Permanganate Oxidizable Carbon Research Articles

Accumulation of chemically degraded organic carbon in the soil profile of Chinese fir plantations

Short-rotation forestry relies on frequent harvests of fast-growing trees, which could deplete soil fertility and soil organic carbon (SOC) reserves. Our objective was to measure the accumulation of SOC fractions, namely the dissolved organic carbon, microbial biomass carbon, particulate organic carbon, permanganate-oxidizable carbon, and non-oxidizable organic carbon, in the soil profile of a Chinese fir plantation. Chronosequences of Chinese fir aged 7, 12, and 33 yr were sampled at depths of 0–20 cm, 20–40 cm, and 40–60 cm. The SOC stock (0–60 cm) was unchanged in the first 12 yr, but after 33 yr, there was a 41%–56% increase in the SOC stock, which reached 81.2 Mg ha−1 (P < 0.05). Permanganate-oxidizable carbon increased with time in the 0–20 cm layer but not in deeper soil depths, whereas non-oxidizable organic carbon accumulated preferentially in the 40–60 cm layer of the soil profile. Inputs of chemically complex plant litter in the soil profile may be important to maintain the oxidizable and non-oxidizable organic carbon in Chinese fir plantations.

Effects of forest floor characteristics on soil labile carbon as varied by topography and vegetation type in the Chinese Loess Plateau

Vegetation type and topographic characteristics are important factors that affect the amount and spatial distribution of the forest floor and the soil carbon cycling. However, the relationships among vegetation type, topographic characteristics, forest floor properties, soil properties and soil labile organic carbon (LOC) fractions remain to be elucidated. Here, we conducted a field observational study to explore the relationships between the soil LOC fractions (microbial biomass carbon (MBC), extractable organic carbon (EOC) and permanganate oxidizable carbon (Pox-C)) and forest floor characteristics under various vegetation types (forest, forest-steppe and steppe) and topographic features (slope position and aspect). Our results showed that the vegetation type and topography are both important factors that significantly influence the forest floor properties (i.e., stock, thickness and coverage). The soil total nitrogen and phosphorus were significantly increased, and the soil pH and bulk density were decreased, with an increase in litter stock, coverage and thickness. Simultaneously, the SOC and soil LOC fractions were increased significantly with the increase in litter stock, coverage and thickness. Over 50% of the variation in the SOC and soil LOC fractions was jointly explained by environmental factors, litter properties and soil properties. Our results demonstrated that the SOC and soil LOC fractions are directly influenced by soil physical and chemical properties (e.g., pH, bulk density and soil total nitrogen) and indirectly affected by external environmental factors. Changes in vegetation and topography lead to increases in the litter stock, coverage, thickness and water content in the backslope position and northern slope, which could create favorable soil nutrient and environmental conditions (e.g., higher soil moisture and lower bulk density) to further enhance SOC and soil LOC fraction sequestration. The forest floor potentially links environmental factors and soil properties and serves as an important factor for soil C cycling.

Visible Near-Infrared Reflectance and Laser-Induced Breakdown Spectroscopy for Estimating Soil Quality in Arid and Semiarid Agroecosystems

Visible near-infrared reflectance spectroscopy (VNIRS) and laser-induced breakdown spectroscopy (LIBS) are potential methods for the rapid and less expensive assessment of soil quality indicators (SQIs). The specific objective of this study was to compare VNIRS and LIBS for assessing SQIs. Data was collected from over 140 soil samples taken from multiple agricultural management systems in New Mexico, belonging to arid and semiarid agroecosystems. Sampled sites included New Mexico State University Agricultural Science Center research fields and several commercial farm fields in New Mexico. Partial least squares regression (PLSR) was used to establish predictive relationships between spectral data and SQIs. Fifteen soil measurements were modeled including the soil organic matter (SOM), permanganate oxidizable carbon (POXC), total microbial biomass (TMB), total bacteria biomass (TBB), total fungi biomass (TFB), mean weight diameter of dry aggregates (MWD), aggregates 2–4 mm (AGG > 2 mm), aggregates < 0.25 mm (AGG < 0.25 mm), wet aggregate stability (WAS), electrical conductivity (EC), calcium (Ca), magnesium (Mg), sodium (Na), and iron (Fe). Overall, calibrations based on measurements irrespective of locations performed better for LIBS and combined VNIRS-LIBS. Measurements separated according to locations highly improved the quality of prediction for VNIRS as compared to combined locations. For example, the prediction R2 values for regression of VNIRS were 0.19 for SOM, 0.30 for POXC, 0.24 for MWD, 0.15 for AGG > 2 mm, and 0.13 for EC in combined datasets irrespective of location. When separated according to locations, for one of the locations, the predictive R2 values for VNIRS were 0.48 for SOM, 0.70 for POXC, 0.67 for MWD, 0.60 for AGG > 2 mm, and 0.51 for EC. The prediction values varied with the sampling time for both LIBS and VNIRS. For example, the prediction values of some SQIs using VNIRS were higher in samples collected in winter for measurements, including SOM (0.90), MWD (0.96), WAS (0.66), and EC (0.94). Using the VNIRS, the corresponding predictive values for the same SQIs were lower for samples collected in the fall (SOM (0.61), MWD (0.45), WAS (0.46), and EC (0.65)). While this study illustrates the prospects of VNIRS and LIBS for estimating SQIs, a more comprehensive evaluation, using a larger regional dataset, is required to understand how the site and soil factors affect VNIRS and LIBS, in order to enhance the utility of these methods for soil quality assessment in arid and semiarid agroecosystems.

Soil labile organic carbon fractions and soil enzyme activities after 10\xa0years of continuous fertilization and wheat residue incorporation

Labile organic carbon (LOC) fractions and related enzyme activities in soils are considered to be early and sensitive indicators of soil quality changes. We investigated the influences of fertilization and residue incorporation on LOC fractions, enzyme activities, and the carbon pool management index (CPMI) in a 10-year field experiment. The experiment was composed of three treatments: (1) no fertilization (control), (2) chemical fertilizer application alone (F), and (3) chemical fertilizer application combined with incorporation of wheat straw residues (F + R). Generally, the F + R treatment led to the highest concentrations of the LOC fractions. Compared to the control treatment, the F + R treatment markedly enhanced potential activities of cellulase (CL), β-glucosidase (BG), lignin peroxidase (LiP), and manganese peroxidase (MnP), but decreased laccase (LA) potential activity. Partial least squares regression analysis suggested that BG and MnP activities had a positive impact on the light-fraction organic carbon (LFOC), permanganate-oxidizable carbon (POXC), and dissolved organic carbon (DOC) fractions, whereas laccase activity had a negative correlation with those fractions. In addition, the F + R treatment significantly increased the CPMI compared to the F and control treatments. These results indicated that combining fertilization with crop residues stimulates production of LOC and could be a useful approach for maintaining sustainable production capacity in lime concretion black soils along the Huai River region of China.

A new in-field indicator to assess the impact of land management on soil carbon dynamics

The assessment of the impacts of land-use and management on soil organic carbon (SOC) dynamics is a major environmental concern, as the soil carbon cycle underpins key ecosystem services. However, assessments based on short-term SOC dynamics face methodological and experimental difficulties. Hurisso et al. (2016) proposed a method to assess SOC dynamics by coupling two methods: Permanganate Oxidizable Carbon (POXC) and Basal Soil Respiration (BSR). This method has been used in laboratory on dried and re-wetted soil samples from temperate regions mainly. In our study, we adapted this method to the field and proposed a cost-effective in-field indicator combining the POXC and in situ Basal Soil Respiration (SituResp® method).We tested the indicator at four study sites (n = 169 points) within various tropical land-use and management contexts based on rubber, soybean and oil palm cropping systems respectively in Thailand, Cambodia and Indonesia. The results demonstrated the relevance, sensitivity and robustness of the POXC-SituResp® indicator to characterize the impact of a gradient of disturbance on SOC dynamics. The results also highlighted the potential of conservation agriculture (no-tillage and crops residues) and compost amendments to accumulate SOC. Rock-Eval® analysis showed that POXC-SituResp® indicator is negatively linked to excess of potentially mineralizable labile carbon. Carbon pools targeted by the POXC were specified by Rock-Eval® pyrolysis measurements to be a rather thermal resistant pool of SOC.Our study confirms that the integrated indicator based on POXC and BSR assess a relative carbon stabilization of SOC pools. This indicator can be measured in the field by a rapid and cost-effective method.

A soil tool kit to evaluate soil properties and monitor soil health changes in smallholder farming contexts

Smallholder farmers often face challenges in managing soil fertility due to limited inputs and high spatial variability on their farms. While improved knowledge of soil constraints could help them manage limited resources more effectively, formal soil analyses are typically out of reach due to high costs of testing and transport associated with regional analytical laboratories. To address these challenges, we assembled a tool kit that uses minimal reagents and low-cost equipment to provide in-field quantitative data that are comparable to formal laboratory methods. We validated our tool kit measurements against standard analyses conducted at national laboratories on soils collected from 36 smallholder farms in Kenya and 115 farms in Peru. Additionally, in Kenya, we evaluated two legume treatments, involving the incorporation of residues from: 1) Lablab purpureus (lablab), versus 2) Phaseolus vulgaris (common bean). The tool kit measurements that were considered include important indicators of soil health (such as permanganate oxidizable carbon (POXC), available P, pH, particulate organic matter (POM), and aggregate stability) that can influence crop yields and multiple soil functions. POXC and pH measured with the tool kit from Kenyan soils were highly correlated to those measured by a standard laboratory (R2 = 0.77; R2 = 0.56; respectively). The tool kit and standard laboratory available P were less well correlated, but also showed a highly significant positive relationship (R2 = 0.30). Similar patterns were noted for POXC, pH and available P measured in Peruvian soils (R2 = 0.75; R2 = 0.75; R2 = 0.35; respectively). Importantly, the tool kit and standard lab analyses also displayed similar abilities to predict maize grain yield in Kenya. When used to detect soil impacts of incorporating P. vulgaris versus L. purpureus, only POM differed significantly between the two legume treatments, although L. purpureus was slightly higher for most of the beneficial soil health properties. Our findings suggest that the tool kit methods proposed here have broad applicability to smallholder farms for explaining variability in crop yields, assessing soil contexts, and quantifying management-induced changes in soil health.

Living Mulch Management Spatially Localizes Nutrient Cycling in Organic Corn Production

Kura clover (Trifolium ambiguum) is a perennial living mulch species that can be used in conjunction with zone tillage to reduce nitrogen pollution, maintain ground cover, and provide nitrogen to crops. In such systems, kura clover is maintained between crop rows by limiting tillage only to within-row areas. However, the effect of zone-tilled living mulches on soil quality and nutrient cycling in these distinct regions is relatively unexplored. We examined three pools of labile soil organic matter (SOM): microbial biomass, particulate organic matter (POM), and permanganate oxidizable carbon (POXC). Soil samples were collected from both within-row and between-row locations of a zone-tilled kura clover living mulch at three time points per year: before spring zone tillage, approximately ten days after spring zone tillage and corn (Zea mays) planting, and at corn harvest in 2015 and 2016. In 2016, POM and POXC decreased within rows relative to between-row regions after tillage, suggesting that zone till management stimulated decomposition of readily available SOM to effectively localize nutrient cycling in this region and slow mineralization between rows where living kura clover remained. This work shows that zone-tilled living mulches may be a promising avenue for enhancing the synchrony of nutrient mineralization specifically within crop rows, while maintaining year-round ground cover between rows.

Cropping System and Rotational Grazing Effects on Soil Fertility and Enzymatic Activity in an Integrated Organic Crop-Livestock System

Alternative grazing systems that incorporate cover crops may be useful to achieve a longer grazing season and maximize forage production. However, little is known about their impact on soil properties, especially in the presence or absence of cattle grazing in the early spring. The aim of this study was to evaluate the interacting effects of cropping systems with and without cattle grazing in rotation with corn or soybean on the balance and dynamics of soil fertility and enzyme activity. This study was conducted as a system experiment between 2015 and 2019 in Minnesota and Pennsylvania, USA. The experimental design was a randomized complete block design with four replications. Treatments included presence or absence of cattle grazing and two types of cropping systems (pasture-rye-soybean-pasture [P-R-SB-P] and pasture-wheat/vetch-corn-pasture [P-W/V-C-P]. Soil samples were collected six times during the study. Soil properties analyzed were soil pH, organic matter, salinity, K, Ca, Mg, cation exchange capacity (CEC), P, β-glucosidase, alkaline phosphatase, aryl-sulfatase, fluorescein diacetate hydrolysis, ammonium, nitrate, permanganate oxidizable carbon (POXC), N%, C%, S%, and C:N ratio. Grazing increased glucosidase activity, available Ca, Mg, NO3−, NH4+, soil pH, soil C%, S%, and the C:N ratio. In the P-W/V-C-P cropping system, soil pH, available Ca, NO3−, and sulfatase activity were found to increase compared with the P-R-SB-P cropping system. In contrast, soil OM, available K, Mg, CEC, glucosidase, phosphatase, POXC, and total C%, N%, and S% were greater in the P-R-SB-P cropping system compared with the P-W/V-C-P cropping system. The results of this study suggested that rotational grazing can increase soil quality and microbial decomposition under the P-W/V-C-P cropping system, and that this result was greater than under the P-R-SB-P cropping system, leading to a faster nutrient cycling. These results show promise for producers who are seeking methods to diversify their farming operation and reduce the need for external inputs.

Participatory design of improved forage/fallow options across soil gradients with farmers of the Central Peruvian Andes

Land use intensity is increasing in Andean smallholder systems, and innovations are needed to sustain soil fertility and productivity of potato-cereal rotations with shortening fallow periods. In collaboration with farmers in central Peru, we assessed forage-based fallows in 58 fields across three production zones over three years. Fallow treatments selected with farmers tested grass-legume mixtures with different combinations of Vicia Sativa (vetch), Avena sativa (oats), Lupinus mutabilis (Andean lupine), Trifolium pratense (red clover), Medicago sativa (alfalfa), and Lolium multiflorum (ryegrass) compared to an unseeded control fallow with natural revegetation. The ability of fallows to quickly cover soil was tested, as was their biomass production in years one and three. Following the incorporation of fallow vegetation in a sub-set of nine fields, we also tested fallows’ effects on soil pH, available phosphorus (P), permanganate-oxidizable carbon (POXC) and potato yield. In year one managed fallows produced from 1.9 to 5.4 Mg ha−1 of forage biomass compared to 0.5 to 1.1 Mg ha−1 in unseeded controls. Managed fallows also exceeded controls in nutrient uptake, soil cover, and forage quality (lower lignin and higher protein content). First-year biomass of vetch and Andean lupine responded differently to soil pH in fields, indicating that appropriate fallow options likely depend on soil context. After three years, total biomass did not differ among treatments. However, legumes had greater biomass in treatments employing perennial species (0.79–1.18 Mg ha−1 of legumes) than in controls (0.15 Mg ha−1). Potato yield and soil fertility was not reduced in managed fallows compared to the control, and an alfalfa + liming treatment yielded higher than the control (p < 0.05). Diseased tubers were also less prevalent in fallows containing ryegrass and clover, versus other treatments (2.7 % vs. 4.7 % diseased; p = 0.05). In a post-hoc analysis considering 41 treatment plots with contrasting cutting regimes, plots that were cut repeatedly throughout the fallow period had more negative changes in POXC than those cut initially and then left to regrow (p = 0.04). In evaluation workshops, farmers emphasized forage production, potato yield, and potato tuber health as evaluation criteria for the fallows, and ranked the alfalfa + liming treatment as the best. In Andean communities with shortening fallow periods, forage-based fallows represent a promising, multi-functional option to maintain soil health and productivity while generating additional sources of high-quality forage. However, future research should examine long-term nutrient and carbon balances under different forage removal scenarios, as well as designing fallows for varied agroecological contexts.

Optimizing acquisition parameters in diffuse reflectance infrared Fourier transform spectroscopy of soils

AbstractThe number of co‐added scans and spectral resolution are two fundamental acquisition parameters in diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). However, systematic studies evaluating these parameters in soil science applications are lacking, especially when using mid‐infrared frequencies (mid‐DRIFTS). The objective of this study was to evaluate how numbers of co‐added scans and spectral resolution affect both qualitative and predictive applications of high‐throughput mid‐DRIFTS of soils. We first explored the literature with a systematic review to better understand variability in acquisition parameters and their hypothesized relationships with mid‐DRIFTS predictive performance (accuracy) of soil organic and/or total carbon (as a reference variable), but no evident relationship could be established across studies. Second, we experimentally evaluated how spectral resolutions (4, 8, 16, and 32 cm−1), and number of co‐added scans (8, 16, and 24 scans) affected (i) specific spectral peaks representing mineral and organic functional groups, and (ii) predictive performance of soil variables clay, sand, pH, total organic carbon, and permanganate oxidizable carbon (POXC). Decreasing the number of co‐added scans from 24 to 8 increased wavenumber‐specific spectral variability and decreased both the predictive performance and the ability to characterize smaller peaks of mineral and organic functional groups. In contrast, broadening spectral resolution from 4 to 32 cm−1 reduced multivariate scores dispersion and had a positive effect on the predictive performance, even though some smaller peaks disappeared in resolutions wider than 8 cm−1. Acquisition parameters can be set to reduce both scanning time and computational demand while maintaining qualitative and predictive applications of mid‐DRIFTS in soil analysis.

Fungal community shifts in soils with varied cover crop treatments and edaphic properties

Cover cropping is proposed to enhance soil microbial diversity and activity, with cover crop type affecting microbial groups in different ways. We compared fungal community compositions of bulk soils differing by cover crop treatment, season, and edaphic properties in the third year of an organic, conventionally tilled rotation of corn-soybean-wheat planted with winter cover crops. We used Illumina amplicon sequencing fungal assemblages to evaluate effects of nine treatments, each replicated four times, consisting of six single winter cover crop species, a three-species mixture, a six-species mixture, and fallow. Alpha-diversity of fungal communities was not affected by cover crop species identity, function, or diversity. Sampling season influenced community composition as well as genus-level abundances of arbuscular mycorrhizal (AM) fungi. Cover crop mixtures, specifically the three-species mixture, had distinct AM fungal community compositions, while cereal rye and forage radish monocultures had unique Core OTU compositions. Soil texture, pH, permanganate oxidizable carbon, and chemical properties including Cu, and P were important variables in models of fungal OTU distributions across groupings. These results showed how fungal composition and potential functions were shaped by cover crop treatment as well as soil heterogeneity.

Assessing the sensitivity and repeatability of permanganate oxidizable carbon as a soil health metric: An interlab comparison across soils

Soil organic matter is central to the soil health framework. Therefore, reliable indicators of changes in soil organic matter are essential to inform land management decisions. Permanganate oxidizable carbon (POXC), an emerging soil health indicator, has shown promise for being sensitive to soil management. However, strict standardization is required for widespread implementation in research and commercial contexts. Here, we used 36 soils—three from each of the 12 USDA soil orders—to determine the effects of sieve size and soil mass of analysis on POXC results. Using replicated measurements across 12 labs in the US and the EU (n = 7951 samples), we quantified the relative importance of 1) variation between labs, 2) variation within labs, 3) effect soil mass, and 4) effect of soil sieve size on the repeatability of POXC. We found a wide range of overall variability in POXC values across labs (0.03 to 171.8%; mean = 13.4%), and much of this variability was attributable to within-lab variation (median = 6.5%) independently of soil mass or sieve size. Greater soil mass (2.5 g) decreased absolute POXC values by a mean of 177 mg kg−1 soil and decreased analytical variability by 6.5%. For soils with organic carbon (SOC) >10%, greater soil mass (2.5 g) resulted in more frequent POXC values above the limit of detection whereas the lower soil mass (0.75 g) resulted in POXC values below the limit of detection for SOC contents <5%. A finer sieve size increased absolute values of POXC by 124 mg kg−1 while decreasing the analytical variability by 1.8%. In general, soils with greater SOC contents had lower analytical variability. These results point to potential standardizations of the POXC protocol that can decrease the variability of the metric. We recommend that the POXC protocol be standardized to use 2.5 g for soils <10% SOC. Sieve size was a relatively small contributor to analytical variability and therefore we recommend that this decision be tailored to the study purpose. Tradeoffs associated with these standardizations can be mitigated, ultimately providing guidance on how to standardize POXC for routine analysis.

Tuning support vector machines regression models improves prediction accuracy of soil properties in MIR spectroscopy

Estimating soil properties in diffuse reflectance infrared Fourier transform spectroscopy in the mid-infrared region (mid-DRIFTS) uses statistical modeling (chemometrics) to predict soil properties from spectra. Modeling approaches can have major impacts on prediction accuracy. However, the impact of selecting best parameters for an algorithm (tuning), to optimize non-linear models for predicting soil properties, is relatively unexplored in the domain of soil sciences. This study aimed to evaluate the predictive performance of linear (partial least squares, PLS) and non-linear (support vector machines, SVM) multivariate regression models in estimating soil physical, chemical, and biological properties with mid-DRIFTS. We evaluated the impact of optimizing two hyperparameters (epsilon and cost) based on the noise tolerance in the ε-insensitive loss function of SVM models using two contrasting and diverse sets of soils, one from northern Tanzania (n = 533) and another one from USA Midwest (n = 400). Regression models were trained on calibration sets (75%) and tested on independent validation sets (25%) separately for each dataset. Support vector machines outperformed PLS models for all tested soil properties (clay, sand, pH, total organic carbon, and permanganate oxidizable carbon) in both datasets. Tuning hyperparameters epsilon and cost maintained or improved prediction accuracy of SVM models based on root mean squared errors of independent validation sets. Support vector machines tuned hyperparameters differed among soil properties and also for the same soil property in distinct datasets, suggesting the need for parameterizing non-linear models for specific soil properties and datasets. Optimizing SVM regression models in mid-DRIFTS improves prediction accuracy of soil properties and therefore will likely enable obtaining more robust predictive outcomes even in datasets with diverse land uses, parent materials, and/or soil orders. We recommend that tuning should be included as a routine step when using SVM for estimating soil properties.

Permanganate oxidizable carbon for soil health: Does drying temperature matter?

AbstractSoil health assessments evaluate and monitor the effects of conservation management on soil properties. A popular measurement, permanganate oxidizable carbon (POXC), is routinely included in these assessments. The standard POXC protocol calls for air‐dried soil samples, but commercial laboratories typically dry samples in a forced‐air oven before routine analysis. In order to evaluate if heat would change POXC measurements, we treated soil (52 silty clay loam and 51 sandy loam samples) with oven drying at 45 and 65 °C and compared their POXC values with those from air‐dried samples. We also examined relationships between POXC values and soil organic matter, pH, and electrical conductivity across drying treatments. Drying soil did not substantially change POXC values for either soil texture and did not change the relationships between POXC and other measured soil properties. This work suggests that commercial laboratories could perform POXC analysis on soil samples dried using heat.

Novel soil quality indicators for the evaluation of agricultural management practices: a biological perspective

Developments in soil biology and in methods to characterize soil organic carbon can potentially deliver novel soil quality indicators that can help identify management practices able to sustain soil productivity and environmental resilience. This work aimed at synthesizing results regarding the suitability of a range of soil biological and biochemical properties as novel soil quality indicators for agricultural management. The soil properties, selected through a published literature review, comprised different labile organic carbon fractions [hydrophilic dissolved organic carbon, dissolved organic carbon, permanganate oxidizable carbon (POXC), hot water extractable carbon and particulate organic matter carbon], soil disease suppressiveness measured using a <i>Pythium</i>-<i>Lepidium</i> bioassay, nematode communities characterized by amplicon sequencing and qPCR, and microbial community level physiological profiling measured with MicroResp^TM. Prior studies tested the sensitivity of each of the novel indicators to tillage and organic matter addition in ten European long-term field experiments (LTEs) and assessed their relationships with pre-existing soil quality indicators of soil functioning. Here, the results of these previous studies are brought together and interpreted relative to each other and to the broader body of literature on soil quality assessment. Reduced tillage increased carbon availability, disease suppressiveness, nematode richness and diversity, the stability and maturity of the food web, and microbial activity and functional diversity. Organic matter addition played a weaker role in enhancing soil quality, possibly due to the range of composition of the organic matter inputs used in the LTEs. POXC was the indicator that discriminated best between soil management practices, followed by nematode indices based on functional characteristics. Structural equation modeling shows that POXC has a central role in nutrient retention/supply, carbon sequestration, biodiversity conservation, erosion control and disease regulation/suppression. The novel indicators proposed here have great potential to improve existing soil quality assessment schemes. Their feasibility of application is discussed and needs for future research are outlined.

Soil carbon dioxide efflux from amended saline and thermally desorbed oil‐contaminated subsoil

AbstractSoil carbon (C) dynamics are often challenged by soil properties like high salt concentration and low organic matter content. To examine options for improving the quality of degraded soils, two pairs of soils, (a) non‐saline and (b) saline surface soils from an agricultural field, and (a) non‐contaminated subsoil and (b) thermal desorption‐treated subsoil from an oil‐contaminated site were collected. For the laboratory incubation, these four soils were treated with three amendments, (a) composted beef manure, (b) spent lime from sugarbeet (Beta vulgaris L.) processing, and (c) commercial mulch (Proganics), and soil CO2 efflux was measured for three consecutive drying–rewetting (DW) cycles. Base efflux and the rate of change in base efflux were calculated from the slope and intercept of a linear fit model of CO2 efflux over time (h), respectively for each DW cycle. Soil, amendment, and DW had significant effect on base efflux and the rate of change in base efflux during DW. Proganics had the highest base efflux of 29.0 and 24.0 μg CO2–C m−2 d−1 for saline and thermal desorption‐treated soils, respectively, and significantly (P &lt; .05) higher than other amendments. Spent lime and compost also significantly (P &lt; .05) increased base efflux over the control. Base efflux had a strong association with permanganate oxidizable carbon (POXC) for all soils, and a strong association with inorganic N for only saline and non‐saline soils. Amendments increased microbial metabolism and have the potential to improve soil health and crop production for soils with severe limitations.

Early response of organic matter dynamics to pine‐biochar in sandy soil under peach trees

AbstractBiochar may enhance soil health in sandy soils under peach [Prunus persica (L.) Batsch] tree production. A study was initiated in the Sandhills of North Carolina by applying pine‐biochar at two different rates (5 and 10%, v/v) and types of application (incorporation to 30 cm [‐Inc] and surface [‐Sur]) in 2017. Soil organic matter (SOM) dynamics was assessed via soil organic carbon (SOC), total nitrogen (TN), permanganate‐oxidizable carbon (POXC), aggregate fractions (macro‐, micro‐aggregates, and clay + silt particles), and enzyme activities (CNPS activity) at 0–15 and 15–30 cm in 2018 and 2019. After the first year of pine‐biochar application, POXC decreased in all biochar treatments, SOC was higher in the 10%‐Inc treatment, whereas CNPS activities and macroaggregates were highest in the 5%‐Sur compared with the non‐treated control. These results suggest early changes in SOM dynamics and biogeochemical cycling and have the potential to guide producers with the long‐term application of pine‐biochar to sandy soils.

Predicting soil permanganate oxidizable carbon (POXC) by coupling DRIFT spectroscopy and artificial neural networks (ANN)

Infrared spectroscopy has transformed soil property quantification by enabling low-cost, high-throughput analysis of soils, enabling mapping and monitoring of this non-renewable resource. However, less evaluated are newly emerging indicators of soil health. Furthermore, as soil spectral libraries expand in size, commonly employed linear models such as partial least squares regression (PLSR) may be challenged by the number and diversity of spectra. Artificial neural networks (ANN) are an emerging deep learning approach that can offer advantages in quantification of soil properties by utilizing non-linear relationships among spectra and soil components. We compared ANN versus PLSR models for predicting an increasingly used soil health indicator, permanganate oxidizable C (POXC), as well as more routinely predicted soil variables (e.g., clay, soil organic C [SOC]), across a gradient of soil organic matter furnished by a deforestation chronosequence in Kenya (n = 144). Candidate ANN architectures were first methodologically evaluated and described to identify best-practices for the application of ANN to soil spectroscopy. Predictions by the resulting ANN relative to PLSR were similar or slightly improved for routinely measured variables that represent soil organic matter (SOC, C:N) and physical properties (clay, silt, sand, bulk density). The accuracy of POXC predictions were similar for ANN (RMSE 102 mg kg−1) and PLSR (RMSE 106 mg kg−1). However, models drew on shared but also distinct wavenumbers, indicating differential use of information in soil infrared spectra by non-linear versus linear chemometric models. Even in relatively small spectral datasets of similar soil types expected to favor PLSR, ANN shows comparable predictive performance. To help guide future applications of ANN in soil spectroscopy, we propose a systematic procedure to select ANN model hyperparameters.

Soil microbial community responses to labile organic carbon fractions in relation to soil type and land use along a climate gradient

There has been a growing interest in studying the labile C pool in order to promote the sequestration and stabilization of soil organic carbon (SOC). Although labile SOC fractions have emerged as standardized indicators because of their potential to detect early SOC trends over time, the relationships between microbial attributes and labile SOC remains poorly understood. In this study, we explored the influence of labile SOC fractions on the topsoil bacteria-archaea community across 28 sites with different land use, climate aridity, and soil types across a wide range of SOC content (0.6–12%) in central Chile. We applied Illumina sequencing to the 16S rRNA to examine shifts in the diversity and composition of these soil microbial communities. Additionally, labile SOC fractions such as the permanganate oxidizable carbon (POXC) and light fraction organic matter (LFOM), along with the soil physicochemical properties were analyzed. The results demonstrated that among all of the environmental factors tested, the pH, POXC/SOC ratio and LFOM were key drivers of microbial community structure (β-diversity). The α-diversity metrics exhibited a decreasing trend when aridity increased, and community structure was found to vary, with high POXC/SOC in sites associated with drier conditions. In addition, POXC/SOC ratios and LFOM were clearly related to shifts in the relative abundances of specific taxonomic groups at genera level. When there was high POXC/SOC and low LFOM content, members of Bacteroidetes (Adhaeribacter, Flavisolibacter, and Niastella), Proteobacteria (Skermanella, Ramlibacter, and Sphingomonas), and Archaea (Thaumarchaeota) were found to be the most dominant groups; however, the microbial taxa responded differently to both labile C fraction types. These results have implications for understanding how labile C content can potentially be used to predict shifts in the microbial community, thus facilitating the development of predictive ecosystem models, as well as early warning indicators for soil degradation.

Management sensitivity, repeatability, and consistency of interpretation of soil health indicators on organic farms in southwestern Ontario

Assessment tools are needed to evaluate the effect of farming practices on soil health, as there is increasing interest from growers to improve the health of their soils. However, there is limited information on the efficacy of different soil health indicators on commercial farms and perhaps less so on organic farms. To assess efficacy, three organic growers in cooperation with the Ecological Farmers Association of Ontario’s Farmer-Led Research Program tested management sensitivity, measurement repeatability, and consistency of interpretation of different soil health indicators. On each farm, we compared permanganate-oxidizable carbon (active carbon), organic matter, wet aggregate stability, phospholipid fatty acid analysis, Haney soil health test, and Haney nutrient test on one field of grower-perceived high productivity, one field of grower-perceived low productivity, and one reference site (undisturbed, permanent cover). Our results were consistent with previous research that showed grower perception of productivity and soil health associated with management-sensitive soil health indicators. Of the indicators tested, active carbon was the only indicator that was sensitive, repeatable, and consistent across the three farms, and soil organic matter was highly repeatable and consistent to detect differences greater than 0.5% organic matter. This study highlights differences among soil health indicators on commercial farms, and it concludes that active carbon and organic matter were the most useful soil health indicators for these organic farms. Participating growers intend to use results to benchmark current soil status and to help guide land management decisions towards improved soil health.