Proceedings - Soil Science Society of America最新文献

No-till (NT) alleviates adverse effects of agricultural production on environmental quality, improves soil health, and reduces greenhouse gas emissions, yet this has not been demonstrated in humid subtropical Mississippi. Research objectives were to evaluate nutrient and C dynamics and soil quality via Soil Management Assessment Framework (SMAF) following 15 years of continuous management under corn (Zea mays L.) (2008–2018) and soybean [Glycine max (L.) Merr.] (2019–2022) on a Dundee silt loam soil. After 15 years, soil organic carbon (SOC) stocks (0- to 30-cm depth) under NT were 25% higher than conventional tillage (CT). Between 2020 and 2022, SOC stocks increased 3 Mg ha⁻¹ under NT and decreased 2 Mg ha⁻¹ under CT. Increased SOC retention under NT could represent an opportunity for increasing the systems’ profitability as C markets expand. Greater SOC and aggregation scores improved SMAF soil quality index (SQI) under NT (71%), compared to CT (66%), underscoring the critical role of organic matter in soil functioning in managed agrosystems. Soybean yields were not linked to SMAF SQI (p > 0.05), suggesting that crop yields are mostly affected by non-edaphic factors (e.g., climate extremes). SMAF illustrated positive impacts of NT on SOC sequestration and soil health, which may foster its adoption as a conservation practice in the Lower Mississippi River basin. As such, NT stands as a climate-smart management practice that allows for sustainable intensification in humid subtropical regions.

Historic atmospheric acidic deposition resulting from the combustion of fossil fuels may alter the pools of important nutrients and base cations in sensitive forest soils. This raises concern that chronic acidic deposition, particularly when coupled with intensive forest biomass harvesting, may diminish long-term soil fertility, forest productivity, and carbon storage potential. To address these concerns, the Fork Mountain long-term soil productivity experiment was initiated in 1996 at the Fernow Experimental Forest, West Virginia. The replicated experimental design consists of 16 plots (0.2 ha) that receive one of four treatments: (1) whole-tree harvesting (removal of all aboveground biomass, WT plots); (2) whole-tree harvesting + ammonium-sulfate fertilization (WT + NS plots); (3) whole-tree harvesting + ammonium-sulfate fertilization + dolomitic lime (WT + NS + Lime plots); and (4) untreated reference plots. We present forest floor and soil chemistry responses after ∼25 years of treatment and evaluate the temporal changes to illuminate these results. Soil acidification has occurred, and base cation movement through the soil profile was observed, with effective cation exchange capacity increasing slightly in the deepest soil horizon by the end of the 25 years. However, some of our hypotheses were not supported. In particular, soil C did not increase over time with fertilization/soil acidification but was mainly altered by WT harvesting, as were other nutrients. Dolomitic lime provided some amelioration of acidification, but surprisingly, most of the changes in base cations appeared to be the results of Mg, not Ca, likely due to greater tree requirements and uptake of Ca.

Land use changes and reforestation impact soil phosphorus (P) distribution over extended periods. This study examines P distribution in forest development from 1957 to 2017 at the Calhoun Critical Zone Observatory in South Carolina. Tracking changes in 0–60 cm mineral soil P fractions through six samplings in eight continuously uncut plots and eight plots cut in 2007 (replanted in 2009), we hypothesized an increase in soil organic P (P_o) over time in uncut plots, at the expense of HCl-extractable P (i.e., Ca-P). This hypothesis is based on the expectation of a transfer of P from easily accessible forms, possibly from historic fertilization to organic reservoirs within the soil. Meanwhile, we expect to lose P_o in cut plots due to disturbance and residue decomposition, and increase bioavailable Mehlich-III extractable P (Mehlich-III P), resin inorganic phosphorus (P_i), and HCO₃ P_i. Results revealed a continued decrease in Mehlich-III P in uncut (38.7–15.7 µg g⁻¹) and cut plots (25.2–17.7 µg g⁻¹) within the 0–7.5 cm range. NaOH-P_o in uncut plots remained stable, while in cut plots, it increased by ∼4 µg g⁻¹ in the 0–7.5 cm soil layer. Slowly cycling P_o (NaOH-P_o) increased during forest regrowth in the cut plots, aligning with rising soil organic carbon and decreasing soil pH. Soil P changes indicate minor declines in available fractions during the initial three decades, with the HCl extractable (Ca-P) fraction experiencing the highest depletion. In the later three decades, P associated with NaOH extraction (i.e., iron [Fe] and aluminum [Al] bound P) declined, although estimated mineral soil P removals during this period were less than accumulated P in tree biomass and forest floor. The total soil P decline from 1990 to 2017 was 34 kg ha⁻¹, suggesting a growing role of P recycling from debris decomposition in supplying soil P to plants.

Fire alters soil hydrologic properties leading to increased risk of catastrophic debris flows and post-fire flooding. As a result, US federal agencies map soil burn severity (SBS) via direct soil observation and adjustment of rasters of burned area reflectance. We developed a unique application of digital soil mapping (DSM) to map SBS in the Creek Fire which burned 154,000 ha in the Sierra Nevada. We utilized 169 ground-based observations of SBS in combination with raster proxies of soil forming factors, pre-fire fuel conditions, and fire effects to vegetation to build a digital soil mapping model of soil burn severity (DSMSBS) using a random forest algorithm and compared the DSMSBS map to the established SBS map. The DSMSBS model had a cross-validation accuracy of 48%. The established technique had 46% agreement between field observations and pixels. However, since the established technique is manual, it could not be compared to the DSMSBS model via cross-validation. We produced SBS class uncertainty maps, which showed high prediction probabilities around field observations, and low probabilities away from field observations. SBS prediction probabilities could aid post-fire assessment teams with sample prioritization. We report 107 km² more area classified as high and moderate SBS compared to the established technique. We conclude that blending soil forming factors based mapping and vegetation burn severity mapping can improve SBS mapping. This represents a shift in SBS mapping away from validating remotely sensed reflectance imagery and toward a quantitative soil landscape model, which incorporates both fire and soils information to directly predict SBS.

The presidedress nitrate test (PSNT) is a nitrogen (N) fertilizer decision support system (DSS) that uses soil test nitrate (NO₃⁻) to provide an N rate recommendation for corn. We studied the effect of soil sample storage and handling on soil test NO₃⁻, ammonium (NH₄⁺), and the N rate recommended by the PSNT. Soils from 35 agricultural fields located in southern Ontario, Canada, were collected in June and July and underwent two soil storage treatments and four soil handling treatments. Soils were either handled immediately or frozen (−15°C) for 3 months before handling. Soil handling included (1) immediate extraction in a moist state or oven-drying for 24 h at (2) 35°C, (3) 65°C, or (4) 105°C. Samples were extracted with a 2.0 M KCl solution for inorganic N determination and immediate, fresh-extracted samples served as baseline soil test values. Ammonium-N was increased by freezing and drying at any temperature, while NO₃⁻ test values were significantly affected by freezing only. However, oven-drying samples changed PSNT DSS N rate recommendations in 34%–43% of location-years when handled immediately and 51%–68% of samples when initially frozen, depending on drying temperature. Most of these deviations were underapplications and relatively small when handled immediately (20 kg N ha⁻¹) or frozen (37 kg N ha⁻¹). We conclude that PSNT samples should not be frozen and that oven-drying often alters PSNT-based N rate recommendations.

Soil wet aggregate stability is widely measured for soil health ratings, and two mobile applications have been recently developed that provide simple and fast measurements of wet aggregate stability on three pea-sized soil aggregates. However, techniques are needed to scale the test to make it practical for studies with large sample numbers. Here, we describe an approach to measure 10-min slaking index on 20–36 aggregates simultaneously using a multi-well plate and automated image analysis. We used this approach to measure 160 soil samples (2120 aggregates) from a long-term tillage and cover crop trial in a corn (Zea mays L.)-based agroecosystem in central Iowa. We evaluated the statistical power of slaking index, needed replication, sensitivity to cultural practices, and sensitivity to sample collection date to inform future sampling efforts. We found that small numbers of highly unstable aggregates lead to skewed distributions for slaking index. We concluded that at least 20 aggregates per sample were useful to provide confidence in measurement precision, although the experiment had high statistical power with only 10–12 replicates per sample. Slaking index was not sensitive to the initial size of dry aggregates (3- to 10-mm diameter); therefore, pre-sieving soils was not necessary. Consistent with prior studies, the field trial showed greater aggregate stability under no-till than chisel plow practice and changing stability over a growing season. This multi-well method will help researchers measure a useful soil health indicator with greater precision, and more efficiently sample spatial and temporal variation.

Soil test correlation determines whether a soil test can be used to predict the need for fertilization based on the critical soil test value (CSTV). Our objectives were to compare the CSTV estimated from five combinations of correlation models and yield sufficiency interpretations and to select one method for soil test correlation performed with the Fertilizer Recommendation Support Tool (FRST). Four models were fit to three datasets with strong (Mehlich-1 K), moderate (Mehlich-3 K), or weak (Olsen P) correlations between soil test P or K and crop relative yield. We tested the arcsine-log calibration curve (ALCC), exponential (EXP), linear plateau (LP), and quadratic plateau (QP) models. The CSTV was defined as 95% of the maximum predicted yield for the ALCC and EXP methods, the join point for LP, and both the join point and 95% of the maximum for the QP providing five CSTV predictions. The five CSTVs ranged from 46 to 66 mg kg⁻¹ for the Mehlich-1 K dataset, 115 to 165 mg kg⁻¹ for the Mehlich-3 K dataset, and 7 to 16 mg kg⁻¹ for the Olsen P dataset. Ten pairwise comparisons showed the estimated CSTV was numerically and sometimes statistically influenced by the model and sufficiency level interpretation. Despite differences among CSTVs, the frequency of significant yield responses above and below the predicted CSTV was generally comparable among the methods, with false-negative errors occurring at 0%–18% of sites for a given dataset. The QP model with a CSTV at 95% of the predicted maximum was selected as the modeling approach for FRST.

The soil supports many ecosystem services (ES) essential to human well-being. Rapid developments in digital soil mapping (DSM) allow the mapping of soil types and soil properties with improved resolution and accuracy. However, the potential of DSM to improve the assessment and mapping of ES is not fully exploited. To better understand this potential, we synthesized the peer-reviewed literature. We examined what empirical studies reveal about the role of soil properties in the assessment of four major ES provided by the forest: (I) timber production, (II) soil carbon storage, (III) regulation of water flow and provision of clean water, and (IV) the soil as a habitat for organisms. Results revealed that soil properties are strongly related to the provision of ES. Therefore, using DSM could greatly improve the assessment of the ES provided by forests. Several variables were related to specific ES regardless of region or ecosystem types, but others were found to be situation-specific (climate and soil type) and need to be considered at the proper scale or within a proper land classification framework. DSM products have the potential to greatly improve the assessment of ES by turning qualitative relationships between soil and ES to quantitative ones. This could also lead to the discovery of new soil–ES relationships. For this potential to be realized, progress should be made in mapping the most crucial soil parameters with greater precision and in promoting the use of soil parameters in ES assessment.

Biochar can deliver many agronomic benefits, though effects may be greatest in suboptimal agricultural soils. The objective of this study was to investigate biochar in prime agricultural soils in a Mediterranean climate. In 3-year irrigated processing tomato (Solanum lycopersicum) field trials, in which three biochars were amended to a sandy and silt loam, biochar did not influence yield. Given the global policy focus on biochar for climate change mitigation and adaptation, however, it is essential to measure more than just agronomic parameters. To this end, a soil health assessment was conducted 2.5 years after biochar amendment. In the fertile silt loam and more nutrient-limited sandy loam, biochars had a variable but positive effect on pH, electrical conductivity, soil potassium, water stable aggregation, and permanganate oxidizable carbon. There was no effect on soil moisture nor potentially mineralizable nitrogen or carbon. In the silt loam, there was no change in microbial biomass or phospholipid fatty acid (PLFA) composition. In the sandy loam, almond shell biochars were associated with a slight increase in total biomass, an increase in the ratio of fungal to bacteria PLFAs, and reductions in multiple PLFA ratios were typically interpreted as indicators of environmental stress. Results of this study demonstrate that biochar may deliver soil health benefits in agricultural soils in a Mediterranean climate. However, increased soil health does not necessarily engender increased agricultural productivity within a 3-year period. Furthermore, increases in soil health indicators were inconsistent across soil and biochar types, underscoring the need for site- and material-specific investigation.

The development of transgenic crop varieties capable of utilizing phosphite (Phi) as a phosphorus (P) source is a promising strategy to increase P use efficiency while decreasing reliance on phosphate (Pi)-based fertilizers. However, little information is available on Phi sorption and desorption in soils. We conducted batch experiments to investigate the sorption of Phi and Pi by three Ultisols from the Coastal Plain of the southeastern United States. At the soils' acidic field pH (pH 4.7–6.2), Pi had a higher affinity than Phi for soil solids, where maximum sorbed concentrations of Pi were an average of 44% greater than those of Phi. The sorption of both P species decreased when experiments were repeated adjusting soil pH to 6.5. More Phi than Pi was recovered during desorption experiments, indicating that Phi was more reversibly sorbed and, therefore, may be more plant-available than Pi. Multiple linear regression between calculated linear distribution coefficients (K_D; 10 mg P L⁻¹ input solutions) and soil properties suggested that amorphous Al- and Fe-oxides controlled Pi sorption. Alternatively, amorphous Al-oxides and gibbsite controlled Phi sorption. Our results show that a lower affinity of Phi than Pi in Ultisols could improve P availability for plant uptake of Phi-based fertilizers but may increase the risk of soil P buildup over time.