorococcus population in large size fractions. The ''particle-associated'' population fraction increased with net primary productivity. Dissolved inorganic carbon was also directly correlated with increased particle association, which, combined with other evidence, could indicate an association with upwelling. We also examined the relationship between particle-associated population and carbon export at 150 m by incorporating published estimates of carbon flux based on TARA optical scattering data. This study highlights the potential importance of particle-associated Prochlorococcus to carbon flux in marine ecosystems and offers a way to convert relative to absolute genome equivalents of microorganisms in archival metagenomic datasets.

{middle dot} Globally, forest ecosystems face widespread mortality events. However, the independent impacts of distinct stressors, such as heat stress vs edaphic drought, remain poorly understood and physiological early warning indicators for tree mortality are urgently required. {middle dot} We exposed well-watered saplings of Fagus sylvatica, Pseudotsuga menziesii and Picea abies to summer heat waves and subsequent natural winter-desiccation. Physiological parameters (e.g. gas exchange, water uptake velocity via 2H labelling, and volatile organic compound emissions) were monitored throughout the growing season and survival was assessed regularly until subsequent spring to capture immediate and delayed mortality as a consequence of legacy effects. {middle dot} Heat exposure without soil water deficit, followed by winter desiccation, triggered species-specific mortality rates (51.8% F. sylvatica, 48.2% P. abies, 16.9% P. menziesii), with P. abies exhibiting significantly faster mortality response than the other species. Reduced water uptake, lower stomatal conductance, impaired photosynthetic efficiency, and altered VOC emissions distinguished non-surviving from surviving saplings months before visible damage in all three species. {middle dot} Heat stress drives mortality independent of edaphic drought, with sub-lethal physiological indicators detectable up to 10 months before visual signs. These early warning indicators could enable damage detection before lethal thresholds are crossed, offering new strategies for mitigating climate change-driven forest decline.

Microbial interactions strongly influence carbon and nitrogen flows in mushroom compost, yet their functional roles during Agaricus bisporus colonization remain unresolved. We combined PLFA-SIP and nanoSIMS imaging with ITS amplicon sequencing to follow resource flows and microbial activity across spatial scales. Stable-isotope tracers (13C-glucose and 15N-ammonium) revealed that A. bisporus simultaneously facilitates and suppresses bacterial populations: fungal activity increased glucose assimilation by bacteria yet reduced overall bacterial biomass. NanoSIMS visualized nutrient-rich microenvironments along hyphae where bacterial 13C and 15N assimilation was elevated. Sequencing showed the fungal community to comprise essentially two organisms, A. bisporus and Mycothermus thermophilus, which differ approximately elevenfold in their content of the fungal biomarker C18:2w6,9c. Total fungal PLFA therefore tracks which of the two dominates as much as it tracks fungal biomass. Together these findings reveal coupled fungal-bacterial nutrient processing and show that biomarker-based estimates of fungal biomass require community composition to be known. Multi-scale isotope probing provides a framework for resolving microbial interactions in complex detrital systems.

Forecasts of biodiversity responses to climate change often rely on space-for-time substitution, in which spatial biodiversity-climate relationships are used to predict biodiversity change through time. Yet this approach is rarely tested directly because long-term biodiversity time series are scarce. Here, we combine global modern and fossil assemblage data of planktonic foraminifera with site-specific sea-surface temperature reconstructions to compare biodiversity-temperature relationships across space and time. Spatial and temporal compositional turnover models showed similar slopes but consistently different intercepts, with spatial models predicting higher turnover across the full temperature gradient. Restricting the spatial comparison to the environmental domain of individual fossil time series reduced, but did not eliminate, this intercept mismatch. For alpha diversity, spatial models more closely recovered the temporal biodiversity-temperature relationship than for compositional turnover. Thus, for the timescales studied here, space-for-time substitution captures the direction of biodiversity change but not its magnitude through time.

Intensifying fire regimes threaten forests globally, but the risk of persistent post-fire forest loss and its potential mitigation remains poorly quantified. We analyzed millions of wildfires worldwide from 2001 to 2024 and tracked recovery in satellite-observed forest structure and ecosystem function. Post-fire persistent forest loss, indicated by modeled non-recovery to pre-fire conditions over decadal timescales, affected 57.1% of burned forest area globally since 2001, with hotspots in Pacific temperate and southern boreal forests. We then identified 'crucial fires' as events exceeding a stringent modeled-risk probability threshold for persistent structural or functional non-recovery, with fire severity strongly predicting this loss. This severity dependence revealed a management pathway, as locations with prior low-severity fire experienced lower severity in subsequent wildfires and had lower modeled probability of becoming crucial. Under a model-based counterfactual scenario, applying the estimated severity attenuation was associated with a 7.6% reduction; the top 1% of road-accessible areas accounted for 35% of this reduction. These results provide a global framework for identifying where wildfire threatens forest resistance and where targeted low-severity fire management like prescribed fire might be used to combat global forest loss.

The ocean tides influence key Earth system processes at a range of spatial and temporal scales. It is known that the geometry of ocean basins is the leading controller of tidal energetics, so well-constrained palaeogeographic reconstructions and tidal properties for Earths past are imperative when investigating other Earth system processes. Here, we present a novel way to constrain both deep-time tidal model results and reconstructions, by combining palaeoecology with sedimentology. We compare new palaeo-tidal model simulations for the Cambrian period, significant for the early origin and radiation of major animal fauna, to tidal proxies. One of the most abundant soft-bodied organisms preserved during this time are cnidarian medusae (jellyfish). A total of 17 cnidarian medusae localities were obtained through the literature, which had an adequate global distribution and occurred at regular intervals throughout the period of study. In some locations there were also estimates of palaeo-tidal range. Our results show a good agreement between the simulations and proxy data. In the few locations where there is disagreement, it is proposed that the palaeogeographic reconstructions are missing details, e.g., island chains, and our results allow for the palaeogeographic reconstructions to be improved. The proxy method presented is promising and can be applied to other time-periods with different marine fossils, particularly at evolutionary and extinction periods where the marginal marine environment is of importance.

This research addresses a central question in Palaeolithic research: how hunter-gatherer mobility was structured across space and time in the Cantabrian Region (northern Iberia), which has human occupation evidence spanning from the Middle Pleistocene through the Holocene. A multidisciplinary framework integrating primarily {delta}3S isotope values, combined with {delta}{superscript 1}3C and {delta}{superscript 1}N, palaeoproteomics, Bayesian age modelling, palaeoclimatic reconstruction, isoscape mapping, and ecological diversity was developed. A total of 905 animal bone collagen samples, with evidence of anthropogenic modifications, from 16 key archaeological sites from the Mousterian to Mesolithic (Marine Isotopic Stage 5 to 1, between 100-7 ka BP) were analysed, permitting the reconstruction of spatial patterns of resource exploitation and human mobility. The {delta}3S isotope values show weak, inconsistent relationships with climatic proxies, suggesting that sulfur signatures are primarily driven by geographic and ecological factors rather than climate. Strong spatial trends are observed, with higher {delta}3S values in coastal zones and lower values inland. Diachronic trends reveal marked shifts in human mobility: smaller ranges during the Mousterian, increasing mobility through the Chatelperronian and especially the Aurignacian, followed by reduced mobility in the Gravettian and Solutrean, and renewed territorial expansion during the Magdalenian and, likely, the Azilian. In contrast, the Mesolithic is characterised by decreased mobility and thus increased territoriality in both coastal and inland contexts. Faunal isotope values and isoscape predictions reveal that some animals were acquired beyond local foraging ranges during the Palaeolithic, particularly in inland regions with lower {delta}3S values. Isotopic niche analyses indicate partial interspecific overlap consistent with ecological flexibility. Macromammal and micromammal diversity exhibit contrasting patterns, with a significant negative correlation in Simpson and Shannon indices. Macromammal diversity correlates negatively with {delta}3S values, linking increased hunting diversity to expanded catchment areas and longer-distance foraging, whereas micromammal diversity shows positive correlations with {delta}3S, {delta}{superscript 1}3C and {delta}{superscript 1}N reflecting stronger climatic influence. Overall, these results demonstrate that hunter-gatherer behaviour in northern Iberia during the Middle and Late Palaeolithic was highly dynamic, combining logistical and residential strategies that shifted in response to changing environmental conditions, resource distributions and cultural adaptations.

Experimentally evolved, heat-tolerant algal symbionts (heat-evolved; HE) offer a promising means of enhancing coral holobiont thermotolerance under rapidly warming oceans. However, translating their benefits into restoration practices requires scalable delivery methods. Coral tissue fusion may provide one such pathway by facilitating HE symbiont transfer to wild corals; however, its feasibility remains largely untested. As an initial test, we paired adult isografts of Galaxea fascicularis and Psammocora columna hosting HE Cladocopium proliferum (SS8) with chemically bleached, SS8-naive recipients. Fusion was first observed after three days in G. fascicularis and nine days in P. columna. In both species, fusion was followed by increased pigmentation and photochemical efficiency at the recipients fusion interface relative to distal tissue and unfused controls. After [~]50 days, SS8 was detected at low levels (<3.5%) in 15/19 fused G. fascicularis recipients, although detection was also common among unfused horizontal-transmission controls maintained in the same water column (13/18). These findings provide the first empirical evidence that conspecific coral tissue fusion is associated with localised physiological recovery and can coincide with HE symbiont acquisition, while highlighting the need to distinguish tissue-mediated transfer from background horizontal transmission. Fusion may therefore represent a complementary pathway for beneficial symbiont delivery in assisted-evolution frameworks.

Urbanization is reshaping freshwater ecosystems, with well-documented effects across gradients of land-use change, hydrologic alteration, and habitat degradation. However, how biodiversity is organized among neighboring urban aquatic habitats that differ in hydrologic connectivity, disturbance transmission, residence time, management history, and opportunities for species movement is often less clear. This creates a challenge for interpreting urban fish communities at local scales as species occurrence may reflect both contemporary habitat filtering and historical contingencies including native persistence, interbasin transfer, stocking, and nonindigenous introductions. Here we use eDNA detections, historical records, phylogenetic information, and species trait data to investigate the fish assemblages of the Charlotte metropolitan region. We detect a highly mixed fauna that also depicts a strong signature of structured biodiversity profiles across taxonomic, phylogenetic, functional, and life-history dimensions between habitat types. In particular, bounded habitats contained assemblages with larger-bodied species that are fecund and faster to reproduce relative to free-flowing habitats. Species-level occurrence models did not support a simple trait-by-habitat rule. Instead our results demonstrate that urban aquatic habitats can sort historically mixed regional species pools into predictable assemblage-level life-history profiles while simultaneously retaining signatures of evolutionary and historical biogeographic contingency.

Coastal forests are increasingly threatened by saturated soil and elevated salinity levels resulting from sea level rise, saltwater intrusion, and storm surges. In response to rising salinization and flooding, healthy coastal forests that rely on freshwater (both wetland forests and low-elevation upland forests) are transitioning into landscapes dominated by dead or dying trees, known as ghost forests. Situated among salt-tolerant shrubs and grasses, ghost forests eventually become marshes or open water. Here, our main objective was to quantify the dynamics and pathways of these forest landscape conversions, as well as the factors contributing to the changes, which is vital for understanding the progression of coastal ecosystem degradation and forecasting future changes. We focused first on identifying the best method to track forest landscape change by exploring the role of multiple remote sensing indices (i.e., multispectral, bi-seasonal, topographical, and phenological metrics) in enhancing the performance of deep learning models (convolutional neural networks, CNNs) for land cover classification in the coastal plain of North Carolina using surface reflectance of Landsat 8 and Sentinel-2 images. Then, we used the best available data (Landsat 8) to understand long-term change and identify patterns of land cover change from 1985 to 2021. Our study reveals that incorporating phenology and topographical indices enhances the separability of the ghost forests class from all other vegetation classes. In our assessment, the higher-resolution Sentinel-2 data (F1 Score = 96.3) outperformed Landsat images (F1 score = 93.4) for the 2021 co-available year. However, Landsat remains an important tool used due to its long-term data record. Therefore, we used Landsat to determine that 21% of forests were lost between 1985 and 2021, and that the rate of loss is increasing. Between 2010 and 2021, 23,876 ha of forest were converted to marsh, ghost forest, and shrub, which is 1.5 times higher than the 16,968 ha lost between 1985 and 2010. These conversions from forest to ghost forest and marshes were driven primarily by proximity to the channel, salinity, and the increasing rate of relative sea level rise (RSLR), which are the key environmental drivers of observed changes. By quantifying these changes, we highlight regions most vulnerable to environmental stressors, providing a basis for targeted conservation strategies.

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.

Denisovans, originally identified from ancient genome from Denisova Cave in Altai, were a sister group to the Neanderthals and were once widely distributed across diverse terrains in the north and south of eastern Asia1-5. Genomic studies suggest that there were multiple events of interbreeding between modern humans (Homo sapiens) and Denisovans somewhere in Asia6. However, little is known about Denisovan living environments, diet, ecological niche, the timing of their disappearance, and the possible coexistence with modern humans in different regions. Here we report the radiocarbon age and stable isotopic signature of Penghu 3, a large Denisovan tibia from Penghu Channel, Taiwan7. The results showed that Penghu 3 dates to approximately 45,000 years ago, the time when modern humans were already widespread in southern parts of Asia. This Denisovan individual inhabited a C4-dominated ecosystem, open environments such as savannahs and floodplains, or a mixture of both, and consumed a high proportion of animal protein similar to some European Neanderthals8-10, with no clear evidence for the use of aquatic resources. These findings have implications for the behavioral flexibility, large body size7, and eventual disappearance of the Denisovans.

High-resolution monitoring of forest structure and productivity is essential for effective natural resource management. However, monitoring approaches such as field-based forest inventories or extensive lidar campaigns are costly, time-intensive, and spatially limited. Therefore, inexpensive and accessible methods are needed. SatCHM (Satellite Canopy Height Model) was developed to be an accessible and open-source tool for researchers, allowing for site-specific and temporally flexible predictions of canopy height with limited computational resources. SatCHM requires four inputs: panchromatic satellite imagery, solar and sensor angle metadata of satellite imagery, digital elevation models (DEMs), and lidar-produced CHMs for an area of interest. After SatCHM pre-processes inputs, data is loaded into a collection of convolutional neural networks (CNNs) for image-to-image regression. This ensemble cooperates to yield high-resolution predictions (up to 0.5-meter) of three-dimensional tree structure with discernible tree crowns across a broader defined area of interest. After calculating the mean absolute error for each prediction output, the median of these mean absolute errors was 6.06 meters.