Unveiling Divergent Trends in Soil Erosion and Soil Organic Carbon Displacement in Response to Climate and Land-Use Changes over China

Soil organic carbon (SOC) is an important component of soil fertility and agricultural production that also controls the atmospheric CO2 which affects the global carbon cycle. Soil erosion is a major hazard which is directly affected by the rainfall change caused by the climate change. SOC is depleted through soil erosion affected by a change in the rainfall pattern. This study aims at quantifying the impact of climate change on future soil erosion and SOC with respect to the different controlling parameters (slope, soil and landuse) of soil erosion. The study area is a part of the Narmada river basin in India. Future rainfall is estimated by least square support vector machine method using Hadley Centre coupled model, version 3 data of A2 scenario. Revised universal soil loss equation has been used to estimate the soil erosion spatially, and field data collection is done to estimate SOC. Regression–kriging (RK) method is used for spatial interpolation of SOC on the top surface considering ancillary information of the land. Results show that sediment load has changed by −5.33, 17.97 and 58.37 % in the 2020s, 2050s and 2080s, respectively, from current erosion rate. Soil erosion and SOC loss rate are higher in a high degree of slope (>20), while SOC stock is low here (5.77 gm/kg). Again, SOC stock (1.27 gm/kg) is high in the clay soil, but soil erosion and SOC loss are less, while sandy loam indicates the opposite. Agricultural land and fallow lands have higher rate of soil erosion and SOC loss, while stock SOC is 12.24 and 9.65 gm/kg, respectively. Results show that soil erosion and SOC loss will be increased in the future and steeper slopes, sandy soil and fallow lands are more vulnerable to the loss.

Soil organic carbon and soil erodibility response to various land-use changes in northern Thailand

Impacts of land use and biophysical properties on soil carbon stocks in southern Yunnan, China

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

137Cs tracing dynamics of soil erosion, organic carbon and nitrogen in sloping farmland converted from original grassland in Tibetan plateau

Estimating temporal and spatial changes in soil organic carbon stocks and its controlling factors in moraine landscapes in Denmark

Abstract. Erosion is an Earth system process that transports carbon laterally across the land surface and is currently accelerated by anthropogenic activities. Anthropogenic land cover change has accelerated soil erosion rates by rainfall and runoff substantially, mobilizing vast quantities of soil organic carbon (SOC) globally. At timescales of decennia to millennia this mobilized SOC can significantly alter previously estimated carbon emissions from land use change (LUC). However, a full understanding of the impact of erosion on land–atmosphere carbon exchange is still missing. The aim of this study is to better constrain the terrestrial carbon fluxes by developing methods compatible with land surface models (LSMs) in order to explicitly represent the links between soil erosion by rainfall and runoff and carbon dynamics. For this we use an emulator that represents the carbon cycle of a LSM, in combination with the Revised Universal Soil Loss Equation (RUSLE) model. We applied this modeling framework at the global scale to evaluate the effects of potential soil erosion (soil removal only) in the presence of other perturbations of the carbon cycle: elevated atmospheric CO2, climate variability, and LUC. We find that over the period AD 1850–2005 acceleration of soil erosion leads to a total potential SOC removal flux of 74±18 Pg C, of which 79 %–85 % occurs on agricultural land and grassland. Using our best estimates for soil erosion we find that including soil erosion in the SOC-dynamics scheme results in an increase of 62 % of the cumulative loss of SOC over 1850–2005 due to the combined effects of climate variability, increasing atmospheric CO2 and LUC. This additional erosional loss decreases the cumulative global carbon sink on land by 2 Pg of carbon for this specific period, with the largest effects found for the tropics, where deforestation and agricultural expansion increased soil erosion rates significantly. We conclude that the potential effect of soil erosion on the global SOC stock is comparable to the effects of climate or LUC. It is thus necessary to include soil erosion in assessments of LUC and evaluations of the terrestrial carbon cycle.

Land Use Change (LUC), especially deforestation in tropical regions, significantly contributes to global anthropogenic greenhouse gas (GHG) emissions. Here, we address potential combined impacts of LUC and Climate Change (CC) on Soil Organic Carbon (SOC) stocks in the Ethiopian highlands. The soil model Q was employed to predict SOC stocks for various combinations of LUC and CC scenarios until the year 2100. Four reference scenarios (cropland, bushland, natural forest, and Eucalyptus plantations under contemporary climatic conditions) were evaluated against reported measurements of SOC stocks. We studied impacts of six common LUC scenarios, including deforestation and planting Eucalyptus, on SOC stocks under contemporary and future climates. To assess the impact of CC, effects of elevated temperature (mean annual temperature + 2.6 °C) together with three litterfall scenarios (no change in litterfall, a 5% reduction and 22% increase, designated CC0, CCd, and CCi, respectively) were considered to test potential vegetation responses to increases in temperature and atmospheric CO2 concentrations. Most of the tested combinations of LUC and CC led to losses of SOC stocks. Losses were most severe, both relatively and absolutely, in the deforestation scenarios: up to 30% was lost if natural forest was converted to cropland and temperature increased (under the CC0 scenario). Gains in SOC stocks of 4–19% were modelled when sparse vegetation was converted to more dense vegetation like Eucalyptus plantation with substantially increased litterfall (the CCi scenario). Elevated temperature accelerated decomposition rates, leading to circa 8% losses of SOC stocks.We conclude that effects of LUC and CC on SOC stocks are additive and changes in litterfall caused by LUC determine which has the largest impact. Hence, deforestation is the biggest threat to SOC stocks in the Ethiopian highlands, and stocks in sparse vegetation systems like cropland and bushland are more sensitive to CC0 than LUC. We recommend conservation of natural forests and longer rotation periods for Eucalyptus plantations to preserve SOC stocks.Finally, we suggest that use of the Q model is a viable option for national reporting changes in SOC stocks at Tier 3 within the LULUCF sector to the United Nations Framework Convention on Climate Change (UNFCCC) as it is widely applicable and robust, although it only requires input data on a few generally available variables.

The topography and land use/land cover (LULC) of the hillslope play a significant influence on soil erosion because of water, which is considered as a principal factor for the reduction of soil organic carbon content. Reliable information on the impact of erosion mechanism on soil organic carbon stock (SOCS) is essential for effectively accounting for the carbon flux that influences climate change. The main objectives of this study were to determine soil erosion based on the variation of 137 Cs (Radiocesium) radionuclide activity at various hillslope positions and LULC in a hilly and mountainous region of the north‐western Himalayas. Additionally, the relationship between 137 Cs concentration, soil erosion rate and SOCS were examined. Fallout radionuclide‐ 137 Cs have emerged as a suitable method for assessing soil erosion in hilly and mountainous regions where rugged topography and extreme weather events restrain the conventional soil erosion assessment. The study revealed very high soil erosion rates of 32.89 and 30.70 t ha −1 year −1 in the lower hillslope positions with cultivated fields. The lowest soil erosion was obtained with a mean of 0.47 t ha −1 year −1 from the ridge with grassland, followed by the upper hillslope (5.50 t ha −1 year −1 under deodar forest and 14.07 t ha −1 year −1 under pine forest), and the middle hillslope (1.58 t ha −1 year −1 for deodar and 7.77 t ha −1 year −1 for pine forest). The soil erosion rates differ significantly between cultivated and forested regions, and there is also a significant difference between deodar and pine forests. Moreover, a significant difference was found between topographic positions concerning 137 Cs, SOCS and soil redistribution rate. This difference was more pronounced at hillslope positions with different LULC. In both disturbed (cultivated) ( r 2 = .111) and undisturbed (forested and grassland) ( r 2 = .356) soils, positive and statistically significant ( p < .005) poor relationships were found between SOCS and 137 Cs inventory. This indicates the presence of various factors influencing the soil organic carbon stock (SOCS) mechanism or the indirect contribution of soil erosion‐induced carbon loss. This suggests that forest cover can enhance SOCS in the soil, mitigating the adverse effects of soil erosion and climate change. Consequently, 137 Cs could be effectively used to quantify the SOC stock in soil redistribution over the hillslope affected by soil erosion. Statistical analyses indicated that the 137 Cs inventory, SOCS and erosion were significantly affected by various hillslope positions and LULC types.

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

Effects of soil erosion and reforestation on soil respiration, organic carbon and nitrogen stocks in an eroded area of Southern China

Grazing exclusion has been widely used to restore the degraded alpine grasslands on the Qinghai-Tibetan Plateau (QTP). However, the dynamics of soil organic carbon (SOC) and soil total nitrogen (STN) pools after grazing exclusion and their controlling factors are currently less understood in this region. Here, a meta-analysis was conducted to quantitatively assess the changes in SOC and STN stocks in topsoil (0–30 cm) following grazing exclusion in three major grassland types (alpine meadow, alpine steppe, and alpine desert steppe) on the QTP and to explore the potential factors controlling the effects of grazing exclusion on SOC and STN stocks. The results showed that overall, grazing exclusion significantly increased SOC stock by 16.5% and STN stock by 11.2%. Significant increases in both SOC and STN stocks were observed after grazing exclusion of alpine meadow. In contrast, grazing exclusion did not improve SOC and STN stocks in the other two grassland types. The difference in mean annual precipitation among grassland types was a likely reason for the different dynamics of SOC and STN stocks after grazing exclusion. The effect sizes of both SOC and STN stocks were positively related to the duration of grazing exclusion, and a positive relationship was detected between the effect size of SOC stock and that of STN stock, demonstrating that the dynamics of SOC and STN were closely coupled during the period of grazing exclusion. However, grazing exclusion had no impact on soil C:N ratio for all grassland types, indicating that soil C:N ratio was generally stable after grazing exclusion. Therefore, it is suggested that the increase in STN can support continuous SOC accumulation following grazing exclusion. In conclusion, the findings suggest that the effects of grazing exclusion on SOC and STN stocks differ among grassland types on the QTP, and grazing exclusion of alpine meadows may provide substantial opportunities for improving SOC and STN stocks in this region.

Evaluation of projected soil organic carbon stocks under future climate and land cover changes in South Africa using a deep learning approach

Land-use changes affect soil organic carbon (SOC) stocks over decades. However, IPCC default for greenhouse gas emissions reporting suggests a simple linear SOC stock change over 20 years only. Using process-based modelling approaches such as RothC to describe SOC dynamics after land-use change requires model validation. However, there are only few long-term field experiments where SOC stocks have been observed long enough to get sufficient data for such a model validation. This lack of data makes validating models for large-scale use challenging.Based on empirical data from over 3000 sites from the German Agricultural Soil Inventory we selected 204 sites with land-use change history within the last 60 years and created an artificial data-set using a reciprocal modeling approach. This approach utilizes machine learning models trained on sites under permanent land use to predict SOC stocks for similar sites where the land use had been changed. In addition, we extracted further empirical data from over 30 sites with land-use change in the temperate zone from a comprehensive meta-analysis.These two datasets were used to test the ability of the well-known SOC model RothC to simulate land-use change effects on SOC stocks. In these tests, we use the observed or predicted SOC stocks assumed at equilibrium to model the carbon input under permanent land use and corresponding SOC dynamics after land-use change. These modelled SOC dynamics are then compared with observed SOC stocks after land-use change.We will discuss opportunities and challenges of using process-based models to describe SOC dynamics after land-use change on regional to national scale.&amp;#160;

Soil organic carbon stock is closely related to aboveground vegetation properties in cold-temperate mountainous forests