Distribution Of Soil Organic Carbon Research Articles

Tillage and Straw Management Practices Influences Soil Nutrient Distribution: A Case Study from North-Eastern Romania

Tillage practices govern crop quality and quantity through soil nutrient availability and crop root systems. A deeper knowledge of the impact of conservation tillage on soil chemical characteristics (such as pH, soil organic carbon, macro and micronutrient storage and distribution) is required for both the promotion of agricultural sustainability and environmental preservation. This study assesses the changes in soil features and properties in the context of a long-field experiment with different tillage systems and straw management practices. Research findings revealed that compared with conventional tillage (CT) conservative tillage with partial straw retention (MT) and no-tillage with straw mulching (NT) substantially boosted the organic carbon (OC) (by 6–19%), total nitrogen (TN) (by 2–12%), and available potassium content (AK) (by 2–5%), in 0–30 cm soil depth. However, the stratification trend was observed for available macro and micronutrient content (Zn, Fe, Mn) in both conservative management practices. The concentration of Cu indicates a constant pattern through a 0–30 cm soil profile with a higher concentration under MT (1.41 mg kg−1) compared to NT (1.10 mg kg−1). In particular, the results failed to establish if conservation tillage can increase the total phosphorus (TP) and potassium content (TK), where only in surface 0–10 cm an increase was observed. This research also suggested that the X-ray fluorescence analysis (XRF) of total micronutrient content (Zn, Cu, Fe, Mn) is minimal or unpredictable with no substantial differences between the tillage systems and straw return management practices. These findings suggest that conservation tillage in north-eastern Romania might be optimal to maintain soil quality status and sustain high yields.

Numerical modeling of PFAS movement through the vadose zone: Influence of plant water uptake and soil organic carbon distribution

In this study, we investigated the effects of soil organic carbon (SOC) distribution and water uptake by plant roots on PFAS movement in the vadose zone with a deep groundwater table under temperate, humid climate conditions. Two series of numerical simulations were performed with the HYDRUS computer code, representing the leaching of historical PFOS contamination and the infiltration of water contaminated with PFOA, respectively. We considered soil profiles with three distributions of SOC (no SOC, realistic SOC distribution decreasing with depth, and uniform SOC equal to the content measured in topsoil), three root distributions (bare soil, grassland, and forest), and three soil textures (sand, sandy loam, and loam). The SOC distribution had a profound impact on the velocity of PFOS movement. The apparent retardation factor for realistic SOC distribution was twice as large as for the scenario with no SOC and more than three times smaller than for the scenario with uniformly high SOC content. We also showed that the root distribution in soil profoundly impacts the simulations of PFAS migration through soil. Including the root zone significantly slows down the movement of PFAS, primarily due to increased evapotranspiration and reduced downward water flux. Another effect of water uptake by plant roots is an increase of PFAS concentrations in soil water (evapo-concentration). The evapo-concentration and the slowdown of PFAS movement due to root water uptake are more significant in fine-textured soils than in sand.

Quantifying aboveground biomass, soil organic carbon and erosion with a detailed crop map and PESERA model in the Yangtze River Basin

AbstractSoil erosion represents a primary threat to soil systems with adverse implications for ecosystem services, crop production, potable water and carbon storage. While numerous studies have quantified the spatial distribution of aboveground Biomass (AGB), soil erosion and soil organic carbon (SOC) in the Yangtze River Basin (YRB), limited attention has been given to assessing the contributions of different land use types and especially crop types to AGB, soil erosion and SOC. In most studies, cropland is taken as a land use class, while detailed crop types and rotation patterns, and their effect on soil erosion and SOC, vary significantly. In this study, we used the Metronamica model to generate a detailed crop rotation and distribution map across the YRB and subsequently employed the Pan‐European Soil Erosion Risk Assessment (PESERA) model to simulate the spatial distribution of AGB, soil erosion and SOC on a monthly basis. PESERA model simulations indicate an average soil erosion rate across the entire YRB of 7.7 ton/ha/yr, with erosion hotspots concentrated in the Sichuan Basin and the central‐southern regions. The southwestern region and western Sichuan show elevated levels of AGB and SOC, while the eastern plains display lower levels. Erosion rates are lowest in areas designated as artificial land, pasture and grassland, whereas croplands and fruit tree plantations experience the highest erosion rates. In terms of crop types, the highest erosion rates and lowest AGB are observed under fallow and potato cultivation, while the lowest erosion rates and highest AGB are found in rice‐wheat rotation fields. To the best of our knowledge, this is the first study taking detailed crop types and patterns into account while evaluating their effect at a relatively large scale (i.e., YRB). These findings can help to develop sustainable soil management and (cropping) conservation strategies.

Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation

Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ha). Nonetheless, both models achieved satisfactory accuracy (R2 ≥ 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.

On the impact of soil texture on local scale organic carbon quantification: From airborne to spaceborne sensing domains

Soil organic carbon (SOC) distribution and interaction with light is influenced by soil texture parameters (clay, silt and sand), which makes SOC prediction complicated, especially in samples with considerable pedological variability. Hence, understanding the relationship between SOC and soil texture is important within the context of SOC prediction using remote sensing data. The main objective of this study was to find the impact of soil texture on the performance of local SOC prediction models that were developed on Sentinel-2 (S2) multispectral and CASI/SASI (CS) hyperspectral airborne data as the main predictor variables. One approach to that objective was to lowering the texture variance by stratification of the samples. Therefore, soil samples collected from four agricultural sites in the Czech Republic were segregated based on the i) site-based and ii) texture-based stratification strategies. Random forest (RF) models were then developed on all stratified classes with and without considering the soil texture parameters as predictor variables and results were compared with those obtained by the RF models developed on the non-stratified (NS) samples. Both stratification strategies provided more homogeneous classes, which enhanced the accuracy of SOC prediction, compared to using the NS samples. In addition, the texture-based RF models yielded higher accuracy predictions than the site-based ones. Except sand, adding texture parameters to the main predictors improved accuracy of the models, so that the highest prediction performance was obtained by a texture-based model developed on clay added CS data. Overall, texture-based stratification could significantly enhance the SOC prediction, when the texture parameters were added to the S2 and CS data as the main predictor variables.

Remote Quantification of Soil Organic Carbon: Role of Topography in the Intra-Field Distribution

Soil organic carbon (SOC) measurements are an indicator of soil health and an important parameter for the study of land-atmosphere carbon fluxes. Field sampling provides precise measurements at the sample location but entails high costs and cannot provide detailed maps unless the sampling density is very high. Remote sensing offers the possibility to quantify SOC over large areas in a cost-effective way. As a result, numerous studies have sought to quantify SOC using Earth observation data with a focus on inter-field or regional distributions. This study took a different angle and aimed to map the spatial distribution of SOC at the intra-field scale, since this distribution provides important insights into the biophysiochemical processes involved in the retention of SOC. Instead of solely using spectral measurements to quantify SOC, topographic and spectral features act as predictor variables. The necessary data on study fields in South-East England was acquired through a detailed SOC sampling campaign, including a LiDAR survey flight. Multi-spectral Sentinel-2 data of the study fields were acquired for the exact day of the sampling campaign, and for an interval of 18 months before and after this date. Random Forest (RF) and Support Vector Regression (SVR) models were trained and tested on the spectral and topographical data of the fields to predict the observed SOC values. Five different sets of model predictors were assessed, by using independently and in combination, single and multidate spectral data, and topographical features for the SOC sampling points. Both, RF and SVR models performed best when trained on multi-temporal Sentinel-2 data together with topographic features, achieving validation root-mean-square errors (RMSEs) of 0.29% and 0.23% SOC, respectively. These RMSEs are competitive when compared with those found in the literature for similar models. The topographic wetness index (TWI) exhibited the highest permutation importance for virtually all models. Given that farming practices within each field are the same, this result suggests an important role of soil moisture in SOC retention. Contrary to findings in dryer climates or in studies encompassing larger areas, TWI was negatively related to SOC levels in the study fields, suggesting a different role of soil wetness in the SOC storage in climates characterized by excess rainfall and poorly drained soils.

Topographic Drivers of Permafrost Organic Carbon Accumulation on the Northern Qinghai–Tibet Plateau

ABSTRACTLarge amounts of soil organic carbon (SOC) have accumulated over thousands of years in the northern permafrost regions. However, the SOC accumulation rates and the effects of topography, vegetation, and soil properties on SOC storage remain poorly constrained, leading to large uncertainties in the estimation of SOC storage and its response to warming. Here, we examined SOC stocks, densities, and accumulation rates using field sampling and radiometric dating in areas with different topographic parameters on the northern Qinghai–Tibet Plateau. Results show that SOC density and stock increases with elevation on south‐facing slopes but decreases with elevation on north‐facing slopes. The carbon accumulation rates in the upper 6 m soil are highest (16.32 g C m−2 year−1) in the north‐facing alpine wet meadow and lowest (1.07 g C m−2 year−1) in the south‐facing alpine steppe. Elevation‐, slope‐, and slope aspect‐induced variations in soil properties and vegetation type are the main factors controlling the spatial SOC distribution. These results imply that the topography strongly affects the spatial heterogeneity of SOC in mountainous permafrost regions. Overall, our findings highlight that topographic factors should be further integrated into carbon models of carbon responses to climate change in permafrost‐affected soils.

Distribution and Storage Characteristics of Soil Organic Carbon in Tidal Wetland of Dandou Sea, Guangxi

In order to study the distribution characteristics of soil organic carbon (SOC) and soil organic carbon storage (SOCS) among different wetland types in Dandou Sea tidal wetland in Guangxi, firstly, based on Sentinel–2 imaging and random forest algorithm, combined with the existing tidal wetland data, a 10 m resolution tidal wetland dataset in Guangxi from 2019 to 2023 was generated, covering mangroves, salt marshes and tidal flats. The results show that the overall accuracy of the recognition results is higher than 96%, and the Kappa coefficient is higher than 0.95, which indicates high accuracy. Subsequently, the distribution characteristics and influencing factors of SOC and SOCS in different habitats were analyzed. The results showed that the SOC content of mangroves and salt marshes was higher than that of tidal flats. The SOC content of mangrove, salt marshes and tidal flats in 0–60 cm soil layer was 5.30–10.42 g/kg, 7.60–9.84 g/kg, and 1.29–2.25 g/kg, respectively. The changes of SOCS were 12.41–26.48 t/ha, 19.58–24.15 t/ha, and 3.61–6.86 t/ha, respectively. With the increase of soil depth, the SOC and SOCS of mangroves decreased gradually, and the SOC and SOCS of salt marshes increased gradually, and SOC and SOCS were mainly affected by soil bulk density (BD), soil moisture content (MC) and pH.

Spatial Distribution of Soil Organic Carbon in the Forests of Nepal

Soil organic carbon (SOC) is the major constituent of the soil organic matter. SOC stocks are determined by several factors such as altitude, slope, aspect, canopy cover, and vegetation type. Using the Third National Forest Inventory (2010–2014) data of Nepal, we assessed SOC status in forests at a national scale for the better understanding of the SOC distribution within Nepal. In this study, we estimated SOC against different factors and tested the spatial distribution of SOC using analysis of variance (ANOVA). The results showed that the forests located at a higher altitude have higher SOC accumulation. In particular, broadleaved forests exhibit a higher amount of carbon stock compared to other forest types. Moreover, forests with a larger canopy cover, located on a higher slope, and with a cooler aspect are associated with a higher accumulation of SOC. The SOC stock in the forest varies according to altitude, slope, aspect, canopy cover, and forest type, which might be attributed to the change in the microclimate of the area. The significant increase in SOC amount with the increase in slope, altitude, and crown cover helps to understand the extent of SOC distribution in forests. Broadleaved forests with a larger canopy cover in the higher altitude region have a higher SOC retention potential, which is likely to contribute to mitigating the impacts of climate change by sinking more carbon into the soil.

Rhizosheath drought responsiveness is variety-specific and a key component of belowground plant adaptation.

Biophysicochemical rhizosheath properties play a vital role in plant drought adaptation. However, their integration into the framework of plant drought response is hampered by incomplete mechanistic understanding of their drought responsiveness and unknown linkage to intraspecific plant-soil drought reactions. Thirty-eight Zea mays varieties were grown under well-watered and drought conditions to assess the drought responsiveness of rhizosheath properties, such as soil aggregation, rhizosheath mass, net-rhizodeposition, and soil organic carbon distribution. Additionally, explanatory traits, including functional plant trait adaptations and changes in soil enzyme activities, were measured. Drought restricted soil structure formation in the rhizosheath and shifted plant-carbonfrom litter-derived organic matter in macroaggregates to microbially processed compounds in microaggregates. Variety-specific functional trait modifications determined variations in rhizosheath drought responsiveness. Drought responses of the plant-soil system ranged among varieties from maintaining plant-microbial interactions in the rhizosheath through accumulation of rhizodeposits, to preserving rhizosheath soil structure while increasing soil exploration through enhanced root elongation. Drought-induced alterations at the root-soil interface may hold crucial implications for ecosystem resilience in a changing climate. Our findings highlight that rhizosheath soil properties are an intrinsic component of plant drought response, emphasizing the need for a holistic concept of plant-soil systems in future research on plant drought adaptation.

Global distribution of surface soil organic carbon in urban greenspaces

Urban greenspaces continue to grow with global urbanization. The global distribution and stock of soil organic carbon (SOC) in urban greenspaces remain largely undescribed and missing in global carbon (C) budgets. Here, we synthesize data of 420 observations from 257 cities in 52 countries to evaluate the global pattern of surface SOC density (0–20 cm depth) in urban greenspaces. Surface SOC density in urban greenspaces increases significantly at higher latitudes and decreases significantly with higher mean annual temperature, stronger temperature and precipitation seasonality, as well as lower urban greenness index. By mapping surface SOC density using a random forest model, we estimate an average SOC density of 55.2 (51.9–58.6) Mg C ha−1 and a SOC stock of 1.46 (1.37–1.54) Pg C in global urban greenspaces. Our findings present a comprehensive assessment of SOC in global urban greenspaces and provide a baseline for future urban soil C assessment under continuing urbanization.

The Content and Stratification of SOC and Its Humified Fractions Using Different Soil Tillage and Inter-Cropping

Five different tillage systems were researched in a Cambisol of a loam texture in the long-term experiment: conventional ploughing at 22–24 cm (CT), shallow ploughing at 16–18 cm (ShT), harrowing at 8–10 cm (MT1), harrowing at 14–16 cm (MT2), and no tilling (NT). The aim of this study was to determine how different tillage and inter-cropping influence the accumulation and distribution of SOC (soil organic carbon) and its compounds in different soil layers. SOC content changed depending on the soil tillage system and inter-crops used. Stratification ratios (SR) of SOC in the surface soil (0–10 cm) to that in the 10–20 cm (SR1) and 20–30 cm (SR2) were calculated. In our research, SR for SOC varied in the range from 0.97 to 1.35 for SR1 and from 1.02 to 1.99 for SR2. The main conclusion was that inter-crops increased the SOC accumulation in the 0–10 cm layer of all investigated treatments. It was concluded that different soil tillage systems and inter-crops influenced processes of soil carbon changes and affected OM humification in the soil. The formation of humified carbon compounds should be considered not only as a preservation and improvement of the soil productivity, but also as an environmental assessment of their impact on the soil sustainability and reduction in carbon dioxide emissions into the atmosphere. Our results suggest that sustainable tillage and inter-cropping management may contribute to climate mitigation regarding SOC accumulation in soil.

Optimizing nitrogen and phosphorus application to improve soil organic carbon and alfalfa hay yield in alfalfa fields.

Soil organic carbon (SOC) is the principal factor contributing to enhanced soil fertility and also functions as the major carbon sink within terrestrial ecosystems. Applying fertilizer is a crucial agricultural practice that enhances SOC and promotes crop yields. Nevertheless, the response of SOC, active organic carbon fraction and hay yield to nitrogen and phosphorus application is still unclear. The objective of this study was to investigate the impact of nitrogen-phosphorus interactions on SOC, active organic carbon fractions and hay yield in alfalfa fields. A two-factor randomized group design was employed in this study, with two nitrogen levels of 0 kg·ha-1 (N0) and 120 kg·ha-1 (N1) and four phosphorus levels of 0 kg·ha-1 (P0), 50 kg·ha-1 (P1), 100 kg·ha-1 (P2) and 150 kg·ha-1 (P3). The results showed that the nitrogen and phosphorus treatments increased SOC, easily oxidized organic carbon (EOC), dissolved organic carbon (DOC), particulate organic carbon (POC), microbial biomass carbon (MBC) and hay yield in alfalfa fields, and increased with the duration of fertilizer application, reaching a maximum under N1P2 or N1P3 treatments. The increases in SOC, EOC, DOC, POC, MBC content and hay yield in the 0-60 cm soil layer of the alfalfa field were 9.11%-21.85%, 1.07%-25.01%, 6.94%-22.03%, 10.36%-44.15%, 26.46%-62.61% and 5.51%-23.25% for the nitrogen and phosphorus treatments, respectively. The vertical distribution of SOC, EOC, DOC and POC contents under all nitrogen and phosphorus treatments was highest in the 0-20 cm soil layer and tended to decrease with increasing depth of the soil layer. The MBC content was highest in the 10-30 cm soil layer. DOC/SOC, MBC/SOC (excluding N0P1 treatment) and POC/SOC were all higher in the 0-40 cm soil layer of the alfalfa field compared to the N0P0 treatment, indicating that the nitrogen and phosphorus treatments effectively improved soil fertility, while EOC/SOC and DOC/SOC were both lower in the 40-60 cm soil layer than in the N0P0 treatment, indicating that the nitrogen and phosphorus treatments improved soil carbon sequestration potential. The soil layer between 0-30 cm exhibited the highest sensitivity index for MBC, whereas the soil layer between 30-60 cm had the highest sensitivity index for POC. This suggests that the indication for changes in SOC due to nitrogen and phosphorus treatment shifted from MBC to POC as the soil depth increased. Meanwhile, except the 20-30 cm layer of soil in the N0P1 treatment and the 20-50 cm layer in the N1P0 treatment, all fertilizers enhanced the soil Carbon management index (CMI) to varying degrees. Structural equation modeling shows that nitrogen and phosphorus indirectly affect SOC content by changing the content of the active organic carbon fraction, and that SOC is primarily impacted by POC and MBC. The comprehensive assessment indicated that the N1P2 treatment was the optimal fertilizer application pattern. In summary, the nitrogen and phosphorus treatments improved soil fertility in the 0-40 cm soil layer and soil carbon sequestration potential in the 40-60 cm soil layer of alfalfa fields. In agroecosystems, a recommended application rate of 120 kg·ha-1 for nitrogen and 100 kg·ha-1 for phosphorus is the most effective in increasing SOC content, soil carbon pool potential and alfalfa hay yield.

Effects of Straw Return Duration on Soil Carbon Fractions and Wheat Yield in Rice–Wheat Cropping System

In China’s subtropical rice–wheat cropping system, the changes in the soil organic carbon (SOC) pool due to long-term straw return and its connection with crop yield remain unclear. This study aims to provide insights into establishing a sensible straw return system by evaluating the differences in the distribution and variation rates of SOC, light fraction organic carbon (LFOC), heavy fraction organic carbon (HFOC), particulate organic carbon (POC), and mineral-associated organic carbon (MOC) in the 0–20 cm soil layer under different durations of straw return. Additionally, the study analyzes the relationship between the changes in SOC and its fractions and wheat yield. The experiment was conducted in 2019 in a rice–wheat rotation field with ten years of straw return treatments: no straw return (NR) or 1, 2, 3, 4, 5, 6, 7, 8, 9 year(s) of straw return (SR1–9), and an additional treatment in 2020 (10 years of straw return, SR10). The results revealed that with an increase in the duration of straw return, the contents of SOC, LFOC, HFOC, and POC gradually increased, showing the highest increments of 45.88%, 187.22%, 41.55%, 97.89%, and 28.21%, respectively, compared to the NR treatment. However, after eight years of straw return, the compound annual increase in soil organic carbon and its components was lower than in years 1–8, indicating a trend of diminishing increments. The SOC content and its variation were significantly correlated with the content and variation of LFOC, HFOC, POC, and MOC, with the highest sensitivity observed for the variation in LFOC, indicating the strong influence of the duration of straw return. The SOC and its fraction contents showed significant positive correlations with wheat yield, with the highest contribution to wheat yield increase attributed to an increase in LFOC content. In summary, straw return enhances the 0–20 cm deep soil carbon pool, with LFOC being the most sensitive indicator, reflecting the influence of the duration of straw return on soil carbon pools.

Dynamics of soil organic carbon pools following conversion of savannah to cocoa agroforestry systems in the Centre region of Cameroon

Afforestation of gramineous-woody savannah with cocoa agroforestry systems (cAFS) is a common farmer practice in Cameroon considered as sustainable. Nevertheless, the effects of afforestation of savannah with cAFS on soil organic carbon (SOC) turnover and content, and the factors controlling SOC accumulation and stabilization are unknown. SOC content at 0–10 cm soil layer, and SOC distribution in soil particle size fractions (0–20 μm fraction considered as mineral-associated organic carbon, MAOC; 50–2000 μm considered as particulate organic carbon, POC; and 20–50 μm), were compared in different systems settled on degraded savannah (orthic ferralsols). These systems included annual cropland (≈ 5 years old), cocoa monoculture (≈10 years old), and cAFS (from 20 to 60 years old) including different shade tree species such as Albizia adianthifolia, Canarium schweinfurthii, Dacryodes edulis, Milicia excelsa and Ceiba pentandra. Savannah and nearby secondary forest patches were also included in the design as controls. Soil 13C was analysed to investigate the soil carbon turnover after afforestation (C3 plants) of gramineous savannah (C4 plants).SOC significantly increased in the 0–10 cm depth from 10.6 ± 3.1 g C kg−1 in degraded savannah to 17.9 ± 5.6 g C kg−1 in cAFS reaching similar levels as in nearby secondary forests (16.3 ± 5.8 g C kg−1), while annual cropland and cocoa monoculture presented a non-significant decrease in SOC content. These changes were due to rapid loss of SOC derived from savannah plants (C4) – about 76% within the first 15 years after conversion, and higher gain of SOC derived from C3 plants in cAFS than in the other land uses (e.g. from 3.4 ± 1.5 g C kg−1 in savannah to 17.8 ± 5.7 g C kg−1 in cAFS). This SOC enrichment in cAFS was distributed in POC (64%), MAOC (30%) and the intermediate 20–50 μm soil fraction (6%). The higher annual litter input accumulated on a longer period in cAFS (20 to 60 years) than in cocoa monoculture (10 years) concomitant with the lower litter recalcitrance of associated trees compared to cocoa could explain the higher enrichment of SOC in all fractions in cAFS. The soil pH and exch. Ca2+ differed under the different shade tree species, and were positively correlated to SOC content. The highest contents of soil exch. Ca2+ induced by Ceiba and Milicia in the top 10 cm soil layer could contribute to increase SOC enrichment under those species through soil aggregation and related C stabilization. We found no strong evidence of the effect of soil texture on additional soil carbon accumulation in cAFS, especially for the more stable C pool (MAOC). Our results evidenced that savannah afforestation with cAFS appears as a valuable option for top soil carbon enrichment and should consider tree species associated to cocoa to enhance soil C sequestration, soil quality and cocoa production sustainability.

Spatial Distribution Patterns of Soil Organic Carbon in Karst Forests of the Lijiang River Basin and Its Driving Factors

The aim of this study was to explore the carbon storage potential of karst forest soils in the Lijiang River Basin, reveal the spatial pattern of soil organic carbon (SOC), investigate the contributions and pathways of each driving factor to the spatial distribution of soil organic carbon, and provide a scientific basis for assessing the carbon cycle function of karst forests in the region. We employed structural equation modeling (SEM) and correlation analysis to investigate the spatial distribution characteristics of forest soil organic carbon in different basin sections (upper, middle, and lower reaches) and soil layers at different depths of the Lijiang River. Additionally, the direct and indirect ratios of each factor were quantified. The results showed that the overall soil layer of karst forest soils in the Lijiang River Basin was shallow, and soil organic carbon was phenoconcentric. The distribution of soil organic carbon content in different watershed sections was upstream > downstream > midstream, and the distribution of readily oxidizable carbon (ROC) and dissolved organic carbon (DOC) was consistent, whereas the distribution of microbial biomass carbon (MBC) was upstream > midstream > downstream. The contribution of various biotic and abiotic factors to the spatial distribution of soil organic carbon in karst forests in the watershed was different, and their contributions were ranked in descending order as:soil physicochemical factors > soil organic carbon active fraction > sample elevation > sample species diversity, with the total effects of 1.148, 0.574, 0.284, and -0.013, respectively. Among them, the sample site elevation had only an indirect effect on soil organic carbon, and the soil organic carbon active fraction had only a direct effect on soil organic carbon. Among the driving factors, total soil nitrogen, soil oxidizable organic carbon, sample site species richness, and soil soluble organic carbon could be used as important predictors of soil organic carbon content in karst forests in the Lijiang River Basin. Therefore, it is necessary to establish an effective eco-environmental protection mechanism covering the whole Lijiang River Basin, to reduce and control the impact of anthropogenic disturbances (especially in the middle urban section of the Lijiang River Basin), and to enhance and protect the species diversity of karst forests in the basin in order to improve soil physicochemical properties, improve and enhance the content of the soil organic carbon active fraction, and enhance the soil organic carbon stocks of karst forests in the Lijiang River Basin through other effective ways, as well as to promote the enhancement of the regional forest carbon sink function.

Topographic correction of visible near‐infrared reflectance spectra for horizon‐scale soil organic carbon mapping

AbstractUnderstanding soil organic carbon (SOC) response to global change has been hindered by an inability to map SOC at horizon scales relevant to coupled hydrologic and biogeochemical processes. Standard SOC measurements rely on homogenized samples taken from distinct depth intervals. Such sampling prevents an examination of fine‐scale SOC distribution within a soil horizon. Visible near‐infrared hyperspectral imaging (HSI) has been applied to intact monoliths and split cores surfaces to overcome this limitation. However, the roughness of these surfaces can influence HSI spectra by scattering reflected light in different directions posing challenges to fine‐scale SOC mapping. Here, we examine the influence of prescribed surface orientation on reflected spectra, develop a method for correcting topographic effects, and calibrate a partial least squares regression (PLSR) model for SOC prediction. Two empirical models that account for surface slope, aspect, and wavelength and two theoretical models that account for the geometry of the spectrometer were compared using 681 homogenized soil samples from across the United States that were packed into sample wells and presented to the spectrometer at 91 orientations. The empirical approach outperformed the more complex geometric models in correcting spectra taken at non‐flat configurations. Topographically corrected spectra reduced bias and error in SOC predicted by PLSR, particularly at slope angles greater than 30°. Our approach clears the way for investigating the spatial distributions of multiple soil properties on rough intact soil samples.

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.

Selective uneven enrichment of soil organic carbon among different-sized sediments under a rain-induced overland flow: 13C stable isotope evidence

Soil organic carbon (SOC) enrichment varies among sediments of different sizes during rain-induced overland flow erosion. This selective transport of SOC is complex in conjunction with the exposure of labile and stable organic carbon (OC), accompanied by heterogeneous aggregate disintegration under raindrop effects. Utilizing the variations in δ13C values of SOC fractions, we traced this selective transport, linking it to aggregate-wrapped SOC changes during erosion. A modified soil pan facilitated the simultaneous monitoring of splash and sheet erosion via artificially simulated rainfall, with control over the intensity and slope. Aggregate composition, SOC distribution, and δ13C values in the erosion samples were analyzed. The results indicated that distinct sorting existed within the aggregate fragments. Along with SOC variation among different sediment sizes, the proportions of clay and fine silt within sediment aggregates increased as a function of slope and rainfall intensity, whereas particulate OC within aggregates decreased. The SOC enrichment ratios (ERocs) and δ13C values in splash-eroded sediments were positively correlated with those in sheet-eroded sediments. The ERocs in splash-eroded sediments were lower than those in sheet-eroded sediments, but δ13C values were the opposite. Moreover, δ13C values of SOC enriched in sediment particles of all sizes from aggregate stripping were lower than those of the original soil. This indicates that raindrop hits promote heavy C loss during sheet erosion, which is different for mineral-associated and particulate OC. As the slope and rainfall intensity increased, δ13C values for all sediment sizes decreased over the course of erosion. Interestingly, the highest δ13C values were observed under a rainfall intensity of 60 mm h−1, whereas the highest SOC concentrations were noted on a 5° slope. These observations suggest divergent mechanisms affect δ13C values and SOC concentrations in eroded sediments. All these results verified that selective sorting existed for the light SOC fraction. Finally, the internal selective transport of one SOC fraction may explain the enhanced mineralization and reaggregation capacity of the deposited sediments.

Variations in soil physico-chemical properties, soil stocks, and soil stoichiometry under different soil layers, the major forest region Liupan Mountains of Northwest China.

Liupan Mountains are an important region in China in the context of forest cover and vegetation due to huge afforestation and plantation practices, which brought changes in soil physio-chemical properties, soil stocks, and soil stoichiometries are rarely been understood. The study aims to explore the distribution of soil nutrients at 1-m soil depth in the plantation forest region. The soil samples at five depth increments (0-20, 20-40, 40-60, 60-80, and 80-100 cm) were collected and analyzed for different soil physio-chemical characteristics. The results showed a significant variation in soil bulk density (BD), soil porosity, pH, cation exchange capacity (CEC), and electric conductivity (EC) values. More soil BD (1.41 g cm-3) and pH (6.97) were noticed in the deep soil layer (80-100 cm), while the highest values of porosity (60.6%), EC (0.09 mS cm-1), and CEC (32.9 c mol kg-1) were reflected in the uppermost soil layer (0-20 cm). Similarly, the highest contents of soil organic carbon (SOC), total phosphorus (TP), available phosphorus (AP), total nitrogen (TN), and available potassium (AK) were calculated in the surface soil layer (0-20 cm). With increasing soil depth increment a decreasing trend in the SOC and other nutrient concentration were found, whereas the soil total potassium (TK) produced a negative correlation with soil layer depth. The entire results produced the distribution of SOCs and TNs (stocks) at various soil depths in forestland patterns were 0→20cm > 20→40cm > 40→60cm ≥ 60→80cm ≥ 80→100 cm. Furthermore, the stoichiometric ratios of C, N, and P, the C/P, and N/P ratios showed maximum values (66.49 and 5.46) in 0-20 cm and lowest values (23.78 and 1.91) in 80-100 cm soil layer depth. Though the C/N ratio was statistically similar across the whole soil profile (0-100 cm). These results highlighted that the soil depth increments might largely be attributed to fluctuations in soil physio-chemical properties, soil stocks, and soil stoichiometries. Further study is needed to draw more conclusions on nutrient dynamics, soil stocks, and soil stoichiometry in these forests.