Communications Earth & Environment

Posidonia oceanica meadows, which underpin Mediterranean coastal ecosystems, are undergoing accelerated decline, partly driven by thermal stress. While previous quantitative studies have identified temperature thresholds beyond which seagrass mortality increases sharply, we show the cumulative and sublethal impacts of prolonged warming under fluctuating subthreshold conditions. To capture these effects, we introduce Stress Degree Days (SDD), a physiologically grounded index derived from an experimentally validated mortality rate function. Using sea surface temperature (SST) data, we quantified the cumulative thermal exposure across the Mediterranean Basin from 2000 to 2020. Leveraging high-resolution satellite imagery and deep learning-based habitat mapping, we linked SDD-derived thermal exposure to meadow fragmentation, which is a proxy for seagrass health. Our results show that high thermal stress (> 50%) is concentrated along the southern and eastern Mediterranean, where meadows exhibit more than 40% cover loss and elevated fragmentation, even though maximum SSTs remained below lethal limits (LT50 = 28.9 {degrees}C). This finding highlights the critical role of chronic sublethal thermal stress in driving structural degradation. Future projections under the RCP8.5, business as usual, and the more moderate RCP4.5 climatic scenarios indicate basin-wide regression, with expected cover losses of approximately 80% and 40%, respectively, by 2100, and near-total habitat suitability collapse in the southern regions. Consequently, fragmentation indices are projected to double or triple, further disrupting clonal connectivity, sediment retention, and oxygen export. In summary, by integrating physiological mechanisms, large-scale remote sensing, and climate modeling, the SDD framework identifies thermal hotspots, reveals emergent vulnerability patterns, and offers a predictive tool to guide conservation strategies in warming oceans.

Mountain ecosystems face unprecedented pressures from anthropogenic activities and climate change, challenging the productivity of these vital habitats. In the Tien Shan mountains, understanding localized responses to these pressures is often hindered by the coarse spatiotemporal resolutions of available data. To address this, we combined high-resolution satellite imagery (1997-2021) to map land-cover dynamics in the Naryn oblast, Kyrgyzstan across a gradient of grazing intensities. We classified and quantified land-cover distribution over 24 years, investigating the roles of topography, elevation, and anthropogenic disturbances as drivers of change. Our results identify intermediate elevations, high degrees of disturbance, and the interaction between the two as the primary contributors to recent transitions in grassland, forest, and barren habitats. By integrating Landsat analysis-ready data, European Space Agency WorldCover dataset and digital elevation models at fine spatial scales, we provide valuable contemporary and historical landscape and habitat-level insights and a high-resolution framework for disentangling climate-driven shifts from land-use impacts. These findings highlight the urgency of localized management in remote, data-poor regions where rapid environmental change threatens both biodiversity and pastoral livelihoods. Our work serves as a critical baseline for characterizing the adaptability of semi-arid mountain rangelands under escalating global and regional pressures.

The contribution of tree foliage to atmospheric methane (CH4) and nitrous oxide (N2O) fluxes remains a major uncertainty in global GHG budgets. We made repeated in situ measurements of foliar CH4 and N2O fluxes across 25 temperate tree species interplanted at a forest restoration site using high-resolution laser spectroscopy. Tree foliage was consistently a net CH4 sink and a net N2O source in all species. Foliar CH4 oxidation increased by [~]33% in fall relative to spring and was [~]3-fold higher in shade-tolerant than shade-intolerant angiosperm species. Species differences accounted for most of the variability in fluxes, while correlations with soil emissions were comparatively weak. Microbial DNA sequencing revealed that the highest CH4-oxidizing angiosperm species (Tilia americana) harbored abundant Type I methanotrophs, whereas the lowest-oxidizing species (Prunus virginiana) had nearly 100-fold lower methanotroph abundance, with a foliar microbial community dominated by facultative methylotrophs. Global warming potential (GWP) scaling indicates that foliar CH4 uptake overwhelmingly dominates the net climate forcing effect. Our results suggest that the large and predictable differences in foliar CH4 uptake among tree species and associated differences in foliar microbial communities are of importance in understanding and potentially enhancing the global terrestrial CH4 sink.

Foraminiferal environmental DNA (eDNA) assemblages have recently emerged as a robust and complementary proxy for relative sea level (RSL) reconstruction. However, unlike traditional morphological methods, eDNA assemblages are influenced by diverse DNA sources, including propagules and juveniles, whose effects on RSL reconstruction remain poorly understood. To assess how foraminiferal eDNA from different life stages vary in taxa composition and impact RSL reconstruction, we analyzed foraminiferal eDNA from bulk, 500-63 m and <63 m size fraction sediments from mangrove and mudflat environments in subtropical Hong Kong. The eDNA assemblages in size-fractioned sediments displayed distinct patterns from those in bulk sediment eDNA across different environments. The propagule and juvenile-derived eDNA <63 m fraction exhibited a similar community structure to bulk eDNA in mudflat environments but diverged in mangrove environments, indicating a greater contribution of propagule and juvenile eDNA to the total eDNA pool in the mudflat environment. We applied Bayesian transfer function modeling to estimate the elevation of samples using different size fractions. eDNA assemblages from the <63 m fraction systematically underpredicted elevation in mangrove environments, while elevations inferred from the 500-63 m fraction and bulk sediment eDNA were accurate. Conversely, all eDNA assemblages in the mudflat-mangrove transitional zone led to the overprediction of RSL. These findings confirm the reliability of bulk sediment eDNA for RSL reconstruction in mangrove environments, while highlighting the need for caution when reconstructing RSL in transitional zones.

1.1Degree Heating Weeks (DHW) is the standard metric for global coral bleaching prediction, yet its performance varies markedly across regions for structurally unexplained reasons. We analyse five years (2020-2024) of standardised bleaching surveys from Japans Monitoring Site 1000 program (26 sites, 113 site-years; balanced panel n = 105) across a 24-35{degrees}N latitudinal gradient to diagnose why DHW fails in subtropical waters. Only 4 of 113 site-years (3.5%) reached the DHW [&ge;] 4 alert threshold, while bleaching (>0%) was recorded in 65 site-years (57.5%). DHW sensitivity for detecting any bleaching was 6.2%. A simple absolute-temperature metric (days with SST [&ge;] 30{degrees}C) significantly outperformed DHW in discriminating [&ge;]50% bleaching (AUC = 0.926 vs 0.667, {Delta}AUC = 0.260, 95% CI [0.154, 0.355], p < 0.001), with the largest gap at low latitudes ({Delta}AUC = 0.293, p < 0.001). The Maximum Monthly Mean (MMM) was strongly correlated with latitude (r = -0.914), compressing the thermal gap available for HotSpot accumulation at low-latitude sites and eliminating HotSpot events at high-latitude sites. This structural insensitivity -- arising from the anomaly-based design of DHW rather than from threshold miscalibration -- operated through two distinct mechanisms across the latitudinal gradient. At low latitudes, where MMM approaches 30{degrees}C, HotSpot signals were compressed below detection thresholds despite widespread bleaching; at high latitudes, SST rarely exceeded MMM, rendering HotSpot events absent altogether. These findings demonstrate that DHWs standard alert framework is structurally non-functional across Japans coral monitoring network and that regional assessment requires metrics independent of the MMM-relative anomaly architecture.

The Humboldt upwelling ecosystem has been intensively harvested by people since the early Holocene. Understanding past and present human choices under climatic variability in these productive environments may hold key insights for its future sustainability by unraveling different adaptive pathways. To this end, we studied shellfish exploitation and climate patterns in the Taltal region of the Atacama desert coast (25{whitebullet}S) from the early Holocene until today using a compilation of archaeological, and modern benthic fisheries data together with direct ecological surveys. In addition we obtained satellite sea surface temperature (SST) and published{delta} 18O SST for the study region. The archaeological record and the modern rocky shore assemblage were dominated by herbivorous gastropods -Fissurella spp., Enoplochiton spp., Tegula spp.-and the carnivorous whelk Concholepas concholepas. Functional composition from the early Holocene to the present was remarkably stable. Using SST as a latent variable, we examined changes in functional composition across the Holocene and in a 16-year series of artisanal fisheries landings using bayesian ordination. The analysis identified functional groups characteristic of kelp ecosystems in association with cooler SST conditions during the Holocene and the present. Changes in functional composition during warm and cold periods of the Holocene broadly mirrored effects of interannual SST variability in the modern fisheries. The archaeological record suggests two cross-Holocene transitions social-ecological transitions. The generalized shoreline harvesting strategy that prevailed during the cold early Holocene shifted to a specialized maritime economy towards the warmer mid-Holocene. The maritime technological and cultural adaptions remained, but were part of more diversified lifestyles in the cooler and more variable late Holocene. The latter emerged at the same time as the modern El Nino climate pattern. Our insights from the direct analysis of human choices and SST variability highlight the role of flexibility and agency under a changing environment. The broad range of human decisions in the past, inform current regulatory frameworks for benthic artisanal fisheries. Marine resources and the livelihoods that depend on them are integrated into coupled coastal socioecological systems; their future sustainability hinges on fostering the different dimension of their adaptive capacity.

AbstractThe ability to accurately assess ecosystem C budgets across scales from individual sites to continents is essential for C accounting, management, and ultimately mitigating climate change. State data assimilation (SDA) provides a framework for harmonizing observations with models, while robustly accounting for and reducing multiple sources of uncertainty. In this study, we employed a hybrid SDA framework that combines process-based terrestrial biosphere modeling, hierarchical Bayesian inference, and machine learning to harmonize bottom-up and remotely-sensed data streams for 8,000 pre-selected 1km2 locations across North America within a hybrid structure. Combining bottom-up soils data (SoilGrids) with spectral (MODIS and Landsat) and microwave (SMAP) remote sensing helps constrain the major C and water stocks through space and time. Machine learning is used both to identify and correct systematic errors in the process model (SIPNET) and to interpolate the pre-selected locations onto a 1km grid, making it computationally feasible to generate annual ensemble maps of the North American carbon budget. Furthermore, the uncertainties for each variable were reduced compared to those from observations or models alone. Spatiotemporal analysis showed a slight decrease in aboveground biomass (AGB) across the western US, a loss of leaf area across the boreal, and a slight greening of the Alaskan tundra. The uncertainty trends suggest a significant reduction in the uncertainty about soil organic carbon (SOC), the largest C reservoir. Validation results show that we accurately estimate C pools, compared to the assimilated data streams and held-out observations of AGB from GEDI, ICESat-2, and the US FIA, and SOC from the ISCN network. Our ML-debiasing algorithm further improved the accuracy of major C pools (AGB, SOC). In general, our continental SDA framework will facilitate global C MRV (monitoring, reporting, and verification) by providing accurate and precise C-cycle estimates, along with their corresponding spatiotemporal uncertainties.

Marine and brackish-water ecosystems are increasingly degraded by cumulative human pressures, with biological invasions representing a major driver of biodiversity loss, ecosystem disruption, and socio-economic impacts. Effective management requires regionally harmonized and scientifically robust baselines capable of supporting coordinated transboundary decision-making. Here we present the first consolidated marine biosecurity baseline for the Regional Organization for the Protection of the Marine Environment (ROPME) Sea Area, a transboundary region characterized by extreme environmental conditions and increasing biosecurity pressure. A total of 192 species (123 extant and 69 horizon), including birds, fishes, tunicates, invertebrates, plants, and chromists, were systematically reviewed, taxonomically validated, and cross-checked against major databases and Member State inputs. Re-evaluation of a previous regional screening revealed substantial inconsistencies, with 24 species ({approx}18%) requiring status correction or exclusion. The resulting consolidated inventory comprised 130 validated retained species supplemented by 62 additional taxa. Extant species were classified according to biogeographic origin and impact status, whereas horizon species were evaluated based on introduction pathways, environmental suitability, and projected climate trends. Risk screening under current and projected climate conditions identified 39 extant species as very high risk, providing an operational basis for progression to full risk assessment and coordinated regional biosecurity management.

Groundwater-dependent ecosystems are biodiversity hotspots that provide habitat for specialised species. The EU Water Framework Directive (WFD) stresses the importance of identifying and protecting these ecosystems. However, they remain poorly mapped in temperate regions, as most studies have focused on (semi-) arid regions, where groundwater use by vegetation is both more prevalent and easier to detect from remote sensing. In this study, we transfer mapping approaches for groundwater-dependent vegetation (GDV) from dry climates into a novel framework for humid climates. To do so, we integrated, ECOSTRESS evapotranspiration data, together with high-resolution remote sensing data, regional geospatial data and field data to identify GDV. To test our framework, we trained and validated Random Forest models with eight predictor variables using 166 ground-truth vegetation plots to map GDV in Saxony-Anhalt (Germany). The final model achieved an overall accuracy of 0.97, identifying 2,067 km2 (41%) of GDV. Currently, only 19% are protected under the EU WFD. The proposed mapping framework offers a new solution for identifying GDV in temperate regions. The new GDV maps can contribute to managing groundwater resources and preserving biodiversity hotspots in regions facing increasing droughts, ultimately supporting implementation of the EU WFD.

Saline endorheic shallow playa-lakes are ecosystems susceptible to extreme geochemical changes because of severe hydro-climatic fluctuations. Under dry conditions, a rigid salt crust can separate the underlying sediments from the atmosphere. This interface is an organic-mineral assemblage of benthic biofilm encapsulated by evaporitic salts. It is well known that its structure, composition and consistency control water evaporation from underlying sediments, but its role in CO2 fluxes is unknown. We therefore measured the CO2 exchanges from sediments and the atmosphere in a hypersaline playa-lake characterized by a thin organic-mineral benthic crust upon drying. Results show that the largest CO2 release to the atmosphere occurs when ambient temperature and sediment humidity are high and low respectively. Nonetheless fluxes were lower than those reported for typical dry freshwater sediments and other hypersaline lagoons. The dry crust contains sedimentary structures that likely reflect the gaseous pressure from the underlying sediments, and its removal provokes a significant increase in net CO2 fluxes. Thus, this interface exerts physical control over both water evaporation and gases exchange such as CO2. Nevertheless, prolonged and severe droughts threaten the integrity of the crust: cracks together with bio-induced burrows and tunnels, likely create preferential pathways for CO2 leakage and enhance oxygen diffusion within the sediments and likely promote aerobic heterotrophic activity, explaining the CO2 leakage observed just below the organic-mineral crust.

Trees can produce, consume, transport, and emit methane (CH), yet the environmental controls and mechanisms underlying these fluxes remain poorly understood. We combined 1,640 stem-chamber observations (2023-2025) with tower-based meteorology, soil moisture and temperature networks, water table monitoring, and non-destructive tomography to test how hydrology, energy balance, species identity, and internal wood condition regulate stem CH flux. Wetland trees emitted approximately 40-fold more CH than upland trees (1.96 vs. 0.05 nmol m-{superscript 2} s-{superscript 1}). At the wetland, a three-way interaction between soil temperature, water table depth, and species explained 65% of flux variance, consistent with soil-derived CH transport through stems. The wetland specialist Nyssa sylvatica emitted an order of magnitude more CH than co-occurring generalists, likely reflecting flood-tolerance adaptations that enhance gas transport. In contrast, upland fluxes showed minimal environmental control (R{superscript 2} < 9%), with most variance occurring as unexplained temporal variation within individual trees--a pattern suggesting competing methanogenic and methanotrophic processes operating near equilibrium. Internal wood condition, assessed via acoustic and electrical resistance tomography, had opposite effects across sites: decay increased emissions in upland trees, likely by creating anaerobic microsites for in situ production, while decay decreased net emissions in wetland trees, likely by impairing transport of soil-derived CH more than it enhanced in situ production. Together, these results indicate that the dominant controls on tree CH flux differ fundamentally between wetland and upland forests, underscoring the need to represent hydrologic setting, species composition, and tree condition when scaling forest CH contributions to regional budgets.

Climate change is profoundly altering forest phenology and productivity across Europe, with particularly strong impacts in Mediterranean regions characterized by high climatic heterogeneity. Understanding how climatic and site-specific drivers regulate the start, end, and length of the growing season, and how these phenological shifts translate into productivity responses, remains a key challenge for predicting forest carbon dynamics. In this study, we investigate phenological timing and total seasonal productivity across multiple Italian forest species spanning Mediterranean, temperate, and mountain environments, leveraging the new High-Resolution Vegetation Productivity and Phenology product from the Copernicus Land Monitoring Service, machine learning (random forests) modeling, and explainable artificial intelligence analysis (SHAP). Our results confirm a general lengthening of the growing season driven mainly by chilling accumulation and spring temperatures. Warmer conditions advance the start of the season by 1-10 days across species, while the combined effects of temperature, radiation, and moisture can extend the growing season by up to 20-30 days. End-of-season dynamics and season length are more strongly controlled by light and water availability than by temperature alone. In several Mediterranean species, the end of the season can advance by up to 40 days due to summer drought, high vapor pressure deficit, and site exposure. Mediterranean species often show compensatory shifts between season onset and senescence, maintaining a relatively stable length of the season, whereas mountain species exhibit a tighter coupling between delayed onset and shortened season length. Phenological shifts are frequently decoupled from productivity, which is mainly regulated by energy and water availability, highlighting species- and site-specific responses to climate change. The findings of this study highlight the substantial advantage of remote sensing data, coupled with machine learning approaches, for advancing the understanding of forest phenology and productivity across broad spatial and climatic gradients.

The voluntary blue carbon market is severely bottlenecked by outdated methodologies that apply broad, coast-level carbon averages across low-resolution spatial units, systematically failing to account for micro-site ecological realities and critical socio-political constraints. To resolve this structural deficit, this paper introduces the High-Resolution Geographically-Explicit Blue Carbon Assessment (HiGEBCA) pipeline, an innovative geospatial architecture that shifts site intelligence from monolithic raster grids to a topologically verified, hyper-dimensional polygon infrastructure. Operating on 1,601 distinct mangrove features across Colombia, the pipeline mathematically binds 47 ecological attributes to each polygon, integrating Monte Carlo uncertainty propagation, climate-stratified soil organic carbon, and rigorous biodiversity quantification spanning 293 taxon-code pairs. A diagnostic CatBoost machine learning emulator (R{superscript 2} = 0.926) deployed within the pipeline empirically demonstrates that local climate classes and biodiversity metrics drive over 96% of the variance in carbon density, proving that traditional broad biome classifications are inadequate for accurate micro-site valuation. Crucially, the HiGEBCA framework pioneers the integration of operational reality into natural capital assessment. When applied to Colombias theoretical national estate of 276,430 hectares (containing an estimated 478 million tCO2e), the pipeline executes a rigorous REDD+ white space assessment alongside hard mathematical filters for legal land tenure, armed conflict, and regulatory overlap. This strict governance filtration shatters the illusion of massive, easily accessible natural capital, systematically reducing the viable, investment-grade portfolio to a highly de-risked 4,000 to 12,000 hectares. Designed for cross-jurisdictional replication, the HiGEBCA pipeline establishes a new, transparent standard for prioritizing high-integrity blue carbon assets, providing a quantitative mandate for investors seeking to maximize climate impact, capture biodiversity premiums, and definitively mitigate operational risk.

Agroforestry is a cornerstone of Natural Climate Solutions, yet the hierarchical importance of its soil organic carbon (SOC) drivers remains poorly resolved across heterogeneous tropical landscapes. Current global assessments predominantly rely on categorical system typologies that mask the continuous influence of biophysical drivers, leaving the reliability of mitigation estimates unclear. Here, we synthesize 643 observations from 54 field studies in Latin America and the Caribbean to decouple the determinants of SOC sequestration using a machine-learning framework. We show that baseline soil carbon stocks and temporal kinetics override management design, collectively explaining [~]85% of sequestration variability, whereas system typology and species richness contribute marginally (R2<0.10). While the median SOC storage rate was 0.26 Mg C ha{superscript 1} yr{superscript 1}, accumulation followed a distinct non-linear trajectory: sequestration intensity peaked early before decelerating sharply after a critical inflection at year 7. Critically, sequestration is governed by a robust negative feedback from initial SOC stocks, which cross a zero-net-gain threshold at [~]80 Mg C ha{superscript 1}. Depth-resolved analyses reveal that subsoil layers (up to 55-75 cm) exhibit a cumulative relative response up to fourfold greater than surface horizons, indicating that conventional shallow monitoring could systematically underestimates long-term stabilization potential. Our findings demonstrate that current carbon accounting frameworks, rooted in generic system averages (IPCC Tier 1), are structurally limited by their inability to account for baseline-dependent saturation feedbacks and non-linear effects. Transitioning toward Tier 3 context-aware, depth-explicit modeling is therefore essential to transform agroforestry from a broad practice into a precision-based, high-integrity Natural Climate Solution. HighlightsO_LISoil carbon sequestration in tropical agroforestry is primarily controlled by baseline soil conditions and temporal dynamics rather than system typology. C_LIO_LIDepth-resolved analyses reveal long-term carbon stabilization processes overlooked by surface-based assessments. C_LIO_LICarbon accumulation is strongly front-loaded, declining sharply after system establishment. C_LIO_LIContext-dependent responses challenge generic carbon accounting frameworks and highlight the need for predictive, site-specific deployment of agroforestry. C_LI

Antarctic marine ecosystems are undergoing rapid physical change, yet the capacity of long-lived polar fishes to adapt genomically remains poorly understood. Antarctic toothfish (Dissostichus mawsoni) are an exploited top fish predator whose early life stages develop beneath the sea-ice edge, where salinity, temperature and circulation are being reshaped by climate change. Using whole-genome resequencing data, we investigated how environmental exposure, particularly during early life, structures patterns of local adaptation in D. mawsoni. We analysed 2.4 million unlinked SNPs from 24 adults sampled across the circumpolar distribution of D mawsoni, and compared variability in putatively-adaptive loci with variation in environmental parameters from the ORAS5 global ocean reanalysis, including salinity, temperature, mixed-layer depth, sea-ice concentration and thickness, and surface currents. To capture uncertainty in ontogenetic exposure, we constructed three environmental scenarios differing in their spatial and temporal representation of conditions: Point of Capture-Time of Capture (POC-C), Spawning Ground-Time of Birth (SG-B), and Point of Capture-Time of Birth (POC-B). Genotype-environment association (GEA) was performed using redundancy analysis conditioned on fishing pressure and latent-factor mixed models, with high-confidence GEA loci being defined as SNPs jointly detected by both approaches and robust to random-predictor tests. The scenario that best explained genomic variation was SG-B, in which environmental variables were averaged over hypothesised spawning grounds during the egg incubation period of D. mawsoni (August - October). Within this scenario, the significant environmental axis, dominated by salinity, was strongly associated with 854 high-confidence GEA loci. Functional enrichment revealed over-representation of gene ontology terms linked to monoatomic ion transport, ion channel complexes and calcium signalling, consistent with salinity-driven selection on osmoregulatory pathways during early development. Our results provide genomic evidence that early-life salinity exposure is a key driver of local adaptation in D. mawsoni, underscore the importance of correctly representing life-stage-specific environments in climate genomics, and highlight a concrete pathway by which climate-induced freshening and sea-ice change may alter recruitment and stock resilience.

Climate change is expected to alter species assemblages by affecting the outcome of competition between species. Investigating processes of competition remains challenging particularly in tree communities, as they unfold over extensive spatio-temporal scales. Here, we developed a deep-learning approach to leverage a novel database of 135 million simulated local-scale tree responses to climate across continental Europe to investigate changes in the competitiveness of nine major tree species under different scenarios of climate change. Specifically, we trained a Deep Neural Network on local process model projections to investigate climate change effects on indicators of competitive strength and species dominance. We found decreasing competitive strength for all investigated evergreen coniferous species across their distribution, while major deciduous broadleaved species such as Quercus robur and Fagus sylvatica increased in competitiveness. Changes in tree species competition with climate differed locally, but most investigated species lost competitive strength at their warm range edges. As a consequence of these changes, up to 19% of Europes forests could experience a change in the dominant tree species until the end of the 21st century. Our results suggest a profound climate-induced reassembly of Europes forests and identify areas that may require specific attention in forest policy and management.

Despite the successful population recovery of the Eurasian beaver (Castor fiber) across much of Eurasia, its subspecies, the Sino-Mongolian beaver (C. f. birulai), remains critically endangered, with an estimated population of approximately 1,500 individuals confined to a small number of isolated and fragmented refugia along the China-Mongolia border. Effective conservation of this highly threatened subspecies requires a holistic perspective that integrates constraints on population dynamics, habitat associations, and future climatic vulnerability. Here, we combined systematic annual field surveys conducted between 2003 and 2023 with historical survey records from 1975 to 1989 in northern Xinjiang, China, to synthesize long-term spatiotemporal population dynamics, evaluate habitat preferences based on nine local environmental variables, and assess future climatic vulnerability using ensemble species distribution models (SDMs) under projected climate change scenarios. We detected a significant and phased population recovery, with beaver colony numbers increasing from 27 (approximately 100 individuals) in 1975 to 227 (681-908 individuals) in 2023. This recovery closely corresponded with major conservation milestones, including the establishment and upgrading of nature reserves, strengthened legislative protection, and enhanced multi-stakeholder collaboration. Habitat analyses further indicated that the Sino-Mongolian beaver preferentially occupied areas characterized by minimal anthropogenic disturbance and stable hydro-geomorphic conditions. Critically, SDM projections revealed that only 14% of the current study area presently exhibits high climatic suitability, and these highly suitable habitats are expected to disappear entirely by the 2050s. Together, our findings provide a comprehensive overview of the historical population recovery and conservation trajectory of the Sino-Mongolian beaver in China, and offer robust scientific support for developing adaptive management strategies in the face of ongoing climate change and increasing human pressures.

Floating photovoltaic (FPV) arrays alter the methane (CH4) cycling dynamics of waterbodies on which they are deployed. Here, we investigated dissolved CH4 dynamics and associated CH4 cycling microbial communities (methanogens and methanotrophs) in the second year of FPV deployment (70% aerial coverage) in experimental ponds. We found that bottom-water CH4 concentrations were twice as high in ponds with FPV compared to those without, while surface water CH4 concentrations were orders of magnitude lower than bottom-waters, but did not differ between treatments. There was no change in the relative abundances of putative sediment methanogens or methanotrophs, but FPV restructured methanogen communities. FPV promoted late-summer methanotroph blooms in the water column, with abundances surpassing 1,000,000 cells mL-1. We conclude that prolonged periods of CH4 production in low oxygen FPV ponds favored blooms of methanotrophs, that may mitigate diffusive CH4 emissions to the atmosphere by consuming dissolved CH4. Scientific Significance StatementProducing energy using floating photovoltaic (FPV) powerplants offers an opportunity to produce renewable energy, spare land, and reduce evaporation from ponds, lakes, and reservoirs. However, FPV deployment in these ecosystems is associated with colder temperatures, less oxygen availability, and changes in carbon cycling processes. Experimental evidence demonstrates an increase in concentrations of methane - a potent greenhouse gas - in ponds following FPV deployment. In this study, we investigate how microbial communities associated with aquatic methane cycling differ between ponds with and without FPV. We show that FPV deployment increases bottom-water methane concentrations and triggers dense blooms of methane-oxidizing bacteria that create a methane biofilter. These results provide the first evidence that microbial communities respond strongly to engineered shading and may help buffer greenhouse gas emissions in solar-covered waters.

Benthic remineralization of organic matter is key to carbon and nutrient cycling, influencing both long-term carbon storage in the sediments and the release of nutrients that support primary production in the water column. With its multiple forms and ages of sea ice, Nares Strait in the Canadian Arctic offers a unique opportunity to address the knowledge gap of variability of benthic remineralization rates along a natural sea ice gradient. Here, we incubated sediment cores in different locations in Nares Strait characterised by different sea ice conditions ranging from first-year ice to multi-year ice, to measure oxygen and nutrient fluxes. To identify potential drivers, we measured environmental variables, identified macrofauna and calculated a suite of taxonomic and functional diversity indices. Our analyses showed that benthic fluxes varied significantly between the northern and southern regions of Nares Strait. The presence of deposit feeders and sea ice cover (number of days since ice-free) were the main drivers in benthic fluxes, explaining 22.6% and 13.9% of the benthic flux variation, respectively. Overall, functional diversity was a better predictor of benthic fluxes than taxonomic diversity, indicating its primary importance in controlling benthic ecosystems functioning. Our results reveal that, from a benthic biogeochemical point of view, Nares Strait seems to be dissected into two main sub-regions: (i) a permanently and highly sea ice-covered area north of Kennedy Channel, resembling deeper regions of the Arctic Ocean and (ii) a seasonally ice-covered area between the North Water Polynya and Kane Basin, where benthic fluxes values are equivalent to those reported in similar continental Arctic shelves. Consequently, the rapid functional shifts resulting from the ongoing decline in sea ice could enhance benthic remineralisation rates if deposit feeder were to become dominant in certain areas, reducing the role of the region and by extension, the Arctic, as a carbon sink.

Understanding how reef-associated biodiversity responds to seascape features is essential for monitoring and conserving coral reef ecosystems. Environmental DNA (eDNA) from seawater provides access to benthopelagic eukaryotic diversity but its relationship with benthic structure remains poorly understood. We conducted simultaneous assessment of benthopelagic eDNA derived from near-reef seawater and benthic photoquadrat surveys across 12 coral reef sites in the northern Red Sea, spanning three seascape regions: the Gulf of Aqaba, nearshore Northern Red Sea (NRS), and offshore NRS. We examined whether spatial patterns in benthopelagic eDNA communities were structured across regions and whether variation in benthic cover explained differences in eDNA-derived assemblages obtained from water samples. Benthopelagic eDNA revealed fine-scale spatial structuring across regions but showed non-significant whole-community correlation with benthic composition. When examined by major taxonomic groups, taxon-specific relationships emerged, with some taxa (i.e., Micromonas sp.) showing increasing relative abundances in reefs characterized by lower benthic complexity. While traditional photoquadrat surveys captured 72 benthic sessile taxa including dominant benthic groups (e.g. hard corals and algae) across four eukaryotic phyla, benthopelagic eDNA documented a broader range of eukaryotic diversity, including planktonic, cryptic, and low abundant taxa spanning 35 phyla. Notably, eDNA detected cryptic organisms overlooked by visual surveys, such as the giant clam Tridacna sp., even where present but not recorded in photoquadrats. Our results demonstrate that benthopelagic eDNA and visual surveys provide complementary perspectives on reef biodiversity. Rather than serving as a direct proxy for benthic structure, benthopelagic eDNA captures spatial and taxonomic patterns that may be overlooked by visual transects, supporting its use in seascape-scale biodiversity assessments and conservation planning efforts in dynamic and understudied reef systems.