Soil erosion can be effectively controlled through vegetation restoration. Specifically, roots combine with soil to form a root-soil complex, which can effectively enhance soil shear strength and play a crucial role in soil reinforcement. However, the relationship between root mechanical traits and chemical compositions and shear performance and reinforcing capacity of soil is still inadequate. In this study, we determined the root chemical properties, performed root tensile tests and root-soil composite triaxial tests using two plants-one with a fibrous root system (ryegrass, Lolium perenne L.) and the other with a tap root system (alfalfa, Medicago sativa L.)-and calculated the factor of safety (FOS). The results revealed that the relationship between root diameter and tensile strength differed among different root characters. Holocellulose content and cellulose content were the main factors controlling the root tensile strength of ryegrass and alfalfa, respectively. The shear properties of the root-soil complex (cohesion (c) and internal friction angle (phi)) are correlated with soil water content (SWC) and root mass density (RMD). Root traits had a more substantial effect on c than phi, with significant differences in c between ryegrass and alfalfa at 7 % and 11 % SWC. The root-soil complex had an optimum RMD, and the maximum increase rates of c were 80.57 % and 34.4 %, respectively. Along slopes, sliding first occurs at the foot of the slope, thus demanding emphasis on protection and reinforcement. On steep gradients with low SWC, ryegrass strongly contributes to soil reinforcement, whereas alfalfa is more effective on gentle gradients with high SWC. The results provide scientific references for species selection for vegetation restoration in the Loess Plateau and a deeper understanding of the mechanical mechanism of soil reinforcement by roots.

Forests are increasingly impacted by climate change, affecting tree growth and carbon sequestration. Tree-ring width, closely related to tree growth, is a key climate proxy, yet models describing ring width or growth often lack comprehensive environmental data. This study assesses ERA5-Land data for tree-ring width prediction compared to automatic weather station observations, emphasizing the value of extended and global climate data. We analyzed 723 site-averaged and detrended tree-ring chronologies from two broadleaved and two gymnosperm species across Europe, integrating them with ERA5-Land climate data, CO2 concentration, and a drought index (SPEI12). A subset was compared with weather station data. For modelling interannual variations of tree-ring width we used linear models to assess parameter importance. ERA5-Land and weather-station-based models performed similarly, maintaining stable correlations and consistent errors. Models based on meteorological data from weather stations highlighted SPEI12, sunshine duration, and temperature extremes, while ERA5-Land models emphasized SPEI12, dew-point temperature (humidity), and total precipitation. CO2 positively influenced the growth of gymnosperm species. ERA5-Land facilitated broader spatial analysis and incorporated additional factors like evaporation, snow cover, and soil moisture. Monthly assessments revealed the importance of parameters for each species. Our findings confirm that ERA5-Land is a reliable alternative for modeling tree growth, offering new insights into climate-vegetation interactions. The ready availability of underutilized parameters, such as air humidity, soil moisture and temperature, and runoff, enables their inclusion in future growth models. Using ERA5-Land can therefore deepen our understanding of forest responses to diverse environmental drivers on a global scale.

Soil-plant-atmosphere interaction (SPAI) plays a significant role on the safety and serviceably of geotechnical infrastructure. The mechanical and hydraulic soil behaviour varies with the soil water content and pore water pressures (PWP), which are in turn affected by vegetation and weather conditions. Focusing on the hydraulic reinforcement that extraction of water through the plant roots offers, this study couples advances in ecohydrological modelling with advances in geotechnical modelling, overcoming previous crude assumptions around the application of climatic effects on the geotechnical analysis. A methodology for incorporating realistic ecohydrological effects in the geotechnical analysis is developed and validated, and applied in the case study of a cut slope in Newbury, UK, for which field monitoring data is available, to demonstrate its successful applicability in boundary value problems. The results demonstrate the positive effect of vegetation on the infrastructure by increasing the Factor of Safety. Finally, the effect of climate change and changes in slope vegetation cover are investigated. The analysis results demonstrate that slope behaviour depends on complex interactions between the climate and the soil hydraulic properties and cannot be solely anticipated based on climate data, but suctions and changes in suction need necessarily to be considered.

Land surface temperature (LST) plays an important role in Earth energy balance and water/carbon cycle processes and is recognized as an Essential Climate Variable (ECV) and an Essential Agricultural Variable (EAV). LST products that are issued from satellite observations mostly depict landscape-scale temperature due to their generally large footprint. This means that a pixel-based temperature integrates over various components, whereas temperature individual components are better suited for the purpose of evapotranspiration estimation, crop growth assessment, drought monitoring, etc. Thus, disentangling soil and vegetation temperatures is a real matter of concern. Moreover, most satellite-based LSTs are contaminated by directional effects due to the inherent anisotropy properties of most terrestrial targets. The characteristics of directional effects are closely linked to the properties of the target and controlled by the view and solar geometry. A singular angular signature is obtained in the hotspot geometry, i.e., when the sun, the satellite and the target are aligned. The hotspot phenomenon highlights the temperature differences between sunlit and shaded areas. However, due to the lack of adequate multi-angle observations and inaccurate portrayal or neglect of solar influence, the hotspot effect is often overlooked and has become a barrier for better inversion results at satellite scale. Therefore, hotspot effect needs to be better characterized, which here is achieved with a three-component model that distinguishes vegetation, sunlit and shaded soil temperature components and accounts for vegetation structure. Our work combines thermal infrared (TIR) observations from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard the LEO (Low Earth Orbit) Sentinel-3, and two sensors onboard GEO (geostationary) satellites, i.e. the Advanced Himawari Imager (AHI) and Spinning Enhanced Visible and Infrared Imager (SEVIRI). Based on inversion with a Bayesian method and prior information associated with component temperature differences as constrained, the findings include: 1) Satellite observations throughout East Asia around noon indicate that for every 10 degrees change in angular distance from the sun, LST will on average vary by 0.6 K; 2) As a better constraint, the hotspot effect can benefit from multi-angle TIR observations to improve the retrieval of LST components, thereby reducing the root mean squared error (RMSE) from approximately 3.5 K, 5.8 K, and 4.1 K to 2.8 K, 3.5 K, and 3.1 K, at DM, EVO and KAL sites, respectively; 3) Based on a dataset simulated with a threedimensional radiative transfer model, a significant inversion error may result if the hotspot is ignored for an angular distance between the viewing and solar directions that is smaller than 30 degrees. Overall, considering the hotspot effect has the potential to reduce inversion noise and to separate the temperature difference between sunlit and shaded areas in a pixel, paving the way for producing stable temperature component products.

In the loess tableland, gully slope instability induces severe soil erosion and land degradation, yet the synergistic effects of dominant vegetation under varying restoration modes combined with dynamic rainfall regimes and topographic variations on gully slope stabilization mechanisms remain inadequately quantified. Therefore, the dominant vegetation species under natural (NR) and artificial restoration (AR) was chosen as the object. Through field sampling, root-soil complex mechanical experiments, and numerical simulations, the protection effect of dominant vegetation under different restoration modes combination with rainfall and topographic variations was investigated. The result revealed significant differences in basic soil physical properties, root morphological characteristics, root and root-soil complex mechanical properties among five dominant vegetated plots under the different restoration modes (P < 0.05). The soil properties in the Scop plot under AR were slightly better than those in the other plots. The roots in the Spp plot developed better under NR. The shear strength of Lespedeza bicolor Turcz. was the highest under NR. The tensile strength of Digitaria sanguinalis (L.) Scop. was greatest under AR. The tensile force and tensile strength of single roots exhibited a significant positive linear correlation and a significant negative exponential correlation, with root diameter, respectively (P < 0.01). For the unstable gully slopes (F-s < 1.0), maximum displacement occurred at the slope foot, where tensile shear failure dominated, while the interior experienced compressive yielding. The grey relational analysis identified rainfall intensity as the primary destabilizing factor, followed by dominant vegetation species, slope height, and slope gradient. Notably, when rainfall intensity reaches or exceeds 0.06 m/h, or when slope height exceeds 20 m combined with long-duration rainfall, the regulatory impacts of dominant vegetation under different restoration modes on the gully slope stability are substantially diminished and become negligible. This study provides a theoretical basis for gully slope protection and ecological environmental construction in loess tableland.

Early water stress detection is important for water use yield and sustainability. Traditional methods using the Internet of Things (IoT), such as soil moisture sensors, usually do not provide timely alerts, causing inefficient water use and, in some cases, crop damage. This research presents an innovative early water stress detection method in lettuce plants using Thermal Infrared (TIR) and RGB images in a controlled lab setting. The proposed method integrates advanced image processing techniques, including background elimination via Hue-Saturation- Value (HSV) thresholds, wavelet denoising for thermal image enhancement, RGB-TIR fusion using Principal Component Analysis (PCA), and Gaussian Mixture Model (GMM) clustering to segment stress regions. The leaves stressed areas annotated in the RGB image through yellow pseudo-coloring. This approach is predicated on the fact that when stomata close, transpiration decreases, which causes an increase in the temperature of the affected area. Experimental results reveal that this new approach can detect water stress up to 84 h earlier than conventional soil humidity sensors. Also, a comparative analysis was conducted where key components of the proposed hybrid framework were omitted. The results show inconsistent and inaccurate stress detection when excluding wavelet denoising and PCA fusion. A comparative analysis of image processing performed on a single- board computer (SBC) and through cloud computing over 5 G showed that SBC was 8.27% faster than cloud computing over a 5 G connection. The proposed method offers a more timely and accurate identification of water stress and promises significant benefits in improving crop yield and reducing water usage in indoor farming.

Soils are generally considered anisotropic with respect to hydraulic conductivity, while the evolution of anisotropy condition is unknown for bare and vegetated soils. Therefore, the main goal of this study is to compare the anisotropic hydraulic conductivity of as-compacted, bare, and vegetated specimens. Accordingly, a series of 54 hydraulic conductivity tests were conducted in a custom-made cube triaxial permeameter. The as-compacted specimens were revealed isotropic because the loosely packed preparation procedure resulted in a dominant flocculent structure. However, a fivefold increase in the anisotropy ratio of bare specimens was measured along the isotropic loading path because of the induced surficial degradation zone formed by irrigation and desiccation processes as evident in preliminary observations and crack network analysis. The variations in anisotropy ratio vs. void ratio function of vegetated soil generally fall below the corresponding function of the bare soil. The function was revealed to have a crossed nature, varying from sub-isotropic to super-isotropic states, corresponding to the lower and upper bounds of 0.3 and 3, respectively. It was postulated that vegetation impacts the flow differently by reducing the potential of desiccation cracks, creating preferential flow through the propagation of primary roots and clogging flow channels by secondary roots.

Glacier forelands provide ideal natural laboratories for studying primary vegetation succession. However, understanding of vegetation dynamics on glacier forelands in the Third Pole (TP) region remains limited. In this study, we employed field sampling and aerial photography to investigate key vegetation parameters (species composition, species diversity, and fractional vegetation cover (FVC)) along chronosequences on nine representative glacier forelands of the TP, spanning continental, subcontinental, and maritime glacier types, then analyzed vegetation changes along successional gradients and assessed floristic similarity both within and among the glacier forelands. Our results showed that species diversity and FVC generally exhibited increasing trends, with fluctuations from young to old forelands. These parameters increased more rapidly on maritime glacier forelands. Plant life-forms were similar during the early stages across all forelands but began to diverge as succession progressed, particularly between different glacier types. Furthermore, floristic similarity was observed between glacier forelands, with the highest similarity occurring between forelands of the same glacier type in adjacent geographic locations. Our findings highlight the critical roles of local climate and geographic factors in shaping proglacial ecosystems and flora, providing a scientific basis for understanding the effects of climate change on proglacial ecosystems and guiding biodiversity conservation efforts.

Alpine wet meadow (AWM), an important wetland type on the Qinghai-Tibet Plateau (QTP), is sensitive to climate change, which alters the soil hydrothermal regime and impacts ecological and hydrological functions in permafrost regions. The mechanisms underlying extreme AWM degradation in the QTP and hydrothermal factors controlling permafrost degradation remain unclear. In this study, soil hydrothermal processes, soil heat migration, and the permafrost state were measured in AWM and extremely degraded AWM (EDAWM). The results showed that the EDAWM exhibited delayed onset of both soil thawing and freezing, shortened thawing period, and extended freezing period at the lower boundary of the active layer. The lower ground temperatures resulted in a 0.2 m shallower active layer thickness in the EDAWM compared with the AWM. Moreover, the EDAWM altered soil thermal dynamics by redistributing energy, modifying soil moisture, preserving soil organic matter, and adjusting soil thermal properties. As for energy budget, a substantial amount of heat in the EDAWM was consumed by turbulent heat fluxes, particularly latent heat flux, which reduced the amount of heat transferred to the ground. Additionally, the higher soil organic matter content in EDAWM decreased the annual mean soil thermal conductivity from 1.42 W m- 1 K-1 in AWM to 1.26 W m- 1 K-1 in EDAWM, slowing down heat transfer within the active layer and consequently mitigating permafrost degradation. However, with continued climate warming, the soil organic matter content in EDAWM will inevitably decline due to microbial decomposition in the absence of new organic inputs. As the soil organic matter content diminishes, soil heat transfer processes will likely accelerate, and the permafrost warming rate may surpass that in undistributed AWM. These findings enhance our understanding of how alpine ecosystem succession influences regional hydrological cycles and greenhouse gas emissions.