Proceedings - Soil Science Society of America最新文献

This study explored the efficacy of soil aggregate indices in quantifying soil structural development, utilizing 5-year field experiment data from the Southeastern United States. The experiment utilized a split-plot design with cover crops (native vegetation as control, cereal rye (Secale cereale L.), winter wheat (Triticum aestivum), hairy vetch (Vicia villosa), and mustard (Brassica rapa) plus cereal rye as the main factor and fertilizer source (no fertilizer as control, inorganic fertilizer with phosphorus, potassium, and elemental sulfur, and poultry litter) as the secondary factor. Aggregate size fractions were determined using the wet-sieving method, and aggregate stability index (ASI), mean weight diameter (MWD), geometric mean diameter (GMD), and fractal dimension (FD) were calculated to assess soil structural stability. Main effects results indicated that cereal rye (55.11%) and poultry litter (50.97%) exhibited the highest ASI values. The highest MWD, GMD, and FD were observed under mustard plus cereal rye (1.187 mm), cereal rye (0.462 mm), and hairy vetch (2.573), respectively. Principal component analysis revealed that cover crops significantly improved soil aggregate structure and stability, overcoming limitations of sole fertilization practices. Regression analysis suggested that ASI, MWD, and GWD positively correlated with soil organic carbon, whereas FD negatively correlated with MWD, GMD, and ASI. Principal component analysis exhibited that FD decreased with increasing soil organic carbon, ASI, MWD, and GMD, demonstrating that lower FD values indicate enhanced soil aggregation and structure. Assessed indices, FD included, effectively gauged soil structural stability. These metrics should be prioritized in managerial decisions to support soil productivity and health in agricultural systems.

Tree species can have great impacts on soil. Since the rhizosphere is more responsive to external inputs than the surrounding bulk soil, we investigated the rhizosphere effect of the exotic slash pine and the native araucaria in long-term conifer monocultures in southern Brazil. Araucaria trees in a natural section of a nearby mixed araucaria forest were taken as the control. We assessed physical, chemical, and mineralogical properties of the underlying subtropical highly weathered soil. We did not find rhizosphere effects for most chemical and physical soil attributes, yet principal component analysis clearly distinguished the effects of the exotic and native conifers on rhizosphere properties by separating slash pine cluster from reforested and native araucaria clusters. Reductions in silt and sand contents under slash pine reforestation led to increases in clay and well-crystallized iron oxides contents. The clay mineralogy comprised kaolinite, mica/illite, and hydroxy-interlayered minerals, with kaolinite enrichment in the rhizospheres of both araucaria sites, mica/illite depletion in the rhizospheres of both araucaria and pine monocultures, and prevalence of well-crystallized iron oxyhydroxides in the slash pine rhizosphere. This study demonstrates a tendency toward increasing soil weathering in the conifer monocultures, potential negative impacts of the faster growing slash pine reforestation on soil organic carbon, available P, and total K possibly by mica/illite depletion, while araucaria had lower impacts on soil properties. These results show long-term potential loss of soil fertility and quality, which should be considered when monitoring soil changes in human modified ecosystems.

The benefits of using cover crops for improving soil and water quality are well known. Less clear is whether cover crops, especially those forming a taproot system, can favor solute transport down to the groundwater by modifying soil hydraulic properties and solute dynamics. In this study, we employed 12 lysimeters to conduct a comparative analysis between a taproot cover crop, specifically forage radish (FR), and bare soil (BS), under three water table management conditions. Our objective was to evaluate whether the enhancement of root-derived macroporosity could have modified water and solute dynamics, and offset the benefits provided by FR that is commonly used to mitigate solute leaching. A tracer solution of bromide (Br⁻) was added to lysimeters, and solute flux concentrations were determined at different depths during a 25-day test. Soil moisture and pressure heads were monitored. Water and solute transport parameters were estimated by inverse modeling using HYDRUS-1D. A complementary laboratory experiment was performed to quantify the effect of FR root apparatus on the macropore structure by using noninvasive X-ray microtomography (µCT). Results showed that the growth of FR within the lysimeters induced alterations in water and solute dynamics compared with BS. This is primarily attributed to its proficiency as solute scavenger, with an uptake capacity of up to 47% of the total injected tracer. Our comparative analysis instead revealed subtle differences in soil structure and hydraulic properties brought about by the presence of FR. Major changes were observed for the saturated hydraulic conductivity (K_s), which increased from an average of 8.4–49.8 cm day⁻¹ within the 20–45 cm layer in BS and FR, respectively. Additionally, there was a difference in immobile water content (θ_im), with the values in FR averaging 21% lower than those in BS. These modifications can be attributed to the formation of fissures and channels, primarily concentrated in the proximity of taproot development, without extending into deep preferential flow pathways. These structural changes were supported by the nondestructive µCT analyses. Upon aggregating the effects observed, solute movement to groundwater was not affected by FR compared to BS conditions.

Interactions between arbuscular mycorrhizal (AM) fungi and free-living nitrogen fixers (FLNF) occur in the rhizosphere where they can enhance plant nutrient acquisition, impact plant growth, and affect soil processes. Tripartite mutualism commonly occurs between nodule-forming plants, symbiotic diazotrophs, and AM fungi, and can occur between non-nodulating plants, FLNF, and AM fungi. However, information on the extent of, and controls on, tripartite mutualism in non-nodulating plant systems is limited to a small number of crop plants and culturable microbial inoculum, mostly in greenhouse growing conditions. We conducted a systematic literature review to synthesize the current understanding of the responses of plants, AM fungi, and FLNF to co-inoculation, as well as the conditions affecting tripartite mutualism and the magnitude and range of benefits conferred. Our review shows that plants generally benefit from co-inoculation with AM fungi and FLNF taxa, but benefits are highly variable and context dependent, ranging from 94% reduction in plant shoot biomass to 255% increase in total plant biomass. Additionally, the presence of AM fungi can increase abundance of FLNF and the presence of FLNF can increase AM fungal root colonization, but these responses also vary widely. Major factors influencing variation in response to co-inoculation by all organisms include plant phenology/age, soil type and nutrient availability, and partner pairing. There is potential for leveraging these tripartite mutualisms to improve plant productivity and soil microbial function, but successful application is more likely with a thorough understanding of the environmental and mechanistic controls on these relationships and testing of field-scale implementation.

Continuous maize (Zea mays L.) (CM) cropping has been proposed to increase soil organic carbon stocks through greater residue return to soils. These residues, however, can contribute to a yield decrease known as the continuous maize yield penalty (CMYP). The objectives of this research were to (1) evaluate the efficacy of residue management practices to mitigate the CMYP when compared to a maize–soybean [Glycine max (L.) Merr.] (MS) rotation and (2) determine effects of long-term rotation or residue sizing on soil microbial communities and carbon-cycling enzyme activities. Two long-term sites (17 and 19 years) with replicated blocks of CM and MS rotation were used. The yield response to management was similar at both sites, with an average CMYP of 2570 kg ha⁻¹ with no residue management, while chopping the residue along with broadcast ammonium sulfate (AMS) reduced the CMYP by 728 kg ha⁻¹ (28.3%). The CMYP was further reduced when a microbial blend was applied with AMS to the sized residues, reducing the CMYP by a total of 1303 kg ha⁻¹ (50.7%). Soil bacterial communities differed by site but were unchanged by crop rotation or residue sizing. Soil fungal assemblage, particularly arbuscular mycorrhizal fungi, was influenced by rotation and site. Sizing of residues resulted in higher soil cellobiohydrolase activity for CM, but not for MS. These findings indicate that the CMYP was not directly associated with the soil bacterial community, and that management to mitigate the CMYP may be aided by elevated levels of fungal diversity under CM.

Rapid and cost-effective techniques for soil analysis are essential to guide sustainable land management and production agriculture. This study aimed at evaluating the performance and consistency of portable handheld Fourier-transform near-infrared spectrometers and the NeoSpectra scanners in estimating 12 common soil physical and chemical properties including pH; organic carbon (OC); inorganic carbon (IC); total nitrogen (TN); cation exchange capacity (CEC); clay, silt, and sand fractions; and exchangeable potassium (K), phosphorus (P), calcium (Ca), and magnesium (Mg). A diverse set of samples (n = 600) were retrieved from a national-scale soil archive of the Kellogg Soil Survey Laboratory of USDA-NRCS and scanned with five NeoSpectra scanners. Predictive models for the soil properties were developed using partial least squares regression (PLSR), Cubist, and memory-based learning (MBL). Cubist outperformed PLSR and MBL, with the best prediction performance for clay, OC, and CEC (R² > 0.7), followed by IC, sand, silt, and Mg (R² > 0.6), and then pH, TN, and Ca (R² > 0.5). K and P were predicted somewhat poorly with R² of 0.48 and 0.22. All five NeoSpectra yielded comparable near-infrared (NIR) spectral data and the PLSR models for the soil properties (in terms of model regression coefficients). However, the consistency assessment showed that the model performance was significantly decreased when the training and testing spectra were from different NeoSpectra scanners. It is concluded that NeoSpectra scanners could be rapid and cost effective for estimating certain soil properties, and calibration transfer should be considered for applications where multiple devices are involved and high estimation accuracy from NIR data is required.

Several short-term studies have investigated 4R (right source, rate, time, and place) N management for dryland wheat (Triticum aestivum L.) production and profitability, but few long-term studies exist in the United States or abroad. This study evaluated long-term impacts of several aspects of 4R N management on dryland hard red wheat yield, protein, and return to N. Experiments were conducted at Nephi and Blue Creek, UT, during 1995–2007. Fourteen N treatments evaluated performance of starter fertilizer, fall applications of anhydrous ammonia (AA) with and without nitrapyrin (AA-Nitrapyrin and AA, respectively), and several split applications in the fall and spring. Across years, winter wheat required N to increase yield, protein, and returns at both sites. Applying 56 kg N ha⁻¹ as AA in the fall usually produced the best return to N compared to other N treatments. Starter N (6 kg N ha⁻¹) at fall planting rarely increased yield, protein, or returns at either site. Across both sites, nitrapyrin increased mean annual yield by 0.6 Mg ha⁻¹ and mean return to N by $150 ha⁻¹. Spring application of N was rarely required and only increased yield in 13% of the years. Results indicate that nitrapryin is often needed with fall AA applications to optimize yield and returns and that starter N or extra N in the spring are rarely economical in dryland wheat in Utah and possibly the greater Intermountain West. Further, N rate had the most influence among 4Rs on wheat production and should be the focus of future efforts to improve 4R stewardship.

Classical soil aggregate stability (AS) methods lack standardized protocols and require long measurement times. However, the fairly new SLAKES method purportedly allows for rapid AS estimation with minimal technical equipment. SLAKES has been tested on fine-textured soils but its suitability for other soil types is unknown. This study investigated SLAKES’ suitability for AS measurements on silty clay, silt loam, and sandy loam soils. For each SLAKES test, three aggregates were immersed in distilled water and imaged for 10 min. SLAKES output includes disaggregation data per aggregate and three coefficients from a Gompertz function that describe slaking dynamics. Four AS descriptors obtained from SLAKES output were investigated: the averaged maximum slaking from a test (a_SK), the maximum slaking for each measurement (aggregate) (a_FT, from fitting a Gompertz function to SLAKES raw data), the averaged a_FT for the measurements in a test (a̅_FT), and the slaking index at 10 min per measurement (SI₆₀₀). The a_SK is a direct descriptor included in the SLAKES output, while a_FT, a̅_FT, and SI₆₀₀ are indirect descriptors. The SI₆₀₀ was the most preferred SLAKES AS descriptor since it is a calculated parameter and due to its sensitivity in detecting AS status among all soil types. The sandy loam soil was the most stable from both the raw SLAKES data and fitting, albeit counterintuitive. SLAKES default measurement time was sufficient for the silty clay and silt loam soils but not for the sandy loam soil. Overall, SLAKES was a useful tool for AS measurements on fine-textured soils but was less suitable for AS measurements on the coarse-textured soil.

Traditional methods for assessing bacterial transport in soil or permeable sand aquifers, such as flow-through experiments, breakthrough curve (BTC), and retention profile (RP) analysis, face challenges due to their complexity and the labor-intensive nature of in situ implementations. This study seeks to address the question: How can the transport behavior of bacteria in soil be predicted in a simpler and more cost-effective manner using RPs? We introduce an RP method designed to overcome these challenges by utilizing soil sampling at various depths to model bacterial breakthrough behaviors with greater efficiency. By employing the one-site attachment/detachment model within the Hydrus 1D framework, our research compares the RP method (three RPs) against the conventional approach (BTC + RP), showcasing its efficacy through column experiments with bioluminescent Escherichia coli in humic acid-coated sand. The results indicate that the accuracy of RP method aligns closely with traditional methods in predicting bacterial transport. This technique allows for the use of solid samples collected from a limited number of depths to predict breakthrough behaviors accurately, making it suitable for evaluating bacterial transport in settings such as farmlands, contaminated lands, riverbanks, and soil aquifer treatment systems. Our findings underscore the RP method's role in streamlining experimental procedures and its potential application in environmental science and agronomy.