Recent climate warming has accelerated permafrost thaw and dynamics of thermokarst lakes (TLs) on the Tibetan Plateau (TP). Yet, owing to the lack of long-term monitoring of TLs, our understanding of lake evolution processes and their driving factors remains uncertain. Here, using the global surface water product and timeseries Landsat imagery, we identified 58,538 TLs (0.01-3 km2) and determined the primary occurrence year of lake changes from 1990 to 2022. Our results indicated that TLs on the TP are primarily located in the central inland region, over 82 % of lakes experienced area expansion, and only 15 % in the northwest show decrease in area. Annual number of lake expansion peaked in 2016, whereas lake shrinkage was most common in 2019. The calculated lake area errors, field investigations, and validation of lake disturbance time demonstrated high accuracy and consistency. We applied the optimal machine learning regression model to distinguish the different drivers for lake expansion and shrinkage. The topographic and climatic factors are primary drivers for lake expansion, while differences in evaporation trend and soil temperature trend might contribute to lake shrinkage. This study highlights the vulnerability of permafrost on the TP to climate change, which can contribute to carbon sequestration estimation and infrastructure maintenance.

Near-surface temperature and moisture are key boundary conditions for simulating permafrost distribution, projecting its response to climate change, and evaluating the surface energy balance in alpine regions. However, in desertified permafrost zones of the Qinghai-Tibet Plateau (QTP), the observations remain sparse, and reported trends vary considerably among sites. This lack of consistent evidence limits the ability to represent microenvironmental processes in models and to predict their influence on permafrost stability. From September 2021 to August 2024, we conducted continuous observations at a desertified permafrost site on the central QTP, covering the vertical range from 150 cm above to 100 cm below the ground surface (boundary layer). Measurements included air and ground temperature, air humidity, soil moisture, wind speed, and net radiation. Results showed that the mean annual air temperature increased with decreasing height at a gradient of approximately 0.42 degrees C/m, while mean annual air humidity remained nearly constant at 56.8 +/- 1.1 % (150-0 cm). In the near-surface soil layer (0 similar to -10 cm), temperature rose by 3.6 +/- 0.1 degrees C and moisture decreased by 34.0 +/- 2.7 %. The mean annual ground temperature increased with depth at a rate of about 0.55 degrees C/m, whereas soil moisture decreased between -20 and -60 cm (52.86 %/m) and increased between -60 and -100 cm (56.30 %/m). Seasonal patterns showed marked difference: in the freezing season, the calculated total temperature increment within the boundary layer (1.91 degrees C) was 61 % lower than the observed value (4.88 degrees C), while in the thawing season, it was 58 % higher (4.38 degrees C > 2.77 degrees C). These results reveal strong vertical gradients and seasonal contrasts in thermal and moisture regimes, emphasizing the need to integrate coupled temperature-moisture processes into boundary layer parameterizations for cold-region environments. Improved representations can enhance permafrost modeling and inform infrastructure design in regions experiencing both warming and desertification.

Aerosols over the Tibetan Plateau (TP) strongly influence regional climate and hydrological cycles. Here we investigate the size-resolved microphysical and optical properties of aerosols in an urban area of the northern TP using a tandem system of a differential mobility analyzer, a condensation particle counter, and a single particle soot photometer. Under the 2021 summer conditions, the average particle number size distribution follows a lognormal pattern, peaking at similar to 70 nm. Refractory black carbon (rBC) aerosols constitute 17.7% of the total particle population in the 100-750 nm mobility diameter (D-mob) range, with their proportion rising to over 50% for D-mob > 500 nm. Most rBC particles are externally mixed, while only 12.2% are thickly coated with non-refractory materials. Externally mixed rBC particles show strong non-sphericity, with a dynamic shape factor increasing from 1.8 at 115 nm to 2.8 at 750 nm, consistent with aggregate structures. In contrast, thickly coated rBC particles are nearly spherical, with coating thickness increasing with size. The total rBC mass estimated from size-resolved measurements closely matches bulk rBC mass directly measured. rBC-free particles exhibit slight non-sphericity, with shape factor positively correlated with refractive index, likely due to dust contributions. Bulk scattering coefficients derived from size-resolved data match those estimated under the well-mixed spherical assumption. However, the later scheme-lacking observational constraints on morphology and mixing state-overestimates absorption by over a factor of three, thereby underestimating the single-scattering albedo. These results provide key constraints for improving aerosol radiative forcing estimates and advancing understanding of aerosol-climate interactions over the TP.

The Three-Rivers Headwater Region (TRHR) is located on the Tibetan Plateau, within a transitional zone between seasonally frozen ground and continuous permafrost. Over 70 % of the region is predominantly covered by alpine grasslands, a vulnerable ecosystem increasingly threatened by ongoing permafrost degradation. This study utilized satellite data to analyze permafrost degradation by measuring active layer thickness (ALT) and the soil non-frozen period (NFP), and to investigate their impacts on alpine grassland growth. Results showed significant permafrost degradation from 2000 to 2020, with ALT thickening at a rate of 7.79 cm/decade (p < 0.05) and NFP lengthening by 1.1 days/yr (p < 0.05). Simultaneously, grassland vegetation exhibited a significant greening trend (0.0014 yr(-1), p < 0.01). Using the partial least squares (PLS) regression method, the study evaluated the relationships between grassland dynamics and permafrost degradation, while jointly accounting for climate variables (temperature, precipitation, and sunshine duration). ALT thickening was the dominant explanatory variable for grassland growth in 11.09 % of the region, and it was positively correlated in relatively cold western and alpine areas, but negatively correlated in the relatively warm eastern and central regions. NFP extension was the dominant explanatory variable for grassland growth in 10.38 % of the region, although its positive correlation weakened as climate conditions transitioned from relatively cold-dry to relatively warm-wet. Although permafrost degradation was positively correlated with grassland greening in relatively cold regions, the diminishing benefit of NFP extension and the adverse effects of ALT thickening may increasingly undermine grassland stability in relatively warm regions under further climate warming.

The Tibetan Railway has introduced pressures on the fragile grassland ecosystems of the Tibetan Plateau. However, the impact of the railway on the carbon sequestration remains unclear, as existing studies primarily focus on in-situ vegetation observations. In this study, we extracted the start and end of the growing season (SOS, EOS) and maximum daily GPP (GPPmax) along the railway corridor from the satellite-derived Gross Primary Productivity (GPP) data, and quantified the extent and intensity of the railway's disturbance on these indicators. We further employed the Statistical Model of Integrated Phenology and Physiology (SMIPP) to translate these disturbances into annual cumulative GPP (GPPann). Results show that Tibetan Railway significantly influences grassland within 50-meters, causing earlier SOS (0.1086 d m-1), delayed EOS (0.0646 d m-1), and reduced GPPmax (0.0069 gC m-2 d-1 m-1) as the distance to the railway gets closer. The advanced SOS and delayed EOS contributed gains of 28.82 and 104.26 MgC y-1, but reduction in GPPmax accounted for a loss of 2952.79 MgC y-1. Railway-induced phenology-physiology trade-off causes GPPann loss of 2819.71 MgC y-1. This study reveals Tibetan Railway's impact on grassland carbon cycling, offering insights for grassland conservation and sustainable transportation infrastructure projects.

The depth of the soil freezing front serves as an integrated indicator of land-atmosphere interactions during the freezing period and plays a critical role in regulating the hydrological cycle, ecological processes, and regional climate on the Qingzang Plateau (QP). While previous studies have primarily focused on interannual variations in the annual maximum freezing depth, limited attention has been paid to the spatiotemporal dynamics of the soil freezing front throughout the freezing season. In this study, we simulated the spatiotemporal variations of the soil freezing front on the QP during the freezing period using the optimal model selected from three machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM), and Multilayer Perceptron (MLP). The results demonstrated that RF outperforms MLP and SVM in accurately simulating the depth of the soil freezing front (R2 = 0.81, RMSE = 28.09 cm, MAE = 18.02 cm). Spatially, the soil freezing front during the freezing period was deeper in the west and north and shallower in the east and south. From 1983 to 2019, both permafrost and seasonally frozen ground regions across the QP exhibited statistically significant declines in soil freezing front depth. From October to November, freezing depth decreases faster in permafrost than in seasonally frozen ground, whereas from December to January it decreases faster in seasonally frozen ground than in permafrost. A comparison between the sub-periods 1983-2000 and 2001-2019 reveals a marked acceleration in the reduction of freezing depth. Additionally, the influence of air temperature on the freezing front is modulated by its depth. The elevation effect is weak in October, strengthens to a predominantly negative influence in November-December, and becomes nonlinear in January, with the strongest negative impact at mid-high elevations and a weaker effect at the highest elevations.

Correlations between the mechanical properties and surface scratch resistance of polylactic acid (PLA) are investigated via tensile and scratch tests on samples after degradation in soil for various times. The results show that the tensile yield strength of PLA is inversely proportional to the natural logarithm of the degradation time, and the scratch resistance and fracture toughness of PLA and the temperature rise near the indenter all increase and then decrease. The surface crystallinity of PLA also increases and then decreases, indicating that it and the scratch resistance are closely related. These findings provide useful information about how PLA behaves under degradation conditions. (c) 2025 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/).

The root-knot nematode, Meloidogyne javanica, is one of the most damaging plant-parasitic nematodes, affecting chickpea and causing substantial yield losses worldwide. The damage potential and population dynamics of this nematode in chickpea in Ethiopia have yet to be investigated. In this study, six chickpea cultivars were tested using 12 ranges of initial population densities (Pi) of M. javanica second-stage juveniles (J2): 0, 0.125, 0.25, 0.5, 1, 2, 4, 8, 16, 32, 64 and 128 J2 (g dry soil)-1 in a controlled glasshouse pot experiment. The Seinhorst yield loss and population dynamics models were fitted to describe population development and the effect on different measured growth variables. The tolerance limit (TTFW) for total fresh weight ranged from 0.05 to 1.22 J2 (g dry soil)-1, with corresponding yield losses ranging from 31 to 64%. The minimum yield for seed weight (mSW) ranged from 0.29 to 0.61, with estimated yield losses of 71 and 39%. The 'Haberu' and 'Geletu' cultivars were considered good hosts, with maximum population densities (M) of 16.27 and 5.64 J2 (g dry soil)-1 and maximum multiplication rate (a) values of 6.25 and 9.23, respectively. All other cultivars are moderate hosts for M. javanica; therefore, it is crucial to initiate chickpea-breeding strategies to manage the tropical root-knot nematode M. javanica in Ethiopia.

Understanding changes in water balance and land-atmosphere interaction under climate change is crucial for managing water resources in alpine regions, especially in the Qinghai-Tibet Plateau (QTP). Evapotranspiration (ET), a key process in the land-atmosphere interaction, is influenced by permafrost degradation. As the active layer in permafrost regions deepens due to climate warming, the resulting shifts in surface hydrologic connectivity and water storage capacity affect vegetation's ability to access water, thereby influencing its growth and regulating ET dynamics, though the full complexity of this process remains unclear. This study employs the Budyko-Fu model to assess the spatiotemporal dynamics of ET and the ET ratio (the ratio of ET to precipitation) on the QTP from 1980 to 2100. While ET shows a continuous upward trend, the ET ratio exhibits a non-monotonic pattern, increasing initially and then decreasing. More than two-thirds of permafrost areas on the QTP surpassed the critical ET ratio threshold by 2023, under three emission scenarios. By 2100, nearly all areas are projected to reach the tipping point, with 97 % affected under the SSP5-8.5 scenario. Meadow and steppe regions are expected to encounter this threshold earlier, whereas forested areas will be less affected, with over 80 % unlikely to reach the tipping point by 2100. Basin-level differences are notable: nearly 90 % of the Qaidam basin exceeded the threshold before 2023, compared to less than 50 % in the Yangtze basin. By 2100, more than 80 % of regions in all basins are expected to cross the tipping point due to ongoing permafrost degradation. This study advances understanding of land-atmosphere interactions in alpine regions, providing critical insights for water resource management and improving extreme weather predictions.

Vegetation greening across the Tibetan Plateau, a critical ecological response to climate warming and land-cover change, affects soil hydrothermal regimes, altering soil moisture (SM) and soil temperature (ST) dynamics. However, its effects on SM-ST coupling remain poorly understood. Using integrated field measurements from a vegetation-soil (V-S) network, reanalysis, and physics-based simulations, we quantify responses of SM, ST, and their coupling to vegetation changes across the Upper Brahmaputra (UB) basin, southern Tibetan Plateau. Results show that strong positive SM-ST correlations occur throughout 0-289 cm soil layers across the basin, consistent with the monsoon-driven co-occurrence of rainy and warm seasons. Spatially, SM-ST coupling strength exhibits pronounced spatial heterogeneity, demonstrating strongest coupling in central basin areas with weaker intensities in eastern and western regions. Overall, vegetation greening consistently induces soil warming and drying: as leaf area index (LAI) increases from 20 % to 180 % of its natural levels, SM (0-160 cm) declines by 15 % to 29 % due to enhanced evapotranspiration and root water uptake. Mean ST simultaneously increases by 1.4 +/- 0.9 degrees C. Crucially, sparsely vegetated regions sustain warming (1.4-2.1 degrees C), while densely vegetated areas transition from initial warming to gradual cooling. These findings advance our understanding of soil hydrothermal dynamics and their broader environmental impacts, improving climate model parameterizations and informing sustainable land management strategies in high-altitude ecosystems.