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Among 50 environments in the United States, we screened 35 hairy vetch (Vicia villosa Roth.) lines for traits of interest to cover cropping. We analyzed the influence of genotype, environment, and the genotype‐by‐environment interaction (G × E) on biomass, vigor, winter survival, emergence, flowering time, and nitrogen fixation. To explore how environments and G × E impacted each trait, we associated environment predictions and G × E loadings with weather and soil parameters. Environment had the largest influence on all traits, representing more than half of the variance. Environment predictions were significantly associated with weather and/or soil parameters for each trait. Biomass was associated with growing degree days, winter survival with freezing degree days without snow cover, growth stage with shortwave radiation, and emergence with soil texture. The G × E interaction was larger than genotypic variance for all traits except for winter survival and flowering time. The G × E interaction loadings were associated with soil sand content for biomass, air temperature for fall vigor and emergence, and snow cover for winter survival. Although it represented the smallest proportion of total variance, genetic effects were significant for all traits except for emergence, Ndfa, %N, and C:N. New hairy vetch breeding lines were superior to all commercially available lines for biomass and winter survival. Biomass harvest timing did not significantly change line rank, indicating that top‐performing lines can be used in diverse management systems. To select for high nitrogen contribution to subsequent crops, breeding programs can indirectly select for biomass rather than expensively evaluating symbiotic nitrogen fixation. [ABSTRACT FROM AUTHOR]

A precise land suitability assessment plays a vital role in modern agriculture to sustain production against population explosions worldwide without affecting natural resources or environmental factors. Further, recent urbanization has led to a reduction in arable land and forced the conversion of non-arable land to arable land. Therefore, developing land suitability with its potential and limitations is essential through advanced techniques like multi-criteria Decision Analysis for the particular area. The current research aimed to assess the land suitability of the Manimutha Nadhi watershed, Tamil Nadu, India, using geographical information system (GIS) and Analytic Hierarchy Process (AHP) methods. This study area, Manimutha Nadhi, covers a total area of 263.89 km2. Using a random sampling technique, 57 soil samples were obtained. The parameters for the AHP study were soil pH, EC, Soil organic carbon (SOC), available NPK, soil texture, and soil erosion. The climatic parameters, Annaula average rainfall (AAR) and Annual average temperature (AAT) and topographic parameter slope of the study area are also used as the criteria for generating final agricultural land suitability. The final suitability map through GIS and AHP was created using weighted overlay analysis. The land suitability class on the basis of FAO classification is highly suitable (S1), moderately suitable (S2), marginally suitable (S3), currently not suitable (N1), and permanently not suitable (N2) for agriculture. The results of the final land suitability map by AHP and GIS revealed that 150.58 km2 (57.09%) of the research region is highly suitable for agriculture (S1). The 29.60 km2 (10.08%) area was moderately suitable (S2) for irrigated agriculture. The 53.37 km2 (20.20%) area was marginally suitable (S3) for irrigated agriculture. The 10.56 km2 (7.53%) area was currently unsuitable (N1) for agricultural uses. The area of about 13.45 km2 (5.10%) was permanently unsuitable (N2) for agriculture. The outcomes can be used as baseline information on the land that could strengthen agriculture production in the Manimutha Nadhi watershed. [ABSTRACT FROM AUTHOR]

Extra and intracellular enzymes help soil microbes to degrade soil organic matter and plant residues into smaller digestible molecules. The goal of this study was to investigate the reaction of urease, alkaline phosphatase, β-glucosidase, and aryl sulfatase to two levels of 0.5% and 1% biochar prepared at 200, 400, and 600°C and corn residues in two clayey and sandy soils. The experiment was conducted as a factorial in a completely randomized design with four replications. The results showed that the addition of amendments changed the biochemical properties of calcareous soils with different textures. Soil enzyme activity increased depending on the use level of biochar and soil texture, while the activity of most soil enzymes decreased with the increase in pyrolysis temperature. The highest increase for the activity of urease (314% in clay soil), alkaline phosphatase (693%) at a rate of 1% of corn residue, β-glucosidase (240% in clay soil) at a rate of 1% of biochar 200°C, and aryl sulfatase (152% in sandy soil) at a rate of 0.5% of biochar 200°C was obtained, while the lowest activity of urease (63% in sandy soil) at the rate of 1% of biochar 600°C, alkaline phosphatase (73%) and β-glucosidase (8% in sandy soil) at a rate of 0.5% of biochar 600°C, and aryl sulfatase (16%) at a rate of 0.5% of biochar 400°C was observed compared to the control. Therefore, to increase the biological and enzymatic activity of calcareous soils, biochars prepared at lower temperatures should be used. [ABSTRACT FROM AUTHOR]

Large grazers modify vegetated ecosystems and are increasingly viewed as keystone species in trophic rewilding schemes. Yet, as their ecosystem influences are context‐dependent, a crucial challenge is identifying where grazers sustain, versus undermine, important ecosystem properties and their resilience. Previous work in diverse European saltmarshes found that, despite changing plant and invertebrate community structure, grazers do not suppress below‐ground properties, including soil organic carbon (SOC). We hypothesised that, in contrast, eastern US saltmarshes would be sensitive to large grazers as extensive areas are dominated by a single grass, Spartina alterniflora. We predicted that grazers would reduce above‐ and below‐ground Spartina biomass, suppress invertebrate densities, shift soil texture and ultimately reduce SOC concentration. We tested our hypotheses using a replicated 51‐month large grazer (horse) exclusion experiment in Georgia, coupled with observations of 14 long‐term grazed sites, spanning ~1000 km of the eastern US coast. Grazer exclusion quickly led to increased Spartina height, cover and flowering, and increased snail density. Changes in vegetation structure were reflected in modified soil texture (reduced sand, increased clay) and elevated root biomass, yet we found no response of SOC. Large grazer exclusion also reduced drought‐associated vegetation die‐off. We also observed vegetation shifts in sites along the eastern US seaboard where grazing has occurred for hundreds of years. Unlike in the exclusion experiment, long‐term grazing was associated with reduced SOC. A structural equation model implicated grazing by revealing reduced stem height as a key driver of reduced soil organic carbon. Synthesis: These results illustrate the context dependency of large grazer impacts on ecosystem properties in coastal wetlands. In contrast to well‐studied European marshes, eastern US marshes are dominated and structured by a single foundational grass species resulting in vegetation and soil properties being more sensitive to grazing. Coastal systems characterised by a single foundation species might be inherently vulnerable to large grazers and lack resilience in the face of other disturbances, underlining that frameworks to explain and predict large grazer impacts must account for geographic variation in ecosystem structure. [ABSTRACT FROM AUTHOR]

Optical methods including laser diffraction have been increasingly used to measure soil texture and particle size distribution. However, they have not been adopted yet as a routine methodology mainly due to the difficulties in comparing their results to more commonly used techniques (i.e., sedimentation methods). Many attempts exist in the literature to find an agreement between methodologies with relative success. In this work, we aim to improve the agreement between methodologies by adjusting parameters of the laser diffraction analysis, including sample treatment (chemical dispersion, carbonate removal, and sand separation), mode of sample addition (subsampling vs. transmittance matching), and analysis parameters (time of sonication and refractive index). Soil texture class determined by laser diffraction agreed with the sieve–hydrometer method in 78% of the runs when the following parameters were used: (1) Refractive index of 1.44 - 0.100i, (2) 180 s of sonication, (3) sand sieving prior to analysis, and (4) sample dispersion by shaking the sample for 1 h with 5% sodium hexametaphosphate. We observed that adding the entire sample to the analyzer (1 g of soil in 100 mL of dispersant) while keeping the appropriate levels of transmittance through dilution (transmittance matching) is a better way of sample addition in comparison to subsampling, especially for coarser soil samples. This work proposes a standard operation procedure that may broaden the adoption of laser diffraction analysis as a routine soil texture methodology. [ABSTRACT FROM AUTHOR]

Soil texture can affect soil temperature, soil moisture, the protection of organic material against microbial degradation, and other soil properties. All these factors potentially influence net nitrogen (N) mineralization. The objective of this analysis is to investigate the relationship between soil texture and net N mineralization using different approaches, including a 10-week laboratory incubation of undisturbed soil cores from 47 sites in California, modeling, and a meta-regression analysis of 461 datasets from 20 studies. In the laboratory incubation as well as in the meta-analysis, total soil N increased significantly with increasing clay content. Net N mineralization expressed in mg kg−1 soil did not change significantly with increasing clay content, but significantly decreased when expressed as a proportion of total soil N. These results are most likely explained by physical and chemical protection of organic molecules by clay minerals. Protection in turn led to the observed increase in total soil N over time. Based on the incubation and measured bulk densities, net N mineralization in the top 15 cm of the soil profile was 30% higher in a sandy loam compared to a clay soil. Model simulations indicated that texture-related differences in soil temperature and moisture have only a small effect on net N mineralization in irrigated agricultural fields under Mediterranean conditions. [ABSTRACT FROM AUTHOR]

The scientific field of precision agriculture employs increasingly innovative techniques to optimize inputs, maximize profitability, and reduce environmental impact. However, obtaining a high number of soil samples is challenging in order to make precision agriculture viable. There is a trade-off between the amount of data needed and the time and resources spent to obtain these data compared to the accuracy of the maps produced with more or fewer points. In the present study, the research was based on an exhaustive dataset of apparent electrical conductivity (aEC) containing 3906 points distributed along 26 transects with spacing between each of up to 40 m, measured by the proximal soil sensor EM38-MK2, for a grain-producing area of 72 ha in São Paulo, Brazil. A second sparse dataset was simulated, showing only four transects with a 400 m distance and, in the end, only 162 aEC points. The aEC map via ordinary kriging (OK) from the grid with 26 transects was considered the reference, and two other mapping approaches were used to map aEC via sparse grid: kriging with external drift (KED) and geographically weighted regression (GWR). These last two methods allow the increment of auxiliary variables, such as those obtained by remote sensors that present spatial resolution compatible with the pivot scale, such as data from the Landsat-8, Aster, and Sentinel-2 satellites, as well as ten terrain covariates derived from the Alos Palsar digital elevation model. The KED method, when used with the sparse dataset, showed a relatively good fit to the aEC data (R2 = 0.78), with moderate prediction accuracy (MAE = 1.26, RMSE = 1.62) and reasonable predictability (RPD = 1.76), outperforming the GWR method, which had the weakest performance (R2 = 0.57, MAE = 1.78, RMSE = 2.30, RPD = 0.81). The reference aEC map using the exhaustive dataset and OK showed the highest accuracy with an R2 of 0.97, no systematic bias (ME = 0), and excellent precision (RMSE = 0.56, RPD = 5.86). Management zones (MZs) derived from these maps were validated using soil texture data from clay samples measured at 0–10 cm depth in a grid of 72 points. The KED method demonstrated the highest potential for accurately defining MZs for irrigation, producing a map that closely resembled the reference MZ map, thereby providing reliable guidance for irrigation management. [ABSTRACT FROM AUTHOR]

In plant roots, arbuscular mycorrhizal fungi (AMF) are the most prevalent microsymbionts, and thereby provide many key ecosystem services to natural and agricultural ecosystems. Despite AMF's significance for the environment and the economy, little is known about the mycorrhizal inoculum potential and diversity of AMF associated with orphan African cereal crops, specially fonio millet (Digitaria exilis stapf.) under field conditions. We hypothesized that the type of fonio millet agroecosystem influences the AMF density and distribution in soils. We therefore, assessed the inoculum potential, density and diversity of AMF spores and soil enzyme activities in five fonio millet agroecosystems belonging to three climatic zones (Sudanian, Sudano-Sahelian and Sudano-Guinean). By combining AMF spore identification from field-collected soils and trap culture, 20 species belonging to 8 genera (Acaulospora, Ambispora, Dendiscutata, Gigaspora, Glomus, Racocetra, Sclerocystis and Scutellospora) were identified. Glomus was the most represented genus with 8 species, followed by Gigaspora (5 species) and Acaulospora (2 species); the remaining genera were each represented by one species. Except for Ambispora which was not found in the Sudanian area, all genera occurred in the three climatic zones. The abundance and diversity of AMF species and FDA-hydrolytic and phosphatase activities varied between fonio millet agroecosystems as well as between climatic zones. Soil pH and soil texture were the variables that best explained the density and distribution of AMF spores. Our results contribute to paving the way towards the development of microbial engineering approaches for agronomic improvement of fonio millet. [ABSTRACT FROM AUTHOR]

Biofuels are essential to ensure the energy transition and mitigating of climate change. However, understanding the impact of land use change (LUC) and management practices on soil organic carbon (SOC) stocks is fundamental to ensuring well‐founded policymaking and assessing the sector's carbon footprint. Here, we conducted a meta‐analysis (511 pairwise observations) to obtain Brazil's SOC stock change factors (SOCscf) for LUC and management practices in sugarcane fields. Our results showed that converting native vegetation to sugarcane reduced the SOC stock in all assessed periods. The conversion from annual crops to sugarcane showed a reduction in SOC stock in the first 10 years but with a recovery over time. The conversion of pasture to sugarcane reduced the SOC stock only in the 10–20‐year period and had a neutral effect in other periods evaluated. However, our dataset showed high variability in SOCscf, with many observations indicating an increase in SOC stock, which is related to degraded pastures. We observed that the SOC accumulation rate for each ton of sugarcane straw was affected by the interaction between soil texture and precipitation. Regarding straw management, a low removal rate (< 34%) did not affect the SOC stock, while moderate (34%–66%) and high (> 66%) removal resulted in losses of 5.0% (SOCscf 0.950) and 9.9% (SOCscf 0.901), respectively. Our results also showed that reduced tillage and vinasse application increased SOC stocks by 24.0% (SOCscf 1.24) and 10.0% (SOCscf 1.10) respectively, proving to be good strategies to support C sequestration in sugarcane fields. Finally, we highlight that our results can contribute to the improvement of public policies and also be used in future life cycle assessment (LCA) and modeling studies, as they provide robust data to establishing regional SOCscf induced by LUC and management practices, enhancing the reliability of the C footprint assessment of biofuel production. [ABSTRACT FROM AUTHOR]

Furrow‐irrigated rice (Oryza sativa L.) production requires additional management options without the cultural strategy of a flood. In 2023, fluridone (Brake) was registered for use in rice production. Precision‐leveling land is an important aspect of maintaining an effective irrigation flow path; however, the removal of topsoil can severely impact crop response from residual herbicides. The objective of this study was to evaluate the impact of fluridone on rice response when applied to a precision‐leveled field following topsoil removal. An on‐farm field study was conducted in 2023 near Osceola, AR, with a Sharkey‐Steele clay complex soil texture. The study consisted of six herbicide treatments applied at the rice three‐leaf stage. These treatments included clomazone, quinclorac, and fluridone at three rates (0.5×, 1×, and 2× of a label rate) and a nontreated control. Across evaluation times, maximum visual rice injury was greater than 25% and 65% for the fluridone 1× and 2× treatments, respectively. Rice canopy coverage was reduced in the fluridone 1× and 2× treatments compared to all other treatments from 6 to 10 weeks after application (WAA). Rice heading in the fluridone 2x treatment was delayed by more than 60 and 30 percentage points at 11 and 12 WAA, respectively, compared to all other treatments. Rough rice yield in the fluridone 2× treatment was reduced by 21% compared to all other treatments. Overall, fluridone 1× and 2× rates caused substantial rice injury and would not be recommended on a precision‐leveled field. Core Ideas: Fluridone at 1× and 2× rates on precision‐leveled ground caused visual rice injury and reduced canopy coverage.Fluridone at a 2× rate on precision‐leveled ground resulted in a severe rice heading delay and yield loss of 21%.Fluridone would not be recommended for use in rice on precision‐leveled fields. [ABSTRACT FROM AUTHOR]

Physicochemical characteristics of soil, especially organic matter and soil texture, affect the optimal plant density in rice (Oryza sativa L.). A split-plot field experiment was done based on a randomized complete block design (RCBD) in four replications in Amol (Northern Iran) on the coastal strip of the Caspian Sea. The experimental treatments, that is, soil fertility (infertile, semi-fertile, and fertile) as the whole-plot factor and plant density (low, medium, and high by 15.2, 19.6, and 27.8 plants m−2, respectively) as the split-plot factor, were studied over 2 years (2022 and 2023). The results indicated the greatest and smallest number of days from planting to tillering and from tillering to flowering for infertile soil, respectively. The maximum root fresh weight was measured during the tillering stage for infertile soil, whereas for fertile soil, the highest root fresh weight was recorded throughout the phases of panicle initiation and flowering. The greatest root length was measured at the tillering stage for 2022 in high-density infertile soil. The lowest number of panicles m−2 and the percentage of full spikelets were obtained from infertile soil. The highest grain yield was obtained from high-density fertile soil. In mechanized rice cultivation, high density is suggested for fertile and semi-fertile soils and low density for infertile soil. [ABSTRACT FROM AUTHOR]

Several recent regional studies have cast doubt on the widespread assumption that nitrogen‐fixing plants (N‐fixers) act as facilitators of neighbouring plant communities. We conducted a meta‐analysis to synthesize the effects of N‐fixers on plant communities and to understand how ecological context moderates these effects. We analysed studies that assessed paired effects of N‐fixers and non‐fixers on soil N, neighbouring‐plant (non‐fixer) biomass and plant community diversity; ecological moderators included climate, soil texture and N‐fixer growth form and invasive status. N‐fixers led to higher soil N and neighbouring‐plant biomass, but lower community diversity compared to non‐fixers. The effect of N‐fixers on neighbouring‐plant biomass was strongly mediated by soil texture; N‐fixer invasive status and growth form were also significant mediators of the facilitative effects of N‐fixers. Synthesis: N‐fixer effects lie on a continuum between facilitation and suppression that is moderated by intrinsic and extrinsic processes, and this analysis provides insight into how these factors moderate the effects of N‐fixers. Overall, N‐fixers facilitate neighbour biomass but suppress diversity, though high variation in these effects can be explained in part by ecological context. [ABSTRACT FROM AUTHOR]

The Soil Water Retention Curve (SWRC) is an essential input for modeling contaminant transport, irrigation scheduling, and other vadose zone soil–water processes. Measurement of SWRC requires instrumentation, skill, time, and cost. Alternatively, SWRC can be estimated from basic soil properties such as bulk density, particle size distribution (PSD), void ratio, plasticity index, etc., but the accuracy of estimates for varying soil textures remains largely unexplored. In this study, the performance of SWRC estimation models based on soil texture was analyzed for improved efficiency and application. Four samples (sand, silt, loam and clay) from the Unsaturated Soil Hydraulic Database (UNSODA) and two field soil samples (silt loam and sandy loam) from agricultural soils of Lower Himalayas were used in the study. Ten SWRC models were categorized and compared based on their applicability and efficiency. Overall, Fredlund and Xing (F&X) based models showed better performance in estimating SWRC for selected soil texture classes. Correlation analysis revealed a significant influence of soil texture class on model performance. Coefficient of variation (CV) showed that the wet region of SWRC was well captured by all models as compared to the dry region. Based on performance, SWRC models were ranked for respective soil texture classes and further evaluated for dry to saturated moisture conditions. Recommended models for respective soil texture classes can be used to estimate SWRC as per the availability of input soil properties, eliminating the need for complex experiments, thus saving considerable time and effort with acceptable accuracy. [ABSTRACT FROM AUTHOR]

The capacity of soil to retain water and make it available to plants is an essential soil functions for the sustainability of terrestrial ecosystems. A lot of progress has been made in estimating water retention and availability as a function of soil texture. On the other hand, a lower effort has been dedicated to seeking correlations between plant-available water (AW) and soil compaction. In this study, we compiled a dataset with 2479 records from experiments conducted in Brazilian soils to evaluate the relationship between AW and bulk density (BD). The dataset was split into sub-datasets defined by soil textural classes to reduce the effect of texture on AW–BD relationships. In each sub-dataset, AW–BD relationships were described by linear regression. In general, there was a weak association between AW and BD. The strongest correlations were found in the Silty Loam (R2 = 0.26) and Loam (R2 = 0.13) classes. However, the partitioning of the overall dataset by textural classes was not effective to eliminate the effect of texture on AW–BD relationships. Still, the data showed that soil compaction may increase or reduce AW. Nevertheless, more experimental research is needed to bring a better understanding of how AW is affected by changes in BD. [ABSTRACT FROM AUTHOR]

In a national park in Northeast Thailand, agricultural land has been converted from natural forest by small-scale farmers for cassava agriculture. We hypothesise that long-termed cassava monoculture leads to the degradation of soil properties. To test the hypothesis, we conducted a five-year (2016–2020) study on the physical and chemical properties of soil in cassava farmland, and also examined the soil properties of its adjacent natural forests, as a control. The examined cassava farmland was converted from the natural forest during the five years from 2011 to 2015. The significant decrease in organic carbon and the increases in exchangeable potassium and bulk density were found in 2016, indicating that these soil properties varied quickly following the farmland conversion. On the other hand, the significant increase in soil nitrogen and the decrease in pH were found later in 2020, indicating that these soil properties were gradually altered by repeated agricultural activities, such as fertilizer application and trampling. In contrast, there were no significant differences in available phosphate, electrical conductivity, cation exchange capacity, and the soil texture (the fractions of sand, silt, and clay) among the forest and farmland soils. The cation exchange capacity was positively correlated to the fraction of clay, the organic carbon, and pH. The use of glyphosate and paraquat herbicides is prohibited within national parks in Thailand. However, in 2020, glyphosate was detected in farmland soil (up to 5.0 mg kg-1) during both the rainy and dry seasons, and glyphosate (up to 2.5 mg l-1) was detected in stream water from the farmland during the dry season at least in 2020. Soil degradation and herbicide pollution may carry a high risk of causing irreversible changes in terrestrial ecosystems. We discuss the root causes of this issue from perspectives of agricultural production, economy, and the environmental impact, and propose effective policy measures. [ABSTRACT FROM AUTHOR]

Nontoxic alternatives to chemical soil fumigants for suppressing soilborne pathogens such as Fusarium oxysporum (Fo), one causative chlamydosporeagent of strawberry black root rot complex prevalent in the Southeastern United States. are urgently needed. A promising alternative is anaerobic soil disinfestation, in which soil is amended with labile organic materials, inigated to field capacity, and tarped to induce anaerobic fermentation for a brief period before planting. Pathogen-suppression mechanisms of anaerobic soil disinfestation include anaerobic conditions and generation of reduced metal cations (Fe2+ and Mn2+) and volatile fatty acids (VFAs; e.g., acetic. n-butyric, isovaleric, and others). However, little is known about how the interaction between VFAs, reduced metals, soil texture, and liming influences suppression of Fo. We investigated Fo suppression by VFAs and reduced metal cations in both aqueous and soil - based incubation trials. Inoculum containing Fo chlamydospores was added to aqueous medium containing either 5 or 10 mmol/liter VFAs and either 0.01 or 0. 05 % (wilwt) reduced metals. In soil - based incubations. chlamydosporeagent containing inoculum was applied to sandy, sandy loam, and silty clay soil saturated by solutions containing 10 or 20 mmol/liter VFAs with or without 0.05% (wt/wt) reduced metals. VFAs, particularly in combination with Fe2+ in aqueous solutions and Mn2+ in soils, significantly reduced Fo viability. At the same time, liming and higher soil clay content reduced the effectiveness of VFAs and reduced metals for suppressing Fo, highlighting the influence of soil pH and soil texture on anaerobic soil disin festation effectiveness. [ABSTRACT FROM AUTHOR]

The aim of this research was to measure wetting front (WF) advances under various conditions using a physical model. WF advance, along with its distribution in soils, is an important parameter in drip irrigation. It is influenced by many factors, including land slope, emitter discharge and soil texture. The effects of these factors were investigated by constructing a physical model (60 cm wide, 120 cm high and 160 cm long). Experiments were conducted using two heterogeneous soils, three land slopes (0, 10 and 20%), three emitter discharges (2, 4 and 8 l/h) and a constant volume of irrigation water (24 l). The results indicated that, on sloping lands, the wetted area of the WF advance downstream from the emitter was, on average, 20–62% greater than that upstream from the emitter. With an increase in land slope, the wetted depth under the emitter decreased by 3–18%. When the land slope was changed from 0 to 10% and then again from 10 to 20%, the maximum radius of the WF increased, on average, by 32, 44.8 and 77.5% for discharges of 2, 4 and 8 l/h, respectively. [ABSTRACT FROM AUTHOR]

Soil is a one of the important physical evidence that could be encountered in any objects including car tire, shoes, or clothes. This study presents the comparison of the soils in Ömerli Dam, Istanbul-Türkiye. 35 of soil samples from 7 different regions have been collected around the lake. FTIR and ICP-OES have been utilized for structural analysis and detection of metal contect in soil samples. Moreover, textural analysis, pH, sedimentation, color tests have been systematically investigated. The image of soil samples is also captured under different light of sources by VSC 8000. The outcome shows that discrimination of soil samples could be studied using various techniques including FTIR, textural analysis, metal concentrations and their color. ICP-OES analysis showed that the soil have various elements such as Si, Fe, Mg, Ca, Cu with a different amounts which provide discrimination for soil samples. The natural pH of the samples varied between 6.1 and 8.3 that are from slightly acidic to moderately alkaline character. [ABSTRACT FROM AUTHOR]

This study aims to examine the physical and chemical conditions of the soil in the rhizosphere of Rhizophora sp. mangroves in East Bintuni Village. The soil samples were collected from two locations, namely, the Rhizopora mangrove around the central market and the mangrove forest on Jalan Nusantara. The results of the laboratory analysis showed that the soil of the Mangrove Mangrove Around the Central Market has a soil texture of 3.75%; dust 54.80%; clay 41.45% so that based on the soil texture triangle by the United States Department of Agriculture (USDA), it belongs to the Silty clay class. The C-organic value of mangrove soil around the market was 5.90% and the archipelago mangrove forests were 5.12% in the very high category. The pH value of the Rhisphere mangrove is 2.95, and the pH value is 3.82, both locations of the pH criteria were very acidic. The Al and Fe values of the RH mangrove are very high (22.86 cmol/kg) and the C-Organic value is very low (39.6 and 41.1, respectively) while the CEC value is medium (18.8 and 41.2, respectively). The results could inform conservation and management practices, helping to preserve and restore mangrove habitats in the region and potentially guiding similar efforts in other coastal areas. In addition, research could examine the long-term effects of these soil conditions on mangrove ecosystems' ability to provide critical ecological services, such as carbon sequestration and coastal protection. [ABSTRACT FROM AUTHOR]

Objectives: Flash floods are natural disasters caused by sudden rise in water levels in mountainous rivers, which are characterized by instantaneity and great destructiveness. In recent years, the frequent occurrence of flash floods in Longnan city, Gansu province, has posed a serious threat to the safety of local people's lives and property, thus it is urgent to carry out a risk assessment of flash floods in this region. Methods: This study takes Longnan city as the study area, and utilizes the MaxEnt model combining with the particle swarm algorithm to evaluate the vulnerability of study area based on 834 flash flood hazard points investigated and 32 disaster-causing factors. It also predicts the spatial pattern changes and potential mass migration trends of the future flash flood vulnerability areas based on three periods of climate data from the current period (2021— 2040) and the future period (2041— 2060, 2061— 2080, 2081— 2100). Results and Conclusions: The area under receiver operating characteristic curve of the results of the study in each period is above 0.85, which indicates that the precision of the results of the method is good. The main cause factors in this study area are driest month precipitation, monthly mean diurnal temperature dif‐ ference, coefficient of variation of precipitation, warmest month maximum temperature, land use, distance from the river, soil texture, profile curvature, elevation, and topographic relief. The flash flood-prone areas in the study area varies in different periods, but are mainly distributed in Wudu District, Wen County and Tanchang County, and the simulation results for the three future periods (2041—2060, 2061—2080, 2081— 2100) reflected a decreasing trend compared with the current period (2021—2040). [ABSTRACT FROM AUTHOR]

Uniform plant spacing, seeding depth, and emergence are important factors heavily influenced by both machine settings and soil conditions. Understanding load distribution across the planter toolbar at varying planter settings and soil conditions provide feedback to improve planter performance and achieve desired seed placement consistency. One important soil property that affects opening disc load requirement in creating seed trench is soil texture which relates to soil strength. However, none of the existing methods (soil apparent electrical conductivity (ECa) maps, historic soil maps, and cone penetrometer) provide accurate soil strength data on a high spatial resolution which could be used to optimize planter performance. This study was conducted to (1) quantify the percentage of time row-planters need uplift during planting and (2) quantify opening disc loads using real-time machine control system recorded data across different ECa zones. Results showed that uplift events varied from 13 to 18% with wing and track sections revealed higher instances of uplift. Higher instances of uplift were observed on the non-track section for planter with wing wheels. Results revealed a modest correlation between soil ECa and opening disc load with 435 N more or 12% higher opening disc load applied on high soil ECa zones as compared in low soil ECa zones. [ABSTRACT FROM AUTHOR]

Restoring biological crust (biocrust) in disturbed drylands is challenging due to the difficult environmental conditions, such as limited soil moisture, low soil nutrients, and extreme temperatures, that impede growth. Understanding how the key components of biocrust—mosses, lichens, and cyanobacteria—react to different environmental factors informs the optimal timing, locations, and species composition for biocrust reintroduction, thereby increasing the likelihood of establishment. Here, we inoculated soils with a diverse range of biocrust organisms, analogous to seeding an area with diverse vascular plant seeds, and varied environmental conditions to observe how these changes influenced the development and functions of reintroduced biocrust. We found that by manipulating soil texture and time spent wet, we can change the proportional cover of biocrust within a restoration‐like setting. Specifically, we found that 4 months after inoculation, finer textured soils that received more water become dominated by moss cover, while coarser textured soils with less water remained dominated by cyanobacteria cover, and the interactions between texture and time spent wet strongly influenced cover. We found biocrust morphological group cover had a small, but detectable, effect on ecosystem functions (soil stability and nitrogenase activity, a proxy for nitrogen fixation), but that environmental conditions had a stronger impact on the functions we measured. Manipulative experiments in controlled environments, like this one, can help elucidate the mechanisms underlying the establishment rate and patterns of biocrusts post‐inoculation, and inform implementation of inoculations in the field. [ABSTRACT FROM AUTHOR]

Nutrient cycling in desert ecosystems is heavily reliant on the fine root turnover and litter decomposition processes of dominant plant species. Based on field investigations and laboratory experiments, we explored fine root production (FRP) and turnover of Salsola passerina in Alxa steppe desert, and assessed fine root and leaf litter input and its correlation with soil C and N stocks, and then compared the variability of soil physicochemical properties at the site below and the interspace of S. passerina canopy. Results showed that fine root biomass dynamics of S. passerina were consistent with soil water content. Annual FRP of S. passerina was 243.3 g m−2 yr−1 and the turnover rate was 2.0 per year. S. passerina contributed 172.2 g C m−2 and 6.8 g N m−2 to soil from its fine root senescence and leaf litter input annually. Compared to the canopy interspace, the soil texture and fertility beneath the shrubs significantly improved, while the soil salinity decreased. The results indicated that the activities of desert shrub growth provided the degraded soil with abundant nutrients through fine root turnover and litter decomposition processes, which promoted soil texture and nutrition heterogeneity at the stand scale, and played an important role in degraded dryland restoration. [ABSTRACT FROM AUTHOR]

Soil organic carbon (SOC) is a crucial component of the global carbon cycle, playing a significant role in ecosystem health and carbon balance. In this study, we focused on assessing the surface SOC content in Shandong Province based on land use types, and explored its spatial distribution pattern and influencing factors. Machine learning methods including random forest (RF), extreme gradient boosting (XGBoost), and support vector machine (SVM) were employed to estimate the surface SOC content in Shandong Province using diverse data sources like sample data, remote sensing data, socio-economic data, soil texture data, topographic data, and meteorological data. The results revealed that the SOC content in Shandong Province was 8.78 g/kg, exhibiting significant variation across different regions. Comparing the model error and correlation coefficient, the XGBoost model showed the highest prediction accuracy, with a coefficient of determination (R²) of 0.7548, root mean square error (RMSE) of 7.6792, and relative percentage difference (RPD) of 1.1311. Elevation and Clay exhibited the highest explanatory power in clarifying the surface SOC content in Shandong Province, contributing 21.74% and 13.47%, respectively. The spatial distribution analysis revealed that SOC content was higher in forest-covered mountainous regions compared to cropland-covered plains and coastal areas. In conclusion, these findings offer valuable scientific insights for land use planning and SOC conservation. [ABSTRACT FROM AUTHOR]

Soil erosion is a crucial geo-environmental hazard worldwide that affects water quality and agriculture, decreases reservoir storage capacity due to sedimentation, and increases the danger of flooding and landslides. Thus, this study uses geospatial modeling to produce soil erosion susceptibility maps (SESM) for the Hangu region, Khyber Pakhtunkhwa (KPK), Pakistan. The Hangu region, located in the Kohat Plateau of KPK, Pakistan, is particularly susceptible to soil erosion due to its unique geomorphological and climatic characteristics. Moreover, the Hangu region is characterized by a combination of steep slopes, variable rainfall patterns, diverse land use, and distinct soil types, all of which contribute to the complexity and severity of soil erosion processes. These factors necessitate a detailed and region-specific study to develop effective soil conservation strategies. In this research, we detected and mapped 1013 soil erosion points and prepared 12 predisposing factors (elevation, aspect, slope, Normalized Differentiate Vegetation Index (NDVI), drainage network, curvature, Land Use Land Cover (LULC), rainfall, lithology, contour, soil texture, and road network) of soil erosion using GIS platform. Additionally, GIS-based statistical models like the weight of evidence (WOE) and frequency ratio (FR) were applied to produce the SESM for the study area. The SESM was reclassified into four classes, i.e., low, medium, high, and very high zone. The results of WOE for SESM show that 16.39%, 33.02%, 29.27%, and 21.30% of areas are covered by low, medium, high, and very high zones, respectively. In contrast, the FR results revealed that 16.50%, 24.33%, 35.55%, and 23.59% of the areas are occupied by low, medium, high, and very high classes. Furthermore, the reliability of applied models was evaluated using the Area Under Curve (AUC) technique. The validation results utilizing the area under curve showed that the success rate curve (SRC) and predicted rate curve (PRC) for WOE are 82% and 86%, respectively, while SRC and PRC for FR are 85% and 96%, respectively. The validation results revealed that the FR model performance is better and more reliable than the WOE. [ABSTRACT FROM AUTHOR]

Land suitability assessment is integral to the advancement of precision agriculture. This inquiry is focused on identifying optimal regions for cultivating Alphonso mango in the coastal belt of Maharashtra, spanning across Palghar, Raigad, Thane, Ratnagiri, and Sindhudurg districts. Employing a GIS-based Analytic Hierarchy Process (AHP) methodology, 10 crucial parameters have been considered, encompassing climatic, physical, and chemical soil characteristics: cation exchange capacity, organic carbon, slope, rainfall, soil pH, soil texture, mean annual soil temperature, base saturation, soil drainage, and soil depth. Weights are assigned to these parameters based on expert opinions and existing literature to determine their significance in developing a soil suitability map. The study reveals distinct land suitability zones for Alphonso mango cultivation. The land suitability map designates 25.78% of the study area as highly suitable, while 9.18% is considered unsuitable for Alphonso mango cultivation. To validate the study, the Receiver Operating Characteristic (ROC) curve has been employed, indicating an 83% approval rate for the reliability and performance of the soil suitability. The results categorise soil suitability classes, providing valuable insights for farmers and agricultural planners to make informed decisions regarding Alphonso mango cultivation in similar geoenvironmental regions. [ABSTRACT FROM AUTHOR]

Purpose: Identify soil properties involved in the adsorption of the bacteriophages (phages) ΦITL-1 and ΦRSP, analyzing different soils and substrates used for greenhouse tomato crops. Methods: Soil samples were collected from greenhouses in Mexico Central, and soil properties were obtained using the NOM-021-RECNAT-2000. For phage adsorption, soil or substrate was mixed with a phage solution, using three different Water Retention Capacity (WRC) levels, incubated under shaking to room temperature, and finally, the plaque-forming units were counted for each phage by titration. Results: The phage elution counts showed that the amount of aqueous solution in the mixture is inversely related to the number of viral particles adsorbed on the soil. Furthermore, the soils with a sandy texture had lower adsorption of phages in comparison with the rest of the soils analyzed, which have clay, clay loam, and sandy loam textures. A correlation analysis showed that soil pH and texture are the properties that most influenced phage adsorption. Finally, a principal component analysis showed that Cation Exchange Capacity (CEC) has a direct relationship with phage adsorption. Conclusion: In the present study, we demonstrated that soil texture, pH, CEC, and WRC are determinant variables that affect the adsorption of R. solanacearum phages ΦITL-1 and ΦRSP. Furthermore, we propose that the responsible mechanism may be due to the richness of cations in the soil, which could imply an electrostatic interaction with some exposed phage proteins. These results highlight the influence of soil properties on biocontrol strategies based on phages, which try to reduce the impact of soil-borne bacterial phytopathogens. [ABSTRACT FROM AUTHOR]

This research used the Revised Universal Soil Loss Equation (RUSLE) with Sediment Delivery Ratio (SDR) model. The analytic hierarchy process (AHP) method, while also incorporating the use of a geographic information system (GIS) and remote sensing (RS) to predict the annual soil loss rate and spatialise the processes of water erosion at the scale of the Loukkos Watershed, Morocco. The RUSLE model and AHP parameters were estimated using RS data, and the erosion vulnerability zones were determined using GIS. We used five parameters, including precipitation erosivity, soil erodibility, slope length and steepness, vegetation cover, and soil erosion control practices in the RUSLE. For the AHP technique, we used seven geo‐environmental factors, including annual average precipitation, drainage density, lineament density, slope, soil texture, land use/land cover and landform maps. The results of RUSLE indicated that the average annual soil loss varied from 0 to 2388.27 t·ha−1·year−1. The total estimated annual potential soil loss was approximately 40 790 220.11 t·ha−1·year−1, and a sediment yield estimated by RUSLE‐SDR was 8 647 526.66 t·ha−1·year−1, equivalent to 6.65 Mm3. This value is very close to the measured value of 6.81 Mm3, for a difference of 0.16 Mm3. Furthermore, the results of the AHP indicate that the soil erosion potential index varies from 0 to 0.205315 t·ha−1·year−1. Overall, nearly 13.7% of the area suffered from severe soil erosion exceeding 50 t·ha−1·year−1. Approximately 80% of the Loukkos Watershed area experienced only slight erosion, while the remaining 6% incurred moderate erosion. Integrating GIS and RS into the RUSLE model and AHP helped us robustly estimate the extent and degree of erosion risk. Territorial decision‐makers should adopt our results to develop soil conservation strategies, water management plans and other necessary soil and water conservation measures for this region. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soil infiltration properties (SIPs) are important components of forest hydrological responses; however, few studies have investigated the mechanisms through which soil physical properties affect SIPs. In this study, two SIPs, the initial infiltration rate (IIR) and saturated hydraulic conductivity (Ks), were quantified at five soil depths (0–10, 10–20, 20–30, 30–40, and 40–50 cm) in three forest stands (pine (Pinus taeda), oak (Quercus acutissima), and bamboo (Phyllostachys edulis) forests). We constructed a structural equation model (SEM) to analyze the main physical properties affecting the SIPs and their influence pathways, and the results show that the IIR and Ks values for the whole soil profile decreased as follows: pine forest > oak forest > bamboo forest. Soil total porosity (STP), soil field capacity (SFC), capillary water holding capacity (CMC), saturated water capacity (SWC), and initial soil water content (ISWC) were positively correlated with the SIPs, while soil bulk density (SBD) was negatively correlated with the SIPs. The SEM indicated that the main positive driver of soil infiltration was STP, while the sand content and SBD reduced soil infiltration. Soil texture indirectly affected SBD by mediating STP, and SBD indirectly affected the SIPs through SWC. These results provide data that support the simulation of subsurface hydrological responses in forests and have significant implications for forest management. [ABSTRACT FROM AUTHOR]

Tourist trampling is a serious disturbance affecting the soil structure and microbial community in forests. However, it is still unclear whether the response of soil microorganisms to trampling is attributed to the alterations in soil physical (soil bulk density and total porosity) or soil chemical (total nitrogen and soil organic carbon) properties. To determine the response and mechanism of soil microbial community composition to tourist trampling, we conducted a field experiment including four levels of trampling intensity (control, mild, moderate, and severe) at the Baotianman forest ecotourism area. With increasing trampling intensity, soil bulk density showed a substantially increasing pattern, whereas soil total porosity, total nitrogen, and soil organic carbon showed a decreasing trend. Compared to the insignificant change under mild trampling, moderate and severe trampling significantly decreased soil bacterial PLFAs (phospholipid fatty acids) by 46.6% and 57.5%, and fungal PLFAs by 36.3% and 61.5%, respectively. Severe trampling showed a significantly negative effect (−4.37%) on the proportion of soil bacterial PLFAs. Changes in soil bulk density and porosity induced by trampling, rather than total nitrogen and soil organic carbon, played a greater role in regulating soil microbial community composition. These findings suggest that soil microbial community composition and biomass are significantly influenced by the changes in soil texture and aeration conditions caused by tourist trampling. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Many soil functions and processes are controlled by the soil particle size distribution. Accordingly, nationwide geoinformation on this soil property is required to enable climate-smart and resilient land management. This study presents a new deep learning approach to simultaneously model the contents of the three particle sizes of sand, silt, and clay and their variations with depth throughout the landscape. The approach allows for the consideration of the natural soil horizon boundaries and the inclusion of the surrounding landscape context of each soil profile to investigate the soil–landscape relation. Applied to the agricultural soil landscape of Germany, the approach generated a three-dimensional continuous data product with a resolution of 100 m in geographic space and a depth resolution of 1 cm. The approach relies on a patch-wise multi-target convolutional neural network (CNN) model. Genetic algorithm optimization was applied for CNN parameter tuning. Overall, the effectiveness of the CNN algorithm in generating multidimensional, multivariate, national-scale soil data products was demonstrated. The predictive performance resulted in a median root mean square error of 17.8 mass-% for the sand, 14.4 mass-% for the silt, and 9.3 mass-% for the clay content in the top ten centimeters. This increased to 20.9, 16.5, and 11.8 mass-% at a 40 cm depth. The generated data product is the first of its kind. However, even though the potential of this deep learning approach to understand and model the complex soil–landscape relation is virtually limitless, its limitations are data driven concerning the approximation of the soil-forming factors and the available soil profile data. [ABSTRACT FROM AUTHOR]

The analysis of ground-penetrating radar (GPR) data is of vital importance for detecting various subsurface features that might manifest as hyperbolic peaks, which are indicators of a buried object or grayscale variation in the case of contrast in the soil texture. This method focuses on identifying exaggerated patterns through a series of image-processing steps. Two GPR images are initially read and preprocessed by extracting channels, flipping, and resizing. Then, specific regions of interest (ROIs) are cropped, and the Fourier transform is further applied to turn them into the frequency domain. With the help of their frequency signatures, these patterns are extracted from the images, and binary masks are constructed to obtain features of interest. These masked images were reconstructed and merged to make hyperbolic features visible. Finally, Local Binary Pattern (LBP) analysis is used to emphasize these hyperbolic peaks, thereby facilitating their recognition across the whole image. The proposed approach improves the detection of performance subsurface features in GPR data; hence, it is an important tool for geophysical surveys and other related applications. The results prove the high performance of the proposed procedure in improving GPR image characteristics. [ABSTRACT FROM AUTHOR]

The resource rule hypothesis predicts that geographic differences in body size among populations of organisms are due to the amount, availability, and quality of food resources. For instance, the body size of large herbivores is often correlated with soil characteristics because better soils produce better forage. In semiarid environments, rainfall variation is an important driver of forage availability, especially highly nutritious annual forbs. Thus, in such pulsed‐resource environments, it is unclear whether the body size of large herbivores is influenced by fixed resources correlated with soil characteristics, irregular resource pulses correlated with rainfall, or both. Furthermore, it is not clear whether phenotypic expression is a function of forage quality or quantity. During the early autumns of 2011–2018, we captured 4554 white‐tailed deer (Odocoileus virginianus) on seven rangeland sites in the semiarid climate of South Texas, USA. The sites range from coastal to 140 km inland and represent gradients in both soil texture and annual rainfall. We recorded age‐ and sex‐specific indices of skeletal size, antler size, and body mass. Site‐specific soil characteristics explained most of the variation in skeletal size; percent sand was inversely related to skeletal size. For environmentally sensitive phenotypes (antler size and body mass), both soil characteristics and rainfall were influencers; increases in rainfall reduced the negative effect of sand. Percent sand and rainfall were positively correlated with annual biomass of preferred forbs, yet all phenotypic traits declined with increases in forb quantity. Increases in percent shrub cover increased all phenotype sizes. Our data suggest that the phenotypic expression of large herbivores in semiarid environments is driven by forage quality via edaphic characteristics rather than forage quantity via rainfall. Specifically, less sand in the soil allows for the development of shrub communities, which in turn provide a consistent source of forage in a variable, pulsed‐rainfall environment. Although forbs are of higher quality, they are highly ephemeral. The availability of a consistent source of forage may enable white‐tailed deer to extend time invested in body growth, which results in greater phenotype size. Our findings align with the resource rule hypothesis that identifies resource availability as a fundamental element explaining geographical variation in phenotypic expression. [ABSTRACT FROM AUTHOR]

Apparent thermal conductivity of soil (λ) as a function of soil water content (θ), i.e., λ(θ) is needed to determine the heat flow in soil. The function of λ(θ) can be used in heat and water flow models for simplicity. The objective of this study was to develop a sigmoidal model based on logistic equation for entire range of soil water contents and a wide range of soil textures that can be used in simulation of heat and water flow in respected modes. Further, performance of the developed sigmoidal model along with two other models in literature was evaluated. In the proposed sigmoidal model, the constants of this model are estimated based on empirical multivariate equations by using soil sand content and bulk density. The sigmoidal model was validated with good accuracy for a wide range of soil textures, as the relationship between the measured and predicted λ showed slope and intercept values of nearly 1.0 and 0.0, respectively. Comparison of the results obtained by sigmoidal model with those obtained from Johansen and Lu et al. models indicated that, the sigmoidal model was superior to the other two models in prediction of λ for a wide range of soil textures and soil water contents. Furthermore, comparison with a recently proposed model by Xiong et al. indicated that our sigmoidal model is superior. Therefore, our developed sigmoidal model can be used in heat and water flow models to predict the soil temperature and heat flow. [ABSTRACT FROM AUTHOR]

Accurate estimation of infiltration rates is crucial for effective irrigation system design and evaluation by optimizing irrigation scheduling, preventing soil erosion, and enhancing water use efficiency. This study evaluates and compares selected infiltration models for estimating water infiltration rates in the Shillanat-iv irrigation scheme in northern Ethiopia. Soil samples were collected to determine textural classes using hydrometer soil texture analysis and the United States Department of Agriculture (USDA) textural triangle. The soil textural map of the study was created using the inverse distance weight interpolation technique in ArcGIS version 10.4. Infiltration rates were measured using the double-ring infiltrometer for five soil textures: clay loam, loam, sandy clay loam, clay, and sandy loam. Six infiltration models (Kostiakov, Modified Kostiakov, Revised Modified Kostiakov, Philip, Horton, and Novel) were employed and evaluated using statistical parameters. Model calibration and validation were conducted using data from 38 points within the study area. The parameter values of the infiltration models were optimized using SPSS statistical software using least-squares errors. The results showed that, Revised Modified Kostiakov, Modified Kostiakov, and Novel infiltration models demonstrated superior capability in estimating infiltration rates for clay loam, loam, and sandy loam soil textures, respectively. Horton's model outperformed other models in estimating infiltration rates for both sandy clay loam and clay soil textures. The appropriately fitted infiltration models can be utilized in designing the irrigation system to estimate the infiltration rate of soil textures within the selected irrigation scheme and at similar sites with comparable soil textures. [ABSTRACT FROM AUTHOR]

Vineyards hold considerable soil variability between regions and plots, and there is frequently large soil heterogeneity within plots. Clay content in vineyard soils is of interest with respect to soil management, environmental monitoring, and wine quality. However, spatially resolved clay mapping is laborious and expensive. Gamma-ray spectrometry (GS) is a suitable tool for predicting clay content in precision agriculture when locally calibrated, but it has scarcely been tested site-independently and in vineyards. This study evaluated GS to predict clay content with a site-independent calibration and four machine learning algorithms (Support Vector Machines, Random Forest, k-Nearest Neighbors, and Bayesian regulated neuronal networks) in eight vineyards from four German vine-growing regions. Clay content in the studied soils ranged from 62 to 647 g kg−1. The Random Forest calibration was most suitable. Test set evaluation revealed good model performance for the entire dataset with RPIQ = 4.64, RMSEP = 56.7 g kg−1, and R2 = 0.87; however, prediction quality varied between the sites. Overall, GS with the Random Forest model calibration was appropriate to predict the clay content and its spatial distribution, even for heterogeneous geopedological settings and in individual plots. Therefore, GS is considered a valuable tool for soil mapping in vineyards, where clay content and product quality are closely linked. [ABSTRACT FROM AUTHOR]

AbstractThe significance of zinc and iron in crop production, particularly in rice-wheat cropping systems, has been increasingly recognized. The present study aimed to determine the effect of different soil samples collected from the rice-wheat cropping system of Haryana with different soil texture on rice grain yield and micronutrient content using a greenhouse trial with four levels of Fe (0, 25, 50 mg kg−1 as soil and 0.5% foliar spray of FeSO4 at 45 DAS) and four levels of Zn (0, 5, 10 mg kg−1 as soil and 0.5% foliar spray of ZnSO4 at 35 DAS). This study discovered that rice grain yield showed a positive correlation with soil Zn and Fe concentrations in soil before sowing and a negative correlation with soil Fe and Zn concentrations in soil after crop harvesting. In most of the soils studied, foliar spray alone Fe @ 0.5% foliar (45 DAS) and Zn @ 0.5% foliar (35 DAS) improved Fe and Zn concentrations in rice significantly more than soil application of 25 mg Fe kg−1 and 5 mg Zn kg−1, respectively. The rice grain yield in clay soil was 14-42% higher than in sandy soil with different doses of Zn and Fe application. The order of preponderance of different Fe and Zn fractions were CA-Fe < OM-Fe < EX-Fe < FeMnOX-Fe < Res-Fe and Res-Zn > FeMnOX-Zn > OM-Zn > CA-Zn > Ex-Zn in the soils, respectively. Conclusively, concomitant consideration of grain yield and grain Zn and Fe concentrations of rice are the sustainable approach toward food targets achievement. [ABSTRACT FROM AUTHOR]

A 2-month incubation study was carried out using two soil types to determine the nitrogen mineralization of different inorganic–organic amendments. The following seven treatments (Ts) were established: T1 = control (no amendment), T2 = 5 g of dry algae per kg of soil (100%DA), T3 = 136 g of agri-mat per kg of soil (100%GAM), T4 = 61 g of ground grass per kg of soil (100%GG), T5 = 0.6 g of N using lime–ammonium nitrate (LAN) + 2.5 g of dry algae (50%DA50NF), T6 = 50%GAM50NF, and T7 = 50%GG50NF. Three samples per treatment were obtained at 0, 3, 7, 15, 30, 45, and 60 days for N mineral determination. A 2-month glasshouse experiment was established afterward with the following five treatments: T1 = control, T2 = 50%DA, T3 = 50%GAM, T4 = 50%GG, and T5 = 100 NF. The results indicate that nitrogen mineralization was significantly higher in organic–inorganic amendments compared with singular organic amendments. The percentage differences ranged from 157% to 195%. The 50%DA treatment increased the spinach yield by 20.6% in sandy loam and 36.5% in loam soil. It is difficult to fully recommend the 50%DA treatment without field-scale evaluation, but it is a promising option to be considered. [ABSTRACT FROM AUTHOR]

Soil hydraulic parameters are vital for precisely characterizing soil hydrological processes, which are critical indicators for regulating climate change effects on terrestrial ecosystems and governing feedbacks between water, energy, and carbon–nitrogen cycles. Although many studies have integrated comprehensive soil datasets, data quality and cost challenges result in data completeness deficiencies, especially for deep soil information. These gaps not only impede methodological endeavours but also constrain soil parameter-based ecosystem process studies spanning from local profiles to global earth system models. We established a soil dataset across the entire Yellow River Basin (YRB) (795,000 km2) using high-density in situ field sampling. This observation-based dataset contains records of soil texture (2924), bulk density (2798), saturated hydraulic conductivity (2782), and water retention curve parameters (1035) down to a maximum depth of 5 m. This dataset, which extends the recorded data range for deep soil hydraulic parameters, is valuable as a direct data resource for environmental, agronomical and hydrological studies in the YRB and regions with similar pedological and geological backgrounds around the world. [ABSTRACT FROM AUTHOR]

One of the most crucial steps in the practical conservation of endangered endemic mountain plants is to address their population size status and habitat requirements concurrently with understanding their response to future global warming. Three endangered Silene species--Silene leucophylla Boiss., S. schimperiana Boiss., and S. oreosinaica Chowdhuri--in Egypt were the focus of the current study. These species were examined for population status change, habitat quality variables (topography, soil features, and threats), and predictive current and future distributions. To find population size changes, recent field surveys and historical records were compared. Using Random Forest (RF) and Canonical Correspondence Analysis (CCA), habitat preferences were assessed. To forecast present-day distribution and climate change response, an ensemble model was used. The results reported a continuous decline in the population size of the three species. Both RF and CCA addressed that elevation, soil texture (silt, sand, and clay fractions), soil moisture, habitat-type, chlorides, electric conductivity, and slope were among the important variables associated with habitat quality. The central northern sector of the Saint Catherine area is the hotspot location for the predictive current distribution of three species with suitable areas of 291.40, 293.10, and 58.29 km² for S. leucophylla, S. schimperiana, and S. oreosinaica, respectively. Precipitation-related variables and elevation were the key predictors for the current distribution of three Silene species. In response to climate change scenarios, the three Silene species exhibited a gradual contraction in the predictive suitable areas with upward shifts by 2050 and 2070. The protection of these species and reintroduction to the predicted current and future climatically suitable areas are urgent priorities. Ex-situ conservation and raised surveillance, as well as fenced enclosures may catapult as promising and effective approaches to conserving such threatened species. [ABSTRACT FROM AUTHOR]

Tardigrades are omnipresent microfauna with scarce record on their ecology in soils. Here, we investigated soil inhabiting tardigrade communities in five contrasting polar habitats, evaluating their abundance, diversity, species richness, and species composition. Moreover, we measured selected soil physico‐chemical properties to find the drivers of tardigrade distribution among these habitats. In spite of reported tardigrade viability in extreme conditions, glacier forelands represented a habitat almost devoid of tardigrades. Even dry and wet tundra with soil developing for over more than 10 000 years held low abundances compared to usual numbers of tardigrades in temperate habitats. Polar habitats also differ in species composition, with Diaforobiotus islandicus being typical species for dry and Hypsibius exemplaris for wet tundra. Overall, tardigrade abundance was affected by the content of nutrients as well as physical properties of soil, i.e. content of total nitrogen (TN), total organic carbon (TOC), stoniness, soil texture and the water holding capacity (WHC). While diversity and species composition were significantly related to soil physical properties such as the bulk density (BD), soil texture, stoniness, and WHC. Physical structure of environment was, therefore, an important predictor of tardigrade distribution in polar habitats. Since many studies failed to identify significant determinants of tardigrade distribution, we encourage scientists to include physical properties of tardigrade habitats as explanatory variables in their studies. [ABSTRACT FROM AUTHOR]

Understanding the factors affecting the total amount and distribution of soil organic carbon (OC) across different functional carbon pools is important to better define the future management of soil OC stocks. The interactions between soil management practices, local physicochemical soil properties and climate are essential for determining the OC content of the soil. Nevertheless, how these factors affect the total amount of OC and its distribution across carbon pools, i.e., more labile particulate (POC) and more stable mineral‐associated (MAOC) organic carbon, is only partly known. In this study, we assessed topsoil (0–20 cm) samples from 93 arable farms in the southern half of Finland to determine the total amount of OC, and its distribution in MAOC and POC, along with relevant soil properties (amount of clay and silt, aluminium and iron oxides and pH), climate (precipitation and temperature) and fertilization (mineral versus organic). The fertilization did not affect the total soil carbon content (12–58 g OC kg−1 soil). The share of OC in the MAOC fraction (on average 86% of total OC) was relatively stable across the large range of OC contents and clay contents (2%–68%). We assessed the highest feasible MAOC of the soils with boundary line analyses and their OC saturation state with Hassink's equation (Hassink, 1997). Only soils with the lowest clay content (<10% clay) were assumed to be carbon‐saturated, suggesting that most of the studied soils have a capacity to accrue more MAOC. Simple linear regression showed that clay, aluminium and iron oxides explained 9%, 21% and 22% of the variation in MAOC, respectively. Multiple regression analyses including the amount of clay, clay+silt, aluminium and iron oxides, pH, type of fertilization, precipitation and temperature as explanatory variables explained 33%–53% of the variation in OC and MAOC. In all soils, aluminium oxides were important explanatory variable for MAOC, whereas Fe oxides were significant only in soils with higher clay content (>30%). In soils with a low clay content (<30%), pH had added value in explaining MAOC. Altogether, it seems that various climatic, edaphic and soil management‐related factors are context‐dependently controlling OC and that soil textural information alone is not necessarily an adequate predictor to assess the MAOC saturation state of the soil. [ABSTRACT FROM AUTHOR]

Despite the high sand content of Yellow River water in arid Northwest China, locals in the region opt to use muddy water to meet the demand for agricultural irrigation. Muddy water irrigation is a complex process and is still poorly understood. In this study, six sets of saturated soil column infiltration tests were designed, considering soil texture (silt loam, sandy loam, and sand) and muddy water sand content (3%, 6%, 9%, and 12%) as the influencing factors, with two sets of validation tests. Change in hydraulic conductivity (Kh), the average change rate of hydraulic conductivity (ΔK), and cumulative infiltration volume (I) were experimentally studied in the context of muddy water infiltration to respectively establish the separate functional models and developed to fit their relationship with time. The study results indicated that the hydraulic conductivity (Kh) decreased with increasing muddy water infiltration time. For silt loam and sandy loam, Kh stabilized at 0.0030 and 0.0109 cm/min, respectively, after 70 min of infiltration. In contrast, Kh in the saturated sandy soil column significantly declined throughout the muddy water infiltration, showing a 90.84% reduction after 90 min compared to the saturated hydraulic conductivity of the sandy soil. As the sand content of the muddy water increased from 3% to 12%, Kh decreased by 83.99%, 90.90%, 91.92%, and 92.21% for 3%, 6%, 9%, and 12% sand content, respectively, in the saturated sandy soil columns at the end of the infiltration period. The I values were 21.20, 9.29, 7.90, and 6.25 cm for 3%, 6%, 9%, and 12% sand content, respectively. The ΔK values were 0.0037, 0.0041, 0.0043, and 0.0044 cm/min2 for the respective sand contents, at an infiltration time of 80 min. The validation test demonstrated that the segmented function model accurately emulated the changes in hydraulic conductivity of sandy soil textures throughout the infiltration period. Results from this study provide a significant basis for understanding the mechanisms to hinder muddy water infiltration and to efficiently utilize muddy water for irrigation. [ABSTRACT FROM AUTHOR]

Differences in land use type and chronological age affect soil properties and plant community characteristics, which may influence soil structural stability and erodibility. However, knowledge on the effects of soil physicochemical properties on soil aggregate stability and erodibility at different land use years is limited. This study selected five land use types: corn field (Year 38th-y), corn intercropped with cabbage field (Year 38th-y + b), fruit and meridian forest (Year 6th-jgl), naturally restored vegetation (Year 6th-zr), and artificial forest (Year 7th-rgl) in the karst landscape of the Chishui River Basin in Yunnan Province. We aimed to identify the influencing factors of soil stability and erodibility under different land use time series. The results indicated that the mean weight diameter (MWD), the geometric mean diameter (GMD), and soil structural stability index (SSI values) were highest in Y6th-zr and lowest in Y7th-rgl. Conversely, the erodibility K value was lowest in Y6th-zr, suggesting that the soil structure in Y6th-zr exhibited greater stability, whereas soil stability in Y7th-rgl was lower. Redundancy and throughput analyses revealed that organic carbon and water-stable aggregates > 2.0 mm content had higher vector values. Soil bulk density, total nitrogen, organic carbon, and soil texture content were the main factors contributing to soil stability variation (0.338–0.646). Additionally, total nitrogen, organic carbon, total phosphorus, and soil texture content drove the variation in K values (0.15–1.311). Natural vegetation restoration measures can enhance soil structure to a certain extent. These findings highlight changes in soil aggregate stability and erodibility over different land use durations. The research results have important theoretical and practical significance for understanding the differences in soil erosion and soil restoration under different land use patterns in the karst landscapes of southwest China. [ABSTRACT FROM AUTHOR]

Aims: Although soil water deficit is the primary constraint on transpiration globally, the mechanisms by which soil drying and soil properties impact transpiration and stomatal regulation remain elusive. This work aimed to investigate how soil textures and vapor pressure deficit (VPD) impact the relationship between transpiration rate, canopy conductance, and leaf water potential of maize (Zea mays L.) during soil drying. We hypothesize that the decrease in soil–plant hydraulic conductance (Ksp) triggers stomatal closure and the latter is soil specific. Methods: Plants were grown in two contrasting soil textures (sand and loam) and exposed to two consecutive VPD levels (1.8 and 2.8 kPa). We measured transpiration rate, canopy conductance, soil and leaf water potentials during soil drying. Results: Transpiration rate decreased at higher soil matric potential in sand than in loam at both VPD levels. In sand, high VPD generated a steeper drop in canopy conductance with decreasing leaf water potential. The decrease in canopy conductance was well correlated with the drop in Ksp, which was significantly affected by soil texture. Conclusions: Our results demonstrated that variations in canopy conductance were not simply a function of leaf water potential but largely affected by soil hydraulics. These results reinforce a model of stomatal closure driven by a loss in soil hydraulic conductivity. Further studies will determine if soil-specific stomatal regulation exists among species. [ABSTRACT FROM AUTHOR]

Soil nutrient cycling, the distribution of soil aggregates, and their stability are directly influenced by soil texture. Different sizes of soil aggregates provide microhabitats for microorganisms and therefore influence soil carbon (C) and nitrogen (N) mineralization. The purpose of the present study was to assess the aggregate stability and dynamics of carbon and nitrogen in macroaggregate size fractions (1-8 mm) with different clay content from meadow soils. Surface soil samples (0-15 cm) were collected from 4- to 5-year-old forage crops. Four macroaggregate size classes were isolated by dry sieving and analyzed for their mass proportions: fine macroaggregates (FM) (less than 1 mm), medium-fine macroaggregates (MFM) (1-2 mm), mediumcoarse macroaggregates (MCM) (2-4 mm), and large-coarse macroaggregates (LCM) (4-8 mm). The dry mean weight diameter (MWD), organic carbon (OC), total nitrogen (TN), carbon and nitrogen of microbial biomass (C-MB, N-MB) were determined. CO2 emission and net nitrogen mineralized (NM) were measured after 14 weeks of incubation. The amounts of FM were significantly lower than those of intermediate macroaggregates (MCM and MFM) and decreased markedly with increasing clay content within soil macroaggregates. In general, the amounts of macroaggregate size fractions were lowest in soils with high clay content. MWD exhibited a significant correlation with particle size distribution, OC, and MB-C. OC, TN, MB-C, and MB-N contents within macroaggregates increased with decreasing macroaggregate size and increasing clay content of macroaggregate fractions. The CO2 emission and NM content increased with increasing macroaggregate size, indicating higher organic C and N mineralization activity in larger macroaggregates. Mineralization of OC was lowest in macroaggregate fractions with the highest clay content. We conclude that clay content can increase the protection of microbial biomass in meadow soils. Small macroaggregates tend to contain more recalcitrant organic matter compared to larger macroaggregates. [ABSTRACT FROM AUTHOR]

Local morphometric variables (LMVs) are frequently found as weaker predictors than other environmental covariates in digital soil mapping. This study tested and evaluated the performance of a hybrid approach combining gradient boosted regression trees (GBRT) and regularized regression (RR) algorithms in predicting soil textural fractions using a set of LMVs in Khuzestan province, Iran. Here five LMVs (slope gradient, slope aspect, horizontal curvature, vertical curvature, and contour geodesic torsion) were derived from a spheroidal equal-angular DEM as original predictors. The results demonstrated that the hybrid approach improved prediction accuracy for sand, clay, and silt contents by an average of 56% compared to the GBRT models. The importance analysis revealed the significant contribution of tree-based variables obtained from decomposing GBRT models in predicting soil textural fractions. This approach could be recommended for digital soil mapping, particularly in situations of limited environmental covariates or geomorphometric techniques that cannot be easily applied. [ABSTRACT FROM AUTHOR]