Changes In Organic Carbon Stocks Research Articles

Bulk density and coarse fragment content of the French soil monitoring network for better assessment of changes of soil organic carbon stocks

Bulk density (BD) and coarse fragments (CF) are often missing in soil monitoring networks. In the French Soil Quality Monitoring Network BD and CF have been measured in two campaigns in sites distributed in a grid over mainland France. The objective of this work is to evaluate i) how BD and CF have changed, ii) how volumetric methods and land use affect the observed trends, and iii) to simulate the impact of BD and CF changes on the estimations of changes of soil organic carbon stocks (SOCS). The results showed no significant change of (Δ) CF between campaigns in either the topsoil or subsoil, while there was a significant decrease of BD only in the topsoil (−3.1 ± 0.9 %). When methods were constant in both campaigns, BD decreased in croplands and grasslands topsoil and it did not change in forests. We could explain a rather low part of the ΔBD variance (R2 = 0.21), mostly linked to the within-site variability of CF and to changes in some methodological aspects between campaigns. We simulated changes in topsoil SOCS, assuming SOC content constant over time; we found negative estimates that were the largest in soils with low CF content (−0.2 ± 0.06 % yr−1 an-1) as well as differences between using site-specific average CF values over both campaigns and using site-specific values of each campaign [-0.17 ± 0.04 % yr−1 vs −0.05 ± 0.06 % yr−1, respectively]. These differences were caused by rocky soils, and were not significant when using only sites with low CF content. Our work highlights some limitations in assessing BD changes using broad-scale soil monitoring networks. These findings have important consequences on the methods used to assess changes in SOCS and their uncertainties at broad-scale. They are timely and relevant given the current proposals to implement soil health monitoring at national, continental and global scale.

Changes in soil organic carbon stocks and mineralization following the replacement of secondary evergreen broadleaf forests with tea (Camellia sinensis L.) plantations

AbstractTea plantation ecosystems have a strong potential to sequester carbon (C) and reduce CO2 emissions. However, the effects of different tea planting periods on soil organic carbon (SOC) stocks and mineralization and related mechanisms are unclear. To address this knowledge gap, we investigated the effects of replacing evergreen broadleaf forests with tea plantations on SOC stocks and mineralization rates by examining alterations in SOC pools and composition, microbial community composition, functional genes related to C‐cycling and enzyme activities. The SOC content in forest, 30‐, 50‐ and 100‐year‐old tea plantations were 1.91%, 2.37%, 2.87% and 3.69%, respectively, in the 0–20 cm soil depth (100‐year‐old > 50‐year‐old > 30‐year‐old > forest). Cumulative CO2–C emissions increased by 38.1% (114 mg C kg−1 soil), 49.9% (157 mg C kg−1 soil), and 100.2% (171 mg C kg−1 soil) compared to forest soil (228 mg C kg−1 soil) after tea had been grown for 30, 50 and 100 years, respectively; however, cumulative CO2 emissions did not differ significantly between the 30‐ and 50‐year‐old plantations. The rate of SOC mineralization was positively related to particulate organic carbon (POC), water‐soluble organic carbon (WSOC), microbial biomass C (MBC), and O‐alkyl C contents, as well as β‐glucosidase/cellobiohydrolase activities and GH48/cbhI abundance; by contrast, the SOC mineralization rate was negatively correlated with the aromatic C content. More importantly, bacteria and fungi related to SOC mineralization, such as WPS‐2 and Acidobacteria, and Sordariomycetes, Tremellomycetes, Mortierellomycetes and Agaricomycetes, respectively, had high relative abundances. Our results indicate that replacing forests with tea plantations enhanced both SOC stocks and mineralization rates and that this effect was positively correlated with tea cultivation time. We reveal that an increased length of the tea planting period was conducive to increasing SOC stocks, and mitigating C losses in tea plantation soils is crucial for establishing an ecologically low‐C tea plantation system.

Abandonment Leads to Changes in Forest Structural and Soil Organic Carbon Stocks in Moso Bamboo Forests.

The important role of soil carbon pools in coping with climate change has become widely recognized. Moso bamboo (Phyllostachys pubescens) is an economically important bamboo species in South China; however, owing to factors such as rising labor costs and increasingly stringent environmental policies, Moso bamboo forests have recently been abandoned. The present study aimed to investigate the effects of abandonment on structural factors and soil organic carbon (SOC) stocks in Moso bamboo forests. We investigated Moso bamboo forests subjected to intensive management or abandonment for different durations and measured forest structural characteristics, mineral properties, soil nutrients, and other soil properties. Although abandonment did not significantly affect the height and diameter at breast height, it increased culm densities, biomass, and SOC stocks. The drivers of SOC stocks depended on soil depth and were mainly controlled by carbon decomposition mediated by soil properties. In the topsoil, mineral protection and soil total nitrogen (TN) exerted significant effects on SOC stocks; in the subsoil, soil TN was the main driver of SOC stocks. As the controlling factors of SOC stocks differed between the subsoil and topsoil, more attention should be paid to the subsoil. Overall, these findings refine our understanding of the structural characteristics and SOC stocks associated with Moso bamboo forest abandonment, serving as a reference for the follow-up management of these forests.

Tracking the Dynamics and Uncertainties of Soil Organic Carbon in Agricultural Soils Based on a Novel Robust Meta-Model Framework Using Multisource Data

Monitoring and estimating spatially resolved changes in soil organic carbon (SOC) stocks are necessary for supporting national and international policies aimed at assisting land degradation neutrality and climate change mitigation, improving soil fertility and food production, maintaining water quality, and enhancing renewable energy and ecosystem services. In this work, we report on the development and application of a data-driven, quantile regression machine learning model to estimate and predict annual SOC stocks at plow depth under the variability of climate. The model enables the analysis of SOC content levels and respective probabilities of their occurrence as a function of exogenous parameters such as monthly temperature and precipitation and endogenous, decision-dependent parameters, which can be altered by land use practices. The estimated quantiles and their trends indicate the uncertainty ranges and the respective likelihoods of plausible SOC content. The model can be used as a reduced-form scenario generator of stochastic SOC scenarios. It can be integrated as a submodel in Integrated Assessment models with detailed land use sectors such as GLOBIOM to analyze costs and find optimal land management practices to sequester SOC and fulfill food–water–energy–-environmental NEXUS security goals.

Carbon footprint of mixed farming crop-livestock rotational-based grazing beef systems using long term experimental data

In the context of ever-growing demand for food and associated concerns regarding the environmental impacts of high-input agricultural systems, there is growing interest in mixed farm enterprises to deliver greater sustainability compared with mono-enterprise production systems. However, assessments of such systems are complex and require high-resolution data to determine the true value and interconnectivity across enterprises. Given the scarcity of information on mixed crop–livestock systems and the difficulties of its analysis, we perform life cycle assessment using temporally high-resolution data (2019–2022) from a long-term experiment in South America to evaluate the ‘cradle-to-farmgate exit’ greenhouse gas emissions intensities of four rotational crop–livestock systems. Systems evaluated were continuous cropping: 2 years of continuous cropping; short rotation: 2-year continuous cropping plus 2-year pasture; long rotation: 2-year continuous cropping followed by 4-year pasture; and forage rotation: continuous pasture. Emissions intensities for beef throughput were reported as kilograms of carbon dioxide equivalents (CO2-eq) per kilogram of liveweight gain (LWG) using the Intergovernmental Panel for Climate Change’s Sixth Assessment Report (AR6 2021) CO2 characterisation factors. Point estimate results were found to be 11.3, 11.8, 11.8 and 16.4 kg CO2-eq/kg/LWG for continuous cropping, short rotation, long rotation and forage rotation, respectively. Emission averages arising from crops, which were separated from animal-based emissions using economic allocation, were 1.23, 0.53 and 0.52 kg CO2-eq/kg for soybean, wheat and oat, respectively. The inclusion of soil organic carbon stock changes had notable effects on reducing each system’s emissions: by 22.4%, 19.2%, 25.3% and 42.1% under continuous cropping, short rotation, long rotation and forage rotation, respectively, when soil organic carbon was included. Given there are few life cycle assessment studies available on such mixed-enterprise ‘semi-circular’ systems, particularly with novel primary data, this study adds critical knowledge to agri-food-related sustainability literature by addressing environmental issues in complex production systems compared to extant and broad coverage of mono-enterprise systems.

Are soil carbon credits empty promises? Shortcomings of current soil carbon quantification methodologies and improvement avenues

AbstractAs the consequences of climate change are looming large, agricultural soil carbon credits have emerged as an increasingly advocated lever to incentivize the reduction of greenhouse gas emissions and promote carbon storing farming practices. These credits are exchanged on self‐regulated voluntary carbon markets, each of them using distinct protocols to assess the changes in soil carbon stocks and convert them into carbon credits. Although serious discrepancies between protocols have already been noted regarding general carbon credit accounting principles, an in‐depth evaluation of how changes in soil organic carbon stocks are calculated is still lacking. In this context, the primary objective of our study was to investigate how changes in soil organic carbon stock are estimated by the major carbon credit protocols worldwide. We evaluated the requirements of each protocol regarding the estimation of the initial SOC stock as well as the modelling and/or measurement of changes in stock with time. We found that existing protocols vary greatly in their scientific rigour. We showed in particular that some protocols do not require in situ soil analyses to estimate initial soil carbon stocks but rely on regional values, leading them to potentially overestimate these stocks by up to 2.5 times. Our study also found that the protocols relying on models require different farming practices and different levels of information for each practice to estimate SOC stock changes. The protocols relying, at least partly, on soil sampling also displayed different requirements for the sampling design, sampling tools, SOC analysis methods and SOC stock calculation methods. On this basis, we suggest reforms designed to improve and standardize the quantification of carbon stock changes in soils and to improve the reliability of soil carbon credits.

Increased straw return promoted soil organic carbon accumulation in China's croplands over the past 40 years

Quantifying changes in soil organic carbon (SOC) stocks within croplands across a broad spatiotemporal scale in response to anthropogenic and environmental factors offers valuable insights for sustainable agriculture aimed to improve soil health. Using a validated and widely used soil carbon model RothC, we simulated the SOC dynamics across intensive croplands in China that support ∼22 % of the global population using only 7 % of the global cropland area. The modelling results demonstrate that the optimized RothC effectively captures SOC dynamics measured across 29 long-term field trials during 40 years. Between 1980 and 2020, the average SOC at the top 30 cm in croplands increased from 40 Mg C ha−1 to 49 Mg C ha−1, resulting in a national carbon sequestration of 1100 Tg C, with an average carbon sequestration rate of 27 Tg C yr−1. The annual increase rate of SOC (relative to the SOC stock of the previous year), starting at <0.2 % yr−1 in the 1980s, reached around 0.4 % yr−1 in the 1990s and further rose to about 0.8 % yr−1 in the 2000s and 2010s. Notably, the eastern and southern regions, comprising about 40 % of the croplands, contributed about two-thirds of the national SOC gain. In northeast China, SOC slightly decreased from 58 Mg C ha−1 in 1980 to 57 Mg C ha−1 in 2020, resulting in a total decline of 28 Tg C. Increased organic C inputs, particularly from the straw return, was the crucial factor in SOC increase. Future strategies should focus on region-specific optimization of straw management. Specifically, in northeast China, increasing the proportion of straw returned to fields can prevent further SOC decline. In regions with SOC increase, such as the eastern and southern regions, diversified straw utilization (e.g., bioenergy production), could further mitigate greenhouse gas emissions.

Impacts of conservation agriculture on soil C and N stocks and organic matter fractions: comparing commercial producer fields with a long-term small-plot experiment in Brown Chernozems of Saskatchewan

Conservation agriculture (CA) is increasingly promoted to build soil organic matter (SOM) based on findings from predominantly small-plot long-term agroecosystem experiments (LTAEs), with minimal on-farm data. Using commercial producer fields ( n = 20) in the Brown Chernozemic soil zones of Saskatchewan, Canada, which were sampled before (1996) and after (2018) adopting direct-seeding and continuous cropping (1997), we examined changes in soil organic carbon (SOC) and soil total nitrogen (STN) stocks, along with C and N stocks in particulate (POM) and mineral-associated organic matter (MAOM), and compared them to an LTAE in the same soil zone. After 21 years, SOC and STN stocks (0–30 cm depth) increased by 13% and 21%, respectively, in commercial producer fields, and were more pronounced in finer- than coarser-textured soils. Conversely, there were no significant changes (0–30 cm depth) after 18 years (1998–2016) with CA (continuous wheat and pulse-wheat under no-tillage (PW-NT)) in the LTAE, except that STN stock for PW-NT decreased by 7.7%. The estimated rate of change to 30 cm depth was similar between the commercial fields and LTAE for SOC (0.28 and 0.16 Mg C ha−1 year−1, respectively), but not STN (0.04 and −0.03 Mg N ha−1 year−1, respectively). Changes were more evident in the MAOM than POM fraction in both cases. Although the impact of CA may be similar, as observed for SOC, actual on-farm changes will depend on site-specific factors, and specific CA practice. Therefore, on-farm monitoring studies are needed for more accurate assessments of SOM changes and C sequestration potentials.

Soil organic carbon as an indicator of land use impacts in life cycle assessment

PurposeAnthropogenic activities are a major driver of soil and land degradation. Due to the spatial heterogeneity of soil properties and the global nature of most value chains, the modelling of the impacts of land use on soil quality for application in life cycle assessment (LCA) requires a regionalised assessment with global coverage. This paper proposes an approach to quantify the impacts of land use on soil quality, using changes in soil organic carbon (SOC) stocks as a proxy, following the latest recommendation of the Life Cycle Initiative.MethodsAn operational set of SOC-based characterisation factors for land occupation and land transformation were derived using spatial datasets (1 km resolution) and aggregated at the national and global levels. The developed characterisation factors were tested by means of a case study analysis, investigating the impact on soil quality caused by land use activities necessary to provide three alternative energy supply systems for passenger car transport (biomethane, ethanol, and solar electricity). Results obtained by applying characterisation factors at local, regional, and national levels were compared, to investigate the role of the level of regionalisation on the resulting impacts.Results and discussionGlobal maps of characterisation factors are presented for the 56 land use types commonly used in LCA databases, together with national and global values. Urban and industrial land uses present the highest impacts on SOC stocks, followed by severely degraded pastures and intensively managed arable lands. Instead, values obtained for extensive pastures, flooded crops, and urban green areas often report an increase in SOC stocks. Results show that the ranking of impacts of the three energy systems considered in the case study analysis is not affected by the level of regionalisation of the analysis. In the case of biomethane energy supply, impacts assessed using national characterisation factors are more than double those obtained with local characterisation factors, with less significant differences in the other two cases.ConclusionsThe integration of soil quality aspects in life cycle impact assessment methods is a crucial challenge due to the key role of soil conservation in ensuring food security and environmental protection. This approach allows the quantification of land use impacts on SOC stocks, taken as a proxy of soil quality. Further research needs to improve the assessment of land use impacts in LCA are identified, such as the ability to reflect the effects of agricultural and forestry management practices.

Distribution Patterns of Sediment Organic Carbon Stocks in Shallow Lakes and the Significance for Sustainable Lake Management: Chaohu Lake in Eastern China as a Case Study

Shallow lake sediments have huge potential for carbon storage, but they are vulnerable to various environmental changes and are highly susceptible to becoming a source of carbon emissions. Understanding the amount of sediment carbon storage can provide information about the potential of shallow lakes in mitigating climate change. In this study, sediment sampling was conducted at 12 study sites in Chaohu Lake, China, and sediment water content, grain size, bulk density, and sediments organic carbon (SOC) content were examined in five layers along the vertical direction, respectively, and the distribution and storage of SOC were estimated. The results showed that the surface sediments in the west lake area of Chaohu Lake would release 66,300 t of SOC to the overlying water body in the future. The sediments in the middle lake area and the east lake area will absorb another 15,900 t and 17,300 t of TOC from the water body in the future, respectively. Overall, the lake-wide sediments will release 33,100 t of SOC into the water body in the future. In addition, the results of the study also indicate that human activities are another major influence on the change in organic carbon stocks in lake sediments, and therefore, proactive measures for the restoration and protection of lake sediments are essential because increasing the SOC stocks in the sediments and maintaining the lakes in a sustainable manner can contribute to the crucial role they play in mitigating climate change.

How Land Use Transitions Contribute to the Soil Organic Carbon Accumulation from 1990 to 2020

Soil organic carbon stock (SOCS) changes caused by land use changes are still unclear, and understanding this response is essential for many environmental policies and land management practices. In this study, we investigated the temporal–spatial and vertical distribution characteristics of the SOCS in the Western Sichuan Plateau (WSP) using the sparrow search algorithm–random forest regression (SSA-RFR) models with excellent model applicability and accuracy. The temporal–spatial variations in the SOCS were modeled using 1080 soil samples and a set of nine environmental covariates. We analyzed the effect of land use changes on the SOCS in the WSP. The total SOCS increased by 18.03 Tg C from 1990 to 2020. The results of this study confirmed a significant increase in the SOCS in the study area since 2010. There was a 27.88 Tg C increase in the SOCS in 2020 compared to the total SOCS in 2010. We found that the spatial distribution of the SOCS increased from southeast to northwest, and the vertical distribution of the SOCS in the study area decreased with increasing soil depth. Forests and grasslands are the main sources of SOCS the total SOCS in the forest and grassland accounted for 37.53 and 59.39% of the total soil organic carbon (SOC) pool in 2020, respectively. The expansion of the wetlands, forest, and grassland areas could increase the SOCS in the study area. A timely and accurate understanding of the dynamics of SOC is crucial for developing effective land management strategies to enhance carbon sequestration and mitigate land degradation.

Assessing changes in soil organic carbon stocks and vulnerability to land degradation in Western Ghats, South India: Is it restorative enough?

AbstractSoil organic carbon stock is an important universal land degradation indicator. Owing to the depletion in soil nutrients, the pace of land degradation has increased in the Western Ghats of South India. To understand the changes in surface and subsurface soil organic carbon stocks and vulnerability to land degradation upon land use change, a study was carried out along the natural forest and coffee plantation ecosystems of Western Ghats in South India. The study sites were located in Chikmagaluru of Karnataka and Wayanad and Idukki districts of Kerala. Soil organic carbon stocks (SOC) at the surface (0–30 cm) were higher, 9.10 t C ha−1 and 7.49 k t C ha−1 in forest soils of Chikmagaluru and Idukki, respectively, and the subsurface (30–100 cm) SOC stocks were higher in the coffee plantation ecosystems, 9.11, 9.87, and 8.41 t C ha−1, respectively, in Chikmagaluru, Wayanad, and Idukki. Vulnerability analysis revealed that Chikmagaluru forest (0.57) and coffee (0.51), Wayanad forest (0.58) and coffee (0.55) land uses were low, and both the land uses in Idukki were medium in the status of land degradation with scores of 0.65 and 0.60, respectively, in forest and coffee ecosystems. The difference in the status of land degradation was mainly because of changes in soil reaction, surface, and subsurface SOC stock. An increase in soil pH, CEC, and available nutrients upon conversion to coffee plantation along with increased subsurface carbon storage have confirmed the restorative properties of coffee land use even after conversion from natural forests.

Study on the Effects of Reducing Nitrogen Fertilizer: Stabilizing Yield and Carbon Sequestration by Synergistic Utilization of Chinese Milk Vetch and Rice Straw in Double-Cropping Rice Area

The excessive application of chemical fertilizers in rice fields exacerbates soil degradation and poses a threat to food security. Achieving an increase in rice production and minimizing environmental costs are inevitable requirements for achieving sustainable rice production. The synergistic utilization of rice straw (RS) and Chinese milk vetch (MV) is a sustainable measure to improve soil quality in Southern China. How this management strategy impacts agricultural productivity and soil carbon (C) sequestration under different fertilization conditions is unclear. Several treatments, including only chemical fertilizer (F), F + MV (FM), F + RS (FS), and F + MV + RS (FMS) under a standard rate of nitrogen (N100) and 40% reduced nitrogen (N60) levels were designed to explore changes in rice yields and soil organic carbon (SOC) concentrations, stocks, and soil labile organic C fractions (permanganate oxidizable C) during 2018–2020 in a double-rice-cropping system. The results show that the FMS treatment reduced soil bulk density to alleviate soil compaction and improved the soil carbon management index. The synergistic utilization of MV and RS replacing 40% of the chemical N fertilizer could still maintain the rice yield. Compared to the F treatment, the average annual grain yield was significantly increased by 9.82% and 5.84% in the FMS treatment; SOC concentration was increased by 16.05% and 19.98% on average (p &lt; 0.05), and SOC stock was increased by 1.78 Mg C ha−1 and 2.37 Mg C ha−1 under the N60 and N100 levels, respectively. The random forest regression model and correlation analysis demonstrated that the inputs of chemical N, organic N and C, and appropriate C/N ratio promoted soil C accumulation. Furthermore, the structural equation model analysis exhibited that the C input affects the highly labile organic carbon (HLOC) and total labile organic carbon (LOC); the HLOC had a positive effect on SOC (p &lt; 0.05). N input had a significant effect on LOC and yield. Our results suggest that the synergistic utilization of MV and RS plays an important role in ensuring stable grain production, improving soil C sequestration capacity, and maintaining soil environmental health in Southern China.

Cultivation of forage maize in boreal conditions – Assessment of trade-offs between increased productivity and environmental impact

The cultivation of whole crop forage maize (Zea mays L.) for cattle feed has a potential for increased forage yield while reducing nitrogen (N) fertilisation compared to perennial grass-based systems. However, the possible environmental trade-offs of forage maize cultivation remain unknown in the boreal region due to the short growing season which limits cultivation practices. The aim of this study was to compare the environmental impact of forage maize with more widely cultivated forage crops in Finland that include perennial silage grass mixtures and whole crop spring cereal harvested as silage. The use of plastic mulch film in forage maize cultivation was included in the assessment as well. A life cycle assessment (LCA) was conducted including impact categories for global warming potential; marine and freshwater eutrophication; terrestrial acidification; freshwater, marine and terrestrial ecotoxicity; land use; and fossil resource depletion. Additionally, soil organic carbon (SOC) stock changes under long-term cultivation of the studied forage crops were simulated with the C-TOOL and Yasso20 models with methodological comparisons. The only clear differences between the studied crops were that the land use was lower (−26–48%) for forage maize, and the freshwater eutrophication (+59–67%) and terrestrial acidification (+10–57%) were higher for perennial grasses compared with other forages. A risk for decreased SOC stock under continuous forage maize cultivation was observed. Forage maize could be used to supplement perennial grass cultivation without major associated environmental risks. Future research shall be conducted on the effect of forage choices on the environmental impact of boreal dairy milk production and on decreasing the current high uncertainty associated with nitrous oxide (N2O) emission factors and SOC stock modelling choices.

Metagenomic insights into microbial diversity and carbon cycling related genes along the elevational gradient in an arid mountain ecosystem

Understanding the elevational patterns of soil microbial carbon (C) metabolic potentials is instrumental for predicting changes in soil organic carbon (SOC) stocks in the face of climate change. However, such patterns remain uncertain in arid mountain ecosystems, where climosequences are quite different from other ecosystems. To address this gap, this study investigated the distribution determinants of microbial communities, C-cycling functional genes, and SOC fractions along the elevational gradient (1 707−3 548 m, a mean annual precipitation (MAP) range of 38 to 344 mm) of the north slope of Central Kunlun Mountain, using a metagenomic approach. Results showed that elevation significantly influenced the α-diversity (Shannon index) and composition of microbial communities as well as the C-cycling functional genes. The α-diversity of microbial taxonomy and C-cycling functional genes linearly increased with the increase in MAP along the elevational gradient. The elevational patterns of genes encoding glycoside hydrolases and glycosyltransferases (GTs) were mainly driven by electrical conductivity (EC), mean average temperature (MAT), MAP, and plant diversity. Furthermore, mineral-associated organic carbon (MAOC), particulate organic carbon (POC), and their sum generally increased with elevation. However, the MAOC/POC ratio followed a unimodal pattern, suggesting greater stability of the SOC pool in the mid-elevation regions. This unimodal pattern was likely influenced by the abundance of Actinobacteria and genes encoding GTs and carbohydrate esterases (CEs) and threshold effects of EC and MAT. In summary, our findings indicate that the distribution patterns of microbial communities and C-cycling functional genes along the elevational gradient in an arid ecosystem are distinct from those of regions with higher MAP, facilitating the prediction of climate change effects on SOC metabolism under more arid conditions. Soil salinity, plant diversity, precipitation, and temperature are the main regulatory factors of microbial C metabolism processes, and they potentially play a central role in mediating SOC pool stability.

Space-time mapping of soil organic carbon stock and its local drivers: Potential for use in carbon accounting

The measurement and tracking of changes in soil organic carbon (SOC) stocks and its underpinning drivers are important in greenhouse gas accounting and carbon trading schemes. While repeated direct measurement of a location over time is the ‘gold standard’ for SOC stock change estimation, this is currently unfeasible at scale due to sample collection and analysis costs. Here, we used a data-driven, space–time digital soil mapping modelling approach (ST-DSM) coupled with an interpretive machine learning (IML) technique to both predict and quantify the relative contributions of covariates to annual SOC stocks and their uncertainty at 0–30 cm depth and at a 90 m spatial resolution for Australia between 1990 and 2018. A quantile regression forest model was calibrated using data from a datacube comprising of SOC stock values collected over the prediction years and a suite of dynamic and static environmental covariates. The evaluation of the ST-DSM model on a test set was satisfactory. Long-term annual mean (Mg C/ha), and total (Pg C) topsoil SOC stock were 37.6 (12.3 – 101.1, 90 % PI) and 28.3 (9.25 – 83.1, 90 % PI) respectively. The mean annual rate of SOC stock change over the Australian continent was 0.11 (±0.22) Mg C/ha yr−1 and the total net change was 23.5 Tg C yr−1, indicating Australia’s soils were a net sink of SOC over the 29-year period. However, SOC stocks declined in the montane ecoregion, a great concern given its fragility and high SOC stock. The long-term mean fraction of photosynthetic vegetation was the most important individual local contributor to SOC stock prediction in many parts of Australia. The aggregated effect of covariates based on the soil forming factors indicates vegetation as the principal local driver of SOC stock across most of the Australian continent, followed by climate. The evaluation of our results against independent, temporally paired field data and estimates from a nationally accepted SOC process-based model yielded promising results. Our approach demonstrates the use of readily available and inexpensive covariates to estimate SOC stock changes, as well as the underlying drivers over a larger area but at a spatial resolution suitable for decision making. This approach presents a new monitoring and verification possibility for carbon projects and national carbon accounting especially with the growing number of existing profile observations in soil databases.

Net global warming potential index rather than soil carbon stock change could provide better understanding of the carbon balance in soil systems.

This study was conducted to determine the soil organic carbon (SOC) stock change factor for green manure crops that was developed by the Intergovernmental Panel on Climate Change (IPCC) Tier 2 method and compare this with the net global warming potential (GWP) index that is used to evaluate the contribution of green manuring to global warming. Four treatments were barley (Hordeum vulgare L.; B), hairy vetch (Vicia villosa R.; HV), a barley/hairy vetch mixture (BHV) and a conventional treatment (C). The aboveground biomass of green manure crops was incorporated into the soil on 25 May 2018, 26 April 2019, 29 April 2020, 30 April 2021 and 2 May 2022. Maize (Zea mays L.) was transplanted as the subsequent crop after the incorporation of green manures. SOC stock decreased with green manures, even though carbon input with green manures, including B, HV and BHV, was greater than that with C. The mean value of the SOC stock change factor for green manure crops, including B, HV and BHV was 0.627 and was significantly lower than that of the C. However, the net GWP also decreased with the incorporation of green manure crops, and the mean value of the relative net GWP index across B, HV and BHV was 0.853. These conflicting results were caused by different estimation methods between annual SOC change (△SOC) and net GWP. The estimation of SOC stock change using △SOC suggested by the IPCC method may overestimate the contribution of green manure crops to global warming. The net GWP method with comprehensive input and output of carbon in the soil system could provide a better understanding of the carbon balance in soil systems. In the current study, the comparison of △SOC and net GWP was conducted for at one site of upland soil for 5years. Therefore, further research on estimating the effect of green manure crops on net GWP in various types of soil for longer years should be conducted.

Changes in soil organic carbon stocks and its physical fractions along an elevation in a subtropical mountain forest

Soil microorganisms are the drivers of soil organic carbon (SOC) mineralization, and the activities of these microorganisms are considered to play a key role in SOC dynamics. However, studies of the relationship between soil microbial carbon metabolism and SOC stocks are rare, especially in different physical fractions (e.g., particulate organic carbon (POC) fraction and mineral-associated organic carbon (MAOC) fraction). In this study, we investigated the changing patterns of SOC stocks, POC stocks, MAOC stocks and microbial carbon metabolism (e.g., microbial growth, carbon use efficiency and biomass turnover time) at 0–20 cm along an elevational gradient in a subtropical mountain forest ecosystem. Our results showed that SOC and POC stocks increased but MAOC stocks remained stable along the elevational gradient. Soil microbial growth increased while microbial turnover time decreased with elevation. Using structural equation modeling, we found that heightened microbial growth is associated with elevated POC stocks. Moreover, MAOC stocks positively correlate with microbial growth but show negative associations with both POC stocks and soil pH. Overall, the increase in SOC stocks along the elevational gradient is primarily driven by changes in POC stocks rather than MAOC stocks. These findings underscore the importance of considering diverse soil carbon fractions and microbial activities in predicting SOC responses to elevation, offering insights into potential climate change feedbacks.

Changes in Soil Organic Carbon Stocks Due to Land Use Changes in the Extended São Francisco River Basin

As the largest carbon reservoir in terrestrial ecosystems, soils play a critical role in food production, mitigation and adaption to climate change, and sustainability of agroecosystems. In this context, the aim of this study is to estimate variations in soil carbon stocks resulting from land use and management changes in different biomes that compose the Bacia Estendida do Rio São Francisco (BESF - Extended São Francisco River Basin), between 1985 and 2017. For this, remote sensing data and information from the IBGE agriculture and livestock census were used, in addition to emission factors to estimate soil organic carbon (SOC) changes. The results indicate that BESF had about 5.70 million ha degraded in the analyzed period, in addition to an increase of 0.72 Tg C year-1 in SOC stocks. The sub-medium São Francisco River basin recorded the highest SOC gain, with an increase of 0.54 Tg C ha-1; on the other hand, the sub-medium São Francisco River sub-basin had the greatest SOC losses, with an estimated reduction of 0.07 Tg C year-1. In short, this study provides important evidence on changes in SOC stocks in the region, emphasizing the importance of native vegetation conversion to agriculture and livestock systems under sustainable soil management for mitigating greenhouse gas emissions and maintaining soil quality.

Impact of future climate warming on soil organic carbon stocks in Inner Mongolia, China

Accurate assessment on temporal and spatial changes in soil organic carbon stocks (SOCS) is essential for evaluating the potential of soil carbon sequestration and formulating effective strategies to mitigate climate change. While most SOCS studies have focused on topsoil, there remains a lack of comprehensive understanding regarding the vertical distribution of SOCS within soil profiles. Furthermore, the key environmental variables influencing deep SOCS are still not fully comprehended. In this study, we employed an integrated approach combining equal-area spline function, boosted regression trees model (BRT), and the space-for-time substitution method to accurately model the three-dimensional distribution of SOCS in response to climate warming in Inner Mongolia, China. A total of 12 environmental variables (generated from climate, topography, biological, and soil property factor) and 208 soil profile data were selected to construct the model. The 10-fold cross-validation technique was employed to assess the predictive performance of the BRT model for soil organic carbon stocks (SOCS) at various depths, using four accuracy validation indicators: root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and Lin's concordance correlation coefficient (LCCC). The results demonstrated the BRT model accurately predicted SOCS with higher LCCC and R2 values, as well as lower RMSE and MAE values. The predicted map revealed higher SOCS concentration in the northeast and lower concentration in the western area. Grassland and forest land were found to store a majority of SOCS, with over 46 % located the topsoil depth of 30 cm. Furthermore, under different climate warming scenarios with temperature increase of 1.5 ℃, 2 ℃ and 4 ℃, there was a corresponding decreased in SOCS by 7 %, 9 % and 17 % respectively at a soil depth. Additionally, this study identified MAT and NDVI as primary environmental variables influencing the spatial distribution of three-dimensional scale SOCS. We believed that accurately predicting and mapping three-dimensional SOCS under different climate warming scenarios will contribute to the development of scientifically sound land management policies aimed at enhancing soil carbon sequestration in the region.