Proceedings - Soil Science Society of America最新文献

Soil organic carbon (SOC) in grasslands plays a central role in global carbon cycling, yet how long-term grazing intensity (GI) and soil texture interact to affect SOC fractions remains unclear. We evaluated SOC partitioning into particulate organic matter carbon (POM-C) and mineral-associated organic matter carbon (MAOM-C) after more than 80 years of cattle grazing in a semiarid mixed-grass prairie in South Dakota. Soils (0–30 cm) were sampled across six pastures managed at high, medium, and low grazing intensities and stratified by texture (clay loam vs. silty clay). Bayesian mixed-effects models accounting for pasture-level variation revealed that while GI did not significantly affect MAOM-C stocks, surface POM-C (0–7.5 cm) was significantly higher under high and medium grazing in clay loam soils, with no significant grazing effects observed in silty clay soils. Across depths, POM:MAOM ratios were elevated in coarser soils and under heavier grazing, suggesting greater POM-C accrual but also increased vulnerability to loss. Correlations showed only modest coupling (r ≈ 0.3, p < 0.001) between POM-C and MAOM-C, underscoring that these pools respond to distinct processes. Overall, our findings indicate that soil texture strongly modulates grazing effects on carbon fractions, with coarse-textured soils favoring POM accumulation and finer soils maintaining more stable MAOM stocks. These results highlight the importance of accounting for soil physical context when evaluating grazing as a tool for enhancing grassland carbon sequestration.

This research investigates the improvement of expansive soils by incorporating fly ash, focusing on its impact on soil engineering properties such as plasticity index (PI), swelling potential (SP), California bearing ratio (CBR), maximum dry density (MDD), and unconfined compressive strength (UCS). The different mix proportions comprised of CM (control mix), FSM 1, FSM 2, FSM 3, FSM 4, and FSM 5 (where FSM is fly ash stabilized mix), were subjected to tests after a curing period of 7, 14, and 28 days. Using the experimental result, FSM 4 was determined to be the most effective mix regarding UCS, PI, SP, CBR, and MDD. The response surface methodology (RSM) was used to model the five properties of the most effective mix, producing R² values of 0.9331 for UCS, 0.9189 for CBR, 0.9368 for PI, 0.9286 for SP, and 0.9421 for MDD in order to increase prediction accuracy. The hybrid quantum neural network–Krylov subspace optimization model (QNN-KSO) was introduced and proved to be the best out of the RSM, deep neural network–grey wolf optimization, and random forest–artificial bee colony out of all six criteria, as it resulted in more reliable and accurate prediction of UCS, CBR, PI, SP, and MDD. The hybrid QNN-KSO model produced excellent performance while minimizing the root mean squared error while achieving an R² value of 0.99 making this an improved modeling technique for soil stabilization.

Understanding potassium (K) speciation in soils is essential for evaluating its availability to plants and guiding sustainable nutrient management. In this study, five distinct soils from Taiwan, representing varying management practices and physicochemical properties—including soils with and without long-term K fertilization, alkaline soil, red soil, and forest soil—were analyzed to determine K speciation. A combination of indirect (sequential chemical extraction) and direct (synchrotron-based X-ray absorption spectroscopy) techniques was employed to comprehensively characterize soil K forms. Wet chemical extraction revealed that >95% of total K resides in the residual fraction, while exchangeable, carbonate-bound, Fe/Mn oxide-bound, and organic-bound forms collectively accounted for <5%. X-ray absorption near-edge structure and extended X-ray absorption fine structure analyses provided insights into the local coordination environment of K, revealing a consistent white line feature at ∼3615.2 eV across samples, with intensity trends indicating K availability in the order: alkaline soil > long-term fertilized soil > forest soil > red soil > unfertilized soil. Linear combination fitting indicated that illite-smectite is the dominant K-bearing phase, while soluble and organic-associated K forms vary with soil type and management. This study demonstrates the advantages of combining wet chemical and synchrotron-based spectroscopic approaches for an accurate, multiscale understanding of soil K speciation.

Most irrigation areas in the Yellow River Basin widely use muddy water irrigation, and the sand in the water is the main characteristic that distinguishes muddy water irrigation from clear water irrigation, resulting in a significant difference in its infiltration mechanism compared with clear water. This research aims to determine the influence of muddy water properties on the infiltration process and pore air pressure in the presence of air resistance. Indoor soil column infiltration tests were used to examine the infiltration procedure and the process of pore air pressure change under various muddy water sand contents and sediment particle compositions. The hydraulic conductivity, cumulative infiltration per unit area, and frontal matrix suction in the traditional Green-Ampt (G-A) model were modified, a saturated layer thickness calculation model was introduced, and an improved G-A model considering air resistance based on the layered assumption was established. The research results indicated that the change in pore air pressure over infiltration time may be split into two stages: rapid change and stable change. The sand content and the physical clay content were positively correlated with the pore air pressure and negatively correlated with the saturated hydraulic conductivity. After the wetting front reached 20 cm below the soil surface, compared to the traditional G-A model, the revised model estimated the infiltration time closer to the measured infiltration time. The improved model significantly improves the prediction accuracy and offers theoretical support for the exploration of muddy water infiltration behavior. The higher the sediment concentration and the higher the clay content, the more obvious the superiority of the modified model becomes.

Mountain hay meadows are a high-elevation forage-producing agroecosystem dependent on flood irrigation and nitrogen (N) fertilization to maintain yields, meaning management has great potential to influence greenhouse gas (GHG) emissions. To assess GHG fluxes and inorganic N dynamics in meadows, field monitoring was established at four ranches in Wyoming and Colorado for 24 months from October 2021 through September 2023. At each ranch, three long-term management systems were compared: unirrigated rangeland, irrigated-unfertilized meadow, and irrigated-fertilized meadow. Soil carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) fluxes were measured along with soil samples (0- to 10-cm depth) analyzed for water content, nitrate (NO₃⁻), and ammonium (NH₄⁺). Flood irrigation resulted in 41%–91% increase in annual CO₂ emissions compared to rangelands. Flood irrigation combined with fertilization increased CO₂ emissions by another 19% in 2023. Both irrigated-fertilized and irrigated-unfertilized meadows emitted CH₄ during flooding, while rangeland soils assimilated CH₄ throughout the study. Unexpectedly, N₂O emissions were highest in rangelands and not influenced by irrigation or fertilization in meadows. Soil NO₃⁻ and NH₄⁺ concentrations were low during the growing season and no correlation between inorganic N and N₂O emissions was observed. Calculated global warming potential in meadows revealed GHG emissions were driven mainly by CO₂, indicating that maintaining photosynthetic carbon (C) sequestration in meadows through optimum agronomic management may be an important strategy to balance GHG emissions.

Soil water retention curves (SWRCs) are traditionally determined in the laboratory, but modern sensors enable their measurement under field conditions. This study compared SWRCs obtained from laboratory and field instrumentation within the same soil volume. A well-aggregated tallgrass prairie soil was instrumented with co-located sensors that measured volumetric water content and matric potential at 3.5-cm depth inside collars that prevented root intrusion, minimized lateral flow, and ensured consistent sensor placement. The field experiment was conducted from June 1 to August 11, 2023, capturing multiple wetting and drying cycles. Afterward, the collars were excavated and analyzed in the laboratory using precision mini-tensiometers and a dewpoint water potential meter. Laboratory-derived SWRCs consistently showed greater water contents near saturation compared to field-derived SWRCs, which were consistent across three drydown periods and collars. The two methods produced nonequivalent SWRCs, likely due to sensor responsiveness, air entrapment, and rapid macropore drainage that limited in situ measurement of near-saturation conditions.

Basic indicators of soil health that influence water infiltration, root growth, gaseous exchange, and overall agronomic productivity are soil physical properties such as bulk density (BD), total porosity (TP), particle density (PD), and penetration resistance (PR). Agricultural practices, particularly tillage and land use, are known to alter soil physical properties by disrupting soil structure and altering soil organic matter content. Therefore, this study aimed to assess the effects of conservation agriculture practices, meadows, and woodlands on above-mentioned soil properties. This on-farm study was conducted at 41 sites located within five counties that covered five soil series (Blount, Eldean, Pewamo, Spinks, and Warsaw) in Central Ohio. From November 2023 to July 2024, soils (0- to 10-cm depth) were sampled from cropland under conventional tillage, minimum tillage (MT), and no-tillage (NT), as well as from meadows and woodlands, to evaluate BD, PD, and TP. PR was measured in the field. All land management practices had been in place for at least 15 years prior to sampling. Data were analyzed using a linear fixed-effects model to test the effects of land use within each soil series. Soil TP, BD, and PR varied significantly (p < 0.05) across land management practices and soil series, with woodland soils consistently showing lower BD and PR, and higher TP compared to those under cropland independent of tillage practice and those under meadow, whereas PD did not differ among practices. Soil TP, BD, and PR were significantly related (R² ≥ 0.33, p < 0.001) to soil organic carbon (SOC) content, reflecting a moderate influence of SOC on reducing soil compaction. Overall, these findings highlight the lasting positive impact of relatively undisturbed land use (woodlands) on soil physical health, while also suggesting that NT and MT may require longer timeframes (>15 years) to induce improvements in soil structure and compaction.

Microwave (MW) soil treatment has proven to have the potential to reduce weeds and enhance soil nutrient availability and crop yields. This study hypothesized similar benefits in newly established pastures. Four treatments (Lucerne and Phalaris, with and without pre-sowing MW soil treatment for 120 s) were tested with four replicate plots (1.5 m² each). Three 700 W MW magnetrons, with a frequency of 2.45 GHz, were attached and remotely connected to the controller circuitry of three domestic MW ovens. Soil physio-chemical properties were analyzed, and plots were harvested via mowing three times during the experiment. Pasture samples were assessed for nutritive value. MW treatment increased nitrate, ammonium nitrogen, and potassium in both species plot soil but decreased soil phosphorus. Germination counts significantly increased in MW-treated Lucerne (p = 0.018) and Phalaris (p = 0.002), while weed counts decreased (p = 0.091 and p < 0.001, respectively). MW-treated Phalaris plots had 30% and 26% higher crude protein and metabolizable energy yields compared to controls (p < 0.05). However, MW treatment did not affect Lucerne's nutrient yields (p > 0.05). The findings suggest MW soil treatment can enhance nutrient yields in Phalaris but not Lucerne, while also aiding weed control. Further research is needed to explore the interactions between pasture species and MW treatment. This technology has potential as a sustainable tool for improving pasture productivity and weed management.

This paper establishes standardized terminology and field documentation protocols for cryostructures and cryogenic soil structures in permafrost-affected soils and provides brief guidance on descriptions of ground ice morphology and ice volume estimates. We consolidate permafrost terminology from Russian and North American literature, clarify long-standing ambiguities, and provide explicit guidelines that align with US Department of Agriculture-Natural Resources Conservation Service soil description standards. Our scheme makes critical distinctions between cryostructure, the distribution of ice within soil, and cryogenic soil structure, the morphological structure of soil resulting from ice formation. The scheme organizes cryostructures into three main categories: non-segregated ice, visible segregated ice, and ice matrices. We introduce standardized codes and parameters for field descriptions of ice and soil that enable machine-readable data collection compatible with existing soil information systems. This standardization will significantly enhance the integration of field observations into landscape-scale assessments of permafrost stability, infrastructure vulnerability, and ecosystem response to permafrost thaw, addressing an urgent need for quantitative data to inform modeling and decision-making in rapidly changing Arctic and subarctic environments.

Enhanced efficiency fertilizers, including urease inhibitors (UIs), nitrification inhibitors (NIs), and dual inhibitors (DIs [UI + NI]), are widely used to reduce nitrogen (N) losses and improve crop nitrogen use efficiency (NUE). However, their relative effectiveness across multiple nitrogen loss pathways remains unclear. This study aimed to address that gap through a 31-day soil column experiment and a 25-day soil incubation study using loamy sand soil. Here we assessed the impact of single and DIs on nitrate (NO₃-N) and ammonium (NH₄-N) leaching, ammonia (NH₃) volatilization, nitrous oxide (N₂O) emissions, and residual soil nitrogen. Treatments included UAN alone and UAN with established (Agrotain, Instinct NXTGEN, and Nitrolock) and novel (VLS-UI, VLS-NI, and VLS-UI + NI) inhibitors. The NIs reduced potential NO₃⁻-N leaching by up to 20% compared to UAN and outperformed DIs by 10%. In contrast, UIs and DIs did not reduce NO₃⁻-N leaching. UI treatments increased NH₄⁺-N leaching, while NIs and DIs had no significant effect. DIs were most effective in reducing NH₃ volatilization (82%–89% reduction), surpassing UIs and NIs (68%–75%). N₂O emissions did not differ significantly among treatments. NIs significantly reduced nitrification potential, with VLS-NI showing the greatest reduction (22%). Soil pH decline correlated with increased NO₃⁻-N leaching and nitrification. Total mineral N leaching accounted for 31% of applied N, and gaseous losses (NH₃ + N₂O) accounted for up to 9%. Overall, NIs were more effective in reducing NO₃⁻-N leaching and nitrification, while DIs were best for controlling NH₃ volatilization. These findings highlight the importance of selecting nitrogen stabilizers based on dominant loss pathways and site-specific conditions to optimize NUE and reduce environmental impacts.