Regional Soil Organic Carbon Stocks Research Articles

Crop yield increments will enhance soil carbon sequestration in coastal arable lands by 2100

Coastal lands are crucial arable land reserves that play a vital role in ensuring future global food security. In arable coastal lands, low soil quality often results in limited crop yield and soil organic carbon (SOC), making them promising sites for enhancing both soil carbon sequestration and agricultural production. However, a scarcity of long-term site experiments has led to a research gap regarding SOC sequestration in coastal arable lands, leaving potential uncertainties due to variations in planting systems, crop yields, and the influence of climate change. In this study, we focused on the Yellow River Delta (YRD) in China, which is a typical coastal agricultural area. We verified the adaptability of the Denitrifcation-Decomposition (DNDC) model in coastal farmlands based on an 11-year long-term observation experiment and continuous sampling survey data. We further explored the spatiotemporal changes of regional SOC stocks under two Shared Socio-Economic Pathways (SSPs) scenarios based on five Global Climate Models (GCMs) derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6), along with three yield increase scenarios from 2020 to 2100. The results indicated that promoting single-cotton cultivation in coastal saline–alkali lands would result in at least 88.2% of farmland being converted into carbon sinks. In contrast, promoting the cultivation of a wheat–maize rotation system can promote regional SOC sequestration as a whole, with a maximum increase of 31.90 Mg C ha−1. By 2100, the SOC stocks decreased in cotton and wheat–maize rotation farmland by 3.9% and 11.6%, respectively, in the SSP585 scenario compared with that in the SSP126 scenario. Except for farmlands with wheat-maize rotation cropping system under the SSP126 scenario, the SOC stocks in all other scenarios are projected to reach their theoretical maximum values before 2050. Additionally, when reaching the North China Plain (S1) and national (S2) high-yield levels of farmland, the SOC stocks in cotton farmland by 2100 increased by 16.7% and 21.6%, respectively, whereas the SOC stocks in wheat-maize farmland increased by 1.8% and 4.8%, respectively. Our study revealed the mutually beneficial relationship between yield increment and SOC sequestration in coastal farmlands under climate change, as well as the potential for future SOC sequestration. We provided scientific support for land management and climate change mitigation strategic decision-making in coastal saline–alkali farmlands.

Scale effect of climate factors on soil organic carbon stock in natural grasslands of northern China

Changes in grassland soil organic carbon stock (SOCS) may significantly affect the regional climate and carbon cycle of terrestrial ecosystems. However, how the impact of climate factors on SOCS and the dominant climate factors are regulated by the area scale of grasslands remains unclear. To understand the scale effects of climate on SOCS and how to accurately estimate SOCS at different scales, three area scales were defined by extending grassland types on the basis of meadow, typical and desert grasslands (Scale I (average area 37.22 × 104 km2) included each of these three types of grasslands, Scale II (average area 74.45 × 104 km2) was achieved by a pairwise combination of these three types of grasslands. Scale III (area 111.67 × 104 km2) was an aggregate of these three types of grasslands), the relationship between climate factors (i.e., mean annual precipitation, mean annual temperature, annual maximum temperature, annual minimum temperature, mean annual ground temperature, mean annual humidity, annual sunshine duration, annual maximum depth of accumulated snow, and the number of snow-covered days) and SOCS at the three scales were explored in the grasslands of northern China. Our results indicated that the total SOCS in grasslands at the three scales was ordered as desert grassland < meadow grassland < typical grassland. Of the nine climate factors, mean annual precipitation, positively correlated with SOCS, was the most significant climatic factor for all three scales. The dominant climatic factors of the SOCS differed across grassland area scales (i.e., MAP and MAH for meadow grassland, AMAT, MAP, NSD, and MAH for typical grassland, MAP, NSD, MAH, AMAT, and ASD for meadow-typical grassland scale, MAP, MAT, and MAGT for typical-desert grassland scale, MAP and MAT for meadow-typical-desert grassland scale). The impact of climate factors on the SOCS decreased as the scale increased. It is essential to screen appropriate climate predictors according to a given area scale when assessing regional SOCS. Multiple climate factors are better predictors for accessing SOCS at a small scale. At a large scale, however, dominant climatic factors are predictors that are more efficient.

Dynamic soil functions assessment employing land use and climate scenarios at regional scale

Soils as key component of terrestrial ecosystems are under increasing pressures. As an advance to current static assessments, we present a dynamic soil functions assessment (SFA) to evaluate the current and future state of soils regarding their nutrient storage, water regulation, productivity, habitat and carbon sequestration functions for the case-study region in the Lower Austrian Mostviertel. Carbon response functions simulating the development of regional soil organic carbon (SOC) stocks until 2100 are used to couple established indicator-based SFA methodology with two climate and three land use scenarios, i.e. land sparing (LSP), land sharing (LSH), and balanced land use (LBA). Results reveal a dominant impact of land use scenarios on soil functions compared to the impact from climate scenarios and highlight the close link between SOC development and the quality of investigated soil functions, i.e. soil functionality. The soil habitat and soil carbon sequestration functions on investigated agricultural land are positively affected by maintenance of grassland under LSH (20% of the case-study region), where SOC stocks show a steady and continuous increase. By 2100 however, total regional SOC stocks are higher under LSP compared to LSH or LBA, due to extensive afforestation. The presented approach may improve integrative decision-making in land use planning processes. It bridges superordinate goals of sustainable development, such as climate change mitigation, with land use actions taken at local or regional scales. The dynamic SFA broadens the debate on LSH and LSP and can reduce trade-offs between soil functions through land use planning processes.

Estimation of Permafrost SOC Stock and Turnover Time Using a Land Surface Model With Vertical Heterogeneity of Permafrost Soils

AbstractWe developed vertically resolved soil biogeochemistry (carbon and nitrogen) module and implemented it into a land surface model, ISAM. The model captures the vertical heterogeneity of the northern high latitudes permafrost soil organic carbon (SOC). We also implemented Δ14C to estimate SOC turnover time, a critical determinant of SOC stocks, sequestration potential, and the carbon cycle feedback under changing atmospheric CO2 concentration [CO2] and climate. ISAM accounted for the vertical movement of SOC caused by cryoturbation and its linkage to frost heaving process, oxygen availability, organo‐mineral interaction, and depth‐dependent environmental modifiers. After evaluating the model processes using the site and regional level heterotrophic respiration, SOC stocks, and soil Δ14C profiles, the vertically resolved soil biogeochemistry version of the model (ISAM‐1D) estimated permafrost SOC turnover time of 1,443 years, which is about 3 times more than the estimation based on the without vertically resolved version of ISAM (ISAM‐0D). ISAM‐1D‐simulated SOC stocks for permafrost regions was 319 Pg C in the top 1 m soil depth by the 2000s, about 80% higher than the estimates based on ISAM‐0D. ISAM‐1D SOC stock and turnover time were compared well with the observations. However, the longer SOC turnover time preserves less SOC stocks due to the lower carbon use efficiency (CUE) for SOC than ISAM‐0D and thus respires more SOC than being transferred downward by cryoturbation. ISAM‐1D simulated reduced SOC sequestration (3.7 Pg C) compared to ISAM‐0D (4.8 Pg C) and published Earth system models (ESMs) over the 1860s–2000s, due to weaker [CO2]‐carbon cycle and stronger climate‐carbon cycle feedbacks, highlighting the importance of the vertically heterogeneous soil for understanding the permafrost SOC sinks.

Multispectral Remote Sensing Data Are Effective and Robust in Mapping Regional Forest Soil Organic Carbon Stocks in a Northeast Forest Region in China

Accurately mapping the spatial distribution information of soil organic carbon (SOC) stocks is a key premise for soil resource management and environment protection. Rapid development of satellite remote sensing provides a great opportunity for monitoring SOC stocks at a large scale. In this study, based on 12 environmental variables of multispectral remote sensing, topography and climate and 236 soil sampling data, three different boosted regression tree (BRT) models were compared to obtain the most accurate map of SOC stocks covering the forest area of Lvshun District in the Northeast China. Four validation indexes, including mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2), and Lin’s concordance correlation coefficient (LCCC) were calculated to evaluate the performance of the three models. The results showed that the full variable model performed the best, except the model using multispectral remote sensing variables. In the full variable model, the regional SOC stocks are primarily determined by multispectral remote sensing variables, followed by topographic and climatic variables, with the relative importance of variables in the model being 63%, 28%, and 9%, respectively. The average prediction results of full variables model and only multispectral remote sensing variables model were 8.99 and 9.32 kg m−2, respectively. Our results indicated that there is a strong dependence of SOC stocks on multispectral remote sensing data when forest ecosystems have dense natural vegetation. Our study suggests that the multispectral remote sensing variables should be used to map SOC stocks of forest ecosystems in our study region.

Mineral control of organic carbon storage in acid temperate forest soils in the Basque Country

Soil minerals are known to play a major role in soil organic carbon (SOC) stabilization. However, the exact nature of the role is still poorly understood as comparative studies are complicated by the fact that mineralogy usually varies with other important factors such as climate, land-use, texture and acidity. This study investigated naturally-occurring minerals and C storage in nine mature, second-rotation Pinus radiata D. Don forest plantations at a similar development stage and growing under similar climatic conditions, but established on soils derived from three different parent materials: sandstone, basalt and trachyte. We quantified the SOC stocks in the 0–20 cm soil layer, clay-size minerals and metal oxides. The distribution of SOC in labile and mineral-bound fractions and the chemical structure of the SOC were also determined, by CPMAS NMR spectroscopy. For similar tree biomass, mean SOC storage was 2 times higher in the soils derived from basalt and 2.5 times higher in the soils derived from trachyte which were relatively rich in chlorite/vermiculite mixed layers and short-range order aluminium and iron forms, than in the sandstone-derived soils dominated by illite and with no short-range order aluminium. The parent material also affected the major C components of the SOC. Thus, the proportion of aromatic-C forms in the total SOC was higher in the sandstone-derived soil than in the soils of volcanic origin. Furthermore, the proportion of SOC in the mineral-bound fraction was around 30% in the sandstone-derived soil and around 50% in the volcanic soils. We conclude that estimates of ecosystem SOC stocks in acid temperate forest soils should include proxies for clay mineralogy, such as phyllosilicate minerals, contents of Fe and Al (hydr-) oxides and non-crystalline compounds. In addition, we recommend the inclusion of soil parent material as a proxy in models aimed at estimating regional SOC stocks.

Estimation of regional soil organic carbon stocks merging classified land-use information with detailed soil data

The Kulunda Steppe in southwestern Siberia is one of the most intensely used agricultural landscapes in the world. Today it is characterized by depletive soil management practices and intensities that are unadapted to the local site conditions. Severe soil degradation and a loss of soil organic carbon (SOC) occurs at agriculturally used areas. So far, only few studies analyzed the spatial extent of these degradation effects and came to inconsistent assessments. We consider that different results arise from different definitions of SOC changes and from different spatial scales. Thus, local soils under different land-uses were sampled to a depth of 30 cm to determine land use dependent changes in topsoil SOC. Site specific soil data was merged with appropriate land-use classifications and soil maps from the mid-1970s and up-to-date data from 2013/2014 to balance land use corrected SOC pools. Here, we use a hierarchical approach to extrapolate local findings to regional and biome scale for typical and dry steppe. At the test area, land-use changed only moderately after the Soviet period. The steppe biomes are also characterized by large areas that are not affected by land-use change and ensuing SOC loss. Agricultural use led to a mean carbon loss of 23.3% for Chernozem soils and 13.9% for Kastanozems. Natural heterogeneities, such as small scale changes in relief or soil type, are missing in small scale maps due to generalization that leads to varying results. The calculated regionwide SOC loss is maximally 15.2% using the small scale map. Following different calculation approaches, according to different map scales, detailed or coarse resolution SOC-stocks differ by up to 59.7%. Consequently, subsequent calculations or modellings may include this uncertainty into consideration.

Effects of past land use on soil organic carbon changes after dam construction

A large-scale and high-dropout water-level-fluctuation zone (WLFZ) was formed by the construction of cascaded large dam in the southwest hydropower base of China. The original land use patterns changed significantly by the formation of the WLFZ, which possibly affected the soil organic carbon (SOC) stocks and local carbon cycle. However, little is known about the effects of land uses before dam construction on the SOC stocks in the WLFZ. To address this, we chose the Nuozhadu mega reservoir built in 2014 in the upper Mekong River basin as our study area. We established five sampling transects around the reservoir and sampled them in 2015. Each transect contained three vertical sampling lines representing three land-use types: natural forest, farmland, and rubber plantations. SOC stocks were determined in the WLFZ and in the infralittoral reference zone (IRZ), and the interactions among SOC, land uses, soil erosion, inundation, and other soil physicochemical properties were analyzed to establish the factors controlling SOC in the WLFZ. The average soil organic carbon density (SOCD) was not significantly different between the WLFZ and IRZ, but it differed significantly among the three types of land uses. The SOC stocks in natural forests of the WLFZ and IRZ were significantly greater than those in the other land use types. The SOCD decreased with increasing elevation in the natural forest and rubber plantation in the WLFZ, while no significant trend was found in farmland. These results indicated that the construction of a large dam in southwestern China may not lead to significant changes in regional SOC stocks, but it can result in the redistribution of SOC in the large-scale and high-dropout WLFZ. Land use before dam construction can affect the background concentrations of SOC, soil physicochemical properties, and soil erosion rate in the WLFZ, which controlled the redistribution of SOC.

The devil is in the detail: Discrepancy between soil organic carbon stocks estimated from regional and local data sources in Flanders, Belgium

AbstractStorage of soil organic carbon (SOC) is an essential function of ecosystems underpinning the delivery of multiple services to society. Regional SOC stock estimates often rely on data collected during land‐use‐specific inventory schemes with varying sampling depth and density. Using such data requires techniques that can deal with the associated heterogeneity. As the resulting SOC assessments are not calibrated for the local scale, they could suffer from oversimplification of landscape processes and heterogeneity. This might especially be the case for sandy regions where typical historical land use practices and soil development processes determine SOC storage. The aims of this study were (a) to combine four land‐use‐specific SOC stock assessments to estimate the total stock in Flanders, Belgium, and (b) to evaluate the applicability of this regional‐scale estimate at the local scale. We estimated the SOC stock in the upper 100 cm of the unsealed area in Flanders (887,745 ha) to be 111.67 Mt OC, or 12.6 ± 5.65 kg OC m−2 on average. In general, soils under (semi‐) natural land‐use types, for example forests, store on average more organic carbon than under agriculture. However, overall agricultural soils store the largest amounts of SOC due to their vast spatial extent. Zooming in on a sandy location study (13.55 km2) revealed the poor performance of the regional estimates, especially where Histosols occurred. Our findings show that a greater spatial sampling density is required when SOC stock estimates are needed to inform carbon‐aware land management rather than to provide for regional reporting.

Soil organic carbon in semiarid alpine regions: the spatial distribution, stock estimation, and environmental controls

Soil organic carbon (SOC) in alpine regions is characterized by a strong local heterogeneity, which may contribute to relatively large uncertainties in regional SOC stock estimation. However, the patterns, stock, and environmental controls of SOC in semiarid alpine regions are still less understood. Therefore, the purpose of this study is to comprehensively quantify the stock and controls of SOC in semiarid alpine regions. Soils from 138 study sites across a typical semiarid alpine basin (1755–5051 m, ~1 × 104 km2) are sampled at 0–10, 10–20, 20–40, and 40–60 cm. SOC content, bulk density, soil texture, and soil pH are determined. Both a classical statistical model (i.e., a multiple linear regression, MLR) and a machine learning technique (i.e., a random forest, RF) are applied to estimate the SOC stock at a basin scale. The study further quantifies the environmental controls of SOC based on a general linear model (GLM) coupled with the structural equation modeling (SEM). SOC density varies significantly with topographic factors, with the highest values occurring at an elevation zone of ~3400 m. The results show that the SOC is more accurately estimated by the RF compared to the MLR model, with a total stock of 219.33 Tg C and an average density of 21.25 kg C m−2 at 0–60 cm across the study basin. The GLM approach reveals that the topography is seen to explain about 58.11% of the total variation in SOC density at 0–10 cm, of which the largest two proportions are attributable to the elevation (44.32%) and the aspect factor (11.25%). The SEM approach further indicates that, of the climatic, vegetative, and edaphic factors examined, the mean annual temperature, which is mainly shaped by topography, exerts the most significant control on SOC, mainly through its direct effect, and also, through indirect effect as delivered by vegetation type. The results of this study highlight the presence of high stocks of organic carbon in soils of semiarid alpine regions, indicating a fundamental role played by topography in affecting the overall SOC, which is mainly attained through its effects on the mean annual temperature.

Effects of topography on soil organic carbon stocks in grasslands of a semiarid alpine region, northwestern China

Soil organic carbon (SOC) in mountainous regions is characterized by strong topography-induced heterogeneity, which may contribute to large uncertainties in regional SOC stock estimation. However, the quantitative effects of topography on SOC stocks in semiarid alpine grasslands are currently not well understood. Therefore, the purpose of this research study is to determine the role of topography in shaping the spatial patterns of SOC stocks. Soils from the summit, shoulder, backslope, footslope, and toeslope positions along nine toposequences within three elevation-dependent grassland types (i.e., montane desert steppe at ~ 2450 m, montane steppe at ~ 2900 m, and subalpine meadow at ~ 3350 m) are sampled at four depths (0–10, 10–20, 20–40, and 40–60 cm). SOC content, bulk density, soil texture, soil water content, and grassland biomass are determined. The general linear model (GLM) is employed to quantify the effects of topography on the SOC stocks. Ordinary least squares regressions are performed to explore the underlying relationships between SOC stocks and the other edaphic factors. In accordance with the present results, the SOC stocks at 0–60 cm show an increasing trend in respect to the elevation zone, with the highest stock being approximately 37.70 g m−2 in the subalpine meadow, about 2.07 and 3.41 times larger than that in the montane steppe and montane desert steppe, respectively. Along the toposequences, it is revealed the SOC stocks are maximal at toeslope, reaching to 14.98, 31.76, and 49.52 kg m−2, which are also significantly larger than those at the shoulder by a factor of 1.38, 2.31, and 1.44, in montane desert steppe, montane steppe, and subalpine meadow, respectively. Topography totally is seen to explain about 84% of the overall variation in SOC stocks, of which 70.61 and 9.74% are attributed to elevation zone and slope position, while the slope aspect and slope gradient are seen to plausibly explain only about 1.84 and 0.01%, respectively. The elevation zone and the slope position are seen to markedly shape the spatial patterns of the SOC stocks, and thus, they may be considered as key indicating factors in constructing the optimal SOC estimation model in such semiarid alpine grasslands.

Carbon, nitrogen and phosphorus stocks differ among vegetation patch types in a degraded alpine steppe

Degradation of grassland creates diverse vegetation patch types with plant species with different palatabilities, potentially affecting ecosystem productivity and soil organic carbon (SOC) sequestration. This study investigated variations in SOC densities and carbon/nitrogen/phosphorus (C/N/P) ratios among vegetation patch types in a degraded alpine steppe on the Qinghai-Tibetan Plateau. We examined soil, shoot and root C, N and P densities, and C/N/P ratios in a growing season for five vegetation patch types dominated by palatable plant species Stipa purpurea, S. purpurea and Poa litwinowiana, and unpalatable plant species Leontopodium nanum, Artemisia nanschanica, and Oxytropis glacialis. Soil C and N as well as shoot and root densities varied among patch types, but not soil C/N. Patches dominated by unpalatable plant species had a lower SOC density, lower soil and plant N/P ratios, and greater plant nutrient densities than those dominated by palatable plant species. Vegetation patch type strongly influenced nutrient densities and ratios in soil-plant systems, and sampling only areas dominated by palatable plant species may overestimate the C sequestration rate at the ecosystem scale. Even though patch-level plant biomass and nutrient density may increase with increasing degradation, the decrease in palatability and SOC storage at the ecosystem scale would impair grassland sustainability as alpine grassland degradation proceeds. The palatability of plants should thus be considered for improving regional SOC stock estimate in future research.

Quantifying and Comparing Soil Carbon Stocks: Underestimation with the Core Sampling Method

Core Ideas Clod and core bulk density measurements were significantly different at all depths. The core sampling method underestimated the soil organic carbon (SOC) stock. Calculating SOC stocks on a mass basis did not overcome sampling method bias. Using clod and core methods interchangeably adds uncertainty to SOC databases. Regional and global SOC stocks may be largely underestimated. Changing climate, land use, and management can impact both surface and deep soil organic carbon (SOC) stocks on decadal timescales, highlighting the importance of accurate measurements of SOC stocks and comparisons. This study compared three soil sampling methods for estimating SOC stocks: clod, core, and excavation. The excavation method was used as the standard by which the other methods were compared. Sampling took place at an intensively managed Douglas‐fir [Pseudotsuga menziesii (Mirb.) Franco] plantation in northwestern Oregon, USA. Soil samples were collected by depth to 150 cm. Clod and core method soil bulk density measurements were significantly different at all depths, with the core method consistently resulting in lower soil bulk density. The core method significantly underestimated soil bulk density at all depths deeper than 20 cm and underestimated the SOC stock to a depth of 150 cm by 36%. Most of this difference occurred deeper than 20 cm, where the majority of SOC stocks were contained across all soil sampling methods. The underestimation of soil mass by the core method similarly affected the fixed depth, genetic horizon, and mass based approaches to quantify SOC stocks. This study demonstrated that (1) commonly used soil sampling methods for measuring soil properties should not be assumed to be interchangeable; and (2) regional and global SOC stocks may be largely underestimated due to shallow sampling and the frequent use of core methods.

Soil organic carbon on the fragmented Chinese Loess Plateau: Combining effects of vegetation types and topographic positions

The influence of vegetation coverage and topography on soil organic carbon (SOC) stocks has been intensively studies. However, very few of the studies have recognized the potential combining effects of vegetation types and topographic positions onto SOC distribution, especially on the Chinese Loess Plateau where vegetation recovery has generated complex combination of fragmented topography and vegetation coverage. This study systematically sampled soil cores (259) from four vegetation types (woodland, grassland, cropland, and orchard) at three topographic positions (tableland, slope and valley bottom). Each soil core was divided into three layers: surface soil (0–20cm), subsoil (20–60cm) and deep soil (60–200cm). Our results show that: (1) the SOC concentration declined over soil depths, regardless topographic positions or vegetation types. The absence of ancient cultivation layers at the valley bottoms further made the SOC stocks deep to 200cm there much less than the tableland with thick loess soil layers (8.3kgkm–2 vs. 13.4kgkm–2). (2) The SOC concentration of cropland varied evidently with topographic positions, with the greatest on the tableland (8.0gkg–1), and the least along the slope (5.3gkg–1). However, grassland was rather stable across the three topographic positions. (3) In addition, the SOC concentrations of the three vegetation types were comparable on the tableland (6.1gkg–1), while differed noticeably at the valley bottoms (5.0gkg–1). Overall, our findings in this study call for the account for each combination of topographic position and vegetation type, so as to properly assess regional SOC stocks for sustainable land use.

A chronosequence approach to estimate the regional soil organic carbon stock on moraines of two glacial fore-fields in SE-Iceland

ABSTRACTSOC has received increased attention over the last decades because of its role as an option to mitigate the effects of increased anthropogenic greenhouse gas emissions. In Iceland, the loss of vegetation and soil due to land-use and natural processes has left large areas as barren deserts. Land restoration actions have the primary goals to prevent land degradation and restore lost ecosystems but the ancillary benefits of SOC accumulation with regard to COP 21 are obvious. Natural vegetation succession is active in areas being exposed by glacial recession since the end of the Little Ice Age in ∼1890. Here, we attempt to estimate the current regional SOC stock on undisturbed moraines in front of two glaciers in SE-Iceland, using surface age, soil properties and vegetation cover data. RapidEye images were used to estimate the surface area of two vegetation classes with <50% and >50% cover. Regional SOC stock was calculated using soil data and the sum of the area of each cover class for each time-zone. The rates of SOC accretion reached the maximum values of 0.004−0.009 kg C m−2 yr−1. The regional SOC stock for the two glacier fore-fields was estimated at 1605 Mg C (0−10 cm) for Skaftafellsjökull (396 ha) and 1106 Mg C (0−5 cm) for Breiðamerkurjökull (632 ha). The current annual increase in the moraine SOC stocks was estimated at 20.7 Mg C yr−1 for Skaftafellsjökull and 19.7 Mg C yr−1 for Breiðamerkurjökull.

Mapping soil organic carbon stocks of northeastern China using expert knowledge and GIS-based methods

The main aim of this paper was to calculate soil organic carbon stock (SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China. A novel prediction process was presented and was referred to as model-then-calculate with respect to the variable thicknesses of soil horizons (MCV). The model-then-calculate with fixed-thickness (MCF), soil profile statistics (SPS), pedological professional knowledge-based (PKB) and vegetation type-based (Veg) methods were carried out for comparison. With respect to the similar pedological information, nine common layers from topsoil to bedrock were grouped in the MCV. Validation results suggested that the MCV method generated better performance than the other methods considered. For the comparison of polygon based approaches, the Veg method generated better accuracy than both SPS and PKB, as limited soil data were incorporated. Additional prediction of the pedogenetic horizons within MCV benefitted the regional SOCS estimation and provided information for future soil classification and understanding of soil functions. The intermediate product, that is, horizon thickness maps were fluctuant enough and reflected many details in space. The linear mixed model indicated that mean annual air temperature (MAAT) was the most important predictor for the SOCS simulation. The minimal residual of the linear mixed models was achieved in the vegetation type-based model, whereas the maximal residual was fitted in the soil type-based model. About 95% of SOCS could be found in Argosols, Cambosols and Isohumosols. The largest SOCS was found in the croplands with vegetation of Triticum aestivum L., Sorghum bicolor (L.) Moench, Glycine max (L.) Merr., Zea mays L. and Setaria italica (L.) P. Beauv.

Soil parent material, texture and oxide contents have little effect on soil organic carbon retention in tropical highlands

In tropical humid conditions, soil organic carbon (SOC) concentrations have been reported to be proportional to clay, clay+silt and Fe/Al oxide contents. Typically, soil texture and mineralogy are strongly dependent on soil parent materials, but it is not known if SOC retention would also be affected by soil parent material. Such relationship, if established, could be useful to estimate regional SOC stocks, since geological maps are more numerous and often more accurate than soil maps. The objective of this study was to assess the effect of parent material, texture,and oxide content on SOC contents in tropical highlands. Thus, samples to 1-m depth were obetained for seven soils derived from quartzite, sericite-schist, itabirite, serpentinite, limestone, gneiss and phyllite. All soils formed under similar climate and native forest, and were located on the midslope position. Despite wide variations in soil texture and mineralogy, there were no valid correlations between SOC and clay, clay+silt or Fe/Al oxide concentrations. Similarly, SOC stocks did not differ significantly when computed for 0–20, 0–40 and 0–100cm layers, and in all soils most SOC was associated with the clay fraction. We propose that such absence of effects of soil parent material, texture and oxide contents on SOC retention can be due to the overriding effect of altitudes of 900–1100m a.s.l., which resulted in higher SOC stocks because of lower mean annual temperatures. These trends are in contrast to those reported for tropical lowlands where the textural and mineralogical controls of SOC retention were first described. Therefore, soils on tropical highlands (>900m) are likely to present similarly high SOC stocks, whereas soil parent material, by means of soil texture, mineralogy and oxide contents would affect SOC retention only at lower altitudes.

Impact of agricultural intensification on soil organic carbon: A study using DNDC in Huantai County, Shandong Province, China

Using the biogeochemical model denitrification/decomposition (DNDC), the dynamic changes of soil organic carbon (SOC) of farmland from the 1980s to 2030s were investigated in Huantai County, a typical intensive agricultural region in the Huang-Huai-Hai Plain of China. Prior to modelling, validation of the DNDC model against field data sets of SOC from Quzhou Experimental Station in the Huang-Huai-Hai Plain was conducted at the site scale. We compared the simulated results with the observed SOC in Huantai County during 1982–2011 under two different classification methods of simulation unit (the first method integrated soil type and land use of Huantai County to form the overlapped modeling units; the second selected the 11 administrative towns as the modeling units), and achieved a high accuracy in the model simulation with the improvement of the model parameters. Regional SOC (0–20 cm) density and stocks for Huantai County in the years 2012–2031 were predicted under different scenarios of farming management. Compared with current management practices, optimized fertilization (20% decrease of mineral N), crop straw incorporation (90%) and appropriate animal manure input (40 kg N ha−1 yr−1) could achieve the highest level of SOC density (56.8% higher than 2011) in the period of 2012–2031. The research highlighted the importance of crop straw incorporation, optimized N fertilization and integration of crop production with animal husbandry on the farmland carbon sequestration for maintaining a high land productivity in the Huang-Huai-Hai Plain.

Multi-level statistical soil profiles for assessing regional soil organic carbon stocks

To support the assessment of soil-related ecosystem service delivery throughout an area of interest, the information content of soil maps needs to be extended with quantitative data about e.g. the soil organic carbon content. Such data are typically provided by soil profile descriptions with associated horizon data. However, the magnitude and spatial density of available profile collections are mostly too limited to allow the coupling of at least one profile description with each soil–land cover combination, further termed land unit (LU). To overcome this lack-of-data-problem, spatial generalisation and modelling approaches have been developed. However, these approaches do not take full advantage of all available data when their density is heterogeneous across the territory. We present a multi-level, both spatial and semantic, generalisation approach to work with detailed LUs in regions where sufficient data is available and with generalised units elsewhere.Applied to the soil map of Flanders, Belgium (18,809 LUs for 9295km2), a database of 7020 profile descriptions with 42,529 horizons and a 3- (coastal region) and 5-level (non-coastal region) generalisation approach, the method succeeded in assigning at least one profile to 18,731 LUs or 98.7% of the territory. Increasing the minimum required number of matching profiles increased the number of LUs characterised at higher levels of generalisation. Using the horizon characteristic ‘organic carbon content’, we estimated the total historical SOC-stock in Flanders at 87.49Mt C and found that increasing the minimum required number of profiles decreased this estimate and increased its uncertainty. The assessed stock is lower than the ones found in previous studies even though they are based on the same collection of soil profiles. We consider our results as more realistic since the proposed method preserves the highest possible spatial and semantic detail.

Estimating soil organic carbon stocks of Swiss forest soils by robust external-drift kriging

Abstract. Accurate estimates of soil organic carbon (SOC) stocks are required to quantify carbon sources and sinks caused by land use change at national scale. This study presents a novel robust kriging method to precisely estimate regional and national mean SOC stocks, along with truthful standard errors. We used this new approach to estimate mean forest SOC stock for Switzerland and for its five main ecoregions. Using data of 1033 forest soil profiles, we modelled stocks of two compartments (0–30, 0–100 cm depth) of mineral soils. Log-normal regression models that accounted for correlation between SOC stocks and environmental covariates and residual (spatial) auto-correlation were fitted by a newly developed robust restricted maximum likelihood method, which is insensitive to outliers in the data. Precipitation, near-infrared reflectance, topographic and aggregated information of a soil and a geotechnical map were retained in the models. Both models showed weak but significant residual autocorrelation. The predictive power of the fitted models, evaluated by comparing predictions with independent data of 175 soil profiles, was moderate (robust R2 = 0.34 for SOC stock in 0–30 cm and R2 = 0.40 in 0–100 cm). Prediction standard errors (SE), validated by comparing point prediction intervals with data, proved to be conservative. Using the fitted models, we mapped forest SOC stock by robust external-drift point kriging at high resolution across Switzerland. Predicted mean stocks in 0–30 and 0–100 cm depth were equal to 7.99 kg m−2 (SE 0.15 kg m−2) and 12.58 kg m−2 (SE 0.24 kg m−2), respectively. Hence, topsoils store about 64% of SOC stocks down to 100 cm depth. Previous studies underestimated SOC stocks of topsoil slightly and those of subsoils strongly. The comparison further revealed that our estimates have substantially smaller SE than previous estimates.