Evaluating a low‐cost portable NIR spectrometer for the prediction of soil organic and total carbon using different calibration models

This study aims to assess the performance of a low‐cost, micro‐electromechanical system‐based, near infrared spectrometer for soil organic carbon (OC) and total carbon (TC) estimation. TC was measured on 151 soil profiles up to the depth of 1 m in NSW, Australia, and from which a subset of 24 soil profiles were measured for OC. Two commercial spectrometers including the AgriSpec^TM (ASD) and NeoSpectra^TM (Neospectra) with spectral wavelength ranges of 350–2,500 and 1,300–2,500 nm, respectively, were used to scan the soil samples, according to the standard contact probe protocol. Savitzky–Golay smoothing filter and standard normal variate (SNV) transformation were performed on the spectral data for noise reduction and baseline correction. Three calibration models, including Cubist tree model, partial least squares regression (PLSR) and support vector machine (SVM), were assessed for the prediction of soil OC and TC using spectral data. A 10‐fold cross‐validation analysis was performed for evaluation of the models and devices accuracies. Results showed that Cubist model predicts OC and TC more accurately than PLSR and SVM. For OC prediction, Cubist showed R² = 0.89 (RMSE = 0.12%) and R² = 0.78 (RMSE = 0.16%) using ASD and NeoSpectra, respectively. For TC prediction, Cubist produced R² = 0.75 (RMSE = 0.45%) and R² = 0.70 (RMSE = 0.50%) using ASD and NeoSpectra, respectively. ASD performed better than NeoSpectra. However, the low‐cost NeoSpectra predictions were comparable to the ASD. These finding can be helpful for more efficient future spectroscopic prediction of soil OC and TC with less costly devices.     

Microbial contribution to SOM quantity and quality in density fractions of temperate arable soils

The formation of soil organic matter (SOM) very much depends on microbial activity. Even more, latest studies identified microbial necromass itself being a significant source of SOM and found microbial products to initiate and enhance the formation of long-term stabilized SOM. The objectives of this study were to investigate the microbial contribution to SOM in pools of different stability and its impact on SOM quality. Hence, four arable soils of widely differing properties were density-fractionated into free and occluded particulate organic matter (fPOM, oPOM < 1.6 g cm⁻³ and oPOM < 2.0 g cm⁻³) and mineral associated organic matter (MOM > 2.0 g cm⁻³) by using sodium polytungstate. These fractions were characterized by in-source pyrolysis-field ionization mass spectrometry (Py-FIMS). Main SOM compound classes of the fractions were determined and further SOM properties were derived (polydispersity, thermostability). The contribution of microbial derived input to arable soil OM was estimated from the hexose to pentose ratio of the carbohydrates and the ratio of C₄–C₂₆ to C₂₆–C₃₆ fatty acids. Additionally, selected samples were investigated by scanning electron microscopy (SEM) for visualizing structures as indicators for the origin of OM. Results showed that, although the samples differed significantly regarding soil properties, SOM composition was comparable and almost 50% of identifiable SOM compounds of all soils types and all density fractions were assigned to phenols, lignin monomers and alkylaromatics. Most distinguishing were the high contents of carbohydrates for the MOM and of lipids for the POM fractions. Qualitative features such as polydispersity or thermostability were not in general assignable to specific compounds, density fractions or different mean residence times. Only the microbial derived part of the soil carbohydrates could be shown to be correlated with high SOM thermostability (r² = 0.63**, n = 39). Microbial derived carbohydrates and fatty acids were both enriched in the MOM, showing that the relative contribution of microbial versus plant-derived input to arable SOM increased with density and therefore especially increased MOM thermostability. Nevertheless, the general microbial contribution to arable SOM is suggested to be high for all density fractions; a mean proportion of about 1:1 was estimated for carbohydrates. Despite biomolecules released from living microorganisms, SEM revealed that microbial mass (biomass and necromass) is a considerable source for stable SOM which is also increasing with density.     

Mapping soil pH levels across Europe: An analysis of LUCAS topsoil data using random forest kriging (RFK)

Soil pH affects food production, pollution control and ecosystem services. Mapping soil pH levels, therefore, provides policymakers with crucial information for developing sustainable soil use and management policies. In this study, we used the LUCAS 2015 TOPSOIL data to map soil pH at a European level. We used random forest kriging (RFK) to build a predictive model of spatial variability of soil pH, as well as random forest (RF) without co-kriging and boosted regression trees (BRT) modelling techniques. Model accuracy was evaluated using a ten-fold cross-validation procedure. While we found that all methods accurately predicted soil pH, the accuracy of the RFK method was best with regression performance metrics of: R² = 0.81 for pH (H₂O) and pH (CaCl₂); RMSE = 0.59 for pH (H₂O) and RMSE = 0.61 in pH (CaCl₂); MAE = 0.41 for pH (H₂O) and MAE = 0.43 in pH (CaCl₂). Dominant explanatory variables in the RF and BRT modelling were topography and remote sensing variables, respectively. The generated maps broadly depicted similar spatial patterns of soil pH, with an increasing gradient of soil pH from north to south Europe, with the highest values mainly concentrated along the Mediterranean coast. The mapping could provide spatial reference for soil pH assessment and dynamic monitoring.     

中国农耕区土壤有机质含量及其与酸碱度和容重关系

对我国农耕区土壤有机质区域变化及其与酸碱度和容重关系进行系统分析,为耕地地力提升和改善土壤结构提供支撑。基于国家级耕地长期定位监测点913个,统计分析全国及7大区域（东北NE、华北NC、西北NW、长江中游MYR、长三角YRD、华南SC、西南SW）耕层土壤有机质含量、酸碱度及容重变化特征。结果表明,全国农耕区耕层土壤有机质含量平均值为22.4~24.8 g/kg。其中有机质含量中等偏低的监测点位占比达72.5%。不同区域耕层土壤有机质含量差异显著（p<0.05）,MYR耕层土壤有机质含量显著高于其他6个区域。全国农耕区耕层土壤pH和容重平均分别为（6.90±1.20）,（1.30±0.15） g/cm³。不同土壤利用方式对土壤有机质、酸碱度及容重产生影响。水田耕层土壤有机质含量显著高于旱地,旱地耕层土壤pH和容重则显著高于水田。亚当斯方程和指数函数分别推荐拟合土壤容重对有机质含量响应关系（R²=0.09,RMSE=0.17,n=759）,以及土壤pH对土壤有机质含量响应（R²=0.16,RMSE=1.24,n=886）。全国农耕区耕层土壤有机质含量总体中等偏低,呈现出东南向西北依次降低趋势。土壤pH及容重与土壤有机质呈现显著的负相关关系。亚当斯模型及指数方程能较好地拟合土壤容重及pH对有机质的响应关系,可用于非线性插值法补充土壤容重及pH缺失值。     

Earthworm populations in relation to soil organic matter dynamics and management in California tomato cropping systems

Earthworms are key regulators of soil structure and soil organic matter (SOM) dynamics in many agroecosystems. They are greatly impacted by agricultural management, yet little is known about how these factors interact to control SOM dynamics. This study sought to explore linkages between agricultural management, earthworms and aggregate associated SOM dynamics through a survey of tomato (Solanum lycopersicum L.) cropping systems in northern California. Earthworms and soil samples were collected between February and April of 2005 from 16 fields under one of three types of residue management: (1) tomato mulch – no postharvest tillage and tomato residues left on the soil surface, (2) cover crop – tomato residues tilled in and leguminous cover crop planted, and (3) bare fallow – tomato residues tilled in and soil surface left exposed throughout the winter. Earthworms were collected via hand-sorting and identified to species, while soils were wet sieved to yield four aggregate size classes: large macroaggregates (>2000 μm), small macroaggregates (250–2000 μm), microaggregates (53–250 μm) and the silt and clay fraction (<53 μm). The combined large and small macroaggregate fraction was then fractionated into coarse particulate organic matter (cPOM; 250 μm), microaggregates within macroaggregates (mM; 53–250 μm) and macroaggregate occluded silt and clay (Msc; <53 μm). The earthworms identified in this survey were composed entirely of exotic species and were dominated by Aporrectodea caliginosa. Earthworm abundance was related to residue management, with the tomato mulch systems averaging 4.5 times greater fresh earthworm biomass than bare fallow (P = 0.024). Aggregate stability and total soil C and N also appeared to be influenced by residue management, such that the tomato mulch system displayed significantly greater mean weight diameters than the bare fallow system (P = 0.049), as well as more than 50% greater total soil C and N (P = 0.049 and P = 0.036; respectively). Earthworm biomass was also found to be positively correlated with total soil C (P = 0.009, R² = 0.39) and N (P = 0.010, R² = 0.039) as well as the proportion of macroaggregate C in the cPOM fraction (P = 0.028, R² = 0.30). Our findings suggest that residue handling and the associated management practices (e.g., tillage, organic vs. conventional agriculture) are important for both earthworm populations and SOM storage. Although earthworms are known to influence SOM in many ways, other factors appear to play a more prominent role in governing aggregate associated SOM dynamics.     

Relationships between C respiration and fine particulate organic matter (250–50 μm) weight

Soil organic matter (SOM) status was evaluated using the relationships between two independent soil variables, i.e., C respiration and the weight of particulate organic matter POM (4000–50 μm) under different vegetation covers and ecosystems of central Belgium. A positive relationship was found between the weight of the finest POM fraction, i.e., fine POM fraction (250–50 μm) and C respiration after 1 week (R² = 0.34, n = 120, p < 0.0001) and 2 weeks (R² = 0.28, n = 120, p < 0.0001) of incubation. Therefore, we assumed that the C respiration and the weight of fine POM might be used to evaluate the SOM status under different vegetation covers and ecosystems.     

Long‐term effects of tillage,nutrient application and crop rotation on soil organic matter quality assessed by NMR spectroscopy

Crop and land management practices affect both the quality and quantity of soil organic matter (SOM) and hence are driving forces for soil organic carbon (SOC) sequestration. The objective of this study was to assess the long‐term effects of tillage, fertilizer application and crop rotation on SOC in an agricultural area of southern Norway, where a soil fertility and crop rotation experiment was initiated in 1953 and a second experiment on tillage practices was initiated in 1983. The first experiment comprised 6‐yr crop rotations with cereals only and 2‐yr cereal and 4‐yr grass rotations with recommended (base) and more than the recommended (above base) fertilizer application rates; the second experiment dealt with autumn‐ploughed (conventional‐till) plots and direct‐drilled plots (no‐till). Soil samples at 0–10 and 10–30 cm depths were collected in autumn 2009 and analysed for their C and N contents. The quality of SOM in the top layer was determined by ¹³C solid‐state NMR spectroscopy. The SOC stock did not differ significantly because of rotation or fertilizer application types, even after 56 yr. However, the no‐till system showed a significantly higher SOC stock than the conventional‐till system at the 0–10 cm depth after the 26 yr of experiment, but it was not significantly different at the 10–30 cm depth. In terms of quality, SOM was found to differ by tillage type, rate of fertilizer application and crop rotation. The no‐till system showed an abundance of O‐alkyl C, while conventional‐till system indicated an apparently indirect enrichment in alkyl C, suggesting a more advanced stage of SOM decomposition. The long‐term quantitative and qualitative effects on SOM suggest that adopting a no‐tillage system and including grass in crop rotation and farmyard manure in fertilizer application may contribute to preserve soil fertility and mitigate climate change.     

Using soil organic matter fractions as indicators of soil physical quality

The objective of this study was to evaluate the use of chemical and physical fractions of soil organic matter (SOM ), rather than SOM per se , as indicators of soil physical quality (SPQ ) based on their effect on aggregate stability (AS ). Chemically extracted humic and fulvic acids (HA and FA ) were used as chemical fractions, and heavy and light fractions (HF and LF ) obtained by density separation as physical fractions. The analyses were conducted on medium‐textured soils from tropical and temperate regions under cropland and pasture. Results show that soil organic carbon (SOC ), SOM fractions and AS appear to be affected by land use regardless of the origin of the soils. A general separation of structurally stable and unstable soils between samples of large and small SOC content, respectively, was observed. SOM fractions did not show a better relationship with AS than SOC per se . In both geographical regions, soils under cropland showed the smallest content of SOC , HA and carbon concentration in LF and HF , and the largest HF /LF ratio (proportion of the HF and LF in percent by mass of bulk soil). With significant associations between AS and SOC content (0.79**), FA /SOC (r  = −0.83*^*), HA /FA (r  = 0.58*^*), carbon concentration of LF (r  = 0.69*^*) and HF (r  = 0.70*^*) and HF /LF ratio (r  = 0.80*^*), cropland showed lowest AS . These associations indicate that SOM fractions provide information about differences in SOM quality in relation to AS and SPQ of soils from tropical and temperate regions under cropland and pasture.     

Comparison of Near Infrared Reflectance Spectroscopy with Combustion and Chemical Methods for Soil Carbon Measurements in Agricultural Soils

As interest in soil organic carbon (SOC) dynamics increases, so do needs for rapid, accurate, and inexpensive methods for quantifying SOC. Objectives were to i) evaluate near infrared reflectance (NIR) spectroscopy potential to determine SOC and soil organic matter (SOM) in soils from across Tennessee, USA; and ii) evaluate potential upper limits of SOC from forest, pasture, no-tillage, and conventional tilled sites. Samples were analyzed via dry-combustion (SOC), Walkley–Black chemical SOM, and NIR. In addition, the sample particle size was classified to give five surface roughness levels to determine effects of particle size on NIR. Partial least squares regression was used to develop a model for predicting SOC as measured by NIR by comparing against SOM and SOC. Both NIR and SOM correlated well (R² > 0.9) with SOC (combustion). NIR is therefore considered a sufficiently accurate method for quantifying SOC in soils of Tennessee, with pasture and forested systems having the greatest accumulations.Abbreviations SOC, soil organic carbon; NIR, Near Infrared Reflectance Spectroscopy; MTREC, Middle Tennessee Research and Education Center; RECM, Research and Education Center at Milan; PREC, Plateau Research and Education Center; PLS, Partial least squares.     

How do earthworms influence organic matter quantity and quality in tropical soils?

Earthworms are important regulators of soil structure and soil organic matter (SOM) dynamics; however, quantifying their influence on SOM cycling in tropical ecosystems remains little studied. Simulated rainfall was used to disrupt casts produced by Amynthas khami and their surrounding soil (control) into a range of small sized aggregates (50-250, 250-500, 500-2000 and 2000-5000 μm). To gain insight into how earthworms influence SOM biogeochemical composition in the aggregates, we carried out elemental and stable isotope analysis, and analytical pyrolysis (Py GC/MS). We also characterized their lignin component after oxidation with cupric oxide (CuO).The C content of smaller size fractions (<500 μm) in the control soil was higher than in the larger fractions. Our study therefore suggests that the aggregate hierarchy concept, which is used to understand soil aggregates and SOM dynamics in temperate soils, may not be applicable to the tropical Acrisol studied here. Earthworms modified SOM organization in soil aggregates. Although the isotope analyses were useful for highlighting SOM enrichment in the earthworm casts, aggregate fractions could not be classified according to particle size. Molecular analyses were necessary to indicate that SOM in all size fractions of casts consisted of relatively undecomposed material. Protection of the most labile SOM structures occurred in the smallest aggregate size fraction (50-250 μm). Py GC/MS showed that earthworm casts and control aggregates <2000 μm could be clearly distinguished according to the molecular properties of their SOM. Aggregates larger than 2000 μm, however, were most probably composed of all fractions and were not different. As a consequence, our results indicate that studies to determine the impact of earthworms on SOM turnover in soil are spatially dependant on the scale of observation.     

Accounting for the effects of water and the environment on proximally sensed vis–NIR soil spectra and their calibrations

Visible–near infrared (vis–NIR) spectroscopy can be used to estimate soil properties effectively using spectroscopic calibrations derived from data contained in spectroscopic databases. However, these calibrations cannot be used with proximally sensed (field) spectra because the spectra in these databases are recorded in the laboratory and are different to field spectra. Environmental factors, such as the amount of water in the soil, ambient light, temperature and the condition of the soil surface, cause the differences. Here, we investigated the use of direct standardization (DS) to remove those environmental factors from field spectra. We selected 104 sensing (sampling) sites from nine paddy fields in Zhejiang province, China. At each site, vis–NIR spectra were recorded with a portable spectrometer. The soils were also sampled to record their spectra under laboratory conditions and to measure their soil organic matter (SOM) content. The resulting data were divided into training and validation sets. A subset of the corresponding field and laboratory spectra in the training set (the transfer set) was used to derive the DS transfer matrix, which characterizes the differences between the field and laboratory spectra. Using DS, we transferred the field spectra of the validation samples so that they acquired the characteristics of spectra that were measured in the laboratory. A partial least squares regression (PLSR) of SOM on the laboratory spectra of the training set was then used to predict both the original field spectra and the DS‐transferred field spectra. The assessment statistics of the predictions were improved from R² = 0.25 and RPD = 0.35 to R² = 0.69 and RPD = 1.61. We also performed independent predictions of SOM on the DS‐transferred field spectra with a PLSR derived using the Chinese soil spectroscopic database (CSSD), which was developed in the laboratory. The R² and RPD values of these predictions were 0.70 and 1.79, respectively. Predictions of SOM with the DS‐transferred field spectra were more accurate than those treated with external parameter orthogonalisation (EPO), and more accurate than predictions made by spiking. Our results show that DS can effectively account for the effects of water and environmental factors on field spectra and improve predictions of SOM. DS is conceptually straightforward and allows the use of calibrations made with laboratory‐measured spectra to predict soil properties from proximally sensed (field) spectra, without needing to recalibrate the models.     

Dry-rewetting cycles regulate wheat carbon rhizodeposition,stabilization and nitrogen cycling

Drying and rewetting of soil can have large effects on carbon (C) and nitrogen (N) dynamics. Drying-rewetting effects have mostly been studied in the absence of plants, although it is well known that plant–microbe interactions can substantially alter soil C and N dynamics. We investigated for the first time how drying and rewetting affected rhizodeposition, its utilization by microbes, and its stabilization into soil (C associated with soil mineral phase). We also investigated how drying and rewetting influenced N mineralization and loss. We grew wheat (Triticum aestivum) in a controlled environment under constant moisture and under dry-rewetting cycles, and used a continuous ¹³C-labeling method to partition plant and soil organic matter (SOM) contribution to different soil pools. We applied a ¹⁵N label to the soil to determine N loss. We found that dry-rewetting decreased total input of plant C in microbial biomass (MB) and in the soil mineral phase, mainly due to a reduction of plant biomass. Plant derived C in MB and in the soil mineral phase were positively correlated (R² = 0.54; P = 0.0012). N loss was reduced with dry rewetting cycles, and mineralization increased after each rewetting event. Overall drying and rewetting reduced rhizodeposition and stabilization of new C, primary through biomass reduction. However, frequency of rewetting and intensity of drought may determine the fate of C in MB and consequently into the soil mineral phase. Frequency and intensity may also be crucial in stimulating N mineralization and reducing N loss in agricultural soils.     

Soil organic matter assessment in natural regrowth,Pueraria phaseoloides and Mucuna pruriens fallow

Biological and chemical components of soil fertility were quantified under three different fallow types and related to soil quality of an Ultisol in southern Cameroon at the end of a 9-month fallow. Soil organic matter (SOM), soil exchangeable Ca²⁺, Mg²⁺ and K⁺ and available P concentrations, effective cation exchange capacity (ECEC) and, soil acidity in the 0–10 and 10–20 cm layers were evaluated under: natural regrowth mainly composed of Chromolaena odorata and the legume cover crops velvet bean (Mucuna pruriens var. utilis) and kudzu (Pueraria phaseoloides). SOM quality was assessed by C mineralisation during a 4-week incubation at 28°C in the laboratory. In addition, particulate organic matter (POM), the most active part of SOM, was fractionated by wet sieving into coarse (4000–2000 μm), medium (2000–250 μm) and fine (250–53 μm) particle size classes and analysed for C and N contents. Under Mucuna, Ca²⁺, K⁺ and P concentrations, ECEC and soil pH were higher and C mineralisation was lower than under natural regrowth and Pueraria in 0–10 cm depth. Soil under natural regrowth had a higher C mineralisation in 0–10 cm indicating more labile SOM than in Pueraria and Mucuna fallow. There was no difference in weight of total POM, for any of the fractions between the three fallow types. However, both leguminous fallow species increased POM quality through a higher N content. Compared to natural regrowth, Pueraria increased N content in coarse POM by 36% in the 0–10 cm layer and by 19% (coarse POM) and 35% (medium POM) in the 10–20 cm layer. Mucuna increased N content in the 0–10 cm layer by 12% (coarse POM), and by 19% (fine POM), compared to natural regrowth. According to the differences in nutrient concentrations, soil acidity and the biological stability of SOM, the three fallow types ranked: Mucuna≥Pueraria>natural regrowth. However, in terms of POM quality the ranking was: Pueraria>Mucuna>natural regrowth.     

Spectroscopy-Based Soil Organic Matter Estimation in Brown Forest Soil Areas of the Shandong Peninsula, China

Soil organic matter (SOM) is important for plant growth and production. Conventional analyses of SOM are expensive and time consuming. Hyperspectral remote sensing is an alternative approach for SOM estimation. In this study, the diffuse reflectance spectra of soil samples from Qixia City, the Shandong Peninsula, China, were measured with an ASD FieldSpec 3 portable object spectrometer (Analytical Spectral Devices Inc., Boulder, USA). Raw spectral reflectance data were transformed using four methods:nine points weighted moving average (NWMA), NWMA with first derivative (NWMA + FD), NWMA with standard normal variate (NWMA + SNV), and NWMA with min-max standardization (NWMA + MS). These data were analyzed and correlated with SOM content. The evaluation model was established using support vector machine regression (SVM) with sensitive wavelengths. The results showed that NWMA + FD was the best of the four pretreatment methods. The sensitive wavelengths based on NWMA + FD were 917, 991, 1 007, 1 996, and 2 267 nm. The SVM model established with the above-mentioned five sensitive wavelengths was significant (R²=0.875, root mean square error (RMSE)=0.107 g kg^-1 for calibration set; R²=0.853, RMSE=0.097 g kg^-1 for validation set). The results indicate that hyperspectral remote sensing can quickly and accurately predict SOM content in the brown forest soil areas of the Shandong Peninsula. This is a novel approach for rapid monitoring and accurate diagnosis of brown forest soil nutrients.     

C and N in soil organic matter density fractions under elevated atmospheric CO2: Turnover vs. stabilization

Turnover of C and N in an arable soil under Free Air Carbon Dioxide (FACE) experiment was studied by the use of ¹³C natural abundance and ¹⁵N-labeled fertilizers. Wheat was kept four growing seasons under ambient and elevated CO₂ concentrations and fertilized for three growing seasons. Density fractionation of soil organic matter (SOM) allowed to track ¹³C and ¹⁵N in free particulate organic matter (fPOM; <1.6 g cm⁻³), particulate organic matter occluded within aggregates with two densities (oPOM 1.6, oPOM 1.6-2.0 g cm⁻³), and in mineral-associated organic matter (>2.0 g cm⁻³) fractions. Elevated CO₂ and N fertilization did not significantly affect C and N contents in the bulk soil. Calculated mean residence time (MRT) of C and N revealed the qualitative differences of SOM density fractions: (i) the shortest MRT_C and MRT_N in fPOM confirmed high availability of this fraction to decomposition. Larger C/N ratio of fPOM under elevated vs. ambient CO₂ indicated an increasing recalcitrance of FACE-derived plant residues. (ii) There was no difference in MRT of C and N between lighter and heavier oPOMs probably due to short turnover time of soil aggregates which led to oPOM mixing. The increase of MRT_C and MRT_N in both oPOMs during the experiment confirmed the progressive degradation of organic material within aggregates. (iii) Constant turnover rates of C in the mineral fraction neither confirmed nor rejected the assumed stabilization of SOM to take place in the mineral fraction. Moreover, a trend of decreasing of C and N amounts in the Min fraction throughout the experiment was especially pronounced for C under elevated CO₂. Hence, along with the progressive increase of C_FACE in the Min fraction the overall losses of C under elevated CO₂ may occur at the expense of older “pre-FACE” C.     

Pathways of litter C by formation of aggregates and SOM density fractions: Implications from 13C natural abundance

Aggregate formation is a key process of soil development, which promotes carbon (C) stabilization by hindering decomposition of particulate organic matter (POM) and its interactions with mineral particles. C stabilization processes lead to ¹³C fractionation and consequently to various δ¹³C values of soil organic matter (SOM) fractions. Differences in δ¹³C within the aggregates and fractions may have two reasons: 1) preferential stabilization of organic compounds with light or heavy δ¹³C and/or 2) stabilization of organic materials after passing one or more microbial utilization cycles, leading to heavier δ¹³C in remaining C. We hypothesized that: 1) ¹³C enrichment between the SOM fractions corresponds to successive steps of SOM formation; 2) ¹³C fractionation (but not the δ¹³C signature) depends mainly on the transformation steps and not on the C precursors. Consequently, minimal differences between Δ¹³C of SOM fractions between various ecosystems correspond to maximal probability of the SOM formation pathways.We tested these hypotheses on three soils formed from cover loam during 45 years of growth of coniferous or deciduous forests or arable crops. Organic C pools in large macroaggregates, small macroaggregates, and microaggregates were fractionated sequentially for four density fractions to obtain free POM with ρ < 1.6 g cm⁻³, occluded POM with two densities (ρ < 1.6 and 1.6–2.0 g cm⁻³), and mineral fraction (ρ > 2.0 g cm⁻³).The density fractions were ¹³C enriched in the order: free POM < light occluded POM < heavy occluded POM < mineral fraction. This, as well as their C/N ratios confirmed that free POM was close to initial plant material, whereas the mineral fraction was the most microbially processed. To evaluate the successive steps of SOM formation, the Δ¹³C values between δ¹³C of SOM fractions and δ¹³C of bulk SOM were calculated. The Δ¹³C indicated that, parallel with biochemical transformations, the physical disintegration strongly contributed to the formation of free and occluded light POM. In contrast, biochemical transformations were more important than physical disintegration for formation of heavy occluded POM from light occluded POM. This was confirmed by review of 70 Δ¹³C values from other studies analyzed Δ¹³C depending on the density of SOM fractions. Accordingly, the successive steps of SOM formation were: fLF_<1.6 = oLF_<1.6 → oDF_1.6–2.0 = MF_>2.0. The obtained steps of C stabilization were independent on the initial precursors (litter of coniferous forest, deciduous forest or grasses).To test the second hypothesis, we proposed an extended scheme of C flows between the 3 aggregate size classes and 4 SOM fractions. Δ¹³C enrichment of the SOM fractions showed that the main direction of C flows within the aggregates and SOM fractions was from the macroaggregate-free POM to the mineral microaggregate fraction. This confirmed the earlier concept of SOM turnover in aggregates, but for the first time quantified the C flows within the aggregates and SOM density fractions based on δ¹³C values. So, the new ¹³C natural abundance approach is suitable for analysis of C pathways by SOM formation under steady state without ¹³C or ¹⁴C labeling.     

Mineralogy and factors controlling charge development of three Oxisols developed from different parent materials

Three Oxisols, developed from serpentinite (Sungai Mas Series), basalt (Kuantan Series) and andesite (Segamat Series), selected to represent the most common Oxisols in Malaysia were sampled and studied. The objectives of this study were: (i) to determine mineralogical composition and factors responsible for changes in point of zero charge (pH₀) of the variable charge component of three Oxisols; (ii) to use pH₀ values to assess degree of chemical weathering; and (iii) to determine the magnitude of variable charge using corrected back-titration technique. The mineralogical composition was determined by X-ray diffraction analysis (XRD). The pH₀ was determined by potentiometric titration in different electrolyte strengths. The magnitude of variable charge generation as a function of soil pH was measured using corrected back-titration to allow elimination of charge overestimation caused by solid dissolution and hydrolysis reactions. The results showed that the mineralogical composition were similar (kaolinite, goethite, hematite and gibbsite) between profiles but different in proportion, except for gibbsite which was absent in the andesite-derived soil. The sequential removal of soil organic matter (SOM), iron oxides and SOM together with iron oxides resulted in the changes of pH₀ from 3.9–5.7 to 5.3–6.7, 2.6–3.7 and 3.3–4.5, respectively. These pH₀ changes indicate SOM and sesquioxides are masking mineral surfaces and are factors responsible for lowering and increasing pH₀ values, respectively. Regression correlation (R² = 0.87^??) showed that for every 1% organic C may decrease 1.0 unit of pH₀ value. The pH₀ values, after SOM removal, are in the order of Sungai Mas ～ Segamat > Kuantan Series. This suggests that the serpentinite and andesite-derived soils have achieved a relatively similar degree of chemical weathering and they are more weathered than the basalt-derived soil. The charge measured by corrected back-titration is 1.5–3.8 cmol_c kg^? 1 at pH 4.5 and increases to 4.2–10.8 cmol_c kg^? 1 at pH 6.5, indicating that the three Oxisols mainly bear variable charge. Charge overestimation resulted from dissolution and hydrolysis reactions during potentiometric titration ranges from 36 to 160%, depending on pH values (the lower the pH the higher is the overestimation). Hence, back-titration is a reliable technique to correct charge overestimation when using the traditional potentiometric titration for highly weathered tropical soils.     

Changes in total and labile carbon and nitrogen contents in a sandy soil after the conversion of a succession fallow to cultivated land

The content of soil organic matter (SOM) can be considered as an important factor for evaluating soil fertility, crop yields, and environmental effects. Sensitive measurements for the assessment of quantitative changes in SOM shortly after the conversion of the management practice would be helpful to understand the SOM‐transformation cycle in more detail. Changes in SOM are reflected in modifications of total organic‐carbon (TOC) and total organic‐nitrogen (TON) contents. They are initially detectable in the readily decomposable fraction. We used hot water–extractable carbon (HWC) and nitrogen (HWN) as measurement of labile pools of SOM and aimed to quantify changes in contents of these C and N fractions in a sandy soil already few years after changing management strategy. In this context, we examined the impact of the conversion of a succession fallow (F) to organic (O) and intensive (I) agriculture on TOC, total N (TN), HWC, and HWN. The conversion of succession fallow to cultivated land resulted in a significant decrease of TOC, TN, and HWC at 0–10 cm soil depth. On average, TOC decreased approx. 0.70 g C kg^–1 (approx. 9% of initial TOC), TN decreased approx. 0.13 g N kg^–1 (approx. 17% of initial TN), and HWC decreased approx. 0.05 g C kg^–1 (approx. 12% of initial HWC) within 3 years. Relatively rapid changes in TOC and TN contents indicated comparatively high proportions of decomposable C and N. These were reflected in comparable high HWC (ranging from 0.37 to 0.59 g C kg^–1 at 0–30 cm soil depth) and HWN (ranging from 0.04 to 0.10 g N kg^–1 at 0–30 cm) contents. These high contents as well as the high HWC : TOC and organic hot water–extractable N (HWN_org) : TN ratios (both between 5% and 7%) implied that the soil investigated has a high ability to provide short‐term available organic C and N compounds. Long‐lasting applications of high quantities of organic fertilizer in the past and high quantities of rhizodepositions were assumed as reasons for the high capability of soil to provide short‐term to medium‐term available C and N. Changes in the HWN content due to the fertilization or crop rotation were mainly based on changes in its inorganic part. This ranged between 10% and 30% of HWN. By discriminant function analysis, it could be shown that the HWN represents a suitably sensitive measurement for the determination of management‐specific impacts in terms of the N, but also of the C cycle. In combination with other C and particularly with other N parameters, the HWN allowed a statistically significant separation of comparable sites varying in management practice already 2 years after the conversion of the management system.     

Near infrared reflectance spectroscopy: A tool to characterize the composition of different types of exogenous organic matter and their behaviour in soil

In addition to total organic carbon and nitrogen, potential organic carbon mineralization under controlled laboratory conditions and indicators such as the indicator of remaining organic carbon in soil (I_ROC), based on Van Soest biochemical fractionation and short-term carbon mineralization in soil, are used to predict the evolution of exogenous organic matter (EOM) after its application to soils. The purpose of this study was to develop near infrared reflectance spectroscopy (NIRS) calibration models that could predict these characteristics in a large dataset including 300 EOMs representative of the broad range of such materials applied to cultivated soils (plant materials, animal manures, composts, sludges, etc.). The NIRS predictions of total organic matter and total organic carbon were satisfactory (R²_P = 0.80 and 0.85, ratio of performance to deviation, RPD_P = 2.2 and 2.6, respectively), and prediction of the Van Soest soluble, cellulose and holocellulose fractions were acceptable (R²_P = 0.82, 0.73 and 0.70, RPD_P = 2.3, 1.9 and 1.8, respectively) with coefficients of variation close to those of the reference methods. The NIRS prediction of carbon mineralization during incubation was satisfactory and indeed better regarding the short-term results of mineralization (R²_P = 0.78 and 0.78, and RPD_P = 2.1 and 2.0 for 3 and 7 days of incubation, respectively). The I_ROC indicator was predicted with fairly good accuracy (R²_P = 0.79, RPD_P = 2.2). Variables related to the long-term C mineralization of EOM in soil were not predicted accurately, except for I_ROC which was based on analytical and well-identified characteristics, probably because of the increasing interactions and complexity of the factors governing EOM mineralization in soil as a function of incubation time. This study demonstrated the possibility of developing NIRS predictive models for EOM characteristics in heterogeneous datasets of EOMs. However, specific NIRS predictive models still remain necessary for sludges, organo-mineral fertilizers and liquid manures.