Understanding the relationship between soil moisture and vegetation is crucial for future projections of ecosystem and water resources. While their hysteresis loop relationship, which arises from their asynchrony in intra-annual variation, remains underexplored. This study used the hysteresis loop type and area (Ah) to characterize the relationship between root zone soil moisture (RZSM) and normalized difference vegetation index (NDVI) across China from 1986 to 2015, and examined its ecological implications. The results identified four types of hysteresis loops. The clockwise loop, with a delayed single peak of RZSM relative to NDVI, was primarily found in north China and the Qinghai-Tibet Plateau, indicating severe water limitation during early growth period. The counterclockwise loop, with an advanced single peak of RZSM relative to NDVI, was common in southeast China's forest, suggesting a shift towards energy limitation. The 8-shaped loop, resulting from double peaks in either RZSM or NDVI due to climate change (e.g., snowmelt) and human disturbance (e.g., irrigation and crop harvest), was observed in northwest China's glaciers and croplands in south and northeast China. The multicrossed loop, marked by multimodal intra-annual variations in both RZSM and NDVI, was predominantly found in northwest China's barren lands. Additionally, from 1986 to 2015, this study observed a shift from 8-shaped or multi-crossed loops to clockwise or counterclockwise loops in some regions like the Yellow River Basin, implying a trend of revegetation. Furthermore, a higher Ah generally indicated more severe water limitation or greater mismatch between RZSM and NDVI. Significant changes in Ah, such as increases in the Yellow River Basin, suggested intensified water limitations, while decreases in southeast and northwest China pointed to an earlier peak of the growing and rainy seasons. This study provides insights into the dynamic interactions between soil moisture and vegetation, offering valuable guidance for ecological management across diverse ecosystems.

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0-40 cm) with a satisfactory accuracy (R-2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.

The Qinghai-Tibetan Plateau (QTP) and the Arctic are prime examples of permafrost distribution in high-altitude and high-latitude regions. A nuanced understanding of soil thermal conductivity (STC) and the various influencing factors is essential for improving the accuracy of permafrost simulation models in these areas. Nevertheless, no comparative analysis of STC between these two regions has been conducted. Therefore, this study aims to investigate the characteristics and influencing factors of STC at varying depths within the active layer (5 to 60 cm) during freezing and thawing periods in the QTP and the Arctic, using the regional-scale STC data products simulated through the XGBoost method. The findings indicate the following: (1) the mean STC of permafrost in the QTP is higher than that in the Arctic permafrost region. The STC in the QTP demonstrates a declining trend over time, while the Arctic permafrost maintains relative stability. The mean STC values in the QTP permafrost region during the thawing period are significantly higher than those during the freezing period. (2) STC of the QTP exhibits a fluctuating pattern at different depths, in contrast, the average STC value in the Arctic increases steadily with depth, with an increase rate of approximately 0.005 Wm-1 K-1/cm. (3) The analysis of influencing factors revealed that although moisture content, bulk density, and porosity are the primary drivers of regional variations in STC between the QTP and the Arctic permafrost, moisture elements in the QTP region have a greater influence on STC and the effect is stronger with increasing depth and during the freeze-thaw cycles. Conversely, soil saturation, bulk density, and porosity in the Arctic have significant impacts. This study constitutes the first systematic comparative analysis of STC characteristics.

Drought, a major abiotic stress, adversely affects the growth, development, and nutrient absorption of legume plants, leading to yield reduction. This study investigated the combined effects of silicon (Si) and the actinobacterial strain Streptomyces chartreusis on water-stress resistance in soybean (Glycine L.). Our experiments, conducted under simulated water deficit conditions, revealed that the combined application of Si and S. chartreusis boosted the morphological, physiological, and biochemical traits of the soybean plants. Si treatment led to higher levels of nitrogen, phosphorus, potassium, and silicon while reducing malondialdehyde (MDA) concentrations (25 %), an indicator of oxidative stress. The use of silicate and S. chartreusis boosted the activity of antioxidant enzymes, such as superoxide dismutase (35 %), catalase (61 %), and peroxidase (58 %), reducing oxidative damage and improving water relations, as shown by the increased relative water content (33 %) and membrane stability index (35 %). The plants treated with both silicate and S. chartreusis exhibited the highest levels of chlorophyll a and b, suggesting improved photosynthetic efficiency. These results highlight the potential of combining Si with beneficial microbial inoculants in sustainable agriculture to enhance soybean resilience to water stress. However, field studies are required to confirm the efficacy of these treatments in agricultural environments.

Global warming is altering soil moisture (SM) droughts in Europe with a strong drying trend projected in the Mediterranean and wetting trends projected in Scandinavia. Central Europe, including Germany, lies in a transitional zone showing weaker and diverging change signals exposing the region to uncertainties. The recent extreme drought years in Germany, which resulted in multi-sectoral impacts accounting to combined drought and heat damages of 35 billion Euros and large scale forest losses, underline the relevance of studying future changes in SM droughts. To analyze the projected SM drought changes and associated uncertainties in Germany, we utilize a large ensemble of 57 bias-adjusted and spatially disaggregated regional climate model simulations to run the hydrologic model mHM at a high spatial resolution of approximately 1.2 km. We show that projections of future changes in soil moisture droughts over Germany depend on the emission scenario, the soil depth and the timing during the vegetation growing period. Most robust and widespread increases in soil moisture drought intensities are projected for upper soil layers in the late growing season (July-September) under the high emission scenario. There are greater uncertainties in the changes in soil moisture droughts in the early vegetation growing period (April-June). We find stronger imprints of changes in meteorological drivers controlling the spatial disparities of SM droughts than regional diversity in physio-geographic landscape properties. Our study provides nuanced insights into SM drought changes for an important climatic transition zone and is therefore relevant for regions with similar transitions.

Rubber-based intercropping is a recommended practice due to its ecological and economic benefits. Understanding the implications of ecophysiological changes in intercropping farms on the production and technological properties of Hevea rubber is still necessary. This study investigated the effects of seasonal changes in the leaf area index (LAI) and soil moisture content (SMC) of rubber-based intercropping farms (RBIFs) on the latex biochemical composition, yield, and technological properties of Hevea rubber. Three RBIFs: rubber-bamboo (RB); rubber-melinjo (RM); rubber-coffee (RC), and one rubber monocropping farm (RR) were selected in a village in southern Thailand. Data were collected from September to December 2020 (S1), January to April 2021 (S2), and May to August 2021 (S3). Over the study period, RB, RM, and RC exhibited significantly high LAI values of 1.2, 1.05, and 0.99, respectively, whereas RR had a low LAI of 0.79. The increasing SMC with soil depths was pronounced in all RBIFs. RB and RM expressed less physiological stress and delivered latex yield, which was on average 40% higher than that of RR. With higher molecular weight distributions, their rheological properties were comparable to those of RR. However, the latex Mg content of RB and RM significantly increased to 660 and 742 mg/kg, respectively, in S2. Their dry rubbers had an ash content of more than 0.6% in S3.

In recent decades, flash drought events have frequently occurred in the humid regions of southern China. Due to the sudden onset and rapid intensification of these droughts, they often cause severe damage to vegetation photosynthesis. However, our understanding of the spatiotemporal evolution characteristics of flash droughts across different vegetation types, as well as the response regularity of photosynthesis to flash droughts, especially early responses, remains limited. This study analyzes the spatiotemporal evolution characteristics of flash droughts for different vegetation types in the Middle and Lower Reaches of the Yangtze River Basin from 2000 to 2023. It uses solar-induced chlorophyll fluorescence (SIF) and fluorescence yield (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{{\upvarphi\:}}_{\text{F}\:}$$\end{document}) to explore the response regularity of vegetation photosynthesis to flash droughts, with a systematic analysis of the 2013 flash drought event. The results show that, over the past 24 years, the frequency of flash droughts for different vegetation types in the Middle and Lower Reaches of the Yangtze River Basin has decreased, but the total duration has increased, with forests experiencing the highest frequency of flash droughts, while cropland experiences the least. Cropland photosynthesis is the most sensitive to flash drought, showing an early response 8-16 days after the onset and reaching a negative anomaly between 24 and 32 days. Forests mainly show an early response between 16 and 24 days and a negative anomaly response between 32 and 40 days. During the 2013 flash drought, cropland showed an early response on the 10th day after the onset and a negative anomaly on the 26th day, while forest responses were later, with early responses on the 20th day and negative anomalies on the 36th day. These results align with long-term statistical data. This study contributes to a deeper understanding of vegetation photosynthesis response regularity to flash droughts and provides insights for developing effective flash drought management strategies.

In the Ulan Buh Desert, which is located in a seasonally frozen region, a frozen soil layer can appear in the winter after the wind erosion of dry sand from the surface of a mobile sand dune, thus altering the wind-sand transport process. To clarify the wind-sand transport pattern after the emergence of a frozen soil layer, this study used wind tunnel experiments to study the variations in the wind erosion rate and sediment transport pattern of frozen and nonfrozen desert soil with different soil moisture contents (1-5%). The results revealed that the relationships of the wind speed, soil moisture content and wind erosion rate are in line with an exponential function, and the wind erosion rate decreases by 6-52% after the desert soil is frozen. When the soil moisture content of the nonfrozen desert and frozen desert soil is 4% and 3%, respectively, the wind erosion rate of the soil can be reduced by more than 65% compared with that of natural dry sand (soil moisture content of 0.28%), i.e., the wind erosion rate can be effectively reduced. The sediment transport rate of nonfrozen desert soil decreases with increasing height, with an average ratio of approximately 65% for saltation. The sediment transport rate of frozen desert soil first increases but then decreases with increasing height, with an average ratio of approximately 80% for saltation. When sand particles hit the source of frozen desert soil, the interaction between particles and bed surface is dominated by the process of impact and rebound, so that more particles move higher, and some sand particles move from creep to saltation. In summary, freezing has an inhibitory effect on the wind-sand activity of desert soil, and freezing makes it easier for sand to move upwards.

Slope failure, as a natural disaster, can cause extensive human suffering and financial losses worldwide. This paper introduces a new soil moisture extended cohesive damage element (SMECDE) method to predict railway slope failure under heavy rainfall. A correlation between rainfall intensity and soil moisture content is first established to create an equivalence between the two. Considering slope failure mechanisms dominated by the loss of soil or the cohesion of slope materials due to heavy rainfall infiltration, the soil moisture decohesion model (SMDM) is developed using previous experimental data to express how soil cohesion varies with different soil moistures and depths. The SMDM is incorporated into the extended cohesive damage element (ECDE) method to fundamentally study slope failure mechanisms under varying soil moisture levels and depths. The proposed SMECDE approach is used to predict the failure propagation of a selected railway embankment slope at the critical soil moisture or rainfall intensity. This SMECDE failure prediction is validated using relevant data from previous fieldwork and meteorological reports on the critical rainfall intensity at the site. Additionally, the corresponding slope damage scale prediction is validated with a large plastic deformation analysis using the commercial FEM package ABAQUS.

Drought is a reoccurring natural phenomenon that presents significant challenges to agricultural production, ecosystem stability, and water resource management. The Central Highlands of Vietnam, a major region of industrial crops and vegetation ecosystems, has become increasingly vulnerable to drought impacts. Despite this vulnerability, limited research has explored the specific characteristics of drought and its seasonal effects on vegetation ecosystems in the region. This study addressed these gaps by providing a detailed analysis of recent soil moisture drought characteristics and their seasonal impacts on vegetation from 2015 to 2023 using weekly soil moisture active passive (SMAP) and moderate resolution imaging spectroradiometer (MODIS) satellite time series observations. This analysis derived the soil moisture anomaly index as a proxy to assess drought characteristics and used correlation analysis to quantify their impacts on seasonal vegetation dynamics. Our spatial analysis identified the most significant drought years in 2015 and 2019 in the study region, while the wettest conditions were detected in 2017 and 2022 over the study period. Notably, significant soil moisture deficits were observed in August and October throughout the study period, even though these months typically fall within the rainy season. On average, nearly 25 drought events were detected in the region from 2015 to 2023 due to soil moisture deficits, each lasting approximately 6 weeks. The impact of drought events on the vegetation ecosystem was seasonally pronounced in spring and winter, where droughts were notably higher. Our results provide valuable insights into informed decision-making and sustainable agricultural practices in the region. Understanding the spatial and temporal patterns of drought and its seasonal effects on vegetation can help policymakers and farmers develop targeted strategies to mitigate the adverse impacts, enhance water management practices, and promote drought-resistant crop varieties, thereby maintaining agricultural productivity and ecosystem health amidst increasing climate variability.