Soil Organic Carbon Research Articles

Organic matter accumulation encouraged K-strategy bacteria increase and metabolism variation in karst vegetation restoration

Vegetation restoration plays a critical role in terrestrial carbon sink increase, especially in subtropic Southwest China which has been the hotspot of vegetation restoration areas in recent decades. However, the variations in microbial community diversity resulting from this intervention remain unclear, and further research is needed to elucidate the complex interactions between microorganisms and soil nutrient elements. Soil samples were collected from three vegetation restoration stages in a karst rocky desertification (KRD) valley of Southwest China, which were named dry cropland (CL), 3–8 years grassland (WL), and afforestation land that recovered more than 20 years (AL), to investigate the soil nutrient and bacterial diversity variation during vegetation restoration course. The soil organic carbon (SOC) and total nitrogen (TN) contents are significantly higher in the afforestation land soil compared to the cropland and grassland soils, while the available nutrient contents decrease during the vegetation restoration course. The soil dominant bacteria genus shifts from R-strategy bacteria in cropland to K-strategy bacteria in afforestation land, and the relative abundances of R-strategy genera remain similar in the grassland and cropland soil. The dual-relative bacteria network evaluates from simple correlation net to very complex ones during the vegetation restoration, of which the core influenced factor alters from available nutrients to organic matter. The results of this study suggest that it will take a relatively longer period for the soil nutrient conditions and bacterial community to recover fully, although vegetation restoration could reduce the impacts of agricultural activities. This study refers to the ecological preservation and restoration strategies under the global climate change background, elucidating the nutrient metabolism variation induced by the accordance variation of organic matter accumulation and soil bacterial life strategy during the ecosystem restoration course.

Assessing spatiotemporal variations of soil organic carbon and its vulnerability to climate change: a bottom-up machine learning approach

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and essential for agricultural productivity. Quantifying its sensitivity to future climate change is vital for sustaining agricultural practices and mitigating greenhouse gas emissions. However, this remains a challenge as long-term SOC data are scarce and substantial uncertainties regarding future climate scenarios. This study presents a bottom-up machine learning framework to assess the spatiotemporal variations of SOC and its vulnerability to climate change in the Jinghe River Basin, a typical loess hilly and gully watershed. Firstly, the long-term (2000-2023) dynamics of SOC was estimated by integrating in-situ measurements with machine learning techniques. Results show that the high SOC values are primarily distributed in the farmland of the mountain-loess transition zone, while the low-value areas are mainly found in the loess region. During the study period, the SOC content exhibited a slight increasing trend with a rate of 0.02 g kg⁻1 yr⁻1 (p = 0.449). The vulnerability of farmland surface SOC to future climate change was then evaluated by combining a robust machine learning model with the bottom-up framework. To this end, the study explored a wide range of possible future climates to identify critical climate thresholds and their spatial variation across the basin’s farmlands. Based on this analysis, this research found that the farmland in the northern basin is generally more susceptible to changing climate with even marginal rises in temperature could lead to severe loss in SOC. These results highlight the need for proactive climate adaptation strategies to safeguard SOC in vulnerable agricultural landscapes, ensuring soil health and resilience in the face of climate change.

An evaluation of soil carbon models and their role on finding ways to net-zero carbon in agricultural systems

The estimation of changes in soil organic carbon (SOC) is a key issue for national green-house gasses (GHG) inventories, climate change mitigation programs and the estimation of carbon footprint of farm products in life cycle assessments. Any strategy related to net-zero carbon in agricultural systems needs to quantify the SOC balance. In this way, SOC models help decision makers involved in agriculture to understand the dynamics of the SOC and the interaction between all variables related to soil, climate, land use, and management, to design the best solution to reduce emissions or enable carbon sequestration. Likewise, it is important to identify suitable models for the region. This study aims to address three main subjects: a) a discussion on the importance of SOC estimation for GHG inventories and the carbon footprint of crops, using the Intergovernmental Panel on Climate Change (IPCC) Tier 1 method and AMG model; b) an evaluation and brief description of the IPCC “Steady State Method” (SSM), using experimental data from two sites in Argentina, comparing these results to AMG and RothC models (both previously validated at those sites); and c) a brief discussion about the potential use of SOC models for what-if management scenarios, their real limitations and future research needs. The three models were consistent in predicting the impact of tillage and the long-term trends in changes in SOC stocks under different management practices. The SSM model was evaluated for the first time in Argentina and performed even better than the other two models. It was consistent with the observed values, when predicting the effect of tillage system under different crop rotations, including pasture systems. Regarding efficiencies of the models, they showed acceptable Nash-Sutcliffe Efficiency (NSE) values, and the root mean square error (RMSE) was also acceptable between 3 % and 7 %, within a range of 4–5 Mg C.ha−1. Therefore, the SSM model proved to be a valuable tool to estimate SOC trends for crop and pasture rotations under different management scenarios (i.e., tillage systems and fertilization), to identify best practices that allow for a zero or positive SOC balance, in two different soil and climate conditions of the Pampean Region of Argentina. In our study, the SSM did have a better fit to the data and, furthermore, this Tier 2 method is simpler than the Tier 3 models, and, therefore, is advantageous for conducting regional assessments and GHG inventories.

Determinants of rhizospheric organic carbon fractions and accumulation in four different vegetations of coastal saline-alkali soils

Rhizosphere processes are key pathways through which plants influence the carbon cycling of diverse ecosystems and are closely associated with vegetation types. However, the environmental responses of rhizospheric soil organic carbon (SOC) mediated by the interaction between rhizospheric effect and vegetation type remain uncertain, severely limiting our assessment of the carbon sequestration potential of different coastal vegetation. Here, we identified the core factors driving changes in various soil carbon fractions in the rhizosphere of four coastal vegetation types by testing the contents of the reactive, dissolved, particulate, mineral-associated, heavy and light fractions of SOC and their relationships with physicochemical properties and enzyme activities. It was found that the rhizosphere effect significantly influenced SOC, with rhizospheric SOC contents varying significantly among vegetation types, ranging from 2.12 to 9.04 g/kg. Besides, rhizospheric soil pH was found to contribute significantly to SOC fractions (except for light organic carbon) and exert significant inhibitory effects on SOC, reactive organic carbon, mineral-associated organic carbon and heavy organic carbon. Despite the different responses of various SOC fractions to physicochemical properties and enzyme activities, soil available phosphorus and alkaline phosphatase activity emerged as core environmental factors influencing rhizospheric SOC accumulation across different coastal vegetation types. This study presents a promising framework for understanding the determinants of SOC fractions in rhizospheric soil, and their accumulation in the vegetation of coastal saline-alkali soils. In addition to alkalinity, phosphorus acquisition capacity can be a key predictor of coastal SOC fractions and their accumulation.

Tree species selection for optimizing soil carbon storage: Insights from litter decomposition and bacterial community analysis in coastal ecosystems

Coastal wetland ecosystems are critical sinks for atmospheric carbon dioxide, playing a vital role in global carbon cycling and climate regulation. The decomposition of leaf litter plays a crucial role in the formation and stability of soil organic carbon (SOC) in these environments. This study investigated the impact of leaf litter decomposition from five tree species (Populus deltoids, Ligustrum lucidum, Taxodium 'Zhongshanshan', Hibiscus hamabo, and Nerium oleander) on SOC dynamics, humus composition, and soil bacterial community structure in a tidal flat. Litterbags were used to monitor the mass loss and changes in litter chemical composition over 270 days. The results revealed significant differences in decomposition rates among the tree species, with Nerium oleander exhibiting the fastest decomposition and Populus deltoids the slowest. Surprisingly, initial litter chemistry did not correlate with decomposition rates; however, changes in lignin and hemicellulose content during decomposition were significantly related to mass loss. Despite its rapid decomposition, Nerium oleander litter resulted in the highest accumulation of SOC, total humus, and humin compared to the other species, challenging the conventional view that slower decomposition leads to greater SOC storage. The soil microbial community structure was significantly influenced by SOC, humus, and litter components, with distinct microbial assemblages associated with each tree species. A random forest model identified key bacterial taxa, predominantly Proteobacteria, as important predictors of SOC content, highlighting the role of bacterial diversity in regulating SOC dynamics. These findings underscore the importance of considering litter quality, decomposition dynamics, and bacterial community composition in strategies aimed at enhancing soil carbon sequestration. This study suggests that selecting tree species with rapidly decomposing litter, such as Nerium oleander, in coastal plantations can be an effective management tool for optimizing soil carbon storage, offering valuable insights for mitigating climate change impacts.

Higher temperature accelerates carbon cycling in a temperate montane forest without decreasing soil carbon stocks

Global warming is expected to accelerate the cycling of soil organic carbon (SOC) and the assimilation of new carbon, but the net effect of those counteracting accelerations and their ultimate effects on SOC are still uncertain. This hinders the prediction of long-term changes in biospheric carbon stocks and SOC-climate feedbacks. Here, we studied the long-term effect of temperature on carbon cycling across a 3.2 °C altitudinal temperature gradient in a temperate forest ecosystem in New Zealand. Across the gradient, soil respiration rates increased with increasing temperature from 9.0 to 10.4 tC ha−1 yr−1, but SOC stocks down to 85 cm depth also tended to increase, from 154 to 176 tC ha−1, albeit non-significantly (P = 0.06). This system was able to maintain higher soil respiration rates at higher temperatures without reducing SOC because the higher respiration rates were sustained by higher litterfall rates. Aboveground litterfall increased from 1.8 to 2.4 tC ha−1 yr−1 and estimated belowground C inputs increased from 7.2 to 8.0 tC ha−1 yr−1 along the temperature gradient. These higher fluxes were associated with significantly (P < 0.05) increased biomass at higher temperatures. As a direct measure of the effect of temperature on carbon cycling processes, we also calculated the turnover rate of forest litter which increased about 1.4-fold across the temperature gradient. This study demonstrates that higher temperatures along the thermal gradient increased plant carbon inputs through enhanced gross primary production, which counteracted SOC losses through temperature-enhanced soil respiration. These results suggest that temperature sensitivities of both plant carbon inputs and SOC losses must be considered for predicting SOC-climate feedbacks.

Afforestation Reduces Deep Soil Carbon Sequestration in Semiarid Regions: Lessons From Variations of Soil Water and Carbon Along Afforestation Stages in China's Loess Plateau

AbstractAfforestation represents an effective approach for ecosystem restoration and carbon (C) sequestration. Nonetheless, it poses notable challenges concerning water depletion and soil drought in (semi)arid regions. The underlying mechanisms regulating the influence of afforestation on soil carbon‐water dynamics, particularly how deep soil C reacts to afforestation‐induced soil drying, remain largely unclear. This study examined the variations of soil water content (SWC), soil organic carbon (SOC), and soil inorganic carbon (SIC) in 500 cm depth along four afforestation stages: abandoned grasslands, shrublands, and 20‐year and 40‐year Robinia pseudoacacia forests (RP20 and RP40) in the semiarid Loess Plateau, China. The results indicated that afforestation has significantly increased SWC (+26.6%), SOC (+44.5%), and SIC (+6.5%) in the shallow layer (0–100 cm) but caused evident soil drying (−60.8%), decrease in SOC (−37.8%), and slight reduction in SIC (−0.3%) in the deep layer (300–500 cm) when compared with grasslands. The seriously decline in the coupling coordination between soil C and SWC in the middle and deep layers indicates the unsustainability of afforestation especially for RP40. Structural equation model showed that the negative impact of afforestation on deep SOC through soil water depletion (−0.38) outweighed the direct positive impact of increased aboveground biomass (AGB) (+0.33). The negative impacts of decreased SWC and increased pH on deep SIC was close to the positive impacts of AGB. Afforestation has different effects on SOC and SIC across shallow and deep layers, and its negative effects on deep soil C should be fully integrated into future forest ecosystem restoration and management efforts.

Straw return can increase maize yield by regulating soil bacteria and improving soil properties in arid and semi-arid areas

Straw return has been found to benefit soil fertility and crop yield, however, by which it affects microbial communities to mediate soil factors driving crop yields under maize continuous cropping systems in dryland areas is still unclear. To fill this gap, a 6-year field experiment was established with five straw return amounts (T0, T1, T2, T3, and T4, representing 0, 3,000, 6,000, 9,000, and 12,000kgha-1 of straw, respectively), and investigated the effects of on soil properties, enzymes, bacterial community composition and diversity, and crop yields. Our analysis showed that soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) contents significantly increased by 1-8%, 5-25%, and 2-9% under straw return treatments, respectively, compared to the T0, and soil catalase, urease, and alkaline phosphatase activities increased by at least 34.00%. Additionally, crop yield significantly increased by 4.23-12.00% under T1-T4 treatments, and showed highly significant relationships with SOC, TN, and TP. Importantly, we found straw return significantly altered the community of bacteria involved in the carbon and nitrogen cycle, and their abundance of strong responses depending on the amounts of straw return. For example, straw input increased the abundance of Proteobacteria (+2.64–5.57%), Acidobacteria (+3.82–13.83%), and Bacteroidetes (+15.37–30.49%). Similarly, the amount of straw application increased the bacterial diversity indexes (Shannon, 2.65–10.93%; Chao1, 13.47–18.50%), and had significant positive correlations with SOC, TN, and TP contents. Structural equation models (SEM) revealed that straw return management practice had positive and indirect effects on crop yields by influencing soil properties or the bacteria community. In conclusion, our findings revealed common associations and variations of bacterial community diversity with soil factors and crop yields at different straw return rates, and these findings provide insights and options for the development of better straw return strategies and sustainable agriculture in semi-arid regions.

Modeling carbon dynamics from a heterogeneous watershed in the mid-Atlantic USA: A distributed-calibration and independent verification (DCIV) approach

The terrestrial ecosystem plays a vital role in regulating regional and global carbon budgets. Ecosystem models are extensively employed to estimate carbon fluxes across different spatial scales. However, there remains a need to reduce the uncertainties associated with model parameterization and input data. To address these limitations, we assessed a distributed-calibration and independent-verification (DCIV) approach that uses (1) remotely sensed net primary production (NPP) and evapotranspiration (ET) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), (2) multi-site eddy covariance net ecosystem exchange (NEE) data; and (3) field sampling of soil organic carbon (SOC) and aboveground biomass (ABG) data to improve the overall predictability of carbon fluxes for the different land use and land cover (LULC) types at a watershed scale. The DCIV approach was applied to an advanced version of the Soil and Water Assessment Tool (SWAT)-Carbon (or SWAT-C), equipped with Century-based SOC algorithms to simulate carbon dynamics for watersheds with heterogeneous vegetation. The objective of the modeling effort was to assess carbon stocks and fluxes under different land management scenarios for a 3000-acre experimental farm and forest preserve in the northeastern United States. Our study showed that a large SOC stock of at least 100 tons ha−1 is stored under mixed forest, deciduous, shrubland, and floodplain (grass). Our study also showed that converting floodplain (grass) to deciduous forest has the potential to increase CO2 uptake (-NEE) by an order of three magnitude and ABG by 77 %, leading to an increased SOC stock of 23 % after twenty years. Similarly, we found that converting ungrazed grassland to grazed pasture leads to a non-statistically decreasing trend of SOC, especially in the 0–30 cm soil layer. Thus, the methodology used in this study can be applied to improve carbon dynamic prediction from a heterogeneous watershed at a regional scale.

Enhancement of soil humic acid hydrophobicity by 5 consecutive years of full-amount straw shallow-mixed field return

Crop yield is directly influenced by the storage and stabilisation of soil organic carbon (SOC), which is determined by the hydrophobicity of soil humic acid (HA). Changes in soil HA hydrophobicity, humic substances, SOC and crop yield were compared after the application of different amounts of straw returns in the field, and the contribution of straw application in enhancing HA hydrophobicity was examined. The treatments included no straw application and soil stirring, no straw application with soil stirring, application of half-amount straw shallow-mixed field return, application of full-amount straw shallow-mixed field return and application of double-amount straw shallow-mixed field return. Using elemental analysis, infrared spectroscopy and fluorescence spectroscopy, the structural hydrophobicity of soil HA was exhaustively characterised. The results showed that the hydrogen to carbon ratio of HA increased by 11.46%, the ratio of hydrophobic to hydrophilic intensity increased by 21.02%, and the ratio of peak B to peak A fluorescence intensity decreased by 32.21% after 5 years of full amount straw shallow-mixing field return compared to no straw application and soil stirring. The observed results indicate that the augmentation in hydrophobicity stimulates the formation of HA, enhances soil humification, elevates SOC content by 9.78% and potentially contributes to the ultimate crop yield increase by 22.98%. Compared with stirring the soil, the contribution rate of applying full amount of straw to increase HA hydrophobicity was 49.57-62.05%, and the contribution rate to increase SOC and yield were 54.59% and 76.37%, respectively. While stirring the soil contributed to increasing hydrophobicity, straw application persisted as the primary factor in enhancing hydrophobicity. The findings of this study have significant implications for understanding the mechanism by which straw improves HA hydrophobicity, thereby facilitating carbon sequestration and increasing crop yield.

Aridity-Driven Change in Microbial Carbon Use Efficiency and Its Linkage to Soil Carbon Storage.

Global warming is generally predicted to increase aridity in drylands, while the effects of aridity changes on microbial carbon use efficiency (CUE) and its linkage to soil organic carbon (SOC) storage remain unresolved, limiting the accuracy of soil carbon dynamic predictions under changing climates. Here, by employing large-scale soil sampling from 50 sites along an ~6000 km aridity gradient in northern China, we report a significant decreasing trend in microbial CUE (ranging from approximately 0.07 to 0.59 across the aridity gradient) with increasing aridity. The negative effect of aridity on microbial CUE was further verified by an independent moisture manipulation experiment, which revealed that CUE was lower under lower moisture levels than under higher moisture levels. Aridity-induced increases in physicochemical protection or decreases in microbial diversity primarily mediated the decrease in CUE with increasing aridity. Moreover, we found a highly positive microbial CUE-SOC relationship, and incorporating CUE improved the explanatory power of SOC variations along the aridity gradient. Our findings provide empirical evidence for aridity-induced reductions in microbial CUE over a broad geographic scale and highlight that increasing aridity may be a crucial mechanism underlying SOC loss by suppressing the ability of soil microorganisms to sequester carbon.

Long-term tillage and crop rotation effects on soil carbon and nitrogen stocks in southwestern Ontario

Conservation tillage and crop rotation diversification have been promoted to increase soil C and N storage; however, the interactive effects of tillage and crop rotation on soil C and N dynamics remain contradictory. Using a long-term (24-yr) experiment established at a clay loam site (Orthic Humic Gleysol) at Ridgetown, Ontario, Canada, the interactive effects of five crop rotations and two tillage systems were tested on soil organic C (SOC) and total N storage in soil depth increments and in the full soil profile (0-0.6 m) in 2019. While crop rotation influenced SOC and total N concentration in top 0.2 m, these effects were minimized when storage was expressed on an equivalent soil mass basis. Over the 0-0.6 m depth, no-tillage had 24 Mg SOC ha-1 and 4.7 Mg total N ha-1 greater content, respectively, than conventional tillage, supporting the value of no-tillage on increasing soil C and N in the long-term. Interestingly, no interactive effects of crop rotation and tillage on soil C and N storage in 0-0.6 m were observed. While the type of crop species and amount of C and N inputs under different crop rotations are important variables impacting the soil C and N storage, our results suggest that the crop rotation diversity was not a major driver of soil C and N in this study. Future mechanistic investigations exploring the persistence and linkage of soil C and N with crop rotation diversity in the tested production systems are needed.

Characterization of organic materials in regulating soil carbon sequestration of urban greenspaces: Links to microbial necromass and community composition

Application of organic material is a win-win strategy that effectively boosts soil carbon (C) storage and promotes organic waste recycling in urban ecosystems. However, the divergent responses of C sequestration to organic materials and the underlying mechanisms remain unclear. Using molecular and litterbag methods, this study examined soil organic C (SOC) content, C sequestration efficiency of organic material (CSE-organic material), microbial necromass and community composition in urban greenspaces amended with different types of organic materials. The field experiment had seven treatments: addition of green waste (GreenWaste), green waste compost (GreenWasteCompost), biogas residue (BiogasResidue), biogas residue compost (BiogasResidueCompost), peat (PEAT), biochar (BioChar), and no organic material (Control). Organic materials after 16 months application increased SOC content by 34.1–87.0% compared with the Control and presented CSE-organic material in the order: BioChar > GreenWasteCompost > PEAT > BiogasResidueCompost > GreenWaste > BiogasResidue. Aromaticity index was positively correlated with CSE-organic material, indicating that aromatic C addition had a strong capacity to enhance C sequestration. Microbial necromass increased from 2.7 g C kg−1 in the Control to 3.9–5.0 g C kg−1 under organic materials addition. Bacterial necromass was enriched in the BiogasResidue and BiogasResidueCompost treatments, primarily because of sufficient substrate that facilitated the proliferation and activity of copiotrophic Firmicutes, whereas fungal necromass was 8.8–19.1% higher in the GreenWaste, GreenWasteCompost, and PEAT treatments than that in the BiogasResidue and BiogasResidueCompost treatments, accompanying by an increasing abundance of Ascomycota. However, the contribution of microbial necromass to the increased SOC was negatively correlated with CSE-organic material, suggesting that the input of recalcitrant C weakened the role of microbial necromass in C retention. Overall, this study reveals that the efficiency of organic materials application in promoting soil C accumulation depends largely on recalcitrant C rather than microbial necromass, which highlights the important role of organic waste acting as a C source in achieving urban sustainable development.

Reseeding increased plant biomass production and soil fertility, but not plant species diversity in degraded grasslands in China

Reseeding is a primary measure to restore degraded grasslands. Numerous studies have conducted experiments to investigate how the properties of grassland ecosystems respond to reseeding in China. However, there is a lack of summary of the results of these studies. Here, we conducted a hierarchical random-effects meta-analysis on the effects of reseeding on plant, soil, and microbial properties. We collected 19 variables, including plant biomass, species diversity and richness, soil organic carbon content, soil total and available nutrients, soil water content, soil microbial biomass and diversity, and enzyme activity, from a dataset of 1363 paired observations (degraded vs. reseeded) from 75 publications. The results showed that reseeding increased aboveground and belowground plant biomass by 70.2% and 68.0% on average, respectively. Reseeding increased soil organic carbon, phosphorus, and potassium contents, but did not affect soil nitrogen levels. Reseeding increased soil microbial nitrogen under conditions of tillage and fertilization. Reseeding age was found to have a positive correlation with species richness, while planting type, fertilization, and tillage did not have a significant impact on the species richness and diversity. Under the treatments of fertilization, non-tillage, and mix-planting, the response ratio of aboveground biomass to reseeding was positively correlated with the response ratio of species diversity to reseeding. Our results concluded that current reseeding practices can significantly improve plant biomass production and soil fertility but have minor effects on plant species diversity. These findings indicate that the preservation of biodiversity should receive greater attention from both researchers and practitioners in grassland remediation in China.

Drainage estimation across mountainous regions from large-scale soil moisture observations

Drainage is a crucial soil hydrological process that governs the partitioning of rainfall into runoff, groundwater recharge, soil water storage and evapotranspiration. Despite its significance, the drainage process is poorly understood due to the difficulty in direct measurements and insufficient understanding of its underlying physical mechanisms. To address these challenges, we present an innovative, physically-based, data-driven approach, SM2D (Soil Moisture to Drainage), to estimate drainage. SM2D was applied and examined using soil moisture data from a large-scale observation network over mountainous areas during 2014–2020. The soil moisture threshold governing drainage initiation proves to be significantly lower than the commonly employed field capacity metric in hydrological models. This threshold is influenced by factors such as mean soil moisture, bulk density, residual soil moisture, soil organic carbon, and parameters n and α of soil retention curve. Notably, field capacity has minimal impact on this threshold. Additionally, our analysis reveals that the drainage process is more influenced by the Soil Water Storage Increment (SWSI) than by mean soil moisture (MSM) that has traditionally been recognized as a key factor in drainage control. In comparison to commonly used exponential equations and those in models such as the Soil & Water Assessment Tool (SWAT), SM2D demonstrates superior performance in estimating drainage. The exponential equation derived from the SWSI outperforms those derived from other soil moisture metrics, including the commonly utilized MSM, challenging prevailing norms in drainage equations. SM2D holds the potential to generate extensive drainage datasets from satellite or large-scale soil moisture observations, advancing large-scale hydrological studies.

Goethite introduction strengthens balck soil carbon sequestration under various water management conditions and its microbial mechanisms

Natural and anthropogenic disturbances lead to degradation of (soil organic carbon) SOC content black soil in northeast china. Goethite (α-FeO (OH)) as widely distributed mineral, has a sequestration effect on SOC. With the diversification of crop cultivation in northeast china, various water management are becoming important. However, SOC sequestration mechanism by goethite under varying water management conditions is still unclear. In our study, we set up 3 groups of experiments: 1) 60% water-holding capacity (60% WHC), 60% water-holding capacity with goethite (60% WHCG), 2), waterlogging (W), waterloggin with goethite (WG), 3) alternation of wetting and drying (AWD), alternation of wetting and drying with goethite (AWDG) to elucidate the sequestration mechanism of SOC by goethite under three water management conditions. Results shows introducing goethite can sequester SOC under three water management conditions, with WG SOC sequestration capacity more than AWDG and 60% WHCG. The main sequestration mechanism of SOC has two aspects, on the one hand, goethite introduction increased significantly SOC functional groups, Fe-bound OC, iron molar ratio and Fe-bound OC/SOC, made SOC was bound to goethite by adsorption and co-precipitation. On the other hand, goethite introduction increased the diversity and abundance of bacteria and fungi by affecting soil pH, iron morphology and valence, induced the enrichment of Bryobacter, Gemmatimonas, Conexibacter, Streptomyces, Gaiella, Rubrobacter and Talaromyces potential carbon sequestrating microorganisms, further contributing to SOC sequestration. This study offers a significant theoretical foundation for elucidating the SOC sequestration mechanism of northeastern black soil.

Constructing Soil–Landscape Units Based on Slope Position and Land Use to Improve Soil Prediction Accuracy

Topography is one of the dominant factors in regional soil formation and development. Soil distribution has a certain pattern from high to low in space, and this pattern has a high degree of consistency with slope position. Most of the current research on soil mapping uses landscape types generated by existing methods directly as environmental covariates, and there are few landscape classification methods specifically oriented toward soil surveys. There is rarely any research on landform classification using relative slope position (RSP) and elevation. Therefore, we designed a landform classification method based on RSP and elevation, Terrainforms (TF), and combined the landform type with land use type to construct soil–landscape units for soil type and attribute spatial prediction. In this study, two commonly used landform classification methods, Geomorphons and Landforms, were also used to compare with this design method. It was found that the constructed soil–landscape units had a high consistency with the soil spatial distribution. The landform types based on RSP and elevation obtained the second-highest prediction accuracy in both soil type and soil organic carbon (SOC), and the constructed soil–landscape types obtained the highest prediction accuracy. The results show that the landform classification method based on RSP and elevation is not easily limited by the analysis scale, and is an efficient and accurate landform classification method. The TF landform type and its constructed soil–landscape types can be used as an important environmental variable in soil prediction and sampling, which can provide some guidance and reference for landform classification and digital soil mapping.

Synergistic regulation of salinity and nutrients on organic carbon mineralization in a 700-year cultivated saline soil chronosequence

Long-term cultivation in reclaimed mudflats significantly impacts soil properties through changes in salinity and organic carbon (OC) inputs, which subsequently affect soil physical, chemical, and biological characteristics. In addition, long-term rice cultivation can help optimize soil health and fertility management in paddy fields, mitigate climate change, and enhance ecosystem services. However, the impact of long-term cultivation on OC mineralization across a salinity gradient remains unclear. During an 80-d incubation experiment, we assessed 13C-labeled glucose mineralization in soils cultivated for 5, 20, 200, and 700 years, each with varying salinity levels. Our results demonstrated that glucose mineralization declined linearly with increasing soil salinity, from 76 % in low-salinity soils to 31 % in high-salinity soils, reflecting a clear physical impact. This process was closely linked with chemical properties, showing a positive correlation with Olsen P and levels of microbial biomass carbon and nitrogen. Soil organic carbon (SOC) mineralization was primarily controlled by dissolved OC regardless of soil salinity. Further investigation revealed significant shifts in the biological properties, notably the bacterial community composition, which varied with the duration of soil cultivation. The bacterial Shannon index increased steadily from 50 to 700 years, forming distinct clusters, influenced primarily by electrical conductivity and pH in high-salinity soils and by soil-labile nutrients in low-salinity soils. The abundance of Acidobacteria, Proteobacteria, and Verrucomicrobia—dominant phyla in soil cultivated for 700 years—is negatively correlated with soil salinity and pH and positively with labile nutrients, glucose, and OC mineralization, whereas the opposite was true for Bacteroidetes and Firmicutes dominant phyla in soil cultivated for 5 years, was affected positively by soil salinity and pH and negatively by labile nutrients and glucose mineralization. In conclusion, soil salinity and nutrients synergistically regulate OC mineralization in a 700-year cultivated saline soil chronosequence. Addressing these factors is critical to enhancing microbial activity and OC accumulation in saline soils, underscoring the importance of integrating measures to reduce salt and increase the import and accumulation of exogenous organic matter.

Life Cycle Assessment of Brazilian Bleached Eucalyptus Kraft Pulp: Integrating Bleaching Processes and Biogenic Carbon Impacts

Bleached eucalyptus kraft (BEK) pulp dominates global pulp production, yet the environmental impacts of its bleaching sequences in Brazil are not fully explored. Addressing this gap, we conducted a comparative life cycle assessment (LCA) of three bleaching sequences: conventional elemental chlorine-free (ECF), ECF with oxygen delignification, and ECF with oxygen delignification plus acid washing. We estimated the average global warming potential (GWP) for BEK delivered to the U.S. and examined how forest carbon cycle (FCC) elements, specifically biogenic GWP (GWPbio) and potential soil organic carbon (SOC) sequestration, influence GWP outcomes. Results show that the ECF sequence with oxygen delignification and acid washing reduces GWP by 11% and outperforms conventional ECF in 10 out of 11 environmental impact categories. The average GWP for Brazilian BEK delivered to the U.S. is 576 kg CO₂-eq/ton. Sensitivity analyses demonstrate that adding GWPbio increases GWP by 18%, whereas accounting for potential SOC sequestration reduces it by 39%. These findings highlight the necessity of optimizing bleaching processes and developing a standardized BEK LCA model for comparing the environmental impact of different fibers. This work sets a precedent for integrating FCC elements into LCAs and underscores the potential of SOC sequestration in mitigating climate change impacts.

A Comprehensive Evaluation of Machine Learning Algorithms for Digital Soil Organic Carbon Mapping on a National Scale

The aim of this study was to narrow the research gap of ambiguity in which machine learning algorithms should be selected for evaluation in digital soil organic carbon (SOC) mapping. This was performed by providing a comprehensive assessment of prediction accuracy for 15 frequently used machine learning algorithms in digital SOC mapping based on studies indexed in the Web of Science Core Collection (WoSCC), providing a basis for algorithm selection in future studies. Two study areas, including mainland France and the Czech Republic, were used in the study based on 2514 and 400 soil samples from the LUCAS 2018 dataset. Random Forest was first ranked for France (mainland) and then ranked for the Czech Republic regarding prediction accuracy; the coefficients of determination were 0.411 and 0.249, respectively, which was in accordance with its dominant appearance in previous studies indexed in the WoSCC. Additionally, the K-Nearest Neighbors and Gradient Boosting Machine regression algorithms indicated, relative to their frequency in studies indexed in the WoSCC, that they are underrated and should be more frequently considered in future digital SOC studies. Future studies should consider study areas not strictly related to human-made administrative borders, as well as more interpretable machine learning and ensemble machine learning approaches.