Controls and relationships of soil organic carbon abundance and persistence vary across pedo-climatic regions.

One of the largest uncertainties in the terrestrial carbon cycle is the timing and magnitude of soil organic carbon (SOC) response to climate and vegetation change. This uncertainty prevents models from adequately capturing SOC dynamics and challenges the assessment of management and climate change effects on soils. Reducing these uncertainties requires simultaneous investigation of factors controlling the amount (SOC abundance) and duration (SOC persistence) of stored C. We present a global synthesis of SOC and radiocarbon profiles (nProfile = 597) to assess the timescales of SOC storage. We use a combination of statistical and depth-resolved compartment models to explore key factors controlling the relationships between SOC abundance and persistence across pedo-climatic regions and with soil depth. This allows us to better understand (i) how SOC abundance and persistence covary across pedo-climatic regions and (ii) how the depth dependence of SOC dynamics relates to climatic and mineralogical controls on SOC abundance and persistence. We show that SOC abundance and persistence are differently related; the controls on these relationships differ substantially between major pedo-climatic regions and soil depth. For example, large amounts of persistent SOC can reflect climatic constraints on soils (e.g., in tundra/polar regions) or mineral absorption, reflected in slower decomposition and vertical transport rates. In contrast, lower SOC abundance can be found with lower SOC persistence (e.g., in highly weathered tropical soils) or higher SOC persistence (e.g., in drier and less productive regions). We relate variable patterns of SOC abundance and persistence to differences in the processes constraining plant C input, microbial decomposition, vertical C transport and mineral SOC stabilization potential. This process-oriented grouping of SOC abundance and persistence provides a valuable benchmark for global C models, highlighting that pedo-climatic boundary conditions are crucial for predicting the effects of climate change and soil management on future C abundance and persistence.

Zinc speciation in highly weathered tropical soils affected by large scale vegetable production.

Agriculture in highly weathered tropical soils often requires considerable application of lime and fertilizers to ensure satisfactory plant nutrient levels. The consequences of these continue long-term applications is not well understood may induce changes in soil chemical properties, the abundance, and speciation of potentially toxic trace element and as well as of micronutrients in agriculture soils. In this study, we evaluated the adsorption (at pH 5) and speciation of Zn in tropical soils (both agricultural and native vegetation) as a function of fertilization and contact time using chemical fractionation analyses and X-ray absorption spectroscopy. The soils overall had high Zn adsorption capacities (∼ 700 mg kg-1), but the agricultural soil was approximately 30 % higher than of the soil under native vegetation, and the proportion of Zn in the mobile fraction was 35 % in native vegetation and 21 % in agricultural soils. Zn speciation via linear combination analysis showed a strong relationship with soil mineralogical composition and reveled that Zn associated with organic matter decreased while Zn associated with P increased after the conversion of soils from native vegetation to highly fertilized soil. Aluminosilicate soil minerals were identified as major sinks of soil Zn, accounting for 34 % of total Zn retention regardless of soil origin and land use. Association of Zn with phosphate (i.e., hopeite) was observed in the agricultural soil samples, which might be an unexpected Zn-bearing mineral in highly weathered tropical soils and could have impacts on Zn plant nutrition.

Magnetic signature and X-ray fluorescence for mapping trace elements in soils originating from basalt and sandstone.

The knowledge of the lithological context is necessary to interpret trace elements concentrations in the soil. Soil magnetic signature (χ) and soil X-ray fluorescence (XRF) are promising approaches in the study of the spatial variability of trace elements and the environmental monitoring of soil quality. This research aimed to assess the efficiency of measurements of χ and XRF sensors for spatial characterization of zinc (Zn), manganese (Mn), and copper (Cu) contents in soils of a sandstone-basalt transitional environment, using machine learning modeling. The studied area consisted of the Western Plateau of São Paulo (WPSP), with soils originating from sandstone and basalt. A total of 253 soil samples were collected at a depth of 0.0-0.2 m. The soils were characterized by particle size and chemical analysis: organic matter (OM), cation exchange capacity (CEC), ammonium oxalate-extracted iron (Feo), sodium dithionite-citrate-bicarbonate-extracted iron (Fed), and sulfuric acid-extracted iron (Fet). Hematite (Hm), goethite (Gt), kaolinite (Kt), and gibbsite (Gb) contents were obtained by X-ray diffraction (XRD). Magnetite (Mt) and maghemite (Mh) contents were obtained by soil χ, while trace elements contents were obtained by XRF and predicted by χ. Descriptive analysis, the test of means, and correlation were performed between attributes. Zn, Mn, and Cu contents were predicted using the machine learning algorithm random forest, and the spatial variability was obtained using the ordinary kriging interpolation technique. Landscape dissections influenced iron oxides, which had the highest contents in slightly dissected environments. Trace elements contents were not influenced by landscape dissections, demonstrating that lithological knowledge is necessary to characterize trace elements in soils. The prediction models developed through the machine learning algorithm random forest showed that χ can be used to characterize trace elements. The similar spatial pattern of trace elements obtained by XRF and χ measurements confirm the applicability of these sensors for mapping it under lithological and landscape transition, aiming for sustainable strategic planning of land use and occupation.

Measuring the immeasurable: A structural equation modeling approach to assessing soil health.

Soil health is recognized as an important ecosystem property sensitive to human impact. As a concept, soil health cannot be directly measured, and so assessment and modeling efforts largely rely upon key biological, chemical, and physical indicators. Efforts to develop an overall soil health index are largely lacking due to significant statistical challenges and the necessity for regional calibration. Taken from the field of educational research, structural equation modeling (SEM) is an attractive approach to enhance the reliability and validity of soil health scoring. Therefore, SEM may be utilized to advance research efforts to understand management practices impacts on soil health. Our objectives were to develop a robust scoring function that (i) captures the concept of soil health and latent variables, (ii) adjusts scores by inherent soil properties and legacy of intensive land use to adequately reflect our regional conditions and contemporary land management, and (iii) meets the diverse practitioner needs. Through this process, we refined our minimum dataset of soil health indicators and reconceptualized soil health indicators into functional properties. Our results support the development of a robust single level or a multilevel SEM model-depending on the practitioner's goals-that accounts for repeated sampling or pseudoreplication. While the SEM scoring functions were highly related to the conventional scoring approach, SEM outperformed the conventional methods in terms of its wider distribution of scores-and thus enhanced discriminatory power on the lower and higher range of scores. We also confirmed that the SEM scoring function that includes adjustments for mineralogy and legacy of intensive land use successfully differentiates among contemporary management practices and land use. Therefore, we have confidence that the tool is reliable and appropriate to further examine more nuanced impacts of land use change and management practices within a given land use across time and space covering a diversity of soils. (300 words).

Soil mineralogy-controlled phosphorus availability in soils mixed with phosphate fertiliser and biochar.

The biochar amendment to soil proved to be beneficial to improve soil quality and provide nutrients. However, the effect of biochar on the availability of P is still controversial. We aim to study the effect of adding phosphate fertiliser and biochar on the P bioavailability in soils of different mineralogies. Eight biochars derived from biomass (rice husk and coffee husk), soil (sandy and clayey), and phosphate fertiliser (triple superphosphate) were produced. The biochar enrichment process with superphosphate was carried out before and after pyrolysis. Thus, we tested two biochar groups: (1) enriched biochars prior to pyrolysis; (2) enriched biochars after pyrolysis. These biochars were tested as P sources in soils of three mineralogies (kaolinite/oxide, kaolinite, and smectite). Batch sorption-desorption experiments were conducted. The sorbed P was fractionated to examine the factors controlling the retention of applied P. In the three soil mineralogies the use of enriched biochars prior to pyrolysis results in lower availability of P. In contrast, the enriched biochars after pyrolysis increase the bioavailability of P. The coffee husk biochar is more suitable than rice husk biochar to protect P from soil retention reactions. The use of sandy soil rather than clayey soil in enriched biochars compositions results in higher P content availability when applied to soils. The factor that controls the retention of P is the reaction between P, organic compounds, and Fe and Al compounds. The greater the relationship between biochar and soluble P in the fertiliser, the higher the increase of P retention.

The mechanistic investigation of geochemical fractionation, bioavailability and release kinetic of heavy metals in contaminated soil of a typical copper-smelter.

Identifying the bioavailability and release-desorption mechanism of heavy metals (HMs) in soil is critical to understand the release risk of HMs. Simultaneously, the mechanistic investigation of affecting the bioavailability of HMs in soil is necessary, such as the grain-size distribution and soil mineralogy. Herein, the bioavailability of HMs (Cu, Cd, Ni, Pb, and Zn) in different area soils near a typical copper-smelter was evaluated by the sequential extraction technique (BCR), diffusive gradients in thin-films (DGT), and DGT-induced fluxes in sediments (DIFS) model. Results showed that the HMs proportion of the residual fraction in all soils was the highest. The average bioavailability concentration (CDGT) of Cu and Cd in industrial soil was the highest, with 45.12 µg· L-1 and 9.06 µg· L-1. The result of DIFS model revealed that the decreased order of the mean value of desorption rate constant (K-1) was Cd > Zn > Ni > Cu > Pb, 5.91 × 10-5, 4.96 × 10-5, 2.89 × 10-5, 9.64 × 10-6, and 8.69 × 10-6, respectively. According to the spatial distribution of release potential (R-value), the release potential of labile-Cu in agricultural soil was the highest, which was mainly attributed to fertilizer application in farmland. Simultaneously, the reduced hydroxyl was also related to the agricultural activities, resulting in the weakened adsorption capacity of HMs by soil. Redundancy analysis (RDA) results showed that the bioavailability of Cd, Ni, and Zn was mainly driven by soil pH, while the bioavailability of Cu and Pb was primarily driven by dissolved organic carbon (DOC). Meanwhile, carbonate minerals had a positive correlation with the bioavailability of Cd, Ni, and Zn, which could promote the release of HMs in mining soil as chemical weathering progresses. In conclusion, this study provides a structured method which can be used as a standard approach for similar scenarios to determine the geochemical fractionation, bioavailability, and release kinetics of heavy metals in soils.

A typical case study from smelter-contaminated soil: new insights into the environmental availability of heavy metals using an integrated mineralogy characterization.

Mineralogy was an important driver for the environmental release of heavy metals. Therefore, the present work was conducted by coupling mineral liberation analyzer (MLA) with complementary geochemical tests to evaluate the geochemical behaviors and their potential environmental risks of heavy metals in the smelter contaminated soil. MLA analysis showed that the soil contained 34.0% of quartz, 17.15% of biotite, 1.36% of metal sulfides, 19.48% of metal oxides, and 0.04% of gypsum. Moreover, As, Pb, and Zn were primarily hosted by arsenopyrite (29.29%), galena (88.41%), and limonite (24.15%), respectively. The integrated geochemical results indicated that among the studied metals, Cd, Cu, Mn, Pb, and Zn were found to be more bioavailable, bioaccessible, and mobile. Based on the combined mineralogical and geochemical results, the environmental release of smelter-driven elements such as Cd, Cu, Mn, Pb, and Zn were mainly controlled by the acidic dissolution of minerals with neutralizing potential, the reductive dissolution of Fe/Mn oxides, and the partial oxidation of metal sulfide minerals. The present study results have confirmed the great importance of mineralogy analysis and geochemical approaches to explain the contribution of smelting activities to soil pollution risks.

The geochemical behaviors of potentially toxic elements in a typical lead/zinc (Pb/Zn) smelter contaminated soil with quantitative mineralogical assessments.

This study comprehensively investigated the potential roles of soil mineralogy identified by the automated mineral liberation analysers (MLA) in the prediction of geochemical behavior of toxic metals in the smelter polluted soils. The results from modal mineralogy revealed that the non-reactive silicate phases such as quartz (42.05%) and biotite (40.43%) were the major mineralogical phases. The element deportment showed that fayalite, lead oxide, apatite, galena and wollastonite were identified as the dominant As, Cd, Pb and Zn bearing minerals. Furthermore, MLA analysis also confirmed that Pb was most concentrated in the smaller particles of lead oxide, which significantly enhanced Pb release in reaction with the chemical extractant during chemical kinetic tests. The results from pH-dependent leaching tests indicated that the leaching concentrations of As, Pb and Zn increased at low and high pH values, but were lowest at the neutral pH range. In addition, the results from the kinetic study demonstrated that the second order model provided the best description for the release patterns of the main metal contaminants in the bioavailability and bioaccessibility tests. The integrated geochemical analysis demonstrated that among these studied elements, As showed a typical geochemical pattern, which was predominantly controlled by 90.09% of fayalite. The above study results would have significant implications for soil remediation and risk management of smelter contaminated sites.

Mineral-nutrient relationships in African soils assessed using cluster analysis of X-ray powder diffraction patterns and compositional methods.

Soil mineral compositions are often complex and spatially diverse, with each mineral exhibiting characteristic chemical properties that determine the intrinsic total concentration of soil nutrients and their phyto-availability. Defining soil mineral-nutrient relationships is therefore important for understanding the inherent fertility of soils for sustainable nutrient management, and data-driven approaches such as cluster analysis allow for these relations to be assessed in new detail. Here the fuzzy-c-means clustering algorithm was applied to an X-ray powder diffraction (XRPD) dataset of 935 soils from sub-Saharan Africa, with each diffractogram representing a digital signature of a soil's mineralogy. Nine mineralogically distinct clusters were objectively selected from the soil mineralogy continuum by retaining samples exceeding the 75 % quantile of the membership coefficients in each cluster, yielding a dataset of 239 soils. As such, samples within each cluster represented mineralogically similar soils from different agro-ecological environments of sub-Saharan Africa. Mineral quantification based on the mean diffractogram of each cluster illustrated substantial mineralogical diversity between the nine groups with respect to quartz, K-feldspar, plagioclase, Fe/Al/Ti-(hydr)oxides, phyllosilicates (1:1 and 2:1), ferromagnesians, and calcite. Mineral-nutrient relationships were defined using the clustered XRPD patterns and corresponding measurements of total and/or extractable (Mehlich-3) nutrient concentrations (B, Mg, K, Ca, Mn, Fe, Ni, Cu and Zn) in combination with log-ratio compositional data analysis. Fe/Al/Ti/Mn-(hydr)oxides and feldspars were found to be the primary control of total nutrient concentrations, whereas 2:1 phyllosilicates were the main source of all extractable nutrients except for Fe and Zn. Kaolin minerals were the most abundant phyllosilicate group within the dataset but did not represent a nutrient source, which reflects the lack of nutrients within their chemical composition and their low cation exchange capacity. Results highlight how the mineral composition controls the total nutrient reserves and their phyto-availability in soils of sub-Saharan Africa. The typical characterisation of soils and their parent material based on the clay particle size fraction (i.e. texture) and/or the overall silica component (i.e. acid and basic rock types) alone may therefore mask the intricacies of mineral contributions to soil nutrient concentrations.

Pre-treatment of soil X-ray powder diffraction data for cluster analysis.

X-ray powder diffraction (XRPD) is widely applied for the qualitative and quantitative analysis of soil mineralogy. In recent years, high-throughput XRPD has resulted in soil XRPD datasets containing thousands of samples. The efforts required for conventional approaches of soil XRPD data analysis are currently restrictive for such large data sets, resulting in a need for computational methods that can aid in defining soil property - soil mineralogy relationships. Cluster analysis of soil XRPD data represents a rapid method for grouping data into discrete classes based on mineralogical similarities, and thus allows for sets of mineralogically distinct soils to be defined and investigated in greater detail. Effective cluster analysis requires minimisation of sample-independent variation and maximisation of sample-dependent variation, which entails pre-treatment of XRPD data in order to correct for common aberrations associated with data collection. A 24 factorial design was used to investigate the most effective data pre-treatment protocol for the cluster analysis of XRPD data from 12 African soils, each analysed once by five different personnel. Sample-independent effects of displacement error, noise and signal intensity variation were pre-treated using peak alignment, binning and scaling, respectively. The sample-dependent effect of strongly diffracting minerals overwhelming the signal of weakly diffracting minerals was pre-treated using a square-root transformation. Without pre-treatment, the 60 XRPD measurements failed to provide informative clusters. Pre-treatment via peak alignment, square-root transformation, and scaling each resulted in significantly improved partitioning of the groups (p < 0.05). Data pre-treatment via binning reduced the computational demands of cluster analysis, but did not significantly affect the partitioning (p > 0.1). Applying all four pre-treatments proved to be the most suitable protocol for both non-hierarchical and hierarchical cluster analysis. Deducing such a protocol is considered a prerequisite to the wider application of cluster analysis in exploring soil property - soil mineralogy relationships in larger datasets.

Impact of brackish groundwater and treated wastewater on soil chemical and mineralogical properties.

The long-term effect of using treated wastewater is not clearly defined: some researchers argue that it is better than freshwater for the soil health; others disapprove, claiming that irrigation with unconventional water resources causes soil degradation. This study assesses the impact of irrigation with non-traditional water on the chemical and mineralogical properties of a calcareous clayey soil from West Texas. The exponential rise in population and the realities of climate change contribute to the global increase in freshwater scarcity: non-conventional water sources, such as treated wastewater (TWW) and brackish groundwater (BGW), offer potentially attractive alternative water resources for irrigated agriculture. For this research, the differences between TWW and BGW were addressed by collecting and analyzing water samples for salt and nutrient content. Soil samples from three horizons (Ap, A, and B) were obtained from three different fields: Rainfed (RF), BGW irrigated, and TWW irrigated. Soil was analyzed for texture, salinity, sodicity, and carbon content. Clay mineralogy of the three different fields was analyzed using the B-horizons. The outcomes from the analysis showed that the BGW from the Lipan aquifer has higher salinity and is harder compared to TWW. Although the exchangeable sodium percentage (ESP), sodium adsorption ratio (SAR), and electroconductivity (EC) increased marginally compared to the control soil (RF), the soils were in good health, all the values of interest (SAR < 13, ESP < 15, pH < 8.5, and EC < 4) were low, indicating no sodicity or salinity problems. Smectite, illite, and kaolinite were identified in the three B-horizon samples using bulk X-ray diffraction (XRD). Overall, no major changes were observed in the soil. Thus, TWW and BGW are viable replacements for freshwater irrigation in arid and semi-arid regions.

Association between parent materials and soil attributes along different geological environments in western Pará, Brazil / Associação entre materiais de origem e atributos de solos ao longo de diferentes ambientes geológicos no oeste do Pará, Brasil

The expansion of the agricultural frontier into different geological environments in the west of the state of Pará, northern Brazil, makes it necessary to know the influence of the parent material on local soil attributes. This study aimed to evaluate the influence of different parent materials on five soil profiles along a lithosequence exposed by the BR-163 highway, which runs from north to south through western Pará. The soils were classified, morphologically described and their main horizons sampled for physical, mineralogical and chemical analyses, including the determination of micronutrients, forms of phosphorus and secondary forms of iron. Multivariate analysis was used to group the different soil-parent material associations. The results demonstrated that the diversity of the parent material was a determinant of soil attributes, and was a conditioning factor for the formation of different clay minerals. Multivariate analysis grouped the soils along the lithosequence into a group formed by profiles derived from basic and intermediate igneous rocks, and a second group consisting of profiles derived from sediments and sedimentary rocks. The profile derived from acidic igneous rock showed greater similarity with the profiles derived from sedimentary materials in comparison to those derived from other igneous rocks.

A expansão da fronteira agrícola em diferentes ambientes geológicos no oeste do Estado do Pará, norte do Brasil, torna necessário conhecer a influência do material de origem sobre os atributos dos solos locais. Este estudo teve como objetivo avaliar a influência de diferentes materiais de origem sobre cinco perfis de solo ao longo de uma litosequência exposta pela rodovia BR-163, que vai de norte a sul pelo oeste do Pará. Os solos foram classificados, morfologicamente descritos e seus principais horizontes amostrados para análises físicas, mineralógicas e químicas, incluindo a determinação de micronutrientes, formas de fósforo e formas secundárias de ferro. Análises multivariadas foram usadas para agrupar as diferentes associações solo-material de origem. Os resultados demonstraram que a diversidade do material de origem foi determinante para os atributos do solo, sendo um fator condicionante para a formação de diferentes argilominerais. A análise multivariada agrupou os solos ao longo da litosequência em um grupo formado por perfis derivados de rochas ígneas básicas e intermediárias, e um segundo grupo constituído por perfis derivados de sedimentos e rochas sedimentares. O perfil derivado de rocha ígnea ácida apresentou maior similaridade com os perfis derivados de materiais sedimentares em comparação àqueles derivados de outras rochas ígneas.

Arsenic-phosphorus interactions in the soil-plant-microbe system: Dynamics of uptake, suppression and toxicity to plants.

High arsenic (As) concentrations in the soil, water and plant systems can pose a direct health risk to humans and ecosystems. Phosphate (Pi) ions strongly influence As availability in soil, its uptake and toxicity to plants. Better understanding of As(V)-Pi interactions in soils and plants will facilitate a potential remediation strategy for As contaminated soils, reducing As uptake by crop plants and toxicity to human populations via manipulation of soil Pi content. However, the As(V)-Pi interactions in soil-plant systems are complex, leading to contradictory findings among different studies. Therefore, this review investigates the role of soil type, soil properties, minerals, Pi levels in soil and plant, Pi transporters, mycorrhizal association and microbial activities on As-Pi interactions in soils and hydroponics, and uptake by plants, elucidate the key mechanisms, identify key knowledge gaps and recommend new research directions. Although Pi suppresses As uptake by plants in hydroponic systems, in soils it could either increase or decrease As availability and toxicity to plants depending on the soil types, properties and charge characteristics. In soil, As(V) availability is typically increased by the addition of Pi. At the root surface, the Pi transport system has high affinity for Pi over As(V). However, Pi concentration in plant influences the As transport from roots to shoots. Mycorrhizal association may reduce As uptake via a physiological shift to the mycorrhizal uptake pathway, which has a greater affinity for Pi over As(V) than the root epidermal uptake pathway.

Correlation of soil organic carbon and nutrients (NPK) to soil mineralogy, texture, aggregation, and land use pattern.

This work investigates the correlations existing among soil organic carbon (C), nitrogen (N), phosphorous (P), potassium (K), and physicochemical properties like clay mineralogy, textural components, soil aggregation, and land use pattern. Seven different locations were chosen in the tropical rainforest climate region of Assam, India, for the work. The soil texture classifications were clay, sandy clay loam, and sandy loam with mixed clay mineralogy consisting of tectosilicates and phylosilicates. Two distinct compositions of total Fe/Al oxides≥11.5 and <10.8% were observed along with two distinct groups of water stable soil aggregates of mean weight diameter≈6.42 and ≤3.26 mm. The soil clay and sand had positive and negative contributions respectively to the soil organic carbon (SOC) protection, which was observed to be dependent on lesser sand content, higher silt+clay content, and the presence of higher percentages of total Fe/Al oxides. Soil clay mineralogy suggested that the mineral, chlorite, favored retention of higher SOC content in a particular site. Under similar climatic and mineralogical conditions, both natural and anthropogenic soil disturbances destabilized SOC protection through SOM mineralization and soil aggregate destabilization as indicated by SOC protective capacity studies. Urbanization resulting in soil compaction contributed to enhanced SOC level through increased contact between the occluded organic carbon and the soil mineralogical constituents.