System-Specific Complex Interactions Shape Soil Organic Carbon Distribution in Coastal Salt Marshes.

Understanding the vertical and lateral distribution of soil organic carbon (SOC) and soil organic carbon density (SOCD) is indispensable for soil use and environmental management because of their vital role in soil quality assessments. Primarily, they are needed in calculating soil organic carbon storage (SOCS). The objective of this research was to provide digital maps of SOC and SOCD variation as well as their uncertainties at multiple standardized depths (H1: 0–5, H2: 5–15, H3: 15–30, H4: 30–60 and H5: 60–100 cm) using a parsimonious model with optimized terrain‐related attributes and satellite‐derived data. SOCS were evaluated at soil subgroup levels. An area of about 808 km 2 with varying elevation, plant cover and lithology from the Miandoab region, West Azerbaijan Province, Iran was selected as a case study area. A total of 386 soil samples were collected from 104 profiles comprising various soil genetic horizons. A continuous spline function was then fitted to the target properties in advance of creating a dataset at five standard depth intervals (following the GlobalSoilMap project). These were then grouped into three classes including top (H1), middle (H2, H3 and H4) and bottom (H5) depths to ease interpretation. Static and dynamic covariates (30‐m resolution) were derived from a digital elevation model (DEM) and a suite of Landsat‐8 spectral imageries, respectively. Four candidate models including stepwise multiple linear regression (SMLR), random forest (RF), cubist (CU) and extreme gradient boosting (XGBoost) Tree were tested in this study. Finally, the digital maps at 30‐m resolution of SOC and SOCD and their uncertainties were prepared using the best‐fit model and the bootstrapping method, respectively. Four soil subgroups (Gypsic Haploxerepts, Typic Calcixerepts, Typic Haploxerepts and Xeric Haplocalcids) were identified across the study area. The covariates had variable contributions on the evaluated models. The XGBoost Tree model generally outperformed other models for prediction of SOC and SOCD ( R 2 = 0.60, on average). Regardless of soil subgroups, the uncertainty analysis showed that the SOCD map had a low prediction interval range value indicating high accuracy. Additionally, the highest SOCS and SOCD was observed at the top followed by middle and bottom depths in the study area. All subgroups exhibited a decreasing trend of SOCD with increasing depth. A similar trend was also observed for SOCS. The highest SOCD (on average) was observed in Gypsic Haploxerepts (4.71 kg C/m 2 ) followed by Typic Calcixerepts (4.46 kg C/m 2 ), Typic Haploxerepts (4.45 kg C/m 2 ) and Xeric Haplocalcids (4.40 kg C/m 2 ). Overall, the SOCS normalized by area within soil order boundaries was greater in Inceptisols than Aridisols across the study area. The findings of this study provide critical information for sustainable management of soil resources in the area for agricultural production and environmental health in the Miandoab region of Iran.

Spatial distribution of soil organic carbon and macronutrients in the deep soil across a chronosequence of tea agroforestry

Using the data compiled from China's second national soil survey and an improved method of soil carbon bulk density, we have estimated the changes of soil organic carbon due to land use, and compared the spatial distribution and storage of soil organic carbon (SOC) in cultivated soils and noncultivated soils in China. The results reveal that ∼ 57% of the cultivated soil subgroups (∼ 31% of the total soil surface) have experienced a significant carbon loss, ranging from 40% to 10% relative to their noncultivated counterparts. The most significant carbon loss is observed for the non‐irrigated soils (dry farmland) within a semiarid/semihumid belt from northeastern to southwestern China, with the maximum loss occurring in northeast China. On the contrary, SOC has increased in the paddy and irrigated soils in northwest China. No significant change is observed for forest soils in southern China, grassland and desert soils in northwest China, as well as irrigated soils in eastern China. The SOC storage and density under noncultivated conditions in China are estimated to ∼ 77.4 Pg (1015 g) and ∼ 8.8 kg C m−2, respectively, compared to a SOC storage of ∼ 70.3 Pg and an average SOC density of ∼ 8.0 kg C m−2 under the present‐day conditions. This suggests a loss of ∼ 7.1 Pg SOC and a decrease of ∼ 0.8 kg C m−2 SOC density due to increasing human activities, in which the loss in organic horizons has contributed to ∼ 77%. This total loss of SOC in China induced by land use represents ∼ 9.5% of the world's SOC decrease. This amount is equivalent to ∼ 3.5 ppmv of the atmospheric CO2 increase. Since ∼ 78% of the currently cultivated soils in China have been degraded to a low/medium productivities and are responsible for most of the SOC loss, an improved land management, such as the development of irrigated and paddy land uses, would have a considerable potential in restoring the SOC storage. Assuming a restoration of ∼ 50% of the lost SOC during the next 20–50 years, the soils in China would absorb ∼ 3.5 Pg of carbon from the atmosphere.

Sea-level rise enhances carbon accumulation in United States tidal wetlands

To better understand carbon, nitrogen, and phosphorus dynamics within small-scale gradients of tidal and vegetation interaction, 13 study sites were established along three transects (near, far, and along a tidal creek) within a salt marsh in northern Jiangsu, China, and soil samples were collected during both the growing and non-growing season; the soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) contents were measured. Spatiotemporal variation in SOC, TN, and TP in coastal salt marsh soils was influenced not only by the physical and chemical properties of the elements themselves, but also by the distribution of local vegetation and repetitive tidal action. Complex interactions between the vegetation and tidal flooding determined spatiotemporal patterns in SOC, TN, and TP. Compared to tidal effects, vegetation effects were more stable and persistent. The spatial distributions of SOC and TN in salt marsh soils (sediment) were relatively consistent, with both SOC and TN levels being higher in vegetated zones as compared to the mudflat. Nutrient levels were also higher further from the tidal creek, and the SOC/TN content was maximized in the S. alterniflora marsh. The TP content was higher in the tidal-creek transect versus the other two transects; among sites, the TP content was higher in the mudflat than the vegetated sites. Within the vegetated sites, the S. alterniflora marsh had the highest TP levels. Seasonal variation in SOC, TN, and TP was minimal compared to differences among vegetated sites within each transect. Differences between transects were also minimal compared to those among vegetated sites within transects. Significant spatial variation was identified in C:N:P stoichiometry across the study area; the comprehensive effects of vegetation and tidal flooding on nutrient stoichiometry in coastal salt marshes dominated by S. alterniflora in eastern China are elevation-dependent. The N/P ratio measured 0.62 ± 0.41, suggesting that plant growth in the study area may be nitrogen limited. Together, the local vegetation and repetitive tidal flooding shaped SOC, TN, and TPs in salt marsh soils, producing similar patterns in nutrient element accumulation, constraining the geochemical behavior and fate of elements, and controlling the spatiotemporal distribution of soil elements. Therefore, it is critical to consider interactions between vegetation and tidal effects, as well as the nonlinear relationship between nutrient input and ecological response in salt marsh ecosystems when managing coastal zones, supporting ecosystem functioning, and conducting ecological risk assessments.

Whole-profile soil organic matter content, composition, and stability under cropping systems that differ in belowground inputs

QUANTIFYING PEATLAND CARBON DYNAMICS USING MECHANISTICALLY-BASED BIOGEOCHEMISTRY MODELS

<p>Bioenergy crops are expected to provide biomass to replace fossil resources and reduce greenhouse gas emissions. In this context, their effect on soil carbon sequestration is of primary importance. There is a wide range of candidate crops including perennial C4 crops or annual crops but their impact on soil organic carbon (SOC) stocks remain very uncertain as shown by the wild variability in published experimental results.</p><p>In this study, we measured the changes in SOC stocks under perennial (miscanthus and switchgrass), semi-perennial (fescue and alfalfa) and annual (triticale and sorghum or maize) bioenergy crops managed with two N fertilisation rates. The experiment called “Biomass & Environment” is located in northern France on a deep loamy soil (Haplic Luvisol) and was set up in 2006. The soil was sampled at the start of the experiment, in 2011-2012 and again in 2018 (0-60 cm, 5 layers). SOC stocks were calculated at equivalent soil mass and δ<sup>13</sup>C was systematically measured and used to calculate changes in new and old SOC stocks. In 2018, the SOC distribution in different soil particle-size fractions was also characterized for some treatments.</p><p>After 12 years, there was a large increase in SOC concentration (+7.6 g kg<sup>-1</sup> on average) under perennial crops in the surface layer (≈ 0-5 cm) but a slight decrease in deeper layers. Changes in δ<sup>13</sup>C also showed that more than half of the new SOC accumulated in the surface layer. In addition, the additional SOC storage in the first layer was found in coarse organic fractions (50-200 and 200-2000 μm) but also in the more stabilised 0-50 μm fraction. SOC concentration under semi-perennial crops increased in the two first layers (≈ 0-20 cm), from 10.2 g kg<sup>-1</sup> in 2006 to 11.6 g kg<sup>-1</sup> in 2018 on average and slightly decreased below. Under annual crops, a decrease in SOC concentration was observed in all layers and particularly in the third layer (≈ 20-33 cm). There was no significant effect of the N fertilisation. Over the old ploughed layer (≈ 0-33 cm), SOC stocks increased between 2006 and 2018 under perennial and semi-perennial bioenergy crops (by 3 and 2 t C ha<sup>-1</sup> on average respectively) and decreased by 7 t C ha<sup>-1</sup> on average under annual crops.</p><p>This study show that different bioenergy crops can have contrasted impacts on SOC stocks but also on SOC distribution in the soil profile.</p>

Land use is a primary driver of the spatial distribution of soil organic carbon (SOC) and significantly influences the terrestrial carbon cycle. This study used the SWAT-C model to simulate the export of SOC, dissolved organic carbon (DOC), and particulate organic carbon (POC) in the Wu River Basin, analyzing the effects of land use on SOC spatial distribution. Model calibration with 2012–2017 total organic carbon (TOC) data achieved Nash-Sutcliffe efficiency values above 0.7, confirming reliability. The simulated results showed an average annual TOC export of 17.3 kgC/ha, with DOC and POC contributing 10.38 kgC/ha and 6.9 kgC/ha, respectively. Bare land had the highest POC export (66.7 kgC/ha), followed by dry cropland (32.3 kgC/ha), while urban areas and coniferous forests exhibited the highest DOC exports (15.1 and 12.4 kgC/ha, respectively). SOC storage was highest in rice field (313 tonC/ha) and lowest in bare land (175 tonC/ha). Sub-watersheds dominated by bare land and dry cropland recorded TOC exports exceeding 21 kgC/ha, marking them as future SOC export hotspots. These findings highlight the significant influence of land use on SOC distribution and provide a scientific basis for ecosystem service preservation, and sustainable watershed management.Key words: Soil organic carbon, SOC storage, SWAT-C model, land use, Taiwan

The profile distributions of soil organic carbon (SOC), soil organic nitrogen (SON), soil pH and soil texture were rarely investigated in the Lancangjiang River Basin. This study aims to present the vertical distributions of these soil properties and provide some insights about how they interact with each other in the two typical soil profiles. A total of 56 soil samples were collected from two soil profiles (LCJ S-1, LCJ S-2) in the Lancangjiang River Basin to analyze the profile distributions of SOC and SON and to determine the effects of soil pH and soil texture. Generally, the contents of SOC and SON decreased with increasing soil depth and SOC contents were higher than SON contents (average SOC vs. SON content: 3.87 g kg−1 vs. 1.92 g kg−1 in LCJ S-1 and 5.19 g kg−1 vs. 0.96 g kg−1 in LCJ S-2). Soil pH ranged from 4.50 to 5.74 in the two soil profiles and generally increased with increasing soil depth. According to the percentages of clay, silt, and sand, most soil samples can be categorized as silty loam. Soil pH values were negatively correlated with C/N ratios (r = −0.66, p < 0.01) and SOC contents (r = −0.52, p < 0.01). Clay contents were positively correlated with C/N ratios (r = 0.43, p < 0.05) and SOC contents (r = 0.42, p < 0.01). The results indicate that soil pH and clay are essential factors influencing the SOC spatial distributions in the two soil profiles.

Feedbacks between atmospheric and terrestrial carbon stocks remain unclear. Soil carbon stores are affected by a complex interaction among several biophysical and hydroclimatic processes, including the dynamics of soil moisture, insolation, and temperature. Studying the spatiotemporal distribution of soil organic carbon (SOC) and its dynamic changes is necessary for building a soil carbon pool inventory, as well as predicting the potential for soil carbon sequestration (Dorji et al., 2014). Many environmental controls on soil organic carbon have been analysed at site-specific plot-scales, while long term temporal studies of SOC dynamics are less common. The continued uncertainty of carbon cycle feedbacks, and the complexity of interactions of controls on, and transport of, soil carbon at regional scales, justifies further investigation. This study investigates the spatiotemporal relationships between surface SOC and a number of environmental variables across a catchment. The findings of this research will contribute to overall understanding of SOC distribution and controls for large regional scales. The catchment for this study is located in the Upper Hunter Valley region of New South Wales, Australia. The study focuses on the Krui River catchment, having an area of 562 km 2 . Soil samples were obtained across the catchment using a 1 km grid scale. Cores with a depth of 220 mm were obtained from 59 grazing sites in 2006 and from 52 grazing sites in 2014, with 41 of the sites common to both 2006 and 2014. At each sampling location, aboveground biomass (AGB), soil moisture, and soil temperature was sampled within a 0.25m 2 quadrat. Land use at each sample site was classified as either cropping or grazing. For a comparison of the temporal variability in SOC concentrations, average SOC from the two sampling dates were compared using Student's t-test. To determine which variables were the most important, principle component analysis was performed for topographic (elevation, slope, aspect, plan curvature, profile curvature, TWI), soil (pH, Electroconductivity, clay %) and vegetation (sampled vegetation biomass, remotely sensed vegetation biomass) variables for the sample sites. SOC, elevation, Normalised Difference Vegetation Index (NDVI) and plan curvature were found to be the most important variables for the first 2 principle components. Linear regression and heteroscedasticity tests were applied to the strongest correlations between SOC and the other variables for both sampling periods. The results of this study show that soil carbon was spatially and temporally stable over medium time scales (8+ years), with the variables of SOC, elevation and NDVI having strong, positive correlations with each other for both sampling periods. Strong, positive Pearson's r correlations were observed between SOC and NDVI, a surrogate for Aboveground Net Primary Production (ANPP), for both sampling periods. Thus regions of higher net primary production corresponding with higher concentrations of SOC. Grazing intensity, represented in this study by sampled AGB, did not affect SOC. Topography strongly influences vegetation via its control on such climate variables as precipitation and temperature. Elevation was found to explain much of the variability in NDVI, and hence SOC, although slope and aspect also had weak to moderate correlations with NDVI. The relationship between SOC and aspect was weak. This study demonstrates that the variables of elevation and NDVI can be used to digitally map the spatiotemporal distribution of SOC across large (~500 km 2 ) catchments of elevations ranging from ~300 to ~1100 m. However, long term seasonal climate variability may affect the predictive ability of SOC using these variables. The spatial and long term temporal stability of catchment SOC demonstrated here has major implications for soil carbon sequestration. SOC across the catchment appears to be at equilibrium, with minimal variation observed after 8 years of continuous grazing. Carbon sequestration methods would therefore require major changes in grazing land-use to achieve observable increases in soil carbon.

Investigations on temporal and spatial variation of slope-scale SOC erosion and deposition

Understanding the vertical distributions of soil organic carbon (SOC) is key to predicting and simulating the influences of climate, global change, and human activities on the terrestrial carbon cycle. SOC was measured at soil depths of 0–10, 0–20, 0–30, 0–50, and 0–100 cm in 2473 soil profiles during China’s second national soil survey that was conducted from 1979 to 1992. SOC was spatially extrapolated for China. Mean SOC densities in the top 1 m ranged from 4.65 kg/m2 for bare ground to 17.32 kg/m2 in grassland land cover. SOC in the top 1 m of soil was estimated at 82.5 ± 19.5 Pg C. The total SOC pool held in the top 10, 20, 30, 50, and 100 cm are 22%, 41%, 54%, 74%, and 100%, respectively. One of the objectives of the study is to examine the association of SOC content with climate and to estimate SOC storage in land-cover types at different soil depths. A partial correlation analysis shows that the mean annual precipitation was positively correlated with SOC content and the mean annual temperature was negatively correlated with SOC content, across all depths. The vertical distribution of SOC had a slightly stronger association with temperature than with precipitation in China.

Understanding the responses of soil organic carbon (SOC) distribution to terrain and land use variations is important for making corresponding measures to enhance the soil quality and its carbon storage. The objective of this study was to characterize the spatial distribution of SOC, and analyze the impacts of environment factors on spatial variation of SOC along the Danjiangkou Reservoir area, China. A village size watershed was selected to investigate the SOC distribution under different terrains and land uses. We found that SOC contents followed a log-normal distribution with arithmetic and geometric means of 6.83 g kg −1 and 6.09 g kg−1, respectively, which were moderately variable (Coefficient of Variation = 49.6%) and demonstrated a moderate spatial dependence according to the nugget ratio (37.8%). The experimental variogram of SOC was best-fitted by a spherical model after the spatial outliers had been detected and subsequently eliminated. From the spatial distribution map of SOC contents, the highest SOC content occurred in the center of the watershed, which were along the main water channel or tributaries and normally had lower altitude. While,the lower values of SOC contents were located at the edge of the watershed, such as in the northwest, southwest and southeast of the area where citrus were normally planted. This spatial distribution pattern of SOC was generally consistent with the spatial structure of terrain and land use on the unique terrain of the agriculture-based reservoir area. Therefore, taking terrain and land use type into account when estimating the spatial variation of SOC pool would increase the accuracy in prediction and modeling of SOC movement at the watershed scale.

Salt marshes are globally widespread, found on low-lying coastal shores, and are highly effective at long-term carbon storage; thus, they are vital for climate change impact mitigation. Accurate carbon stock estimation requires an understanding of local-scale spatial variability of carbon storage and the facilitating processes. Few studies investigate the cumulative impact of controlling factors on within-site carbon distribution. This study utilises 60 cores from a salt marsh in Turvey Nature Reserve (Rogerstown Estuary), on the Irish east coast, to investigate spatial variability in soil organic carbon (SOC) content, alongside bio-sedimentary, and environmental factors. Mean carbon density (CD) was 11.1 ± 4.2 kg m−3 at 10-cm depth, ranging from 5.2 to 22 kg m−3 (423% increase) across the marsh. We recommend that to obtain measurements across the full range of the site, for small sample sizes (n < 20), random sampling should be used (mean difference between the site-wide CD and ‘subsample CD’ ranged from 0.04 (n = 10) to 0.29 (n = 5) kg m−3) and marsh edge clustering should be avoided. These results provide the first ever systematic record of local-scale (within ~ 800 m2) SOC and CD variability within an Irish east coast salt marsh and the variation of known influencing factors (including sedimentary and environmental). We also present the first study to systematically provide guidance on capturing marsh-wide SOC and CD most effectively based on limited sampling. The outputs help constrain uncertainties around scaled-up carbon accumulation estimates for regional, national and international inventories.