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The shortage of water resources is a crisis for human ecosystems. Compared with other ecosystems, the impact on agricultural ecosystems is more prominent. In order to alleviate this situation, a new type of agricultural hydrogel, agarose-bacterial cellulose hydrogel, was synthesized by replacing the traditional petroleum-based monomer with natural polysaccharide. Bacterial cellulose was used as raw material for the synthesis of hydrogels using agarose as matrix template and N, N'- methylenebisacrylamide as cross-linkers. In the present study, the hydrogel has optimized the ratio of the three synthesized polymers and characterized this hydrogel using FTIR spectra, XRD, and SEM. The findings demonstrated that bacterial cellulose was adequately incorporated into the agarose hydrogel and that the pores of AB1 were more significant than those of AA and AB2, which provided crucial support for the hydrogel's ability to encourage plant development. By mixing hydrogel with soil, the effects of soil which have composite hydrogel and without composite hydrogel on plant germination and growth were studied. The results showed that adding bacterial cellulose increased the water retention and holding capacity of agarose hydrogel. Moreover, the plant germination rate and growing trend in soil with hydrogel were better than those without hydrogel. This low-cost, quickly made hydrogel has great application potential in agricultural soil. [ABSTRACT FROM AUTHOR]

Under a warming climate, occurrences of wildfires have been increasingly more frequent in boreal and arctic forests during the last few decades. Wildfires can cause radical changes in the forest ecosystems and permafrost environment, such as irreversible degradation of permafrost, successions of boreal forests, rapid and massive losses of soil carbon stock, and increased periglacial geohazards. Since 2016, we have gradually and more systematically established a network for studying soil nutrients and monitoring the hydrothermal state of the active layer and near-surface permafrost in the northern Da Xing'anling (Hinggan) Mountains in Northeast China. The dataset of soil moisture content (0–9.4 m in depth), soil organic carbon (0–3.6 m), total nitrogen (0–3.6 m), and total phosphorus and potassium (0–3.6 m) have been obtained by field sampling and ensuing laboratory tests. Long-term datasets (2017–2022) of ground temperatures (0–20 m) and active layer thickness have been observed by thermistor cables permanently installed in boreholes. The present data can be used to simulate changes in permafrost features under a changing climate and wildfire disturbances and to explore the changing interactive mechanisms of the fire-permafrost-carbon system in the hemiboreal forest. Furthermore, can provide baseline data for studies and action plans to support the carbon neutralization initiative and assessment of ecological safety and management of the permafrost environment. This dataset can be easily accessed from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.300933 , Li and Jin, 2024). [ABSTRACT FROM AUTHOR]

Although irrigation scheduling has been studied for diverse vegetable crops, much less attention has been given to irrigation scheduling for the seed crops on which these production systems rely. In spinach, for which irrigation scheduling needs are likely to vary greatly between seed and leaf production, this leaves seed producers without adequate resources to make irrigation scheduling decisions. Our research sought to fill this gap by evaluating two alternative irrigation scheduling strategies (a publicly available decision-support tool and soil moisture sensors) and four soil moisture thresholds for irrigation for their impacts on vegetative growth, marketable seed yield, seed quality, and the severity of Stemphylium leaf spot (caused by Stemphylium vesicarium and Stemphylium beticola), a common foliar disease of spinach, under sprinkler irrigation. We found that in all 3 years of the study, earlier and more frequent irrigation increased vegetative growth. However, marketable seed yield only increased relative to the control treatment based on farmers' standard irrigation practices in 1 of the 3 years--a year with an abnormally late planting date. This indicates that vegetative growth is more responsive than seed yield to earlier and more frequent irrigation, and that increases in vegetative growth do not translate directly to increased marketable seed yield. Contrary to the expected increase in Stemphylium leaf spot severity with increasing irrigation, the severity decreased in both years it was measured, likely as a result of the small stature of the spinach seed parent lines used in our study and opportunistic pathogenicity on moisture-stressed plants. These results provide a useful foundation from which spinach seed producers can make irrigation management decisions for their crops that underpin a valuable global industry. [ABSTRACT FROM AUTHOR]

This study investigates the interannual variability of summer precipitation over Central Asia and explores its precursory signals through soil moisture (SM) and sea surface temperature (SST) anomalies. The results reveal that southern Central Asia (SCA) is a crucial SM‐precipitation coupling region where summer precipitation is significantly linked to the preceding April SM in the Turan Plain, between the Caspian Sea and the Tibetan Plateau. The preceding Turan Plain SM (TPSM) anomaly can reflect the ensuing summer SM anomalies in the SCA region due to the persistence of SM. The higher TPSM can stimulate anomalous convective ascent and associated negative geopotential height anomalies over the SCA region, which is favourable for more SCA precipitation (SCAP) during summer. Additionally, Indian and Pacific Ocean SST (IPOS) anomalies can regulate the summer SCAP through ocean and land relay effects. The preceding April can reflect the subsequent summer SST anomalies across the northern Indian Ocean and South China Sea, which trigger a Matsuno‐Gill response and induce anomalous water vapour transport into the SCA region, providing favourable moisture conditions for more SCAP during summer. Apart from such an ocean relay effect, the preceding IPOS can modulate the April TPSM first and then affect the summer SCAP through the land relay effect caused by persistent SM anomalies from April to summer. The combined effect of the preceding TPSM and IPOS on the summer SCAP is more pronounced than the respective effect of either TPSM or IPOS. Incorporating the TPSM signal as a supplementary precursor can enhance the predictive skill of summer SCAP. These findings may provide valuable insights into the reasons and prediction of the variability of summer SCAP. [ABSTRACT FROM AUTHOR]

This study represents the findings of the measurement of natural radioactivity in soil and water samples collected from the upper Himalayas region along the Manali–Leh Highway. The activity concentration values of terrestrial radionuclides in soil samples are measured using an n-type HPGe detector. The radiological hazards are also estimated through the evaluation of radium equivalent activity (Req), external and internal hazard index (Hex, Hin), alpha index (Iα), gamma index (Iγ), air absorbed dose, and indoor and outdoor effective dose. The level of Uranium in surface and ground water samples collected from the region is determined using the LED Fluorimetry technique. Annual effective dose, radiological and chemical toxicity risk, and hazards quotient due to the presence of uranium in water samples are also calculated. The values of these parameters are compared with permissible limits. [ABSTRACT FROM AUTHOR]

Vegetation growth is adversely impacted by multiple climate extremes related to the water and thermal stress over the Tibetan Plateau (TP). However, it remains unknown at which stress level these climate extremes can trigger the abrupt shifts of vegetation response to climate extremes and result in the maximum vegetation response across TP. To fill this knowledge gap, we combined the hydrometeorological data and the satellite-derived vegetation index to detect two critical thresholds that determine the response of vegetation productivity to droughts, high-temperature extremes, and low-temperature extremes, respectively, during 2001–2018. Our results show that the response of vegetation productivity to droughts rapidly increases once crossing −1.41±0.6 standard deviation (σ) below the normal conditions of soil moisture. When crossing −2.98σ±0.9σ, vegetation productivity is maximum damaged by droughts. High-temperature extremes, which have the two thresholds of 1.34σ ±0.4σ and 2.31σ±0.4σ over TP, are suggested to trigger the strong response of vegetation productivity at a milder stress level than low-temperature extremes (two thresholds: −1.44σ±0.5σ and −2.53σ±0.8σ). Moreover, we found the compounded effects of soil moisture deficit in reducing the threshold values of both high- and low-temperature extremes. Based on the derived thresholds of climate extremes that impact vegetation productivity, Earth System Models project that southwestern TP and part of the northeastern TP will become the hotspots with a high exposure risk to climate extremes by 2100. This study deciphers the high-impact extreme climates using two important thresholds across TP, which advances the understanding of the vegetation response to different climate extremes and provides a paradigm for assessing the impacts of climate extremes on regional ecosystems. [ABSTRACT FROM AUTHOR]

During the present era of climate change, recognizing non-stationarity is crucial when assessing the inevitability of meteorological droughts. Agricultural drought is the focus of agricultural production. With improved drought detection methods and diverse indices, comprehensively characterizing agricultural drought requires consideration of multiple factors. Hence, this study integrates non-stationary meteorological and soil drought to formulate a composite meteorological-soil joint drought within the context of climate change. In this study, a non-stationary meteorological drought index (NSPEI) and a soil moisture index were integrated to create a unified multidimensional risk meteorological-soil joint drought (MR-MSJD) for agricultural analysis across ten major river basins in China. The aim was to investigate the multidimensional joint probabilistic spatial–temporal patterns of MSJD. The results show that the non-stationary meteorological and soil drought exhibited consistent variations, and the developed MSJD effectively captured the joint probability of these two drought occurrences. The joint probability of meteorological and soil drought was found to be higher in eastern and northeastern China compared to other basins, with a notably lower joint probability observed in the Pearl River Basin and the Southeast Coastal Basin. The multidimensional analysis of past MSJD detection results reveals a gradual increase in MSJD probability. Under the 1.5 °C rise scenario, the joint occurrence probability doubles, leading to a 15% and 10% increase in severe combined drought. Moreover, under the 2.0 °C rise scenario, the combined drought probability exhibits a further 15% increase compared to the 1.5 °C rise scenario. Our methodology can be applied to other climate variables, providing critical insight for a number of sectors that are accustomed to deploying resources based on historical probabilities. [ABSTRACT FROM AUTHOR]

Summary: Understanding the capacity of temperate trees to acclimate to limited soil water has become essential in the face of increasing drought risk due to climate change. We documented seasonal – or phenological – patterns in acclimation to water deficit stress in stems and leaves of tree species spanning the angiosperm phylogeny.Over 3 yr of field observations carried out in two US arboreta, we measured stem vulnerability to embolism (36 individuals of 7 Species) and turgor loss point (119 individuals of 27 species) over the growing season. We also conducted a growth chamber experiment on 20 individuals of one species to assess the mechanistic relationship between soil water restriction and acclimation.In three‐quarters of species measured, plants became less vulnerable to embolism and/or loss of turgor over the growing season. We were able to stimulate this acclimatory effect by withholding water in the growth chamber experiment.Temperate angiosperms are capable of acclimation to soil water deficit stress, showing maximum vulnerability to soil water deficits following budbreak and becoming more resilient to damage over the course of the growing season or in response to simulated drought. The species‐specific tempo and extent of this acclimatory potential constitutes preadaptive climate change resilience. [ABSTRACT FROM AUTHOR]

Aims: Arbuscular mycorrhizal fungi (AMF) play a crucial role in enhancing plant resistance to drought stress by improving the plant-water relationship. However, the precise mechanism of AMF-mediated water transport to host plant roots remains elusive. Methods: In a compartmentalized experiment comprising both plant and non-plant compartments, we employed heavy-oxygen water (18O-labeled) to directly trace and quantify the transport of water by AMF hyphae to alfalfa under the condition of high soil moisture (70% of the maximum field water holding capacity) and low soil moisture (40% of the maximum field water holding capacity). Results: Our findings revealed that irrespective of soil moisture levels, hyphae entering the 18O-labeled compartment (AM treatment) significantly enriched 18O in alfalfa transpiration water compared to no hyphae entering the 18O-labeled compartment (NM treatment). We calculated the direct water transport by AMF using a standard isotope mixing model, demonstrating that in high and low- moisture soil substrates, AM fungi contributed 12.32% and 17.03% of the total transpiration water, respectively. Conclusions: These results highlight that the direct transport of water from AMF hyphae to horticulture plants should not be underestimated in comparison to plant transpiration demand. Moreover, the water contribution of AM fungal hyphae to host plants is more significant in arid soil, especially in dry soil substrate. This underscores the critical role of mycelial water transport in supporting plant survival under water-limiting conditions. [ABSTRACT FROM AUTHOR]

Aims: Gradients in water potential of soil and plant system drives the water movement in soil-plant-atmospheric continuum. Here, we demonstrate how root water potential measured directly from the roots upon changes in soil water potential would contribute to the understanding of the drought response in Chrysopogon zizanoides. Methods: Plants of Chrysopogon zizanoides L. were sampled at different soil water status (inducing drought) and growth periods (3-, 4- and 5- months). The roots and leaves of the plants were dissected to measure the root water potential and specific leaf area, respectively. The root water potential was measured in a WP4C dew-point potentiometer. Root diameter corresponding to the roots measured for root water potential was also measured. Results: Our findings showed a logarithmic increase in gradient between soil and root water potential under the induced drought stress, similar to the existing findings of root hydraulic conductance. Specific leaf area significantly decreased with root water potential, indicating the hydraulic continuity between roots and leaves. A new power law correlation between root diameter and root water potential established a trait-based understanding of root water uptake. Conclusion: The aggregation of such root water potential measurements using potentiometer would offer strategies to explore the implications of below-ground plant behaviour in applications such as slope stability and irrigation. [ABSTRACT FROM AUTHOR]

Aims: Water-absorbing polymer (WAP) is recognized as a suitable soil additive for enhancing water retention and storage in the root zone under arid condition. The presence of such additives may alter the soil water characteristic curve (SWCC) and hence, may affect the plant growth. The effect of WAP on SWCC particularly, with the presence of vegetation is rarely explored. Therefore, this study investigates the combined influence of WAP and vegetation on SWCC for unraveling the soil-plant-WAP-atmosphere interaction. Methods: Two different WAPs along with vegetation species Solanum Lycopersicum species, were considered. The SWCCs along with its model parameters (Air entry value (AEV); Plant available water content (PAWC), FC (Field Capacity) and Permanent Wilting Point (PWP)) were established for silty loamy soil considering the different combinations of WAPs and vegetation. The changes in root structure were analysed with and without the presence of WAP. Results: Parameters such as FC, PWP and PAWC are increased by more than 1.5 times with the presence of WAP and vegetation compared to control soil This is mainly attributed to the alteration in pore volume in the soil matrix. Root-induced soil showed higher moisture retention than control soil at a specific suction which is affected by the root biomass/architecture. Conclusions: The study indicates that the WAP helps to reduce water demand during arid condition. This study also demonstrates the usefulness of SWCC as a tool to unravel the combined influence of WAP and vegetation on soil-water storage and water retention characteristics of soil associated with soil-WAP-root-atmosphere interaction. [ABSTRACT FROM AUTHOR]

Background and Aims: Selection effect (SE) and complementarity effect (CE) are often considered as two key indicators to mediate the positive diversity-productivity relationship in the maize-legume intercropping system, as intercropping generally enables crops to use the available resources more efficiently than monoculture. Yet, it is unclear whether soil moisture drives the SE and CE transformation, plant-plant interaction, and accordingly affect the productivity. Methods: A two-year field experiment was conducted to explore the impacts of soil water status (with and without plastic mulching) on interspecific interaction and productivity and its key mechanism in the maize-faba bean intercropping system. Results: Low soil moisture reduced the net effect (NE) and land equivalent ratio (LER) with evident yield loss (NE < 0 and LER = 1.05), whereas the improved soil moisture reversed this trend and resulted in overyielding (NE > 0 and LER = 1.13). Regardless of soil moisture, faba bean was the dominant species and maize was the inferior one. Low soil moisture promoted the contribution of SE to productivity (P < 0.05). In contrast, high moisture turned to lower the competition intensity of faba bean against maize and accordingly promote the transformation of biodiversity effect from SE to CE. The main mechanism was that the water competition imposed by faba bean strips on maize ones decreased the NE through reducing photosynthetic rate and water use efficiency of maize. Conclusion: The adaptive transitions of interspecific relationship and the biodiversity effect were driven by soil water availability. This novel phenomenon should be emphasized in the crop diversity management of intercropping system in the rainfed region. [ABSTRACT FROM AUTHOR]

Background and Aims: The intercropping has great advantages in production gain, resources use and soil quality improvement. However, the effects of perennial forage legumes intercropped with annual grain crop on soil alkali-salinity was not well revealed. This study aimed to propose a spring wheat (Triticum aestivum L.)/alfalfa (Medicago sativa L.) intercropping and reveal whether this cropping system could ameliorate soil salinity. Methods: A two-year field experiment was conducted under 3 cropping systems at 3 irrigation amounts in the inland arid area of northwestern China. The cropping systems were sole spring wheat cropping (W), 12 rows spring wheat/4 rows alfalfa intercropping (W12A4) and 8 rows spring wheat/4 rows alfalfa intercropping (W8A4), and irrigation amounts included 450 (full irrigation amount, If), 360 (moderate irrigation amount, Im) and 180 mm (low irrigation amount, Il). Results: The intercropping system, especially W8A4, could more decrease soil salinity, pH and topsoil bulk density, and increase soil water content, topsoil porosity, and Ca2+ and Mg2+ contents, compared to W. Soil electrical conductivity was positively correlated with topsoil bulk density and negatively correlated with topsoil porosity, which were enhanced by intercropping and irrigation. There was weak correlation between soil electrical conductivity and soil water content. W12A4 and W8A4 led to reduction in contents of Na+, K+, Cl−, and SO42−, while Ca2+ and Mg2+ accumulated in the soil. Conclusion: Intercropped alfalfa and spring wheat could reduce soil salinity, improve soil structure and ions balance. It was recommended that W8A4 with 360 mm irrigation could be extensively used in the arid area of northwestern China, gaining grain and forage production, and helping reduce salt accumulation. [ABSTRACT FROM AUTHOR]

Background and aims: The frequent occurrence of extreme rainfall events results in soils experiencing drying–rewetting (DRW) cycles. Such rewetting can lead to a surge in soil CO2 emissions; however, the main regulatory factors involved in this priming effect are unclear. Methods: In this study, we conducted a meta-analysis using data extracted from 43 published papers, to determine the direct regulatory factors involved in the priming effect of soil CO2. Results: The results indicated that the priming effect of rewetting on soil CO2 emissions was influenced by ecosystem type, soil properties, climatic factors, and the number of DRW cycles. The priming effect was the highest in cropland but the lowest in grassland when taking flux values observed before rewetting as the control group. It was also greater in acidic soils (pH < 6.5) and soils with a high clay fraction (clay ≥ 30%) than in other soils. The effect size (lnRR) of soil CO2 emissions was exponentially related to the mean annual precipitation (MAP), and decreased with increases in MAP. In DRW experiments, the priming effect of the first rewetting on soil CO2 emissions was the largest, an effect that gradually decreased with the number of DRW cycles, before disappearing completely. Most importantly, soil moisture influenced the peak time and the pulse time of the priming effect: the greater the change in soil moisture, the longer the peak time duration; the higher the maximum soil moisture content after rewetting, the longer the pulse time duration; and the lower the initial soil moisture content, the bigger the priming effect. Conclusion: Generally, physical mechanisms, especially soil moisture, directly regulate the CO2 priming effect during DRW cycles. Thus, this study provides a theoretical basis for assessing and predicting the impact of future precipitation changes on soil carbon cycling. Future studies should also carefully monitor any changes in soil microorganisms in response to changes in soil moisture during DRW cycles, because these appear to be significantly involved in CO2 release from soils. [ABSTRACT FROM AUTHOR]

Aims: Soil microbial and enzymatic activity have important roles in soil health, nutrient cycle and plant growth. Biochar is an excellent biomass for increasing soil water content, but some biochar compounds, due to their high pH, are harmful to the soil. This study aimed to investigate the effect of biochar and sulfur-modified biochar on improving the soil water content and biochemical properties in a millet cropping system. Methods: The field experiment was performed in a completely random design with three replications. Experimental treatments included control, 15 t ha− 1 sunflower biochar (B), and 15 t ha− 1 sulfur-modified biochar (BS). Results: Biochar (B and BS) improved the soil water content by 47% and 35%, respectively, compared to the control. B and BS treatments improved soil biological properties, including microbial biomass carbon, basal respiration, and the activity of catalase, dehydrogenase, urease, and alkaline phosphatase enzymes compared to the control. The application of B and BS treatments decreased soil EC and sodium adsorption ratios compared to the control. The highest (8.26) and lowest (7.83) values of soil pH were related to the B and BS treatments, respectively. Treatment of soil with B and BS enhanced soil dissolved organic carbon (90% and 33%), available nitrogen (74% and 48%), and available phosphorus (60% and 96%) compared to the control. The application of B and BS treatments enhanced plant nutrients (nitrogen, phosphorus, and potassium) and the leaf relative water content by 40% and 14%, respectively. Biochar (B and BS) improved millet yield by 58% and 115%, respectively, compared to the control. Conclusion: Sulfur increased the efficiency of biochar in amending saline and calcareous soil and enhanced millet yield by improving the chemical properties (pH and CEC) of biochar. [ABSTRACT FROM AUTHOR]

Purpose: The patterns of biomass allocation are particularly important because it is related to crop yield, plant growth rate and plant survival in a changeable environment and constant growth. Our study aimed to develop a new model to describe the allocation strategies of maize. Methods: We identified 73 sets of data about the effect of environmental factors (water factors and nutrient factors) on maize dry matter allocation to test the functional equilibrium theory. We then coupled the Friedlingstein model (describe the influence of environmental factors) and the Logistic model (describe the trend of biomass during growth) to describe the growth of maize in the vegetative growth stage. Model performance was evaluated with experimental data including soil volume moisture content (θ), soil temperature (Ts), leaf area index (LAI), and dry matter from a five-year maize experiment under two irrigation treatments. Results: The shoot to root ratio decreased as the water and nutrient stress level increased. The average coefficient of determination (R2) of three organs over five years was 0.92, 0.65, and 0.58 for the Coupled model, Friedlingstein model, and Logistic model, respectively. In addition, by an allometric analysis we found that the allocation strategies of maize were related to yield. Conclusion: For maize, an annual crop, environmental factors and ontogeny are crucial. Hence, in the Coupled model we established, it was taken into account to present better simulation accuracy and possibly provide a new insight for yield prediction in the early growth stage. [ABSTRACT FROM AUTHOR]

Aims: Quantitative characterization of the time-lag effect between canopy temperature and atmospheric temperature and its controlling factors in the agricultural ecosystem may contribute to a higher inversion accuracy of soil water content using canopy-air temperature information. Methods: Tc of winter wheat were continuously monitored, and the data of such environmental factors as solar radiation (Rs), atmospheric temperature (Ta), relative humidity (RH) and soil water content (SWC) were simultaneously collected. Results: Hysteresis existed between Tc and Ta over the diel cycles, and different weather and irrigation levels did not change the direction of the time lag loop. the key driver regulating the diel hysteresis pattern between Tc and Ta varied under different weather: on rainy days, key driver was Rs while on cloudy and sunny days, the key driver was RH. the multiple regression model indicated that together Rs, Ta, RH, and SWC explained 58 ± 10% of the variation of time-lag effect. Path analysis showed on rainy days the key driver (Rs and RH) could enhance the time-lag effect through other indirect factors (Ta and SWC); on cloud days the key driver (RH and SWC) could inhibit the time-lag effect through other indirect factors (Ta); On sunny days this mutual inhibition was further significant. Conclusions: These findings indicated a dynamic process of time-lag effect between Tc and Ta with different weather and different irrigation levels. This study contributes to the understanding of the time-lag effect and its driving factors and this analysis provides the basis for further improvement in monitoring crop water deficit. [ABSTRACT FROM AUTHOR]

Glyphosate (Gly) and its formulations are broad-spectrum herbicides globally used for pre- and post-emergent weed control. Glyphosate has been applied to terrestrial and aquatic ecosystems. Critics have claimed that Gly-treated plants have altered mineral nutrition and increased susceptibility to plant pathogens because of Gly ability to chelate divalent metal cations. Still, the complete resistance of Gly indicates that chelation of metal cations does not play a role in herbicidal efficacy or have a substantial impact on mineral nutrition. Due to its extensive and inadequate use, this herbicide has been frequently detected in soil (2 mg kg−1, European Union) and in stream water (328 µg L−1, USA), mostly in surface (7.6 µg L−1, USA) and groundwater (2.5 µg L−1, Denmark). International Agency for Research on Cancer (IARC) already classified Gly as a category 2 A carcinogen in 2016. Therefore, it is necessary to find the best degradation techniques to remediate soil and aquatic environments polluted with Gly. This review elucidates the effects of Gly on humans, soil microbiota, plants, algae, and water. This review develops deeper insight toward the advances in Gly biodegradation using microbial communities. This review provides a thorough understanding of Gly interaction with mineral elements and its limitations by interfering with the plants biochemical and morphological attributes. Glyphosate (Gly) contamination in water, soil, and crops is an eminent threat globally. Various advanced and integrated approaches have been reported to remediate Gly contamination from the water-soil-crop system. This review elucidates the effects of Gly on human health, soil microbial communities, plants, algae, and water. This review develops deeper insight into the advances in Gly biodegradation using microbial communities, particularly soil microbiota. This review provides a brief understanding of Gly interaction with mineral elements and its limitations in interfering with the plants biochemical and morphological attributes. [ABSTRACT FROM AUTHOR]

A positive relationship between protein concentration and yield has been documented in different combinations of genotype and environment, often under potential conditions. However, the ecophysiological bases underlying this positive relationship under heat stress (HS) and drought stress (DS) during seed filling are still lacking. Our objective was to evaluate the relationship between seed protein content and concentration with yield in field experiments exposed to HS, DS and HS × DS interaction during the seed filling. Two field experiments were conducted and assimilates accumulation, remobilization and redistribution patterns were analysed in high and low seed protein soybean genotypes. The crop was exposed to four treatments: control (ambient temperature and soil water content near field capacity), HS (episodes above 32°C, 6 h d−1) during 15 days, DS (soil water content ≤25% of field capacity) during the whole seed filling and HS × DS. Significant and positive relationships between seed protein content and concentration with yield were observed across treatments and genotypes. Under DS and HS × DS, assimilates available during the seed filling decreased, and assimilates remobilization and partition to seeds were limited, responses significantly associated with seed protein content and concentration, and yield reductions. Furthermore, we demonstrated here that the high leaf N content at the beginning of seed filling, the short early reproductive phase duration, the high source to sink ratio and the high dry matter stem remobilization capacity, as well as the low seed number and high seed weight are intrinsic characteristics of the high protein genotype that could be associated with its high seed protein content and concentration and yield under stressful conditions. This knowledge is key to develop soybean management strategies to improve seed protein level and yield under contrasting productive scenarios. [ABSTRACT FROM AUTHOR]

Soil mesofauna play pertinent roles in soil processes. For example, microarthropods strongly influence rates of microbial decomposition. The relationship between mesofauna and their environment are understudied in low Arctic ecosystems compared to other regions. A more detailed grasp of these soil assemblages is necessary for understanding the current functioning of these ecosystems. We characterized the soil mesofauna community across different low Arctic habitats to determine which soil properties commonly correlated with soil fauna would best explain their distribution, abundance, and diversity. Samples were taken near five different lakes in northern Finland, in both alpine meadows and sub-alpine birch forests, across a span of available soil habitats (measured by pH, salinity, organic and nitrogen content, soil moisture). Total abundance of the mesofauna community was influenced by a combination of soil factors, but most individual taxa, as well as measures of diversity were best explained by models of one or two influential soil parameters. Poduromorpha springtails and Oribatid mites were best modeled by measures of resource availability, although only Oribatids were significantly, positively related to these resources. All mites and Entomobryomorphid springtails were positively influenced by physicochemical soil moisture and/or salinity. Salinity, in particular, had a strong influence on overall mesofauna community composition. Our results provide further insight into soil fauna assemblages in Northern Finland and further, more extensive research would contribute to a more comprehensive foundation. This will allow for better monitoring of community changes and responses in the face of climate change in the low Arctic. [ABSTRACT FROM AUTHOR]

This description outlines a Geographic Information System (GIS)-based rainfall-runoff model that simulates the flow of water in a river basin. The model operates on a daily time step and consists of 4 non-linear storage components: Interception, soil moisture, channel, and groundwater. It employs (SCS) Unit Hydrograph model to determine unit hydrograph ordinates. The model replicates the movement and storage of water in various parts of the basin, including vegetation, the soil surface, the soil profile, and groundwater layers. To address uncertainty, a Monte Carlo simulation feature is integrated into the model. Monte Carlo Simulation involves predicting outcomes by generating numerous iterations using estimated ranges of values for variables with inherent uncertainty. This feature generates required number of sample sets with random parameter values. The model is run for all these realizations during a calibration period, and performance metrics like NSE are calculated for each calibration year to assess prediction uncertainty, model parameter weights are computed by normalizing the corresponding likelihood values. These weights sum up to one and represent the probabilistic distribution of predicted variables, illustrating the impact of structural and parameter errors on model predictions. A sensitivity analysis reveals that the Muskingum constants K and X have the greatest influence on model performance, while parameters Фgw, Фsw, Фfc, and Фpc have a minimal effect on the model's performance. The outcomes presented in the findings indicate that the Soil moisture accounting Model successfully forecasted peak discharge by leveraging the existing historical data. The accuracy of both volume and timing in the predictions suggests the model's appropriateness for the examined catchments. [ABSTRACT FROM AUTHOR]

Effects of different management measures of afforestation on SWC (a) and the Pearson correlation coefficient between different impact factors of afforestation and the R (b) in northern China. [Display omitted] • We collected data comprising 1226 observations at 98 sites in northern China to assess the variation in soil water content (SWC) by afforestation. • The SWC has been decreased at rates of 0.6 mm decade–1 and 3.2 mm decade–1 by coniferous forest and broadleaf forest, respectively. • The effects of afforestation on soil water depend on prior land use types, tree taxa and the mean annual precipitation regime. • Afforestation might lead to a soil water deficit crisis in northern China in the long term at the regional scale. Trading water for carbon has cautioned large-scale afforestation in global drylands. However, model simulations suggested that the consumption of soil water could be partially offset by increasing precipitation due to vegetation feedback. A systematic meta-analysis of long-term and large-scale field observations is urgently required to address the abovementioned limitations, and the implementation of large-scale afforestation since 1978 in northern China provides an ideal example. This study collected data comprising 1226 observations from 98 sites in northern China to assess the variation in soil water content (SWC) with stand age after afforestation and discuss the effects of tree species, precipitation and conversions of land use types on SWC. We found that the SWC has been decreased by coniferous forest and broadleaf forest at rates of 0.6 and 3.2 mm decade–1, respectively, since 1978. There is a significant declining trend of SWC with the stand age of plantations, and the optimum growth stage for plantation forest is 0–20 a in northern China. However, we found increases in SWC for the conversion from grassland to forest and in the low-precipitation region, both are corresponding to the increased SWC in coniferous forest. Our study implies that afforestation might lead to a soil water deficit crisis in northern China in the long term at the regional scale but depends on prior land use types, tree taxa and the mean annual precipitation regime, which sheds light on decision-making regarding ecological restoration policies and water resource management in drylands. [ABSTRACT FROM AUTHOR]

Addressing impacts of flash droughts (FDs) on the water‐food nexus requires a understanding of FD mechanisms and drivers at the watershed level. Examining climatic drivers, dry and wet spell lengths from 1980 to 2019, we analyzed FD spatial and temporal characteristics, emphasizing areal extent, onset time, and duration. Our findings reveal substantial variations in FDs among different watersheds. Notably, watersheds in the Southern Hemisphere are witnessing expanding, faster‐developing, and longer‐lasting FDs, aligning with climate variations in precipitation and temperature. Additionally, at the watershed scale, the onset and duration of FDs are more influenced by the intensity (magnitude and variability) of climatic drivers than the average length of wet and dry periods. FD‐extents, however, correlate with both climatic conditions and wet and dry periods, underscoring watershed connectivity. Ultimately, our results underscore the necessity for research to comprehend the interplay between FDs and watershed characteristics and how it manifests in overall water resource management. Plain Language Summary: Flash droughts (FDs), which are sudden and severe dry periods, are causing problems for our water and food systems and making it harder to prepare for disasters. To address these challenges effectively, it is crucial to gain a thorough understanding of the underlying mechanisms and factors driving FDs at the watershed level. In this study, we looked at climatic patterns alongside the lengths of dry and wet periods spanning from 1980 to 2019. Our primary focus was on three key aspects: the extent of FDs, when they begin, and how long they persist. Our research findings demonstrate considerable variations in FDs occurrences across different regions. Notably, in the Southern Hemisphere, FDs are expanding rapidly, developing more swiftly, and enduring for extended periods, closely mirroring shifts in precipitation and temperature patterns. Interestingly, the onset and duration of FDs seem to depend more on the intensity of climatic factors than on how long it's been dry or wet. The expansion of FDs in a region is linked to both the climatic and dry/wet periods, emphasizing the geophysical connectivity within a watershed. Key Points: Watersheds in tropical, temperate climates, and with savanna and grassland land cover are more susceptible to flash droughts (FDs)FDs extents are affected by intraannual precipitation variability, but not by intraannual air temperature variabilityThe onset and duration of FD at the watershed scale are influenced more by climate variables, than average wet/dry spell periods [ABSTRACT FROM AUTHOR]

The response of soil microorganisms and plants in soil ecosystems to biochar is well recognised. However, biochars' impact on large soil animal, such as ants, is inadequately understood, with only limited studies focusing on the abundance and mortality rates of some specific ant species. In this study, soil physicochemical properties, and ant community diversity and functional characteristics were compared between experimental plots with and without biochar application. No significant differences in soil (soil physicochemical properties) or ants (ant community richness, species abundance, and morphological characteristics) were observed between the two plots before biochar application. However, the biochar-treated plot soil surface temperatures, pH, and soil water content were significantly higher after 48 weeks. Biochar application promoted Cardiocondyla nuda (by 426%) and Formica japonica abundance (by 93%), but decreased Solenopsis invicta invasive ant species richness (by 54%), consistent with the fact that changes in soil properties were more beneficial to the former two species. In addition, in biochar-treated plots, F. japonica and S. invicta generally showed larger body size (18% and 6.7%), larger eyes (2.7% and 4.0%), and longer femurs (6.3% and 7.9%), which enabled them to respond better to potential barriers, such as plants. Our results highlighted that, besides species abundance and community structure, certain ant functional morphological indicators were also informative in evaluating biochar ecological implications. Highlights: Biochar application enhanced soil temperature, pH, and water content. Ants showed larger body size, larger eyes, and longer femurs with biochar application. Biochar promoted ant richness by creating ant-preferred habitats. [ABSTRACT FROM AUTHOR]

Vessel traits contribute to plant water transport from roots to leaves and thereby influence how plants respond to soil water availability, but the sources of variation in fine root anatomical traits remain poorly understood. Here, we explore the variations of fine root vessel traits along topological orders within and across tropical tree species. Anatomical traits were measured along five root topological orders in 80 individual trees of 20 species from a tropical forest in southwestern China. We found large variations for most root anatomical traits across topological orders, and strong co-variations between vessel traits. Within species, theoretical specific xylem hydraulic conductivity (K th) increased with topological order due to increased mean vessel diameter, size heterogeneity, and decreased vessel density. Across species, K th was associated with vessel fraction in low-order roots and correlated with mean vessel diameter and vessel density in high-order roots, suggesting a shift in relative anatomical contributors to K th from the second- to fifth-order roots. We found no clear relationship between K th and stele: root diameter ratios. Our study shows strong variations in root vessel traits across topological orders and species, and highlights shifts in the anatomical underpinnings by varying vessel-related anatomical structures for an optimized water supply. [ABSTRACT FROM AUTHOR]

Endophytes generally increase antioxidant contents of plants subjected to environmental stresses. However, the mechanisms by which endophytes alter the accumulation of antioxidants in plant tissues are not entirely clear. We hypothesized that, in stress situations, endophytes would simultaneously reduce oxidative damage and increase antioxidant contents of plants and that the accumulation of antioxidants would be a consequence of the endophyte ability to regulate the expression of plant antioxidant genes. We investigated the effects of the fungal endophyte Epichloë gansuensis (C.J. Li & Nan) on oxidative damage, antioxidant contents, and expression of representative genes associated with antioxidant pathways in Achnatherum inebrians (Hance) Keng plants subjected to low (15%) and high (60%) soil moisture conditions. Gene expression levels were measured using RNA-seq. As expected, the endophyte reduced the oxidative damage by 17.55% and increased the antioxidant contents by 53.14% (on average) in plants subjected to low soil moisture. In line with the accumulation of antioxidants in plant tissues, the endophyte increased the expression of most plant genes associated with the biosynthesis of antioxidants (e.g., MIOX, crtB, gpx) while it reduced the expression of plant genes related to the metabolization of antioxidants (e.g., GST, PRODH, ALDH). Our findings suggest that endophyte ability of increasing antioxidant contents in plants may reduce the oxidative damage caused by stresses and that the fungal regulation of plant antioxidants would partly explain the accumulation of these compounds in plant tissues. [ABSTRACT FROM AUTHOR]

[Display omitted] A troubling feedback loop, where drier soil contributes to hotter climates, has been widely recognized. This study, drawing on climate model simulations, reveals that maintaining current global soil moisture levels could significantly alleviate 32.9% of land warming under low-emission scenarios. This action could also postpone reaching critical warming thresholds of 1.5 °C and 2.0 °C by at least a decade. Crucially, preserving soil moisture at current levels could prevent noticeable climate change impacts across 42% of the Earth's land, a stark deviation from projections suggesting widespread impacts before the 2060s. To combat soil drying, afforestation in mid-to-low latitude regions within the next three decades is proposed as an effective strategy to increase surface water availability. This underscores the substantial potential of nature-based solutions for managing soil moisture, benefiting both climate change mitigation and ecological enhancement. [ABSTRACT FROM AUTHOR]

The measurement of soil water content is a very important factor in plant cultivation, both from an economic and ecological point of view. Proper estimation of moisture content not only allows for proper yields but can also contribute to ecologically appropriate use of fresh water, of which the world's resources are limited. It is important, for example, that the moisture content in the root area of plants is optimal for their growth, while over-watering can result in losses in the form of water, which seeps below the root layer and is lost. The novel, inexpensive electronic meter for measuring soil moisture is presented in the article. The meter, based on a capacitive method, uses an optimization algorithm to calculate soil electrical permeability and a simplified new formula between soil electrical permeability and volumetric moisture content. Moreover, by using two high-frequency signals for measurements, it is possible not only to estimate moisture content but also soil conductivity. Both readings obtained from the meter not only allow for rational management of crop optimization for economic reasons but are also important for environmental protection. In addition, the inexpensive meter, based on the principle of operation presented, can be made as an IoT module, which allows for its wide application. [ABSTRACT FROM AUTHOR]

Vegetation primarily draws water from soil moisture (SM), with restoration in drylands often reducing SM storage (SMS). However, anomalies have been detected in the Beijing–Tianjin Sand Source Region (BTSSR) of China via the Global Land Data Assimilation System (GLDAS) and Gravity Recovery and Climate Experiment (GRACE). This study quantified the sources of increased SMS in drylands to elucidate the effects of vegetation restoration on SMS. The results indicated the following: (1) In vegetated drylands, 46.2% experienced a significant increase in SMS while 53.8% remained stable; both were positively correlated with the normalised difference vegetation index (NDVI). (2) The increase in SMS was accompanied by a decrease in groundwater storage (GWS), as indicated by the significant correlation coefficients of −0.710 and −0.569 for SMS and GWS, respectively. Furthermore, GWS served as the primary source of water for vegetation. (3) The results of the redundancy analysis (RDA) indicated that the initial vegetation, the driver of the observed trend of increased SMS and decreased GWS, accounted for 50.3% of the variability in water storage. Therefore, to sustain dryland ecosystems, we recommend that future vegetation restoration projects give due consideration to the water balance while concurrently strengthening the dynamic monitoring of SMS and GWS. [ABSTRACT FROM AUTHOR]

Wildfires in Mediterranean areas are becoming more frequent, and the fire season is extending toward the spring and autumn months. These alarming findings indicate an urgent need to develop fire susceptibility methods capable of identifying areas vulnerable to wildfires. The present work aims to uncover possible soil moisture and vegetation condition precursory signals of the largest and most devastating wildfires in Greece that occurred in 2021, 2022, and 2023. Therefore, the time series of two remotely sensed datasets–MAP L4 Soil Moisture (SM) and Landsat 8 NDVI, which represent vegetation and soil moisture conditions—were examined before five destructive wildfires in Greece during the study period. The results of the analysis highlighted specific properties indicative of fire-susceptible areas. NDVI in all fire-affected areas ranged from 0.13 to 0.35, while mean monthly soil moisture showed negative anomalies in the spring periods preceding fires. Accordingly, fire susceptibility maps were developed, verifying the usefulness of remotely sensed information related to soil moisture and NDVI. This information should be used to enhance fire models and identify areas at risk of wildfires in the near future. [ABSTRACT FROM AUTHOR]

The use of bistatic polarimetric SAR for rough surface observation has attracted increasing interest in recent years, with its acquisition of additional polarimetric information. In this paper, we investigate the sensitivity of polarimetric variables to soil moisture and surface roughness, with the intention of locating favorable bistatic geometries for soil moisture retrieval. However, in the bistatic setting, the expanded imaging geometry is convolved with the polarimetric scattering response along with the in-scene variations in the soil moisture and surface roughness. The probing polarization states continuously evolve with the bistatic geometry, incurring varying polarization orientation angles. In this investigation, we propose to first compensate the bistatic polarimetric observations for the geometry-induced polarization rotation. Simulations based on a two-scale rough surface scattering model are then used to evaluate the optimal imaging geometry for the best sensitivity to the soil moisture content. We show the different sensing geometries associated with a full list of common polarimetric variables, as we seek favorable bistatic geometries in non-specular directions. The influences of both surface roughness scales are evaluated, with the small-scale roughness parameter imposing the greatest limitation on our results. [ABSTRACT FROM AUTHOR]

The 2012 satellite ASTER geoscience maps of Australia were designed to provide public, web-accessible, and spatially comprehensive surface mineralogy for improved mapping and solutions to geoscience challenges. However, a number of the 2012 products were clearly compromised by variable green and/or dry vegetation cover. Here, we show a strategy to first estimate and then unmix the contributions of both these vegetation components to leave, as residual, the target surface mineralogy. The success of this unmixing process is validated by (i) visual suppression/removal of the regional climate and/or local fire-scar vegetation patterns; and (ii) pixel values more closely matching field sample data. In this process, we also found that the 2012 spectral indices used to gauge the AlOH content, AlOH composition, and water content can be improved. The updated (new indices and vegetation unmixed) maps reveal new geoscience information, including: (i) regional "wet" and "dry" zones that appear to express "deep" geological characters often expressed through thick regolith cover, with one zone over the Yilgarn Craton spatially anti-correlated with Archaean gold deposits; (ii) a ~1000 km wide circular feature over the Lake Eyre region defined by a rim of abundant "muscovite" that appears to coincide with opal deposits; (iii) a N–S zonation across the western half of the continent defined by abundant muscovite in the south and kaolinite in the north, which appears to reflect opposing E ↔ W aeolian sediment transport directions across the high-pressure belt; (iv) various paleo-drainage networks, including those over aeolian sand covered the "lowlands" of the Canning Basin, which are characterized by low AlOH content, as well as those over eroding "uplands", such as the Yilgarn Craton, which have complicated compositional patterns; and (v) a chronological history of Miocene barrier shorelines, back-beach lagoons, and alluvial fans across the Eucla Basin, which, to date, had proved elusive to map using other techniques, with potential implications for heavy mineral sand exploration. Here, we explore the latter three issues. [ABSTRACT FROM AUTHOR]

To address the issue of estimating soil moisture at a hyper-resolution scale, a methodology referred to as Precision Irrigation Soil Moisture Mapper (PrISMM), that includes three key components, is developed: high-resolution remotely sensed optical and thermal data, surface energy balance modeling, and site-specific soil analysis. An Unmanned Aerial Vehicle/System (UAV or UAS) collects high-resolution multispectral imagery in the Dallas–Fort Worth metropolitan study area. Orthomosaics are converted to thermal inertia estimates in a spatially distributed format using the remotely sensed data combined with a set of surface energy balance modeling equations. Using thermal and physical properties of soil gained from site-specific soil analysis, thermal inertia estimates were further converted from thermal inertia to daily volumetric soil water content (VSWC) with a horizonal resolution of 8.6 cm. A ground truthing dataset of measured VSWC values taken from a Time Domain Reflectometer was compared with model results, producing a reasonable correlation with an average coefficient of determination of (R2) = 0.79, an average root mean square error (RMSE) = 0.0408, and mean absolute error (MAE) = 0.0308. This study highlights a practical approach of estimating VSWC for irrigation purposes while providing superior spatio-temporal coverage over in situ methods. The authors envision that PrISMM can be implemented in water usage management by relating VSWC with weather forecasts and evapotranspiration rates to develop time-based spatially distributed irrigation management plans. [ABSTRACT FROM AUTHOR]

Forest growth varies across landscapes due to the intricate relationships between various environmental drivers and forest management. In this study, we analysed the variation of tree growth potential across a landscape scale and its relation to soil moisture. We hypothesised that soil moisture conditions drive landscape-level variation in site quality and that intermediate soil moisture conditions demonstrate the highest potential forest production. We used an age-independent difference model to estimate site quality in terms of maximum achievable tree height by measuring the relative change in Lorey's mean height for a five year period across 337 plots within a 68 km2 boreal landscape. We achieved wall-to-wall estimates of site quality by extrapolating the modelled relationship using repeated airborne laser scanning data collected in connection to the field surveys. We found a clear decrease in site quality under the highest soil moisture conditions. However, intermediate soil moisture conditions did not demonstrate clear site quality differences; this is most likely a result of the nature of the modelled soil moisture conditions and limitations connected to the site quality estimation. There was considerable unexplained variation in the modelled site quality both on the plot and landscape levels. We successfully demonstrated that there is a significant relationship between soil moisture conditions and site quality despite limitations associated with a short study period in a low productive region and the precision of airborne laser scanning measurements of mean height. [ABSTRACT FROM AUTHOR]

Surface soil moisture (SSM) at high spatial resolution is an essential land parameter for agricultural applications like irrigation mapping, scheduling, crop water stress assessment, etc. However, available satellite derived soil moisture products are inadequate for meeting the requirements of agricultural applications due to coarse scale soil moisture (~10–40 km). In this article, we developed an operational framework for first of its kind sub-km (~500 m) operational soil moisture product over India by utilizing ISRO’s EOS-04 C-band synthetic aperture radar (SAR) data based on active-passive approach. The potential of EOS-04 SAR for sub-km scale is demonstrated and tested over major cropland sites covering highly heterogeneous and dynamic crop conditions in different agro-climatic regions over India which shows a good agreement with in situ datasets with mean ubRMSE, ranging from 0.051 to 0.078 m³ /m³. [ABSTRACT FROM AUTHOR]

Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Drought stress severely affects the normal growth and development of wheat, leading to total crop failure, reduced yields, and quality. To address the lag and limitations inherent in traditional drought monitoring methods, this paper proposes a multimodal deep learning-based drought stress monitoring S-DNet model for winter wheat during its critical growth periods. Drought stress images of winter wheat during the Rise-Jointing, Heading-Flowering and Flowering-Maturity stages were acquired to establish a dataset corresponding to soil moisture monitoring data. The DenseNet-121 model was selected as the base network to extract drought features. Combining the drought phenotypic characteristics of wheat in the field with meteorological factors and IoT technology, the study integrated the meteorological drought index SPEI, based on WSN sensors, and deep image learning data to build a multimodal deep learning-based S-DNet model for monitoring drought stress in winter wheat. The results show that, compared to the single-modal DenseNet-121 model, the multimodal S-DNet model has higher robustness and generalization capability, with an average drought recognition accuracy reaching 96.4%. This effectively achieves non-destructive, accurate, and rapid monitoring of drought stress in winter wheat. [ABSTRACT FROM AUTHOR]

Efficient methods for predicting weather-related hazards are crucial for stakeholders managing environmental risks. Many environmental hazards depend on the evolution of meteorological conditions over protracted periods, requiring assessments that account for evolving conditions. The TAMSAT-ALERT approach addresses this challenge by combining observational monitoring with a weighted climatological ensemble. As such, it enhances the utility of existing systems by enabling users to combine multiple streams of monitoring and forecasting data into holistic hazard assessments. TAMSAT-ALERT forecasts are now used in a number of regions in the Global South for soil moisture forecasting, drought early warning and agricultural decision support. The model presented here, General TAMSAT-ALERT, represents a significant scientific and functional advance on previous implementations. Notably, General TAMSAT-ALERT is applicable to any variable for which time series data are available. In addition, functionality has been introduced to account for climatological non-stationarity (for example due to climate change); large-scale modes of variability (for example El Nino), and persistence (for example of land-surface condition). In this paper, we present a full description of the model, along with case studies of its application to prediction of Central England Temperature, Pakistan vegetation condition and African precipitation. [ABSTRACT FROM AUTHOR]

To compare water stress tolerance traits between different fruit tree species under the same experimental conditions can provide valuable information for understanding the mechanisms underlying water stress tolerance in a broader sense. This work aimed to determine and compare the water stress tolerance of six fruit tree species typically cultivated in Mediterranean regions, i.e., pomegranate, fig, mandarin, avocado, and two Prunus species ('R40' and 'R20') and evaluate its association with water use and growth under water deficit. Iso-anisohydric behavior (low to high water stress tolerance) was assessed through a multi-trait approach and associated with growth and water use under well-watered and water deficit conditions. Avocado and mandarin were classified as species with stricter stomatal control over water potential, while pomegranate, fig, and Prunus spp. showed a lesser stomatal control. This classification was supported by the multi-traits analysis, which showed that avocado and mandarin, in contrast to the rest of the species, were characterized by more sensitive gas-exchange thresholds. A more isohydric behavior was associated with lower soil water use capacity, but higher root hydraulic conductivity, and a lower growth capacity. Some traits, such as the fraction of transpirable soil water thresholds, root hydraulic conductivity, and residual soil water content, provide valuable information to discriminate between species or genotypes that are better adapted to water deficit conditions. These traits explain the position of the species in the iso-anisohydric spectrum and allow us to understand and develop better strategies for water management in agricultural systems. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) is crucial for improving crop water-use efficiency and facilitating precision irrigation. The Penman–Monteith (P-M) model is a widely used approach for ET calculation, with canopy resistance (rc) acting as a critical determinant of accuracy that is greatly affected by meteorological, crop, and soil factors. This study focused on the calibration of two rc models: Jarvis (JA) and coupled resistance (CO), utilizing ant colony optimization (ACO) and the least square method (LSM). Data from an eddy covariance system and a meteorological station in the Huailai summer maize field (115°47'E, 40°20'N) for the year 2013 were employed for model parameterization. Performance evaluation of these models was conducted using ET measurements obtained through the eddy covariance system in 2014. Path analysis was conducted to elucidate the impact of net radiation (Rn), temperature (T), vapor pressure deficit (VPD), soil water content (θ) and leaf area index (LAI) on rc. Results revealed a decrease in rc during growing season, with influencing factors ordered as Rn, LAI, VPD, T, and θ. The CO model optimized by ACO exhibited superior accuracy, with R2 of 0.89. Integration of the ACO-optimized the CO model into P-M model for ET estimation also demonstrated the highest accuracy with R2 of 0.72. JA model optimized by ACO provided satisfactory results in both parameters calibration and ET estimation. Therefore, the ACO-optimized CO model was recommended as the optimal approach for rc calculation of summer maize in semi-arid area. Additionally, the JA model optimized by ACO was proposed as a credible alternative to the CO model. These findings contribute to the refinement of ET estimation methodologies, offering valuable insights for precision agricultural water management practices. [ABSTRACT FROM AUTHOR]

As the Hass avocado crop expands exponentially in Colombia, concern about its increasing water use is on the rise. This research aimed to develop IS-SAR, a free-access web application to schedule irrigation for Valle del Cauca's Hass growers. We calibrated the water cloud (WCM) and artificial neural network (ANN) models using field data measurements from Hass avocado orchard plots in Valle del Cauca (Colombia) and Sentinel 1 (S1) satellite imagery measurements and evaluated their performance computing the root-mean-square error (RMSE) and Pearson correlation coefficient (r ). IS-SAR estimates the surface soil water content from the most recent S1 image, becomes it in water depth, and recommends to users apply irrigation according to allowable depletion limits, computed from a spatially distributed θ at field capacity and permanent wilting point obtained from a soil database of the study area. Our results indicate that the surface soil water content was retrieved with a better performance by the ANN (RMSE = 0.05 m3 m−3, r = 0.74 ), compared with the WCM (RMSE = 0.06 m3 m−3, r = 0.47 ). IS-SAR simulations in validation orchard plots result in irrigation events of up to 107 L tree−1 for 3.4 h. The IS-SAR web application provides near-real-time irrigation information to assist Hass avocado growers in designing better irrigation routines and improving the regional understanding of water crop consumption. [ABSTRACT FROM AUTHOR]

Since a trend towards aridification is expected in Algeria, as in the countries of the Maghreb and the Mediterranean basin, changes in precipitation and temperature can have a significant impact on various water and energy balance processes and, consequently, on surface soil moisture (SSM). The latter is an important measure for monitoring and even forecasting meteorological and hydrological droughts, as well as irrigation for water resource optimization. This study examines the spatiotemporal sensitivity of SSM to variations in precipitation and temperature in different climatic zones of the Cheliff basin. The monthly mean data from four datasets of SSM, extracted from two reanalysis products (ERA-Land and ERA5), active and passive microwave satellite observations (ESA CCI SM), GLEAM model, along with precipitation and temperature records over the period from 1980 to 2018 from 104 weather stations, were analyzed by using the Modified Mann–Kendall test (MMK) and canonical correlation; the study revealed that (1) SSM generally increased from September to December or March, depending on the dataset; (2) monthly precipitation increased from September to November; (3) SSM decreased from June to August, coinciding with rising temperatures; (4) the results of the canonical analysis revealed that monthly SSM is positively correlated with delayed precipitation from 1 to 3 months, depending on the climatic zone; (5) SSM is negatively correlated with temperatures over the previous 2 months for the stations in Csa and Bsk climate zones and with temperatures over the previous 1 and 2 months for the stations in Bsh climate zone from 1 to 2 months prior, also depending on the climatic zone. These results highlight the crucial role of SSM in monitoring and forecasting weather events such as droughts and provide insights for irrigation strategies aiming to optimize water resources. [ABSTRACT FROM AUTHOR]

Previous studies have emphasized the significant influence of the atmospheric heat source of the Tibetan Plateau (TPHS) on the weather and climate in East Asia, but the causes and mechanisms of the TPHS variations remain unclear. In this study, the physical linkage between the winter northern Eurasian snow depth and early summer (May and June) TPHS during 1950–2019 is investigated. Our results indicate that excessive winter northern Eurasian snow can decrease the early summer TPHS through a delayed hydrological effect. In winter, excessive northern Eurasian snow depths lead to more snowmelt and wetter local soil in early summer. The wetter soil not only reduces the surface temperatures in northern Eurasia but also cools the atmosphere in the middle and upper troposphere. This cooling enhances the meridional temperature gradient between northern and southern Eurasia, which reinforces the westerly jet stream at mid-latitudes. The strong westerly jet stream enhances the sensible heat flux over the Tibetan Plateau (TP) by increasing the near-surface wind speed. Moreover, the enhanced meridional temperature gradient generates an anticyclonic and high-pressure anomaly over the southwestern side of the TP, thus decreasing the latent heat release over the TP. Because early summer marks the beginning of the rainy season on the TP, the TPHS in early summer is dominated by latent heat released by precipitation, which means that the wetter soil caused by the excessive winter snow depth in northern Eurasia eventually weakens the TPHS in early summer. [ABSTRACT FROM AUTHOR]

The oxygen and hydrogen isotopic composition (δ18O, δ2H) of plant tissues are key tools for the reconstruction of hydrological and plant physiological processes and may therefore be used to disentangle the reasons for tree mortality. However, how both elements respond to soil drought conditions before death has rarely been investigated. To test this, we performed a greenhouse study and determined predisposing fertilization and lethal soil drought effects on δ18O and δ2H values of organic matter in leaves and tree rings of living and dead saplings of five European tree species. For mechanistic insights, we additionally measured isotopic (i.e. δ18O and δ2H values of leaf and twig water), physiological (i.e. leaf water potential and gas-exchange) and metabolic traits (i.e. leaf and stem non-structural carbohydrate concentration, carbon-to-nitrogen ratios). Across all species, lethal soil drought generally caused a homogenous 2H-enrichment in leaf and tree-ring organic matter, but a low and heterogenous δ18O response in the same tissues. Unlike δ18O values, δ2H values of tree-ring organic matter were correlated with those of leaf and twig water and with plant physiological traits across treatments and species. The 2H-enrichment in plant organic matter also went along with a decrease in stem starch concentrations under soil drought compared with well-watered conditions. In contrast, the predisposing fertilization had generally no significant effect on any tested isotopic, physiological and metabolic traits. We propose that the 2H-enrichment in the dead trees is related to (i) the plant water isotopic composition, (ii) metabolic processes shaping leaf non-structural carbohydrates, (iii) the use of carbon reserves for growth and (iv) species-specific physiological adjustments. The homogenous stress imprint on δ2H but not on δ18O suggests that the former could be used as a proxy to reconstruct soil droughts and underlying processes of tree mortality. [ABSTRACT FROM AUTHOR]