Abstract Increasing Arctic rainfall significantly impacts snow and ice processes, land runoff, and the ecological environment. However, the extent to which the rainfall increase is regionally dependent and how it responds to the large retreat of sea ice remains inadequately understood. This study quantifies the Arctic land rainfall increases attributable to sea ice loss under 2°C global warming using multi‐ensemble experiments combining all forcing with sea ice loss forcing. The findings indicate that sea ice retreat is responsible for 16% of the increase in summer Arctic land rainfall, with significant increases covering 46% of the region responses to 2°C warming. The most pronounced responses were observed along the Arctic coasts of Siberia and North America. Local warming caused by sea ice retreat contributes 68% of the rainfall increase, while the remainder results from the increase in total precipitation.

Plant growth and survival are fundamentally constrained by water transport from roots to leaves, impacting carbon assimilation and associated labile carbon pools. However, physiological constraints on growth and survival vary with plant age, due to changes in metabolic sinks and increases in hydraulic path length from rhizosphere to canopy. We investigated crown dieback, growth, hydraulics, carbon assimilation and nonstructural carbohydrate (NSC) storage in relation to increasing basal diameter of two dominant shrub species (Caragana korshinskii and Artemisia ordosica) at the southeastern edge of the Tengger Desert, China. The aim was to identify mechanisms of decreased performance with plant size in dryland shrubs. Clear contrasts in stomatal regulation of leaf water potentials were detected between species. Despite these contrasts, radial growth, hydraulic transport efficiency (Ks), and carbon assimilation similarly declined in both species with increasing plant size, while NSC reserves remained unchanged. Xylem embolism (percentage loss of conductivity) increased with plant size, resulting in significant reductions in carbon assimilation in both species. Results indicate that hydraulic and potentially carbon assimilation constraints, rather than NSC depletion, govern growth-related dryland shrub decline. These findings improve our understanding of how population demography impacts dryland forest response to climate change.

ABSTRACTAngelica sinensis plants suspected of virus infection were collected from Gansu Province, China, and small RNA sequencing was used to identify the causal agent of the symptoms. Alfalfa mosaic virus (AMV) was found to be present, and reverse transcription‐quantitative PCR (RT‐qPCR) was used to confirm that 10% of the symptomatic plants were infected. Fourteen days after AMV inoculation, transcriptomic analyses showed that the anthocyanin, flavone and flavonol biosynthesis pathways were up‐regulated in the leaves of A. sinensis. Proteomic analyses showed that the up‐regulated proteins in leaves inoculated with AMV were mainly concentrated in the phenylpropanoid biosynthesis pathway and the peroxidase structural domain. Fifteen proteins (genes) were jointly up‐regulated, enriched for the molecular function GO term oxidoreductase activity, acting on NAD(P)H and oxidoreductase activity, and the subcellular localisation of the differential genes was mainly concentrated in the cytoplasm and chloroplast. Differentially expressed genes were enriched in pathways such as phytopathogen interaction and phenylpropane biosynthesis in roots 35 days after AMV inoculation compared to healthy controls. F5H, CHIL, CCoAOMT, COMT and CCR genes related to ferulic acid metabolism were significantly down‐regulated in expression, and four MYB transcription factor genes related to the biosynthetic pathway of phenylpropanes were significantly up‐regulated. These results provide insight into the mechanisms of AMV infection and may be helpful for the cultivation of new A. sinensis varieties with high ferulic acid content.

ABSTRACTThe offshore Bengal Basin experienced sedimentation due to the interaction between the Indo‐Asian collision and the amalgamation of Indo‐Burma. To infer the provenance, paleoweathering and tectonic evolution of the Neogene sedimentary rocks from the Sangu Gas Field in the Bay of Bengal, Bangladesh, this study presents a new set of whole‐rock geochemical and detrital zircon U–Pb data. Major and trace element geochemistry indicates that these Neogene sediments originated from an active continental margin (ACM) tectonic environment associated with the recycled orogen, aligning well with the sandstones' quartz‐feldspar‐lithic composition. The geochemical characteristics and elemental ratios of the Neogene sedimentary rocks [e.g., Eu/Eu* (0.55–0.58), (La/Lu)N (9.2–10.0), La/Sc (2.30–3.98) and (La/Yb)N (8.46–10.03)], indicate a primary origin from felsic source rocks. The source rocks are dominantly granites that had undergone mild to moderate chemical weathering. The U–Pb ages of the Pliocene Tipam Group and the Miocene Surma Group range from 22.49 to 2794.45 and 28.04 to 3168.21 Ma, respectively. The sandstones of the Tipam and Surma groups exhibit a notable zircon age peak at around 440–620 Ma, which bears similarities to the Tethyan Himalaya (TH), Upper Lesser Himalaya (ULH) and Indo‐Burman Ranges (IBR). The secondary peaks at ~1500–2000 Ma correspond to the Lesser Himalaya (LH) ages. The additional subordinate peaks at ~700–1200 Ma reflect the age of the Higher Himalaya (HH). The notable increase in the younger detrital zircon (< 200 Ma) populations was observed in the Tipam Group samples (~22%). These additional young zircons were possibly derived from the recycled Paleogene arc of the Indo‐Burma Ranges that might have originated from the Burma magmatic arc.

Soil microbial communities play vital roles in driving ecosystem restoration. However, understanding of the successional dynamics of abundant and rare bacterial subcommunities and their relationships with ecosystem multifunctionality during restoration, particularly in desertified ecosystems, remains limited. Here, we examined the succession of abundant, intermediate, and rare bacterial subcommunities over a 53-year restoration chronosequence following the implementation of straw checkerboard barriers in the Tengger Desert, China. Our findings revealed that the establishment of straw checkerboard barriers significantly increased the richness of abundant, intermediate, and rare taxa over time. However, our results indicated a divergence in ecological processes underpinning the successional dynamics of soil bacterial communities. Stochastic processes and homogeneous selection primarily governed the assembly of abundant and rare subcommunities, respectively, as evidenced by fundamental differences in their niche breadth. More importantly, we further uncovered a dual mechanism underlying the relationships between soil bacterial communities and ecosystem multifunctionality. Abundant taxa were integrally associated with multiple nutrient cycling-related functions simultaneously, likely mediated through coordinated environmental responses or potential interspecies connections, whereas rare taxa were more linked to individual functions independently. These findings deepen our understanding of the successional dynamics of soil microbial communities and the microbe-ecosystem multifunctionality relationships in desert restoration.

ABSTRACT Forest mean canopy height (CMH) and aboveground biomass (AGB) are key indicators of forest ecosystem productivity. However, in high-altitude mountainous areas, complex topography and limited field data make accurate assessments challenging. This study was conducted in the Taohe National Nature Reserve, Gansu Province, China. The Sentinel-2 imagery and DEM were fused to estimate the AGB and CMH using four machine learning algorithms: random forest (RF), XGBoost, CatBoost, and multilayer perceptron. The stratified sampling was used to reduce the underestimation of high AGB values and overestimation of low AGB values in RF training. Results show that the RF model had the best estimation effect on AGB (R² = 0.6612), and the CatBoost model had the best estimation effect on CMH (R² = 0.7394). SHapley additive exPlanations (SHAP) analysis revealed that slope aspect was the greatest impact on CMH, whereas the Sentinel-2 blue band (B2) had the greatest impact on AGB. CMH plays an important role in improving the accuracy of AGB estimation. Based on the optimal model, AGB and CMH maps with a resolution of 10 m were generated, revealing a clear east–west biomass gradient. This study highlights the effectiveness of combining machine learning with SHAP-based interpretability for forest monitoring in complex mountainous environments.

Isolated permafrost is widely distributed in freeze–thaw transition zones, characterized by blurred boundaries and strong spatial variability. Traditional methods such as drilling and electrical resistivity surveys are often limited in achieving efficient and continuous boundary identification. This study focuses on a typical isolated permafrost region in Northeast China and proposes a boundary detection strategy based on multi-frequency electromagnetic (EM) measurements using the GEM-2 sensor. By designing multiple frequency combinations and applying joint inversion, a boundary identification framework was developed and validated against borehole data. Results show that the multi-frequency joint inversion method improves the spatial identification accuracy of permafrost boundaries compared to traditional point-based techniques. In areas lacking boreholes, the method still demonstrates coherent boundary imaging and strong adaptability to geomorphological conditions. The multi-frequency joint inversion strategy significantly enhances imaging continuity and effectively captures electrical variations in complex freeze–thaw transition zones. Overall, this study establishes a complete non-invasive technical workflow—“acquisition–inversion–validation–imaging”—providing an efficient and scalable tool for engineering site selection, foundation design, and permafrost degradation monitoring. It also offers a methodological paradigm for electromagnetic frequency optimization and subsurface electrical boundary modeling.