Proceedings - Soil Science Society of America最新文献

The growing water scarcity jeopardizes crop production for global food security, a problem poised to worsen under climate change–induced drought. Amending soils with locally derived biochar from pyrolyzed agricultural residues may enhance soil moisture retention and resilience, in addition to climate change mitigation. However, prior studies on the hydrologic benefits of biochar focused on optimal moisture, not water-limited conditions where biochar's large wettable surface area could aid plants and microbes. We hypothesized that biochars differing in feedstocks would positively augment soil moisture and respiration, with overall impacts most beneficial under drier conditions. Using water vapor sorption isotherms, we used film theory to estimate the specific surface area (SSA) of biochars. We then modeled and tested the moisture retention of a coarse-textured soil amended with biochar. Additionally, a 109-day lab incubation experiment was also conducted to examine biochar effects on respiration across a moisture range spanning optimal to wilting point. Among seven tested biochars, almond shell biochar significantly increased soil moisture and yield the second highest SSA. Despite drying treatments, the amended soil maintained higher respiration than the control, indicating enhanced biological activity. The results demonstrate biochars counter drying effects in coarse soils through physical and biological mechanisms linked to increased sorptive capacity. Our findings contribute to the development of sustainable water and waste management strategies tailored to the needs of California Central Valley, where the potential for biochar application is substantial. Above all, our research fills a crucial gap by providing context-specific insights that can inform the effective utilization of locally produced biochars in the face of increasing water scarcity and excess biomass challenges.

Zinc (Zn) is the micronutrient commonly found deficient in agricultural soils worldwide, limiting crop yield and reducing food quality. Zinc-enriched fertilizers have been successfully used to tackle crop Zn deficiency. However, Zn solubility is reduced after addition to phosphate fertilizers due to the formation of sparingly soluble precipitates, decreasing Zn availability to crops. We hypothesized that the availability of Zn in the fertilizer to plants is related to its speciation in the fertilizer. We evaluated a range of ammonium phosphate fertilizers using X-ray absorption near-edge structure and assessed the water-solubility of Zn in the formulations. Four Zn species were identified in these fertilizers, with zinc ammonium phosphate the most abundant one. The speciation of Zn in the fertilizer had little relationship with the water solubility of Zn in the final product. Zinc solubility was driven by fertilizer pH, with lower pH resulting in higher solubility. We concluded that added Zn reacts with the fertilizer matrix to form mainly zinc (ammonium) phosphates, and when the fertilizer is dissolved in water, hopeite controls the solubility. Based on these findings, we tested whether a barrier coating between the P granule and the Zn compound could prevent reaction between Zn and P and thus enhance Zn availability. Indeed, higher Zn uptake was observed in an isotopically labeled fertilizer growth trial when a barrier coating physically separated Zn and P in the fertilizer. In summary, Zn availability to crops can be maximized by decreasing fertilizer pH and separating P and Zn in the granule.

Crambe (Crambe abyssinica Hochst) is an important grain crop for biodiesel production. The objective of this study was to evaluate how spatial distribution of soil properties affects crambe grain yield and oil content. We analyzed six different sampling densities, with a distance between sampling points ranging from 5.5 to 44 m, to identify correlations among soil and crop variables, and the best spatial distribution. Crambe oil content was not correlated to any of the physicochemical properties, whereas crambe grain yield was correlated with total porosity and exchangeable Al and Ca, effective cation exchange capacity, available P, K, Cu, and Zn, and aluminum and base saturation, with highly significant correlation (p < 0.001) for P and K and Cu and Zn. Most soil properties had spatial dependence degrees from weak to strong, and were modeled by spherical or exponential semi-variograms. Spatial data showed that low grain yield is associated with high seed oil content, while crambe grain yield was more correlated with phosphorous availability in soil in the first year (2012) and with Ca, Mg, and soil organic matter in the second year (2013). Spatial variability in soil nutrients is attributed to uneven distribution of fertilizers and surface runoff. The results demonstrate sampling density must be increased to generate more accurate maps for soil chemical properties affecting crambe. The use of a grid of 25 points in a 625 m² of land is suggested, providing more than 60% accuracy for grain yield estimation and more than 40% for most chemical properties’ estimation.

A major challenge to implementing effective soil health assessments is how to distinguish the effects of management from underlying soil variability driven by inherent soil properties. This challenge has important consequences for the use of soil health indicators as tools for monitoring and assessment because soil-forming factors constrain the range of indicator values and the magnitude of management-induced changes. Here, we present results from a statewide survey of 15 soil health indicators measured on 30 fields on commercial farms across four major land resource areas in Minnesota. Fields included in the study differed in tillage, cover crop implementation, and crop rotation. Within each field, we collected samples from upper and lower hillslope positions to quantify the effect of topography. We consistently detected differences in soil health indicators between regions (13/15 indicators) and hillslope positions (8/15 indicators). However, only wet aggregate stability was sensitive to management across regions and years, highlighting the importance of physical indicators of soil health. This result was surprising in light of existing literature supporting the sensitivity of many soil health indicators to management, but it is consistent with other studies conducted in high organic matter soils in the Upper US Midwest. Our results highlight the need for regionally representative datasets to guide the development of interpretations and benchmarks for soil health indicators. This is particularly important when soil health indicators are applied outside traditional research contexts (such as in commercial soil health testing), where interpretation must take place without the benefit of historical baseline data.

Soil organic matter is assumed to accumulate with conservation management. On-farm surveys using paired-farm and chronosequence approaches could validate assumptions, as well as provide a diversity of soils and management conditions to assess organic matter fractions. The objective of this study was to assess how land use and pasture management affected the gradient of organic matter fractions from active to resistant. Particulate and non-particulate (also called mineral-associated) organic C and N fractions were isolated and soil-test biological activity was measured from 304 profiles at 0- to 10-, 10- to 30-, and 30- to 60-cm depths on 31 private farms in Virginia. Root-zone enrichment contents of these soil properties were calculated following subtraction of a baseline from total stocks of each soil profile. Land use was a key factor affecting root-zone enrichment (0- to 30-cm depth) of particulate organic C (Mg C ha⁻¹) (p ≤ 0.05): conventional-till cropland (6.3) = no-till cropland (9.2) < grassland (14.2) < woodland (16.7). Root-zone enrichments of soil C and N fractions increased with pasture age to a plateau achieved by 25 years and were optimized at cattle stocking rate of 1.0 ± 0.2 Mg live weight ha⁻¹. Feeding hay increased root-zone enrichment of soil-test biological activity (49 kg CO₂-C 3 day⁻¹ [Mg hay]⁻¹). Although non-particulate organic C and N dominated, accumulation with time and steady-state concentration of particulate fractions were vital steps toward greater soil organic matter under conservation management. Root-zone enrichment calculations from on-farm sampling were helpful in distinguishing true effects of management from pedogenesis on soil organic matter formation.

Biological soil crusts (biocrusts) are crucial elements of desert ecosystems, exhibiting patchy distribution patterns across the soil surface and significantly impacting surface soil nutrient dynamics. However, the influence of biocrust patch units, serving as fundamental functional entities, on microbial nutrient restriction remains underexplored. This study conducted measurements on moss crust patches of varying sizes and subcrust soils. Stoichiometric analysis of extracellular enzyme activities (EEAs) related to carbon, nitrogen, and phosphorus was performed, along with vector and redundancy analyses to evaluate microbial nutrient limitation and key influencing factors. The findings reveal that both patch size and soil layer of biocrusts collectively influence soil nutrients and enzyme dynamics, with heightened enzyme activity observed in the crust layer. Vector analysis based on EEA stoichiometry indicates that moss crust patch size insignificantly impacts microbial nutrient restriction within the crust layer. However, microbial nitrogen restriction in the subcrust layer demonstrates a “single-peak” trend, initially increasing before gradually declining. This suggests that microorganisms in medium-sized crust patches exhibit peak activity, intensifying nutrient competition. This research underscores the pivotal role of biocrust patch units as fundamental functional entities, offering comprehensive insights into microbial metabolic constraints under crust cover. The findings underscore the significant implications of enzyme stoichiometric characteristics for desert land management and conservation.

Gelisols (permafrost-affected soils in US Soil Taxonomy) are extensive in Alaska, currently occurring on ∼45% of the land area of the state. Gelisol taxonomic criteria rely on the presence of near-surface (less than 2 m deep) permafrost, but ongoing climatic and environmental change has the potential to affect the presence of near-surface permafrost across much of Alaska throughout the 21st century. In this study, we utilized scenarios of near-surface permafrost loss and active layer deepening through the 21st century under low (SRES B1, RCP 4.5), mid- (SRES A1B), and high (SRES A2, RCP 8.5) emissions scenarios, in conjunction with the statewide STATSGO soil map, to generate spatially explicit predictions of the susceptibility of Gelisols and Gelisol suborders to taxonomic change in Alaska. We find that 15%–53% of Alaskan Gelisols are susceptible to taxonomic change by mid-century and that 41%–69% of Alaskan Gelisols are susceptible to taxonomic change by the end of the century. The extent of potential change varies between suborders and geographic regions, with Gelisols in Northern Alaska being the most resilient to taxonomic change and Western and Interior Alaskan Gelisols most susceptible to taxonomic change. The Orthel suborder is likely to be highly restricted by the late 21st century, while Histels and Tubels are more likely to be of greater extent. These results should be taken into consideration when designing initial survey and re-mapping efforts in Alaska and suggest that Alaskan Gelisol taxa should be considered threatened soil taxa due to the proportional extent of likely loss.

Forests around the world, and in the case of this study, the coastal Pacific Northwest United States, store large amounts of carbon, both above ground in the trees and below ground in soils. Understanding the effects of forest disturbance, including timber harvesting, is important in order to evaluate the role that forestry plays in the global carbon cycle. Soil carbon can be difficult to assess with enough precision to detect the kinds of changes that are expected, yet a series of small changes over time in the same direction could have important cumulative effects. In this study, eight randomly selected Douglas-fir forest stands in Oregon and Washington were sampled at 300 points each using a fixed-depth sampling approach to attempt to detect a 5% or higher change in soil carbon storage to 1 m, longitudinally from pre-harvest to 10 years post-harvest. There was moderate variability in results over time at individual sites, with some sites decreasing slightly and others increasing slightly. Only two sites achieved lower than the 5% minimum detectible difference target. The remaining six sites were able to detect 5.7%–10.7% differences. In one case, an unexpectedly large increase in mineral soil carbon 10 years post-harvest occurred without clear explanation. On average, forest floor carbon stores were 20% larger 10 years post-harvest than pre-harvest. Even with the large increases excluded, both the fixed-depth approach and equivalent soil mass correction showed there was no significant change in mineral soil carbon stores to 1 m at 10 years post-harvest in the region.

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.

Field capacity is a dubious soil physical property, but its use continues because of its perceived value for representing a soil's capacity to store water. Appropriate field capacity estimates can be useful for interpreting data from soil moisture sensors, including those in large-scale monitoring networks, but suitable methods for defining field capacity in this context are unclear. Motivated by the desire to determine optimal field capacity values for the Oklahoma Mesonet, our objectives were (1) to develop and apply an automated time series analysis algorithm to estimate volumetric soil water content at field capacity and corresponding matric potential and (2) to compare the resulting water contents to those calculated from traditional matric potential thresholds (−33 and −10 kPa). Across 118 Oklahoma Mesonet sites and three soil depths (5, 25, and 60 cm), a matric potential threshold of −10 kPa underestimated field capacity water content by 0.010–0.014 cm cm⁻³ (3–4%) on average, and a threshold of −33 kPa underestimated it for every site and depth by 0.055–0.078 cm cm⁻³ (16%−22%) on average. Median matric potentials corresponding to field capacity were −7.6 kPa at the 5-cm depth, −7.2 kPa at the 25-cm depth, and −7.3 kPa at the 60-cm depth. The algorithm developed here can be used to estimate field capacity wherever adequate data are available, and for sites where soil water retention properties are known, matric potentials at field capacity can also be estimated. Using a matric potential of −33 kPa as a standard threshold to represent field capacity is not scientifically justified and should be discontinued.