The Arctic has been warming much faster than the global average, known as Arctic amplification. The active layer is seasonally frozen in winter and thaws in summer. In the 2017 Arctic Boreal Vulnerability Experiment (ABoVE) airborne campaign, airborne L- and P- band synthetic aperture radar (SAR) was used to acquire a dataset of active layer thickness (ALT) and vertical soil moisture profile, at 30 m resolution for 51 swaths across the ABoVE domain. Using a thawing degree day (TDD) model, ALT=K root TDD, we estimated ALT along the ABoVE swaths employing the 2-m air temperature from ERA5. The coefficient (K) calibrated has an R2=0.9783. We also obtained an excellent fit between ALT and K root(TDD/theta) where theta is the soil moisture from ERA5 (R2=0.9719). Output based on shared-social economic pathway (SSP) climate scenarios SSP 1-2.6, SSP 2-4.5, and SSP 5-8.5 from seven global climate models (GCMs), statistically downscaled to 25-km resolution, was used to project the impacts of climate warming on ALT. Assuming ALT=K root TDD, the projections of UKESM1-0-LL GCM resulted in the largest projected ALT, up to about 0.7 m in 2080s under SSP5-8.5. Given that the mean observed ALT of the study sites is about 0.482 m, this implies that ALT will increase by 0.074 to 0.217 m (15% and 45%) in 2080s. This will have substantial impacts on Arctic infrastructure. The projected settlement Iset (cm) of 1 to 7 cm will also impact the infrastructure, especially by differential settlement due to the high spatial variability of ALT and soil moisture, given at local scale the actual thawing will partly depend on thaw sensitivity of the material and potential thaw strain, which could vary widely from location to location.

This study integrates a dynamic plant growth model with a three-dimensional (3D) radiative transfer model (RTM) for maize traits retrieval using high spatial-spectral resolution airborne data. The research combines the Discrete Anisotropic Radiative Transfer (DART) model with the Dynamic L-System-based Architectural maize (DLAmaize) growth model to simulate field reflectance. Comparison with the 1D RTM SAIL revealed limitations in representing row structure effects, field slope, and complex light-canopy interactions. Novel Global Sensitivity Analyses (GSA) were carried out using dependence-based methods to overcome limitations traditional variance-based approaches, enabling better characterization of hyperspectral sensitivity to changes in leaf biochemistry, canopy architecture, and soil moisture. GSA provided complementary results to assess estimation uncertainties of the proposed traits retrieval method across growth stages. A hybrid inversion framework combining DART simulations with an active learning strategy using Kernel Ridge Regression was implemented for traits estimation. The approach was validated using ground data and HyPlant-DUAL airborne hyperspectral images from two field campaigns in 2018 and achieved high retrieval accuracy of key maize traits: leaf area index (LAI, R2=0.91, RMSE=0.42 m2/m2), leaf chlorophyll content (LCC, R2=0.61, RMSE=3.89 mu g/cm2), leaf nitrogen content (LNC, R2=0.86, RMSE=1.13 x 10-2 mg/cm2), leaf dry matter content (LMA, R2=0.84, RMSE=0.15 mg/cm2), and leaf water content (LWC, R2=0.78, RMSE=0.88 mg/cm2). The validated models were used to generate two-date 10 m resolution maps, showing good spatial consistency and traits dynamics. The findings demonstrate that integrating 3D RTMs with dynamic growth models is suited for maize trait mapping from hyperspectral data in varying growing conditions.

Land-cover changes and new ecosystem trajectories in Interior Alaska have altered the structure and function of landscapes, with regional warming trends altering carbon and water cycling. Notably, these changes include the increased distribution of tall woody vegetation, trees and shrubs, in landscapes that historically only supported low shrub vegetation cover. In Denali National Park, Alaska, this phenomenon has altered primary succession pathways towards tundra ecosystems with the establishment and expansion of balsam poplar (Populus balsamifera) trees. In this study, we examine how snow, soil, and vegetation processes interact within this altered successional pathway towards further landscape change following glacial recession. In a sequence of outflow terraces, we found that variations in snow depth, functional soil depth, leaf area index, overstory height, and understory height were all significantly correlated with each other, with those effects largely explained by the presence of poplar. Poplar-dominated plots had deeper snowpacks, deeper functional soil depths, taller overstory and shrub heights, and greater LAI than in non-poplar plots of the same landscape age. These findings suggest a feedback cycle where the establishment of taller vegetation (here, poplar) alters ecosystem processes in the following notable ways: taller vegetation is able to trap more snow by reducing wind exposure and limiting sublimation; this snow provides water through additional snowmelt and insulation, keeping soils warmer and lessening permafrost development, leading to deeper functional soil depths. This feedback demonstrates poplar's ability to modify the environment as an ecosystem engineer, engineering a trajectory away from the otherwise expected permafrost-underlain tundra.

Bats are indispensable members of the natural world, supporting its delicate balance. Bats have vital roles in controlling insect populations and enhancing soil fertility. They also help in the harvesting and dispersal of seeds, pollination in plants, and nutrient recycling and distribution. However, through evolution over millions of years, they have also adapted their immune system so that they may carry numerous types of pathogens, the majority of which are viruses, without these pathogens having any serious ill effects on bats themselves. Their anatomical adaptation to flight and the reduced immune response to DNA damage during flight have also contributed to bats becoming reservoirs of deadly pathogenic diseases. This review discusses the different adaptations of bats with a special focus on the immune system that have helped them evolve as a reservoir for various viruses. The study also enumerates how the increase in global warming, the consequent changes in climatic conditions, habitat destruction, and bushmeat consumption increase the chances of an outbreak of novel zoonotic disease when humans come in contact with bats.

With Arctic amplification, hydrological conditions in Arctic permafrost regions are expected to change substantially, which can have a strong impact on carbon budgets. To date, detailed mechanisms remain highly uncertain due to the lack of continuous observational data. Considering the large carbon storage in these regions, understanding these processes becomes crucial for estimating the future trajectory of global climate change. This study presents findings from 8 years of continuous eddy-covariance measurements of carbon dioxide (CO2) and methane (CH4) fluxes over a wet tussock tundra ecosystem near Chersky in Northeast Siberia, comparing data between a site affected by a long-term drainage disturbance and an undisturbed control site. We observed a significant increasing trend in roughness lengths at both sites, indicating denser and/or taller vegetation; however, the increase at the drained site was more pronounced, highlighting the dominant impact of drainage on vegetation structure. These trends in aboveground biomass contributed to differences in gross primary production (GPP) between the two sites increasing over the years, continuously reducing the negative effect of the drainage disturbance on the sink strength for CO2. In addition, carbon turnover rates at the drained site were enhanced, with ecosystem respiration and GPP consistently higher compared to the control site. Because of the artificially lower water table depth (WTD), CH(4 )emissions at the drained site were almost halved. Furthermore, drainage altered the ecosystem's response to environmental controls. Compared to the control site, the drained site became slightly more sensitive to the global radiation (R-g), resulting in higher CO(2 )uptake under the same levels of R-g. Meanwhile, CH(4 )emissions at the drained site showed a higher correlation with deep soil temperatures. Overall, our findings from this WTD manipulation experiment show that changing hydrological conditions will significantly impact the Arctic ecosystem characteristics, carbon budgets, and ecosystem's response to environmental changes.

Coal mining has significant economic and environmental implications. The extraction and combustion of coal release harmful chemicals and dust, impacting air, soil, and water quality, as well as natural habitats and human health. This study aimed to investigate the association between global DNA methylation, DNA damage biomarkers (including telomere length), and inorganic element concentrations in the blood of individuals exposed to coal mining dust. Additionally, polycyclic aromatic hydrocarbons were analyzed. The study included 150 individuals exposed to coal mining and 120 unexposed controls. Results showed significantly higher global DNA hypermethylation in the exposed group compared to controls. Moreover, in the exposed group, micronucleus frequency and age showed a significant correlation with global DNA hypermethylation. Blood levels of inorganic elements, including titanium, phosphorus, sodium, aluminum, iron, sulfur, copper, chromium, zinc, chlorine, calcium, and potassium, were potentially associated with DNA methylation and oxidative damage, as indicated by comet assay results. Furthermore, exposure to polycyclic aromatic hydrocarbons such as fluoranthene, naphthalene, and anthracene, emitted in mining particulate matter, may contribute to these effects. These findings highlight the complex interplay between genetic instability, global DNA hypermethylation, and environmental exposure in coal mining areas, emphasizing the urgent need for effective mitigation strategies.

Alpine treelines ecotones are critical ecological transition zones and are highly sensitive to global warming. However, the impact of climate on the distribution of treeline trees is not yet fully understood as this distribution may also be affected by other factors. Here, we used high-resolution satellite images with climatic and topographic variables to study changes in treeline tree distribution in the alpine treeline ecotone of the Changbai Mountain for the years 2002, 2010, 2017, and 2021. This study employed the Geodetector method to analyze how interactions between climatic and topographic factors influence the expansion of Betula ermanii on different aspect slopes. Over the past 20 years, B. ermanii, the only tree species in the Changbai Mountain tundra zone, had its highest expansion rate from 2017 to 2021 across all the years studied, approaching 2.38% per year. In 2021, B. ermanii reached its uppermost elevations of 2224 m on the western aspects and 2223 m on the northern aspects, which are the predominant aspects it occupies. We also observed a notable increase in the distribution of B. ermanii on steeper slopes (> 15 degrees) between 2002 and 2021. Moreover, we found that interactions between climate and topographic factors played a more significant role in B. ermanii's expansion than any single dominant factor. Our results suggest that the interaction between topographic wetness index and the coldest month precipitation (Pre(1)), contributing 91% of the observed variability, primarily drove the expansion on the southern aspect by maintaining soil moisture, providing snowpack thermal insulation which enhanced soil temperatures, decomposition, and nutrient release in harsh conditions. On the northern aspect, the interaction between elevation and mean temperature of the warmest month explained 80% of the expansion. Meanwhile, the interaction between Pre(1) and mean temperature of the growing season explained 73% of the expansion on the western aspect. This study revealed that dominant factors driving treeline upward movement vary across different mountain aspects. Climate and topography play significant roles in determining tree distribution in the alpine treeline ecotone. This knowledge helps better understand and forecast treeline dynamics in response to global climate change.

Societal Impact StatementIntervention strategies that involve supplementing crop-lands with silicon have significant scope for carbon capture and drought mitigation, offering wide-ranging societal impacts. These include contributing to decarbonisation goals, enhancing food security, providing economic benefits and reducing environmental damage associated with intensive agronomic practices. This article highlights emerging evidence that suggests elevated atmospheric CO2 and water limitation may impair silicon accumulation in plants. While this does not negate the outlined societal benefits, we argue that these limitations must be thoroughly quantified and incorporated into large-scale implementation plans to ensure the reliability and effectiveness of silicon intervention strategies. Silicon accumulation in plants is increasingly recognised as playing an important functional role in alleviating environmental stresses. Most research to date has focussed on relieving agronomic stresses in crops, including pest and pathogen damage, soil salinity and drought. Recently, attention has turned to large-scale silicon application to agricultural landscapes as a potential anthropogenic climate change mitigation strategy. This includes silicon fertilisation to enhance soil carbon storage through advanced weathering of silicates, or by incorporating carbon in phytoliths in plant tissues. While these geoengineering approaches have potential, they could also present significant challenges. This article explores the opportunities and limitations for silicon-based interventions in mitigating the impacts of rising atmospheric carbon dioxide levels and increased incidences of drought. We argue that despite the promise of silicon supplementation in reducing plant stress under climate change, research paradoxically shows that these very climate conditions can significantly impede silicon accumulation in plants. We propose a framework to guide the development of silicon intervention strategies to mitigate climate change and the research questions that should be addressed to ensure their effectiveness under future environmental conditions.

Carbonaceous aerosol components (CACs) significantly influence global radiative forcing and human health. We developed a simultaneous inversion algorithm for four CACs: black carbon (BC), brown carbon (BrC), watersoluble organic matter (WSOM), and water-insoluble organic matter (WIOM), considering their distinct optical, solubility, and hygroscopicity properties. Using AERONET data, we inverted the global concentrations of these components for 2022. We observed that the mass concentration of black carbon (BC) is highest in the South Asian region, with an annual average of 4.74 mg m(-2). High values of brown carbon (BrC) correspond well with regions and seasons of biomass burning, with the annual average reaching 9.03 mg m(-2) at sites in Central and West Africa. Water-insoluble organic matter (WIOM) is the most predominant component in carbonaceous aerosols, with an annual average concentration as high as 53.11 mg m(-2) at the Dhaka_University site in Eastern South Asia. Additionally, the study also points out a significant correlation between the dominant components of carbonaceous aerosols and their seasonal variations with local emissions. Furthermore, the validation of optical parameters against official AERONET products demonstrates a good correlation.

Global warming is progressing more rapidly in the Arctic compared with other regions of the world, and the increasing temperature has caused gradual permafrost thaw, resulting in significant changes in hydrological processes. However, the quantitative contributions of different water sources to Arctic watersheds under ongoing climate change remain poorly understood. Therefore, this study aims to address this gap by applying a water isotope-based mixing model to better quantify the sources and pathways of water flow in permafrost-affected catchments. In this study, isotopic and chemical data were used to determine the water sources and flowpaths of the Sagavanirktok (Sag) River on the North Slope in Alaska (USA) in the summer of 2022. Results obtained using a Bayesian mixing model indicate that meltwater from permafrost ice wedges contributes 17.7% upstream and 22.2% downstream to the Sag River. At the upstream with a frozen active layer or transient layer (including seasonal intrasediment ice), lower active layer water (mineral-rich) and upper active layer water (organic-rich) accounted for 31.5% and 18.1%, respectively. By contrast, at the downstream, the contribution of active layer water was 26.9%, which was similar to that of the other sources. The sources and flowpaths of Arctic freshwater affect changes in the geochemical characteristics of the freshwater, which is channeled to the Arctic Ocean through major Arctic rivers. This study quantitatively assesses permafrost ice wedge melt in an Arctic basin and provides insights to facilitate investigations of hydrological processes and geochemical changes associated with climate change in Arctic water systems.