Mean Soil Organic Carbon Stock Research Articles

Relative and absolute difference in soil organic carbon stocks in grassland soils in Ireland: Impact of rock fragments, bulk density and calculation methods

On-farm management measures can sequester carbon by removing carbon dioxide from the atmosphere and storing it securely for long periods, in our soils. Estimates of soil organic carbon (SOC) stocks differ by calculation methods in terms of how they account for the coarse >2 mm fraction (i.e. rock fragments) of the soil. Irish grassland soils have variable volumetric stone contents and the extent of overestimation is unknown. Without best practice guidance, calculations of SOC in these soils are vulnerable to overestimation. The objectives of the present study for grassland soils in Ireland were to: 1) calculate mean SOC stocks using different methods by soil horizon and volumetric stone content class; 2) highlight relative differences in SOC stocks between these calculation methods and 3) compare normalised layer (Ly, fixed depth) versus horizon (Hz) type derived sampling data in terms of SOC stocks, to establish a best practice standardised sampling protocol. Five methods (M, 1–3 overestimate SOC stocks, whereas 4–5 are equivalent and are closest to reality) to calculate SOC stocks were used in combination with three soil databases i.e. Irish Soil Information System (I-SIS), the Heavy Soils Programme (HSP) and the Soil Quality Assessment Research Project (SQUARE). Objectives 1 and 2 were assessed using all three databases across methods, whereas objective 3 used the SQUARE database and M4. These data were sorted into volumetric stone content (%) classes (< 5%, 5–10%, 10–20%, 20–30% and > 30%) and sampling horizon (O, A, E, A/B, B, B/C, and C) with SOC stocks calculated using M1–5 equations. Results confirmed the high volumetric stone content assumption of grassland soils in Ireland (exception O horizons). Volumetric stone contents ranged from 0% to 36% for all horizons. When M1–5 are considered the average relative difference in SOC stocks between M1 and M5 was 18.9% (max: 388%), M2 and M5 was 7.7% (max: 60.7%) and M3 and M5 was 8.9 (max: 310%). In terms of Ly versus Hz sampling, no significant differences were found for the A horizons sampled. However, in Ireland, best practice should still utilise elements from both Ly (using an auger to get fixed depth soil samples; analysed for organic C) and Hz (using a soil profile pit to extract representative BD cores and to gather bulk samples for volumetric stone content analysis) approaches in the field. Laboratory methods used must fit with the needs and assumptions of equations M4/5 to calculate SOC stocks (thereby minimising overestimation and indeed underestimation).

Soil organic carbon stocks in native forest of Argentina: a useful surrogate for mitigation and conservation planning under climate variability

BackgroundThe nationally determined contribution (NDC) presented by Argentina within the framework of the Paris Agreement is aligned with the decisions made in the context of the United Nations Framework Convention on Climate Change (UNFCCC) on the reduction of emissions derived from deforestation and forest degradation, as well as forest carbon conservation (REDD+). In addition, climate change constitutes one of the greatest threats to forest biodiversity and ecosystem services. However, the soil organic carbon (SOC) stocks of native forests have not been incorporated into the Forest Reference Emission Levels calculations and for conservation planning under climate variability due to a lack of information. The objectives of this study were: (i) to model SOC stocks to 30 cm of native forests at a national scale using climatic, topographic and vegetation as predictor variables, and (ii) to relate SOC stocks with spatial–temporal remotely sensed indices to determine biodiversity conservation concerns due to threats from high inter-annual climate variability.MethodsWe used 1040 forest soil samples (0–30 cm) to generate spatially explicit estimates of SOC native forests in Argentina at a spatial resolution of approximately 200 m. We selected 52 potential predictive environmental covariates, which represent key factors for the spatial distribution of SOC. All covariate maps were uploaded to the Google Earth Engine cloud-based computing platform for subsequent modelling. To determine the biodiversity threats from high inter-annual climate variability, we employed the spatial–temporal satellite-derived indices based on Enhanced Vegetation Index (EVI) and land surface temperature (LST) images from Landsat imagery.ResultsSOC model (0–30 cm depth) prediction accounted for 69% of the variation of this soil property across the whole native forest coverage in Argentina. Total mean SOC stock reached 2.81 Pg C (2.71–2.84 Pg C with a probability of 90%) for a total area of 460,790 km2, where Chaco forests represented 58.4% of total SOC stored, followed by Andean Patagonian forests (16.7%) and Espinal forests (10.0%). SOC stock model was fitted as a function of regional climate, which greatly influenced forest ecosystems, including precipitation (annual mean precipitation and precipitation of warmest quarter) and temperature (day land surface temperature, seasonality, maximum temperature of warmest month, month of maximum temperature, night land surface temperature, and monthly minimum temperature). Biodiversity was influenced by the SOC levels and the forest regions.ConclusionsIn the framework of the Kyoto Protocol and REDD+, information derived in the present work from the estimate of SOC in native forests can be incorporated into the annual National Inventory Report of Argentina to assist forest management proposals. It also gives insight into how native forests can be more resilient to reduce the impact of biodiversity loss.

Carbon Stocks and Potential Greenhouse Gas Production of Permafrost‐Affected Active Floodplains in the Lena River Delta

AbstractArctic warming increases the degradation of permafrost soils but little is known about floodplain soils in the permafrost region. This study quantifies soil organic carbon (SOC) and soil nitrogen stocks, and the potential CH4 and CO2 production from seven cores in the active floodplains in the Lena River Delta, Russia. The soils were sandy but highly heterogeneous, containing deep, organic rich deposits with &gt;60% SOC stored below 30 cm. The mean SOC stocks in the top 1 m were 12.9 ± 6.0 kg C m−2. Grain size analysis and radiocarbon ages indicated highly dynamic environments with sediment re‐working. Potential CH4 and CO2 production from active floodplains was assessed using a 1‐year incubation at 20°C under aerobic and anaerobic conditions. Cumulative aerobic CO2 production mineralized a mean 4.6 ± 2.8% of initial SOC. The mean cumulative aerobic:anaerobic C production ratio was 2.3 ± 0.9. Anaerobic CH4 production comprised 50 ± 9% of anaerobic C mineralization; rates were comparable or exceeded those for permafrost region organic soils. Potential C production from the incubations was correlated with total organic carbon and varied strongly over space (among cores) and depth (active layer vs. permafrost). This study provides valuable information on the carbon cycle dynamics from active floodplains in the Lena River Delta and highlights the key spatial variability, both among sites and with depth, and the need to include these dynamic permafrost environments in future estimates of the permafrost carbon‐climate feedback.

Effects of different tillage and residue management systems on soil organic carbon stock and grain yield of rice–wheat double cropping system

Of late, intensive agricultural practices are often associated with many negative implications for soil systems, such as decline in soil organic matter and biological diversity, and increase in the risk of soil erosion, and degradation of soil physical quality. However, conservation agriculture (CA) offers minimum soil disturbance, improving and creating more efficient use of natural resources, enhancing use efficiency of external inputs and increasing soil functioning, organic matter content, and biodiversity. However, CA practices need to be redefined at the specific field level or growing conditions to promote sustainable production system without deteriorating soil health, and to manage profitability. Therefore, a fixed-site field experiment was conducted to evaluate the effects of different tillage and residue management practices; CT0 (puddled transplanted rice followed by conventional tilled wheat sown with residue removal); CTR (puddled transplanted rice followed by conventional tilled wheat sown with residue retention); NT0 (direct seeded rice followed by zero-tilled wheat sown with residue removal); NTR (direct seeded rice followed by zero-tilled wheat sown with residue retention) on soil organic carbon (SOC) stock and grain yield of rice–wheat double cropping system. The results showed that the mean SOC stock increased by 31%, 21.9% and 15.3% and by 35.2%, 22% and 17% under NTR, CTR, and NT0 compared with CT0. Furthermore, the SOC sequestration rate in NTR was significantly higher than other treatments. Particulate organic carbon (POC) concentration was 58.4% higher in 0–15 cm than 15–30 cm soil layer, and the maximum concentration was recorded under NTR and minimum was under CT0. The highest average rice grain yield was recorded under CTR, which was 5.5%, 16.2% and 24.3% higher than CT0, NTR and NT0, respectively. Both NTR and CTR produced more average wheat yield, which was 8.4% and 8.5% higher than CT0 and NT0, respectively. Principal component analysis (PCA) also showed that cumulative cropping system yield and SOC were increased under CTR, NTR as compared to other treatments. Therefore, it can be drawn that residue retention could be a useful management practice to increase SOC stock and grain yield under both tillage practices in the rice–wheat cropping system.

Evaluation and mapping soil organic carbon in seasonally frozen ground on the Tibetan Plateau

Seasonally frozen ground (SFG) significantly contributes to global carbon sinks. Global warming and anthropogenic-induced disturbances threaten the carbon storage capacity of SFG. Challenges in evaluating the SFG carbon storage potential include the lack of understanding of the control mechanisms of soil organic carbon (SOC) variations and timely spatial estimates of SOC. In this study, we investigated SOC stocks in SFG in the Tibet Autonomous Region, China, in 2020 and 2021. We employed partial least squares structural equation modeling (PLS-SEM) to explore the effect of complex processes (interacting roles of climate, plant physiology and phenology, freeze–thaw cycle, soil environment, and C inputs) on SOC and mapped SOC stocks in the topmost 30 cm. We identified four causal pathways: (1) an indirect pathway representing the effect of climate on plant physiology and phenology through changes in freeze–thaw cycles and soil environment, (2) an indirect pathway representing the effect of climate on C inputs through changes in freeze–thaw cycles, soil environment and plant physiology and phenology, (3) an indirect pathway representing the effect of climate on freeze–thaw cycles, and (4) an indirect pathway representing the effect of climate on the soil environment through changes in freeze–thaw cycles. C inputs exerted the greatest control on SOC. The effect of these factors decreased with increasing soil depth. We used PLS-SEM to generate maps of SOC stocks in SFG at a 500 m resolution with a moderate accuracy. The estimated mean SOC stocks in the 0–30 cm layer reached 6.87 kg m−2, with a 95% confidence interval ranging from 6.2 to 7.5 kg m−2. Our results indicated that it is critical to consider the depth dependence of the direct and indirect effects of environmental factors when assessing the control mechanisms of SOC variations. In this work, we also demonstrated that spatially explicit SOC estimates based on timely investigations are important for assessing C stocks against the background of considerable environmental changes across the Tibetan Plateau.

Changes in soil properties with long-term organic inputs due to distance from homestead and farm characteristics in southern Ethiopian farmlands

Traditional farming systems across much of Sub-Saharan Africa have greater organic inputs near to the homestead than in fields further away. This is likely to produce a fertility gradient that impacts production capacity, and so provides an opportunity to explore impacts of organic amendments on soils. Across 198 farm plots in 69 households in Halaba, Southern Ethiopia, we investigated the influence of different organic input systems on soil properties. The study also examined the influence of household and farm characteristics on the adoption of land management practices and its impact on soil properties. Samples were taken from farm plots located close (<30 m), near (30–300 m) and far (>300 m) from the homestead, representing different levels of organic amendments. Soils located close to homesteads had significantly greater soil organic carbon, cation exchange capacity and soil nutrient content compared to soil located near and far from the homestead areas. Soil organic carbon concentrations close to the home were 15%, 27% and 45% greater than farm plots located at far from the home in Andegna Choroko, Asore and Lay Arisho kebeles, respectively. Across all sites, the mean soil organic carbon stock ranged from 20.6 t ha−1 to 84.6 t ha−1, depending on the location of the plots with respect to the homestead. Household and farm characteristics also influenced land management practices and soil properties. In some catchments, farm plots managed by female headed households and relatively rich farmers displayed significantly greater soil organic carbon than farm plots managed by male headed and relatively poor households. This was likely due to greater organic inputs in female headed households in areas where men were otherwise engaged in off-farm activities and in wealthier households with greater access to organic manures. Tree cover in farmlands influenced accumulation of soil organic carbon. The results suggest that out-scaling farm management practices that are common around homesteads, such as adding animal manure or household wastes and maintaining tree cover, would help to improve key soil properties and agricultural productivity.

Woody species diversity and carbon stock potentials in homegarden agroforestry and other land use systems, northern Ethiopia

Homegarden agroforestry (HGAF) provides wider ecosystem services in the agricultural landscapes in the tropics. However, the potentials of the homegardens for floristic species conservation and climate change mitigation were less empahsized. The present study was designed to investigate woody species diversity, carbon stock, and the relationships between woody plant species and carbon stock in the HGAF and other land use types. Three land use types were purposively selected, totalling 60 nested sample plots. The stand structure and woody plant species diversity were determined. Biomass carbon stocks were estimated employing appropriate allometric equations. Soil Organic Carbon (SOC) stocks (at 0–30 and 30–60 cm layers) were calculated. The result of the study showed a total of 38 woody plant species recorded from both HGAF and exclosures, but no report from cropland. The abundance, basal area, stem density, species richness, and Shannon and Simpson diversity indices were significantly higher in the HGAF than in exclosures. The mean SOC stock was the highest in HGs (122.13 ± 19.12 Mg ha-1). The estimated mean total ecosystem carbon stock of HGAF, cropland, and exclosure was 171.17 ± 37.25, 78.06 ± 11.97, and 92.5 ± 17.33 Mg ha-1, respectively, which was statistically significant among land use types. A positively significant correlation was observed between diversity, richness, and abundance of woody species and carbon stocks both in the HGAF and exclosure land use systems. The current study confirmed that increased woody species diversity in HGAF enhanced carbon sequestration. The HGAF land use in the northern parts of the country is scanty as compared to the southern part, where there is a rich woody species diversity. Therefore, it is recommendable to promote HGAF across agricultural landscapes of the study area, which enhances biodiversity conservation and mitigation of climate change impacts.

Limitations of farm management data in analyses of decadal changes in SOC stocks in the Danish soil‐monitoring network

AbstractChanges in soil organic carbon (SOC) storage in agricultural land are an important part of the Land Use, Land‐Use Change and Forestry component of national greenhouse gas emission inventories. Furthermore, as climate mitigation strategies and incentives for carbon farming are being developed, accurate estimates of SOC stocks are essential to verify any management‐induced changes in SOC. Based on agricultural mineral soils in the Danish soil‐monitoring network, we analysed management effects on SOC stocks using data from the two most recent surveys (2009 and 2019). Between 2009 and 2019, the average increase in SOC stock was 1.2 Mg C ha−1 for 0–50 cm despite a loss of 1.2 Mg C ha−1 from the topsoil (0–25 cm), stressing the importance of including deeper soil layers in soil‐monitoring networks. Comparing all four national surveys (1986, 1997, 2009, 2019), the mean SOC stock of mineral soils in Denmark appears stable. The change in SOC stock between 2009 and 2019 was analysed in detail in relation to management practices as reported by farmers. We found that the effects of single management factors were difficult to isolate from co‐varying factors including soil parameters and that the use of farm management data to explain changes in SOC stocks observed in soil‐monitoring networks appears limited. Uncertainty in SOC stock estimates also arises from low sampling frequency and statistical challenges related to regression to the mean. However, repeated stock measurements at decadal intervals still represent a benchmark for the overall development in regional and national SOC storage, as affected by actual farm management.

Improvement of spatial estimation for soil organic carbon stocks in Yuksekova plain using Sentinel 2 imagery and gradient descent-boosted regression tree.

Carbon sequestration in earth surface is higher than the atmosphere, and the amount of carbon stored in wetlands is much greater than all other land surfaces. The purpose of this study was to estimate soil organic carbon stocks (SOCS) and investigate spatial distribution pattern of Yuksekova wetlands and surrounding lands in Hakkari province of Turkey using machine learning and remote sensing data. Disturbed and undisturbed soil samples were collected from 10-cm depth in 50 locations differed with land use and land cover. Vegetation, soil, and moisture indices were calculated using Sentinel 2 Multispectral Sensor Instrument (MSI) data. Significant correlations (p≤0.01) were obtained between the indices and SOCS; thus, the remote sensing indices (ARVI 0.43, BI -0.43, GSI -0.39, GNDI 0.44, NDVI 0.44, NDWI 0.38, and SRCI 0.51) were used as covariates in multi-layer perceptron neural network (MLP) and gradient descent-boosted regression tree (GBDT) machine learning models. Mean absolute error, root mean square error, and mean absolute percentage error were 3.94 (Mg C ha -1), 6.64 (Mg C ha-1), and 9.97%, respectively. The simple ratio clay index (SRCI), which represents the soil texture, was the most important factor in the SOCS estimation variance. In addition, the relationship between SRCI and Topsoil Grain Size Index revealed that topsoil clay content is a highly important parameter in spatial variation of SOCS. The spatial SOCS values obtained using the GBDT model and the mean SOCS values of the CORINE land cover classes were significantly different. The land cover has a significant effect on SOC in Yuksekova plain. The mean SOCS for continuously ponded fields was 45.58 Mg C ha-1, which was significantly different from the mean SOCS of arable lands. The mean SOCS in arable lands, with significant areas of natural vegetation, was 50.22 Mg C ha-1 and this amount was significantly higher from the SOCS of other land covers (p<0.01). The wetlands had the highest SOCS (61.46 Mg C ha-1), followed by the lands principally occupied by natural vegetation and used as rangelands around the wetland (50.22 Mg C ha-1). Environmental conditions had significant effect on SOCS in the study area. The use of remote sensing indices instead of using single bands as estimators in the GBDT algorithm minimized radiometric errors, and reliable spatial SOCS information was obtained by using the estimators. Therefore, the spatial estimation of SOCS can be successfully determined with up-to-date machine learning algorithms only using remote sensing predictor variables. Reliable estimation of SOCS in wetlands and surrounding lands can help understand policy and decision makers the importance of wetlands in mitigating the negative impacts of global warming.

Modeling and mapping spatial distribution of baseline soil organic carbon stock, a case of West Hararghe, Oromia Regional State, Eastern Ethiopia

ABSTRACT Location-specific information on soil organic carbon (SOC) helps to identify potential sources and sinks of carbon. The objective of this study was to produce a 30m-resolution digital map of SOC stock for selected districts in West Hararghe Zone of Ethiopia. 148 soil samples(0-30cm) were collected for SOC analysis and BD estimation. Eighteen environmental covariates were acquired from satellite sources, digital elevation model (DEM), and maps. A random forest model was fitted to the data. The accuracy of the prediction was tested using the 10-fold cross-validation method. The model explained 36% of the variance (R2) with a root mean square error of 9.51. The most relevant predictors were normalized difference vegetation index (NDVI), temperature, and elevation. The predicted total SOC stock value was 240.5TgC and ranged between 17.91 and 70.16 t/ha, with a mean of 38.82 t/ha. The soils under agricultural land had a higher amount of carbon than forestland. The mean SOC stock was relatively higher in fine-textured soils and lower in soils, which are dominantly found in drier areas. This study could help provide information on a less expensive method of SOC stock estimation. In addition, the study produced an updatable baseline SOC stock map.

The size of clearings for charcoal production in miombo woodlands affects soil hydrological properties and soil organic carbon

Charcoal production is a major driver of forest degradation in miombo woodlands. Forests play a crucial role in regulating the hydrological cycle, so it is critical to understand how forest degradation and management practices impact water availability, particularly in drylands. Few studies have examined the effect of forest clearing size on the hydrological functioning of soil, particularly under real-world conditions where, following clearing, forests are subject to multiple and prolonged anthropogenic disturbances, as occurs in miombo woodlands which are cleared for charcoal production and commonly used for livestock grazing. The pilot project Transforming Tanzania's Charcoal Sector was established in 2012 with the aim of establishing a sustainable wood harvesting system for charcoal production based on rotational harvesting cycles that allow for natural forest regeneration. Two clearing sizes were established: large clearings (300 × 300 m) harvested by clear-felling, and small clearings (50 × 50 m) harvested in a checkerboard pattern. We examined the effect of these two clearing sizes on soil hydrological properties and soil organic carbon (SOC) in Kilosa district, Morogoro, Tanzania. Our analysis included four treatments: large clearings, small clearings, small intact plots (unharvested plots within the checkboard pattern), and village land forest reserve. For each treatment we assessed the tree cover and measured soil infiltration capacity, soil bulk density, SOC stock, and texture. We also examined the relationship between these variables and the distance to the closest road to better understand the impact of livestock and human disturbance. Our results show that large clearings had the lowest mean infiltration capacity (121 ± 3 mm h−1) and SOC stock content (12 ± 0.2 tonnes ha−1), and the highest bulk density (1.6 ± 0.005 g cm−3) of all the treatments. We found a positive relationship between infiltration capacity and basal area (R2 = 0.71) across all treatments. We also found that infiltration capacity, SOC stock and tree basal area increased with increasing distance from the closest road, while bulk density decreased. We conclude that, in terms of their impact on soil hydrological functioning and SOC stock, small clearings, while not completely unaffected, are better than larger ones. In small clearings, concurrent reductions in tree cover and a relatively low impact on soil hydrological properties could result in increased soil and groundwater recharge compared to unharvested forest areas. Controlling livestock grazing can further minimize soil degradation, producing additional gains.

Crop intensification effects on soil quality and organic carbon stocks: a case study of Haramosh Valley in Central Karakorum, Pakistan

ABSTRACT Agricultural operations such as excessive tillage and intense cropping deplete soil organic carbon (SOC), making sustainable agriculture management critical for reducing greenhouse gas (GHG) emissions. This study evaluates the impact of crop intensification on soil quality and soil organic carbon stocks (SOCS) under double cropping (DC) and single cropping pattern (SC) in upper Haramosh of Gilgit, Pakistan. Soil samples were taken from cropping zones (DC and SC) under three depths (0–20, 20–40, and 40–60 cm). Standard methods were used to analyze selected soil quality parameters and SOC. Statistical analysis using ANOVA showed that soil temperature, moisture, pH, SOC, and SOCS highly significantly differed (p < 0.001) for different cropping patterns (DC and SC), whereas bulk density (BD), electrical conductivity (EC), and clay were not significantly different. The SC retained 4.4% more moisture and had lower BD than the DC, while BD increased with increasing depth. The texture of the soil was sandy loam at both cropping zones. The mean SOC and SOCS of SC were greater (by 12%) than in the DC zone. Pearson correlation showed a significant and positive correlation of SOC stock with SOC, moisture (p < 0.01), and EC (p < 0.05), but had a negative correlation with bulk density, pH (p < 0.01), and sand (p < 0.05). DC apparently degraded soil quality and organic carbon reserves, thus reducing the soil health in mountain agriculture.

Soil organic carbon estimation along an altitudinal gradient of chir pine forests in the Garhwal Himalaya, India: A field inventory to remote sensing approach

AbstractChir pine (Pinus roxburghii, Sarg.) forests are dominant in the Indian Himalayan region and act as a huge carbon (C) sink. However, measuring the C sink in soil is complex and time‐intensive, and therefore the present study attempts to estimate the soil organic carbon (SOC) through a remote sensing (RS) approach. We estimated SOC stock of chir pine forests along an altitudinal gradient at three soil depths (0–30, 30–60 and 60–100 cm) in the Garhwal Himalaya, Uttarakhand. Fourteen forest stands at four altitudes, viz., &lt;1000 m above sea level (m asl), 1001–1400 m asl, 1401–1800 m asl and &gt;1801 m asl were surveyed and served for data collection. A model for predicting SOC was developed through stepwise regression analysis based on vegetation information and altitude as independent variables with the field data on SOC. For vegetation information, we used the normalized difference vegetation index (NDVI) measured through remote sensing (RS). The mean SOC stock up to 100 cm depth was increased with increasing altitude and were in the order of 69.66 ± 19.86, 85.27 ± 17.53, 95.68 ± 7.90 and 148.41 ± 71.39 million g ha−1 (million gram per hectare) for &lt;1000, 1001–1400, 1401–1800 and &gt;1801 m_asl, respectively. The result showed that NDVI was a good predictor for SOC estimation. The model predicted SOC stock between 57 and 152 million g ha−1 with a mean of 93 million g ha−1, which was close to the SOCs from field inventory. Therefore, RS could be used to precisely map the SOC stock in the chir pine forests of the Himalayas through NDVI and provide information to policymakers for forest management.

Uncertainties of soil organic carbon stock estimation caused by paleoclimate and human footprint on the Qinghai Plateau

BackgroundQuantifying the stock of soil organic carbon (SOC) and evaluating its potential impact factors is important to evaluating global climate change. Human disturbances and past climate are known to influence the rates of carbon fixation, soil physiochemical properties, soil microbial diversity and plant functional traits, which ultimately affect the current SOC storage. However, whether and how the paleoclimate and human disturbances affect the distribution of SOC storage on the high-altitude Tibetan Plateau remain largely unknown. Here, we took the Qinghai Plateau, the main component of the Tibetan Plateau, as our study region and applied three machine learning models (random forest, gradient boosting machine and support vector machine) to estimate the spatial and vertical distributions of the SOC stock and then evaluated the effects of the paleoclimate during the Last Glacial Maximum and the mid-Holocene periods as well as the human footprint on SOC stock at 0 to 200 cm depth by synthesizing 827 soil observations and 71 environmental factors.ResultsOur results indicate that the vegetation and modern climate are the determinant factors of SOC stocks, while paleoclimate (i.e., paleotemperature and paleoprecipitation) is more important than modern temperature, modern precipitation and the human footprint in shaping current SOC stock distributions. Specifically, the SOC stock was deeply underestimated in near natural ecosystems and overestimated in the strongly human disturbance ecosystems if the model did not consider the paleoclimate. Overall, the total SOC stock of the Qinghai Plateau was underestimated by 4.69%, 12.25% and 6.67% at depths of 0 to 100 cm, 100 to 200 cm and 0 to 200 cm, respectively. In addition, the human footprint had a weak influence on the distributions of the SOC stock. We finally estimated that the total and mean SOC stock at 200 cm depth by including the paleoclimate effects was 11.36 Pg C and 16.31 kg C m−2, respectively, and nearly 40% SOC was distributed in the top 30 cm.ConclusionThe paleoclimate is relatively important for the accurate modeling of current SOC stocks. Overall, our study provides a benchmark for predicting SOC stock patterns at depth and emphasizes that terrestrial carbon cycle models should incorporate information on how the paleoclimate has influenced SOC stocks.

Estimating soil organic carbon and nitrogen stock based on high-resolution soil databases in a subtropical agricultural area of China

Quantifying soil organic carbon stock (SOCS) and total nitrogen stock (STNS) of the agriculture soils in China is crucial for predicting the future of global climate change and planning agricultural management practices. However, most of existing studies were based on relatively coarse soil databases, leading to large discrepancies in the SOC and STN estimates. The present study was conducted in Changting County of Fujian Province in China, covering an area of 29,375ha. A high-resolution soil database at a county-scale of 1:10,000 was employed to analyze the SOC density (SOCD) and STN density (STND) under different soil groups and land use types. Results indicated that the mean SOCD and SOCS for the surface layer (0–15 cm) were 2.93 ± 0.38 kg C m−2 and 861 Gg, respectively, and those for STND and STNS were 0.37 ± 0.06 kg N m−2 and 108 Gg, respectively. The SOCD and STND showed significant disparities among soil groups and land use types. We also compared the SOCD, SOCS, STND and STNS estimated from a coarser 1:1000,000 soil database, which was the most detailed soil database at the national scale, with the estimates in this study. The relative deviations in estimating SOCD and STND by soil groups from the coarser database were 8.1% and 60.6%, respectively, which could be primarily attributed to the assignment errors of soil attributes and polygon area variations in the coarse-scale soil database. Moreover, we found that the dominant factors determining SOCD were topographic and climatic factors (e.g. elevation and mean annual precipitation), while farming practices (e.g. N fertilizer application and irrigation conditions) as well as elevation were more important for STN estimates. Further, the deviations of STN estimates from the coarse- and fine-scale soil database were higher than those of the SOC estimates because: (1) The topographic and climatic factors had slight effects on STND from coarse- and fine-scale soil database while significantly affected SOCD; and (2) STN estimates tended to be more easily influenced by anthropic farming practices (e.g. significant irrigation conditions and N fertilization application) in the coarse-scale database than that in the fine-scale database. Therefore, a high-resolution soil database may improve the accuracy of SOC and STN assessment, especially for STN assessment, and the application of finer soil databases is a critical step for estimating SOCS and STNS at national and even global levels, and thus for accurately assessing regional C budget.

Soil organic carbon stocks and stability of organic matter in permafrost-affected soils of Yamal region, Russian Arctic

Chemical composition of soil organic matter determines its decomposability and may affect soil microbial activity. This is very important for understanding variability in soil organic carbon pools in context of changes in plant cover or climate. This paper is aimed to characterize existing carbon pools and molecular organization of the humic acids, isolated from various permafrost-affected soils of Yamal region and to assess the potential vulnerability of soils organic matter in context of possible mineralization processes. Soils for most of studied sites were characterized predominantly by acidic to strong acidic pH. Profile distribution of carbon, nitrogen and C:N ratio showed non-gradual changing with the depth due to manifestation of cryopedogenesis in soil profiles which lead to cryogenic mass transfer. Mean soil organic carbon stocks for the study area were 7.9 ± 2.2 kg m−2 (for 0–10 cm layer), 15.0 ± 5.5 kg m−2 (for 0–30 cm), 24.0 ± 8.0 kg m−2 (for 0–100 cm). Analysis of soil organic carbon stocks among predominant soil types (Russian soil classification system) revealed relatively high variability of values in 0–10 cm (from 4.5 kg m−2 in Peaty Gleyzem underlain by permafrost to 9.6 kg m−2 in Peaty Podzol underlain by permafrost) and 0–30 cm layers (from 9.9 kg m-2 in Cryic Podbur underlain by permafrost to 24.1 kg m−2 in eutrophic peat soil underlain by permafrost). Results of solid-state 13C NMR spectrometry showed low amounts of aromatic fragments in studied soils. All studied soils are characterized by predominance of aliphatic structures, and also carbohydrates, polysaccharides, ethers and amino acids. High content of aliphatic fragments in studied humic acids shows their similarity fulvic acids. Low level of aromaticity reflects the accumulation in soil of poorly decomposed organic matter due to cold temperatures. Our results provide further evidence of high vulnerability and sensitivity of permafrost-affected soils organic matter to Arctic warming. Consequently, these soils may play a crucial role in global carbon balance under effects of climate warming.

High‐yielding forage grass cultivars increase root biomass and soil organic carbon stocks compared with mixed‐species permanent pasture in temperate soil

AbstractAgricultural grass cultivars bred for increased forage yield commonly have extensive root systems. As roots are an important input of organic matter into the soil, it follows that such cultivars could lead to important increases in soil organic carbon (SOC), but this, and the mechanisms involved, are poorly understood with little empirical field evidence. We assessed the effect of two cultivars, Lolium perenne L. cv. “AberMagic” and L. perenne L. × Festuca pratensis Huds. cv. “Prior”, in comparison with mixed‐species permanent pasture (“Pasture”) in a field experiment on temperate alluvial soil in the southwest UK. Root and SOC stocks, and specific plant‐derived lipids as mechanistic biomarkers for shoot and root inputs of C, were measured on intact 1‐m volumetric soil cores collected on four dates in 2013–2015. Total grass yields were greater for both grass cultivars (40–43 Mg ha−1) than Pasture (39 Mg ha−1), and by 2015 root stocks in the upper 0.1 m were significantly greater by more than 4.7 Mg ha−1. At 0.1–0.3 m depth, SOC stocks (per 0.1‐m depth) were significantly greater under the two grass cultivars (24–50 Mg ha−1) compared to Pasture (18–32 Mg ha−1). In the full 1‐m profile, mean SOC stocks were 137, 133 and 110 Mg ha−1 for AberMagic, Prior and Pasture, respectively, matching root biomass distribution. Odd‐chain n‐alkane concentrations were significantly greater for shoots than roots (274 vs. 64 mg kg−1, respectively), and roots had significantly greater concentrations than shoots of even‐chain hydroxy fatty acids (1829 vs. 305 mg kg−1, respectively) and diacids (317 vs. 93 mg kg−1, respectively). This confirmed lipids as candidate biomarkers for distinguishing shoot and root inputs into the soil, with roots being the dominant source of SOC. Based on the observations of increased forage yield and SOC stock, high‐yielding forage grass cultivars can contribute to future strategies for climate‐smart agriculture in grassland‐dominated temperate regions.Highlights Selected root traits for increased depth, density and diameter may increase SOC in grassland. The effect of two high‐yielding forage grass cultivars were assessed in a field trial. Fast‐growing, high‐yielding cultivars enhanced root and SOC stocks compared to typical pasture. Lipid biomarkers confirmed that root inputs were the predominant C input to soil.

Soil Organic Carbon Stocks in Afforested Agricultural Land in Lithuanian Hemiboreal Forest Zone

In the context of the specificity of soil organic carbon (SOC) storage in afforested land, nutrient-poor Arenosols and nutrient-rich Luvisols after afforestation with coniferous and deciduous tree species were studied in comparison to the same soils of croplands and grasslands. This study analysed the changes in SOC stock up to 30 years after afforestation of agricultural land in Lithuania, representing the cool temperate moist climate region of Europe. The SOC stocks were evaluated by applying the paired-site design. The mean mass and SOC stocks of the forest floor in afforested Arenosols increased more than in Luvisols. Almost twice as much forest floor mass was observed in coniferous than in deciduous stands 2–3 decades after afforestation. The mean bulk density of fine (&lt;2 mm) soil in the 0–30 cm mineral topsoil layer of croplands was higher than in afforested sites and grasslands. The clear decreasing trend in mean bulk density due to forest stand age with the lowest values in the 21–30-year-old stands was found in afforested Luvisols. In contrast, the SOC concentrations in the 0–30 cm mineral topsoil layer, especially in Luvisols afforested with coniferous species, showed an increasing trend due to the influence of stand age. The mean SOC values in the 0–30 cm mineral topsoil layer of Arenosols and Luvisols during the 30 years after afforestation did not significantly differ from the adjacent croplands or grasslands. The mean SOC stock slightly increased with the forest stand age in Luvisols; however, the highest mean SOC stock was detected in the grasslands. In the Arenosols, there was higher SOC accumulation in the forest floor with increasing stand age than in the Luvisols, while the proportion of SOC stocks in mineral topsoil layers was similar and more comparable to grasslands. These findings suggest encouragement of afforestation of former agricultural land under the current climate and soil characteristics in the region, but the conversion of perennial grasslands to forest land should be done with caution.

Fire-fallow agriculture as a sustainable cropping system for maintaining organic carbon in Mar\xe9 Loyalty Island (New Caledonia, southwest Pacific)

The Loyalty Islands are part of the French archipelago of New Caledonia in the Southwest Pacific. In these islands, Gibbsic Ferralsols (Humic) are traditionally used for fire-fallow cultivation (FFC) by the Kanak people, but the planting of perennial orchards has been encouraged over the past two decades. The impacts of this policy on soil organic carbon (SOC) are nevertheless unknown, especially in these clay-free soils in which organic matter is the main contributor to soil fertility. SOC and permanganate oxidizable organic carbon (POXC) were studied in the soils of avocado orchards, FFC, and secondary and native forests. Mean SOC stocks are particularly high, ranging between 71.9 and 194.4 MgC ha−1 in an equivalent soil mass of 2000 Mg ha−1, but they are significantly impacted by land use. Avocado farming reduced SOC stocks by about 30% compared to forest soils, even if fields were established on secondary forests that had already experienced SOC losses. In contrast, FFC did not impact them. The POXC content decreased as the degree of soil anthropization increased; however, it was less sensitive than SOC in highlighting the impacts of land use. SOC storage can be achieved through changes in agricultural practices in avocado farming, with support for farmers in transitioning from family farming to perennial cultivation and the policy management of secondary forests designed to enhance the recovery of native forests.

Changing soil organic carbon with land use and management practices in a thousand-year cultivation region

Soil organic carbon (SOC) is a critical mass of global terrestrial carbon store that can be altered by land use and land management practices. As an important grain production area in the Yellow River basin, there have been intensive agricultural activities in the Guanzhong Plain for over 1000 years. The conversion of cropland into orchard and changes in land management practices could have altered the distribution and amount of SOC stores in the region. To determine spatial variations in SOC and its response to changes in land use and land management practices in the thousand-year cultivated region, SOC content was measured at 127 sites, including 117 sites in the 0–100 cm soil layer and 10 sites in the 0–1000 cm soil layer. The results showed a pronounced decline in SOC content with increasing depth in the upper 100 cm soil layer, whereas it was relatively low and stable in deeper soil layers. SOC stock in the 0–100 and 100–1000 cm soil layers accounted for 16.9% and 83.1%, respectively, of the total SOC stock in the 0–1000 cm soil profile. Compared with the 1980s, mean SOC stock in the 0–100 cm soil layer significantly increased (by 0.69 kg m−2) over the 40-year period. Furthermore, no significant difference was observed in SOC content between cropland and orchard land soils for both the 0–100 and 100–1000 cm soil layers. Land management practices (irrigation and fertilization), climatic variables (precipitation and temperature), and soil properties (pH and clay content) together influenced the spatial variations in SOC in the 0–60 cm soil depth. However, variations were dominantly driven by soil properties at depths below 60 cm. Therefore, while SOC in layers below 100 cm was critical for carbon budget estimations, SOC was not altered by changes in agricultural land use in both the shallow and deep soils of the study area. Agricultural management practices, soil properties, and organic carbon storage in deep soils need to be considered in future carbon budget studies in cultivated lands, especially in regions with deep soils.