Understanding soil organic carbon (SOC) distribution and its environmental controls in permafrost regions is essential for achieving carbon neutrality and mitigating climate change. This study examines the spatial pattern of SOC and its drivers in the Headwater Area of the Yellow River (HAYR), northeastern Qinghai-Xizang Plateau (QXP), a region highly susceptible to permafrost degradation. Field investigations at topsoils of 86 sites over three summers (2021-2023) provided data on SOC, vegetation structure, and soil properties. Moreover, the spatial distribution of key permafrost parameters was simulated: temperature at the top of permafrost (TTOP), active layer thickness (ALT), and maximum seasonal freezing depth (MSFD) using the TTOP model and Stefan Equation. Results reveal a distinct latitudinal SOC gradient (high south, low north), primarily mediated by vegetation structure, soil properties, and permafrost parameters. Vegetation coverage and above-ground biomass showed positive correlation with SOC, while soil bulk density (SBD) exhibited a negative correlation. Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. These findings likely enhance the understanding of carbon storage controls in vulnerable alpine permafrost ecosystems and provide insights to mitigate carbon release under climate change.

Ensuring the accuracy of free-field inversion is crucial in determining seismic excitation for soil-structure interaction (SSI) systems. Due to the spherical and cylindrical diffusion properties of body waves and surface waves, the near-fault zone presents distinct free-field responses compared to the far-fault zone. Consequently, existing far-fault free-field inversion techniques are insufficient for providing accurate seismic excitation for SSI systems within the near-fault zone. To address this limitation, a tailored near-fault free-field inversion method based on a multi-objective optimization algorithm is proposed in this study. The proposed method establishes an inversion framework for both spherical body waves and cylindrical surface waves and then transforms the overdetermined problem in inversion process into an optimization problem. Within the multi-objective optimization model, objective functions are formulated by minimizing the three-component waveform differences between the observation point and the delayed reference point. Additionally, constraint conditions are determined based on the attenuation property of propagating seismic waves. The accuracy of the proposed method is then verified through near-fault wave motion characteristics and validated against real downhole recordings. Finally, the application of the proposed method is investigated, with emphasis on examining the impulsive property of underground motions and analyzing the seismic responses of SSI systems. The results show that the proposed method refines the theoretical framework of near-fault inversion and accurately restores the free-field characteristics, particularly the impulsive features of near-fault motions, thereby providing reliable excitation for seismic response assessments of SSI systems.

This study highlights the results of a palaeoecological analysis conducted on five permafrost peatlands in the northern tundra subzone along the Barents Sea coast in the European Arctic zone. The depth of the peat cores that were sampled was approximately 2 m. The analysis combined data on the main physical and chemical soil properties, radiocarbon dating, botanical composition, and mass fraction of polycyclic aromatic hydrocarbons (PAHs). The concentrations of 16 PAHs in peat organic layers ranged from 140 to 254 ng/g, with an average of 182 ng/g. The peatlands studied were dominated by PAHs with a low molecular weight: naphthalene, phenanthrene, fluoranthene, pyrene, chrysene. The vertical distribution patterns of PAHs along the peat profile in the active layer and permafrost were determined. PAHs migrating down the active layer profile encounter the permafrost barrier and accumulate at the boundary between active layer and permafrost layer. The deep permafrost layers accumulate large amounts of PAHs and PAH derivatives, which are products of lignin conversion during the decomposition of grassy and woody vegetation during the Holocene climate optima. The total toxic equivalency concentration (TEQ) was calculated. Peatlands from the Barents Sea coast have low toxicity for carcinogenic PAHs throughout the profile. TEQ ranged from a minimum of 0.1 ng/g to a maximum of 13.5 ng/g in all peatlands investigated. For further potential use in Arctic/sub-Arctic environmental studies, PAH indicator ratios were estimated. In all investigated sections and peatland horizons, the most characteristic ratios indicate the petrogenic (natural) origin of PAHs.

Thawing permafrost alters climate not only through carbon emissions but also via energy-water feedback and atmospheric teleconnections. This review focuses on the Tibetan Plateau, where strong freeze-thaw cycles, intense radiation, and complex snow-vegetation interactions constitute non-carbon climate responses. We synthesize recent evidence that links freeze-thaw cycles, ground heat flux dynamics, and soil moisture hysteresis to latent heat feedback, monsoon modulation, and planetary wave anomalies. Across these pathways, both observational and simulation studies reveal consistent signals of feedback amplification and nonlinear threshold behavior. However, most Earth system models underrepresent these processes due to simplifications in freezethaw processes, snow-soil-vegetation coupling, and cross-seasonal memory effects. We conclude by identifying priority processes to better simulate multi-scale cryosphere-climate feedback, especially under continued climate warming in high-altitude regions.

Hypochlorite (ClO-) is a highly reactive chemical extensively used in households, public areas, and various industries due to its multiple functions of disinfection, bleaching, and sterilization. However, overuse of ClO- may contaminate the water, soil, air and food, leading to negative impacts on the environments, ecosystems and food safety. Meanwhile, excessive ClO- in human body can also cause severe damage to the immune system. Thus, the development of effective and precise detection tools for ClO- is of great significance to better understand its complicated roles in environments and biosystems. Herein, a new high-performance ratiometric fluorescent probe 2-amino-3-((10-propyl-10H-phenothiazin-3-yl)methylene)-amino)maleonitrile (PD) was developed for effective detection of ClO- in various bio/environmental and food samples. Probe PD exhibits highly-specific ratiometric fluorescent response to ClO- with rapid response (< 1 min), excellent sensitivity (detection limit, 47.4 nM), wide applicable pH range (4 -12), and excellent versatility in practical applications. In practical applications, PD enables the sensitive and quantitative detection of ClO- levels in various water samples, bio-fluids, dairy products, fruits and vegetables with high-precision (recoveries, 97.00 -104.40 %), as well as the successful application for visual tracking ClO- in fresh fruits and vegetables. Furthermore, test strips containing PD offer a visual and convenient tool for quick identification of ClO- in aqueous media by the naked eye. Importantly, the good biocompatibility of PD enables its practical applications in real-time bioimaging of endogenous/exogenous ClO- levels in living cells, bacteria, onion cells, Arabidopsis, as well as zebrafish. This study provided an effective method for visual monitoring and bioimaging of ClO- levels in various environments, foods and living biosystems.

CONTEXT: Policy issues in most nations include adapting primary agricultural production to reduce greenhouse gas (GHG) emissions. Commitments have been established through multi-lateral agreements targeting GHG emission reductions to abate climate change impacts. In response to policy initiatives targeted at industries such as agriculture, producers are adopting innovative production methods and technologies to provide environmental services and mitigate emissions. GHG emissions arising from livestock production contribute to a damaging narrative surrounding agriculture, particularly beef production. OBJECTIVE: The purpose of this study is three-fold, quantifying (a) net emissions,2 (b) changes in practice, and (c) economic outcomes attributed to the forage production facet of cow-calf production. METHODS: The Saskatchewan Forage Production Survey was developed to gather forage management practices data, placing emphasis on land use and land management changes. Canada's whole-farm assessment model, Holos, was applied as a carbon accounting framework to derive the net emissions of the forage production cycle. RESULTS AND CONCLUSIONS: Results indicate carbon sequestration increased between the periods of 1991-94 and 2016-19. Gross emissions decreased to a larger degree and net emission results for the forage production facet of the Saskatchewan cow calf sector are -0.123 Mg CO2e/ha/yr in 2016-19. SIGNIFICANCE: Recommendations include the renewal of forage rejuvenation funding programs that may improve forage yields and carbon sequestration potential. Further, the expansion of term conservation easement programs to include non-native forage lands is recommended to incentivize the retention of forage land.

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.

This study evaluated the usability and effectiveness of robotic platforms working together with foresters in the wild on forest inventory tasks using LiDAR scanning. Emphasis was on the Universal Access principle, ensuring that robotic solutions are not only effective but also environmentally responsible and accessible for diverse users. Three robotic platforms were tested: Boston Dynamics Spot, AgileX Scout, and Bunker Mini. Spot's quadrupedal locomotion struggled in dense undergrowth, leading to frequent mobility failures and a System Usability Scale (SUS) score of 78 +/- 10. Its short, battery life and complex recovery processes further limited its suitability for forest operations without substantial modifications. In contrast, the wheeled AgileX Scout and tracked Bunker Mini demonstrated superior usability, each achieving a high SUS score of 88 +/- 5. However, environmental impact varied: Scout's wheeled design caused minimal disturbance, whereas Bunker Mini's tracks occasionally damaged young vegetation, highlighting the importance of gentle interaction with natural ecosystems in robotic forestry. All platforms enhanced worker safety, reduced physical effort, and improved LiDAR workflows by eliminating the need for human presence during scans. Additionally, the study engaged forest engineering students, equipping them with hands-on experience in emerging robotic technologies and fostering discussions on their responsible integration into forestry practices. This study lays a crucial foundation for the integration of Artificial Intelligence (AI) into forest robotics, enabling future advancements in autonomous perception, decision-making, and adaptive navigation. By systematically evaluating robotic platforms in real-world forest environments, this research provides valuable empirical data that will inform AI-driven enhancements, such as machine learning-based terrain adaptation, intelligent path planning, and autonomous fault recovery. Furthermore, the study holds high value for the international research community, serving as a benchmark for future developments in forestry robotics and AI applications. Moving forward, future research will build on these findings to explore adaptive remote operation, AI-powered terrain-aware navigation, and sustainable deployment strategies, ensuring that robotic solutions enhance both operational efficiency and ecological responsibility in forest management worldwide.

Terrestrial ecosystems, account for approximately 31% of the global land area and play a significant role in the biogeochemical cycling of toxic elements. Previous studies have explored the spatial patterns, effects, and drivers of toxic elements along urban gradients, agricultural lands, grasslands, and mining sites. However, the elevational patterns of toxic elements in montane ecosystems and the underlying drivers remain largely unknown. Atmospheric deposition is a crucial pathway through which toxic elements accumulate along terrestrial elevational gradients. The accumulation of toxic elements exhibited seasonal variability along elevational gradients, with higher deposition occurring in summer and winter. Approximately 46.77% of toxic elements (e.g. Hg) exhibited increasing trends with elevation, while 22.58% demonstrated decreasing patterns (Ba, Co). Furthermore, 8.06% displayed hump-shaped distributions (Ag), and 22.58% showed no distinct patterns (As and Zn). The accumulation of these elements is influenced by several key factors, including atmospheric deposition (26.56%), anthropogenic activities (14.11%), and precipitation (10.37%) primarily via wet deposition of atmospheric pollutants. The accumulation of toxic elements threatens terrestrial biodiversity by disrupting food chains, altering community structures, and causing individual mortality. These disruptions also pose risks to human health through contaminated food sources and food webs, potentially leading to health issues like cancer, organ damage, and reproductive challenges. This review offers key insights into the factors affecting the accumulation and distribution of toxic elements along elevation gradients. It also lays the groundwork for further study on how toxic elements impact ecosystem functions, which is crucial for protecting biodiversity under climate change.

Freeze-thaw-induced N2O pulses could account for nearly half of annual N2O fluxes in cold climates, but their episodic nature, sensitivity to snow cover dynamics, and the challenges of cold-season monitoring complicate their accurate estimation and representation in global models. To address these challenges, we combined in situ automated high-frequency flux measurements with cross-ecoregion soil core incubations to investigate the mechanisms driving freeze-thaw-induced N2O emissions. We found that deepened snow significantly amplified freeze-thaw N2O pulses, with these similar to 50-day episodes contributing over 50% of annual fluxes. Additionally, freeze-thaw-induced N2O pulses exhibited significant spatial heterogeneity, ranging from 3.4 to 1184.1 mu g N m(-2) h(-1) depending on site conditions. Despite significant spatiotemporal variation, our results indicated that 68%-86% of this variation can be explained by shifts in controlling factors: from water-filled pore space (WFPS), which drove anaerobic conditions, to microbial constraints as snow depth increases. Below 43% WFPS, soil moisture was the overwhelmingly dominant driver of emissions; between 43% and 66% WFPS, moisture and microbial attributes (including denitrifying gene abundance, nitrogen enzyme kinetics, and microbial biomass) jointly triggered N2O emissions pulses; above 66% WFPS, microbial attributes, particularly nitrogen enzyme kinetics, prevailed. These findings suggested that maintaining higher soil moisture served as a trigger for activating microbial activity, particularly enhancing nitrogen cycling. Furthermore, we showed that hotspots of freeze-thaw-induced N2O emissions were linked to high root production and microbial activity in cold and humid grasslands. Overall, our study highlighted the hierarchical control of WFPS and microbial processes in driving freeze-thaw-induced N2O emission pulses. The easily measurable WFPS and microbial attributes predictable from plant and soil properties could forecast the magnitude and spatial distribution of N2O emission hot moments under changing climate. Integrating these hot moments, particularly the dynamics of WFPS, into process-based models could refine N2O emission modeling and enhance the accuracy of global N2O budget prediction.