Changes In Soil Organic Carbon Content Research Articles

Carbon sequestration potential and its main drivers in soils under alfalfa (Medicago sativa L.)

As a perennial forage crop, alfalfa (Medicago sativa L.) has been extensively utilized for the vegetation restoration of degraded soil and provides feedstock for forage. Its high usage can be attributed to its high yield potential and the increasing soil organic carbon (SOC) sequestration of alfalfa cultivation. However, the impact of land conversion to alfalfa on SOC content and its underlying drivers remain unclear. We performed a meta-analysis at the global scale to explore the quantified effects of alfalfa cultivation on SOC content and identify its controlling factors. We employed 1699 pairwise data points from 90 publications based on cropland/abandoned land conversion to alfalfa. Globally, cropland (cropland-alfalfa) and abandoned land (abandoned land-alfalfa) conversion to alfalfa enhanced SOC content by 12.1 % and 13.7 %, respectively. Alfalfa exhibited greater SOC content benefits in the surface soils (0–20 cm) with a lower level of initial SOC (<16 g kg−1), regardless of the land conversion type. Cropland-alfalfa was observed to increase SOC content with fertilization, irrigation, and conventional tillage in the long term (>5 years). Furthermore, abandoned land-alfalfa enhanced SOC content in the absence of alfalfa biomass removal and for longer cultivation durations (>5 years). Boosted regression tree analyses indicated variations in soil properties (75 % for cropland-alfalfa and 65 % for abandoned land-alfalfa) as the primary factors driving changes in SOC content. The dominant drivers were determined as the soil layer (51.6 %), cultivation duration (13.1 %), and initial SOC (12.9 %) for cropland-alfalfa, and initial SOC (43.7 %), soil layer (24.6 %) and cultivation duration (17.1 %) for abandoned land-alfalfa. Land conversion to alfalfa has great potential for SOC sequestration, particularly in low-fertility soils. Therefore, alfalfa cultivation is highly recommended for degraded lands due to its SOC sequestration benefits in vegetation restoration.

Plant- and microbial-mediated soil organic carbon accumulation in Spartina alterniflora salt marshes

Coastal wetlands play a crucial role in the global carbon (C) cycle; however, they have been affected by the invasive plant Spartina alterniflora. The impacts of S. alterniflora invasions on soil organic carbon (SOC) source and composition in wetlands are poorly understood compared to SOC stocks. This hinders the accurate estimation of blue C budgets owing to the long-term effects of S. alterniflora invasions. Here, a space-for-time substitution method was applied to investigate SOC accumulation in invasive 5-, 10-, 15-, 18-, and 21-year-old S. alterniflora communities. This was compared with bare flat in the topsoil (0–10 cm) and subsoil (30–60 cm) of coastal wetlands. Biomarkers (lignin phenols and amino sugars) and Fourier transform infrared spectroscopy were used to describe the accumulation patterns of plant- and microbial-derived C across varying S. alterniflora invasion times, as well as associated stabilization mechanisms. Plant-derived C dominated the SOC content compared to microbial-derived C during S. alterniflora invasions, while microbial-derived C played a more critical role in SOC stability than that of plant-derived C. At both soil depths, microbial-derived C gradually increased with increasing invasion time, whereas plant-derived C initially increased and then decreased, consistent with changes in SOC content. The variation in inundation conditions, influenced by tides, emerged as a significant factor affecting the accumulation of plant- and microbial-derived C, as well as SOC stability. Decreased inundation frequency and increased oxygen exposure, driven by tides, may lead to a rapid rise in SOC mineralization and the enrichment of microbial-derived C at the expense of plant-derived C. Consequently, this process improved SOC stability. These findings hold substantial implications for potential C loss resulting from the long-term impacts of S. alterniflora invasions. Furthermore, they may help predict the long-term effects of S. alterniflora invasions on blue C budgets within the context of global change scenarios.

Dynamic modeling of topsoil organic carbon and its scenarios forecast in global Mollisols regions

Global Mollisols regions play crucial roles in maintaining world food security, performing ecosystem services and global carbon cycling. Little is known about the spatial and temporal variability of soil organic carbon (SOC), future trends, and the driving forces of changes in each Mollisols region. The aim of this work is to trace the SOC dynamics during the 2000–2020 period and forecast its dynamics for 2020–2040 period (every 5 years) across the global Mollisols regions, highlighting the driving factors for these changes. We used bare soil images and environmental covariates to construct a robust prediction model of SOC using machine learning. The best model was used to forecast future changes in SOC content under different emission scenarios. Also, the role of different predictor variables in predicting and driving SOC changes is indicated with the help of the shapley value algorithm. Results show that SOC content in the current global Mollisols regions is 26.45 g kg−1 in Ukraine, 21.34 g kg−1 in Northeast China, 21.05 g kg−1 in the USA and 15.59 g kg−1 in Argentina. However, they have been decreasing since 2001 and showed a slowing trend, with the highest and lowest rates of 11.45% in Ukraine and 7.33% in the USA, respectively. The forecast under different climate scenarios shows a slight decrease in SOC content within a range of 0.46%–1.22%. Among them, SSP 245 is more consistent with the current trend of SOC content, while SSP585 indicates the greatest loss of SOC content. Results revealed that the driving factors for SOC prediction in descending order were meteorologic, parent material, terrain and vegetation. All soil and meteorology variables contributed by 71%, while soil texture fractions and temperature were the top 20% of these variables. The main factors driving SOC changes from high to low latitudes are temperature, precipitation, and vegetation. It can be concluded that the temporal transfer model is a powerful tool to trace and forecast the dynamics of SOC in Mollisols regions at the global scale, enabling a clear understanding and ranking the factors affecting this process under diverse climate conditions.

Detecting the temporal trend of cultivated soil organic carbon content using visible near infrared spectroscopy

Monitoring changes in soil properties is essential to ensure ecosystem function and agricultural productivity. This study evaluated the ability of visible near infrared (Vis-NIR) spectroscopy to detect the temporal trend in soil organic carbon (SOC) content after 5 years in a 12 km2 agricultural catchment in western France. Partial least squares regression models were developed using soil samples from a local dataset collected in 2013 at two depths (198 samples at 0–15 cm and 196 samples at 15–25 cm) to predict SOC content of 111 new samples collected in 2018 at the same locations and at similar depths (0–15 cm and 15–25 cm). Two approaches, which differed in whether or not they considered the SOC content variability that can result from collecting soil samples at two depths, were applied. For both approaches, the potential benefit of “temporal spiking” was evaluated by adding 10% of 2018 samples to the 2013 dataset. The results showed that removing outliers and stratifying the calibration dataset by depth yielded the highest accuracy, with SOC RMSEP of 4.1 and 2.7 g.kg−1 for 0–15 and 15–25 cm, respectively. Moreover, temporal spiking improved five of eight predictions (stratifying or not the calibration dataset by depth, removing or not poorly predicted outliers), with increases in the ratio of performance to deviation of 0.10–0.44. Furthermore, comparing observed and predicted changes in SOC content showed that Vis-NIR spectroscopy estimated its trend over time in most cases.

Unraveling the significance of soil organic carbon-gravel parameterization: Insights into soil water and heat transport on the Tibetan Plateau

In the Tibetan Plateau (TP) soil water and heat transfer process, soil organic carbon (SOC) and gravel content are considered as the most influential soil texture factors. However, the issues of underestimating SOC and neglecting gravel effect affected the simulation performance of CLM5.0 on soil moisture (SM) and soil temperature (ST). This paper proposed a new parameterization scheme, the organic carbon-gravel (OC-G) scheme, to simulate ST and SM from 1990 to 2018. The results showed that correlation between the simulated and observed ST or SM was higher, and the error was smaller, after the modification of the parameterization scheme. This improvement justifies the applicability of the scheme for soil hydrothermal simulations on the TP. The experiment described that ST and SM were more sensitive to changes in SOC content. And changes in gravel or SOC content had the “Same-Frequency” effect in the northeast and southeast TP. When the SOC and gravel content changed at the same time, the effects on ST and SM were a “cumulative” effect. The change directly affected the memory time of ST and SM in summer. Specifically, when the SOC content was increased, the memory time of SM increased in the northwest and decreased in the southeast. When gravel content was increased, the memory time of SM decreased in the northwest but increased in the southeast, but the memory time of ST remained largely unchanged. Changes to the abnormal duration may alter summer weather and climate in Eastern China.

Temporal changes in soil chemical compositions in acidified mountain forest soils of Czech Republic

The study aimed to investigate the temporal changes of pH, sorption complex, and structure of soil organic matter through the forest soil profile under beech and spruce forests located in Jizera mountains (Czech Republic) and affected by natural and anthropogenic acidification. Soil samples were collected in four different years (2008, 2013, 2015, and 2020) in each horizon: fermented horizons (F), humified horizons (H), organo-mineral horizons (A), and subsurface mineral horizons (B) (cambic or spodic). The cation exchange capacity (CEC), base saturation (BS), exchangeable element contents, pH, and soil organic carbon content (SOC) were determined. The infrared soil spectra were used to calculate indices of potential wettability, aromaticity, and decomposition. Our results showed that most nutrients and aliphatic compounds were retained in the uppermost soil layers. The aromaticity of organic matter increased with depth, while polysaccharides, regarding the decomposition compound, disappeared through the soil horizons. In a long-term observation, SOC content had constantly increased under beech, while spruce remained stable in the organic horizons. Exchangeable element contents increased in each horizon, except for Al and Fe; their content quickly decreased in F horizons and slowly decreased in H horizon under both forest tree species, while the deeper horizons remained constant, but increased in A horizon under spruce. Continuously increasing base cations concentrations in sorption complex of both forest tree species during the study period revealed the effect of forest stand types on acid deposition reduction and mitigation. The temporal changes in CEC, BS, SOC, and soil wettability are more intensive in beech than in spruce forest floor.

Anthropogenic soil management performs an important role in increasing soil organic carbon content in northeastern China: A meta-analysis

The black soil region of northeastern China stores large amounts of soil organic carbon (SOC), so understanding the changes of SOC content and its influencing factors is necessary for understanding the global carbon cycle. These changes, however, vary with tillage, fertilization, cropping system and other soil management methods. Synthesizing and evaluating these studies is necessary to understand the mechanism of change in SOC content and for predicting future SOC content in cropland ecosystems in this region. We therefore used a meta-analysis of 666 observations from 91 publications to clarify the effects of type of soil management (tillage, fertilization and cropping system) on SOC content. The results indicated that soil management significantly increased SOC content by 8.3% compared to the initial content. SOC content increased significantly by 16.2% with organic fertilizer (OF) and by 19.6% with organic fertilizer combined with chemical fertilizer but decreased significantly by 3.9% without fertilization compared to the initial experiments (P < 0.05). SOC content increased significantly by 9.3% and 5.6% under conventional and deep tillage, respectively. SOC content increased significantly by 13.5% and 4.0% under crop monoculturing and crop rotation, respectively. The effect size of SOC content was significantly correlated with mean annual precipitation, mean annual temperature, the contents of clay and soil nutrients. The results will help us to understand the responses of SOC content to various types of soil management and to identify the most suitable soil management type in northeastern China.

Digital Mapping of Soil Organic Carbon Using UAV Images and Soil Properties in a Thermo-Erosion Gully on the Tibetan Plateau

Thermo-erosion gullies (TGs) are typical thermokarst features in upland permafrost; the soil organic carbon (SOC) of TGs has an important influence on soil quality in cold regions. The objectives of this study were to estimate the spatial distribution of SOC content in a typical TG on the northeastern Tibetan Plateau in China by using soil properties from seven different TGs and covariates from unmanned aerial vehicle (UAV) images, and to characterize the SOC content changes in four representative landscape regions (NO-Slumping, Slumping1, Slumping2, and Slumped) within this typical TG. The support vector machine (SVM) was the optimal machine learning algorithm for SOC content prediction, which explained 53.06% (R2) of the SOC content variation. Silt content was the most influential factor which demonstrated a positive relationship with SOC content in different TGs. In addition, the SOC content in the TGs was related to the landscapes. Severe Slumping (Slumping2: 150.79 g·kg−1) had a lower SOC content than NO-Slumped (163.29 g·kg−1) and the initial slumping stage (Slumping1: 169.08 g·kg−1). The results suggested that SVM was an effective algorithm to obtain a profound understanding of the SOC content over space, while future research needs to pay more attention to the SOC content distribution in the different TGs.

Altered Organic Matter Chemical Functional Groups and Bacterial Community Composition Promote Crop Yield under Integrated Soil–Crop Management System

Sustainable agricultural production is essential to ensure an adequate food supply, and optimal farm management is critical to improve soil quality and the sustainability of agroecosystems. Integrated soil–crop management based on crop models and nutrient management designs has proven useful in increasing yields. However, studies on its effects on the chemical composition of soil organic carbon (SOC) and microbial community composition, as well as their linkage with crop yield, are lacking. Here, we investigated the changes in SOC content, its chemical functional groups, and bacterial communities, as well as their association with crop yield under different farmland management based on four farmland management field trials over 12 years (i.e., FP: farmer practice; IP: improved farmer practice; HY: high-yield system; and ISSM: integrated soil–crop system management). The crop yield increased by 4.1–9.4% and SOC content increased by 15–87% in ISSM compared to other farmland management systems. The increased proportion of Methoxy C and O-alkyl C functional groups with a low ratio of Alkyl C/O-alkyl C, but high Aliphatic C/Aromatic C in ISSM hints toward slow SOC decomposition and high soil C quality. The relative abundances of r-strategists (e.g., Firmicutes, Myxobacteria, and Bacteroidetes) was highest under the ISSM. Co-occurrence network analysis revealed highly complex bacterial communities under ISSM, with greater positive links with labile SOC functional groups. The soil fertility index was the main factor fueling crop yields, as it increased with the relative abundance of r-strategists and SOC content. Our results indicated that crop yield advantages in ISSM were linked to the high C quality and shifts in bacterial composition toward r-strategists by mediating nutrient cycling and soil fertility, thereby contributing to sustainability in cropping systems.

Assessing residue and tillage management options for carbon sequestration in future climate change scenarios

Soil carbon depletion is a major concern for food security in drylands. The objective of this study is to test tillage with residue management under sequential and intercropping systems for carbon sequestration in semi-arid tropical drylands of India. We report the findings from a long-term field experiment (9 years) used to simulate the effect of residue and tillage management in Maize-chickpea sequential and Maize-Pigeonpea intercropping systems for the four possible future climate projections using APSIM model. These findings demonstrate a sustainable route with inclusive growth, as pledged at the UN climate change summit. A comparison of results under SSP 2.6 and 4.5 Wm−2 with SSP 8.5 shows that demand pressure from competitive marketplaces inhibits the establishment of soil carbon sinks and significantly reduces crop yields, likely due to indiscriminate chemical fertilizer use. We observed that a better decision in selecting cropping system might improve soil organic carbon content (SOC). SOC content ranging from 0.9 to 1.2% in Maize-pigeonpea intercropping and 0.85–1.1% in maize-chickpea sequential cropping systems, demonstrate good potential in the climate change mitigation exertions. Early SOC saturation (20 years) led to a decreased carbon stock in topsoil without residue addition practises. The addition of crop residues significantly increased SOC levels under both conventional and minimum tillage and created additional income for farmers. Simulation analysis showed impact of SOC changes on crop yield which remained nearly stable for 85 years. Therefore, hardy straw biomass of crops covering a large tract in dryland tropics, can be a scalable and sustainable solution to yield losses, while mitigating climate change through carbon sequestration.

土壤碳氮特征沿干旱梯度时空格局及对气候变化的响应——基于中国生态系统研究网络(CERN)长期定位监测数据

PDF HTML阅读 XML下载 导出引用 引用提醒 土壤碳氮特征沿干旱梯度时空格局及对气候变化的响应——基于中国生态系统研究网络(CERN)长期定位监测数据 DOI: 10.5846/stxb202205311527 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 中国科学院国际合作局对外合作重点项目(121311KYSB20170004);中国科学院战略性先导科技专项(XDA19020305);中国博士后科学基金面上资助项目(2020M670439) Spatio-temporal patterns of soil carbon and nitrogen characteristics along aridity gradients and their responses to climate change: Based on long-term field observation data of Chinese Ecosystem Research Network Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:土壤碳氮含量及其化学计量特征是表征生态系统碳汇能力和土壤质量的重要指标,在支撑生态系统结构功能以及缓解气候变化中起着关键作用。利用中国生态系统研究网络(CERN)长期定位监测数据,分析了土壤碳氮特征沿干旱梯度的时空规律及其对气候变化的响应。结果表明:空间上,典型荒漠草原生态系统随着干旱加剧,土壤有机碳和全氮含量减少,土壤有机碳对干旱响应的敏感性降低,而土壤全氮对干旱响应的敏感性增加,土壤有机碳随土壤全氮含量的增加而增加。时间上,2005-2018年,荒漠草原生态系统土壤有机碳和全氮含量变化速率沿干旱梯度表现出由负转正的增加趋势,其中,干旱区呈减少趋势,半干旱和半湿润地区呈增加趋势,鄂尔多斯站和沙坡头站呈显著增加趋势。从影响因素来看,土壤碳氮特征对降水量增加的敏感性沿干旱梯度呈现出先增强后减弱的"上凸"抛物线趋势,温度变化对土壤碳氮特征的调控没有表现出明显的干旱梯度效应。土壤碳氮比、土壤有机碳含量、土壤全氮含量对降水量和平均温度变化响应的敏感性均依次降低。不同干旱梯度土壤碳氮特征的变化规律为未来气候变化下生态系统结构与功能预测提供科学依据。 Abstract:Soil organic carbon content (SOC), soil total nitrogen content (TN) and its ecological stoichiometric characteristics indicate the carbon sink efficiency and soil quality of ecosystem, and play the critical role in supporting ecosystem structure and function and mitigating climate change. Using long-term field observation data of ecological stations of the Chinese Ecosystem Research Network (CERN), this study analyzed the spatio-temporal patterns of the SOC, TN and its stoichiometric characteristics of soil, and their responses to climate change along aridity gradient. Results showed that with the aridity intensifying spatially, the SOC and TN decreased, the response sensitivity of SOC to aridity decreased and that of the TN increased. The SOC was increased along the TN increasing. Temporally, the rate of SOC and TN changes with aridity gradient showed increased with the aridity mitigating, which were negative in the aridity region and positive in semi-arid region from 2005 to 2018. The SOC and TN of Shapotou station and Erdos station were significant increased with aridity change in past more than one decade. Additionally, the response sensitivity of the SOC, TN and stoichiometric characteristics to precipitation increasing showed an "upwardly convex" pattern, which firstly increased and then decreased with the aridity gradient, but none for temperature. The response sensitivity of the SOC, TN and carbon-nitrogen ratio to changes in precipitation and temperature were as follows: the sensitivity of soil carbon-nitrogen ratio > the sensitivity of SOC > the sensitivity of TN. It is implied that the rule of the SOC, TN and its ecological stoichiometric characteristics changes in different aridity gradient region provide the scientific basis for the of ecosystem structure and function prediction under future climate change. 参考文献 相似文献 引证文献

Soil organic carbon primarily control the soil moisture characteristic during forest restoration in subtropical China

Soil organic carbon (SOC) is a crucial component of the soil carbon pool that regulates fundamental soil properties and water status. In the global context of restoring vegetation, the soil carbon-water coupling relationship has gained attention. In particular, the regulatory mechanism of SOC on soil moisture requires further research. In this study, three typical forests in subtropical China were chosen as restoration sequences to investigate the changes in SOC and soil moisture during subtropical forest restoration and its regulation mechanisms: broadleaf-conifer mixed forest (EF), broad-leaved forest (MF), and old-growth forest (LF). The soil water content (35.71 ± 1.52%), maximum water holding capacity (47.74 ± 1.91%), capillary water holding capacity (43.92 ± 1.43%), and field water holding capacity (41.07 ± 1.65%) in LF were significantly higher than those in EF (p &amp;lt; 0.01). As forest restoration progressed, the amount of litter returning to the soil increased gradually, and the SOC content (0–100 cm) increased from 9.51 ± 1.42 g/kg (EF) to 15.60 ± 2.30 g/kg (LF). The SOC storage increased from 29.49 ± 3.59 to 42.62 ± 5.78 Mg/ha. On one hand, forest restoration led to a change in SOC content, which optimizes the soil structure and enhances soil porosity (path coefficient of 0.537, p &amp;lt; 0.01), further leading to a change in soil water content (path coefficient of 0.940, p &amp;lt; 0.01). On the other hand, the increase in SOC influenced the change in soil nutrient content, i.e., total nitrogen (TN) and total phosphorus (TP) (path coefficient of 0.842, p &amp;lt; 0.01). Changes in SOC and soil nutrients stimulated changes in the stoichiometric ratio, i.e., C:P and N:P (path coefficients of 0.988 and –0.968, respectively, p &amp;lt; 0.01), and the biological activity in soil changed appropriately, which eventually led to a change in soil water content (path coefficient of –0.257, p &amp;lt; 0.01). These results highlight the changes in SOC and soil water content (SWC), as well as the mechanism of SOC controlling SWC as a result of vegetation restoration, which is of tremendous importance for advancing our understanding of the eco-hydrological process of subtropical forest restoration.

Understanding the influencing factors and mechanisms (land use changes and check dams) controlling changes in the soil organic carbon of typical loess watersheds in China

AbstractStudying the distribution patterns and controlling mechanisms of soil organic carbon (SOC) based on the comprehensive performance of vegetation restoration and check dams at the watershed scale is important for understanding carbon cycling processes in nature. Two typical watersheds (Xinshui River and Zhujiachuan watershed) of the Loess Plateau were selected to evaluate the factors affecting the change in SOC content, and then the key factors were considered in the genetic algorithm‐support vector regression (GA‐SVR) model to predict SOC content. The results showed that the topography, vegetation, and soil characteristics had significant effects on the SOC content in the upland hillslopes, while the SOC content in the check dams was significantly affected by depth and soil characteristics. The soil organic carbon storage (TSOC) in the check dams could be evaluated and predicted by the vegetation index (NGRDI) and area of the subwatershed. The GA‐SVR model had good prediction accuracy and stable performance in predicting SOC content. According to the model simulation results, bulk density (BD), mean weight diameter (MWD), elevation, NGRDI, clay ratio (CR), and slope could be used to predict the surface SOC content of the Loess Plateau. Furthermore, depth, CR, MWD, BD, and median particle size (D50) could be applied in the model to predict the SOC content at different depths in the check dams. This study explored the potential control factors of SOC content and predicted SOC content from multiple angles, which can provide basic support for the study of the carbon sequestration on the Loess Plateau.

Changes of SOC Content in China’s Shendong Coal Mining Area during 1990–2020 Investigated Using Remote Sensing Techniques

Coal mining, an important human activity, disturbs soil organic carbon (SOC) accumulation and decomposition, eventually affecting terrestrial carbon cycling and the sustainability of human society. However, changes of SOC content and their relation with influential factors in coal mining areas remained unclear. In the study, predictive models of SOC content were developed based on field sampling and Landsat images for different land-use types (grassland, forest, farmland, and bare land) of the largest coal mining area in China (i.e., Shendong). The established models were employed to estimate SOC content across the Shendong mining area during 1990–2020, followed by an investigation into the impacts of climate change and human disturbance on SOC content by a Geo-detector. Results showed that the models produced satisfactory results (R2 &gt; 0.69, p &lt; 0.05), demonstrating that SOC content over a large coal mining area can be effectively assessed using remote sensing techniques. Results revealed that average SOC content in the study area rose from 5.67 gC·kg−1 in 1990 to 9.23 gC·kg−1 in 2010 and then declined to 5.31 gC·Kg−1 in 2020. This could be attributed to the interaction between the disturbance of soil caused by coal mining and the improvement of eco-environment by land reclamation. Spatially, the SOC content of farmland was the highest, followed by grassland, and that of bare land was the lowest. SOC accumulation was inhibited by coal mining activities, with the effect of high-intensity mining being lower than that of moderate- and low-intensity mining activities. Land use was found to be the strongest individual influencing factor for SOC content changes, while the interaction between vegetation coverage and precipitation exerted the most significant influence on the variability of SOC content. Furthermore, the influence of mining intensity combined with precipitation was 10 times higher than that of mining intensity alone.

Response of soil organic carbon content to crop rotation and its controls: A global synthesis

Determining the effect of crop rotation (CR) on soil organic carbon (SOC) and its controls is vital for improving the potential benefits of CR in agroecosystems to achieve carbon neutrality. However, there has been no comprehensive and systematic evaluation of the response of SOC content to CR and its underlying drivers on the global level. Using 513 pairwise data from 167 studies, we conducted a global-scale meta-analysis to illuminate the changes in SOC content induced by CR and to explore the roles of climatic, edaphic, and agronomic factors in driving such changes. Results revealed that CR overall enhanced SOC content by 6.6% relative to continuous crop monoculture. SOC content under CR increased more in regions with intermediate mean annual temperature (MAT, 8–15°C) and precipitation (MAP, 600–1000 mm) than in regions with other climate types. CR had greater SOC content benefits in neutral (pH = 6–8) soils with loamy texture and medium levels of initial SOC (15–20 g kg–1) and total nitrogen (1.00–1.50 g kg–1). Also, CR performed better in the soybean-based cropping systems with more rotation cycles, longer rotation length, medium nitrogen fertilization input rate (100–200 kg N ha–1 yr–1), and the applications of no-till, straw retention, and organic fertilizers. Furthermore, the variance partitioning analysis revealed that soil (31%) and climate variables (18%) accounted for the major variations in SOC content response. Moreover, the random forest model demonstrated that soil texture, climatic factors (i.e., MAT and MAP), and initial SOC content were the predominant drivers of the response of SOC content. Overall, our findings highlight that CR is a critical practice to increase SOC content in global croplands, whereas the variations in response are governed by specific climatic, edaphic, and agronomic factors. This study helps to establish and manage site-specific CR systems that could enhance SOC in agroecosystems, ultimately facilitating carbon neutrality.

Climate change induces carbon loss of arable mineral soils in boreal conditions.

One‐fourth of the global soil organic carbon (SOC) is stored in the boreal region, where climate change is predicted to be faster than the global average. Planetary warming is accelerated if climate change promotes SOC release into the atmosphere as carbon dioxide. However, the soil carbon‐climate feedbacks have been poorly confirmed by SOC measurements despite their importance on global climate. In this study, we used data collected as part of the Finnish arable soil monitoring program to study the influence of climate change, management practices, and historical land use on changes in SOC content using a Bayesian approach. Topsoil samples (n = 385) collected nationwide in 2009 and 2018 showed that SOC content has decreased at the rate of 0.35% year−1 on average. Based on the Bayesian modeling of our data, we can say with a certainty of 79%–91% that increase in summertime (May–Sep) temperature has resulted in SOC loss while increased precipitation has resulted in SOC loss with a certainty of 90%–97%. The exact percentages depend on the climate dataset used. Historical land use was found to influence the SOC content for decades after conversion to cropland. Former organic soils with a high SOC‐to‐fine‐fraction ratio were prone to high SOC loss. In fields with long cultivation history (>100 years), however, the SOC‐to‐fine‐fraction ratio had stabilized to approximately 0.03–0.04 and the changes in SOC content leveled off. Our results showed that, although arable SOC sequestration can be promoted by diversifying crop rotations and by cultivating perennial grasses, it is unlikely that improved management practices are sufficient to counterbalance the climate change‐induced SOC losses in boreal conditions. This underlines the importance of the reduction of greenhouse gas emissions to avoid the acceleration of planetary warming.

On-Farm Relationships Between Agricultural Practices and Annual Changes in Organic Carbon Content at a Regional Scale

Both soil quality degradation and climate change mitigation issues emphasize the need to increase, or at least stabilize, the topsoil organic carbon content (wt%) in arable land. This on-farm study aimed at measuring the impact of agricultural practices on changes in soil organic carbon (SOC) content over 10 years. A total of 120 fields belonging to 120 farms representative of the cropping systems and soil properties in Western Switzerland (Lake Geneva region) was randomly selected. The field 0–20 cm topsoil was sampled at a 10-years interval, and the corresponding cropping practices were gathered using farmer’s interviews and the mandatory records of yearly practices at field level in Swiss-farms. Only 1) organic matter inputs and 2) cover-crop intensity were significantly correlated to SOC increase while 3) the soil tillage intensity and 4) the soil saturation in carbon expressed as a SOC to clay content ratio were correlated to SOC decrease. Among others, temporary meadows were not correlated to changes in SOC content mainly due to increased tillage and decreased cover-crops between meadows. Organic farming did not correlate either with SOC changes due to the large tillage intensity applied for weed control. The observed SOC content changes ranged from −56‰ to +74‰ and were well explained by a linear regression model with additive effect of the four identified SOC change factors. The additivity of these factors means that farmers can emphasize the methods of their choice when regenerating their soils. This study advocates that strict no-till is not required at low carbon saturation level (small SOC:Clay ratio). However, as carbon saturation increases, conservation tillage and then no-till practices become necessary to further increase SOC contents. These findings are in accordance with previous studies showing that since 2015 SOC is increasing at more than +4‰ on average in the region and provide practical insights to further manage the transition of farming systems towards soil regeneration.

Simulation of Soil Organic Carbon Content Based on Laboratory Spectrum in the Three-Rivers Source Region of China

Soil organic carbon (SOC) changes affect the land carbon cycle and are also closely related to climate change. Visible-near infrared spectroscopy (Vis-NIRS) has proven to be an effective tool in predicting soil properties. Spectral transformations are necessary to reduce noise and ensemble learning methods can improve the estimation accuracy of SOC. Yet, it is still unclear which is the optimal ensemble learning method exploiting the results of spectral transformations to accurately simulate SOC content changes in the Three-Rivers Source Region of China. In this study, 272 soil samples were collected and used to build the Vis-NIRS simulation models for SOC content. The ensemble learning was conducted by the building of stack models. Sixteen combinations were produced by eight spectral transformations (S-G, LR, MSC, CR, FD, LRFD, MSCFD and CRFD) and two machine learning models of RF and XGBoost. Then, the prediction results of these 16 combinations were used to build the first-step stack models (Stack1, Stack2, Stack3). The next-step stack models (Stack4, Stack5, Stack6) were then made after the input variables were optimized based on the threshold of the feature importance of the first-step stack models (importance &gt; 0.05). The results in this study showed that the stack models method obtained higher accuracy than the single model and transformations method. Among the six stack models, Stack 6 (5 selected combinations + XGBoost) showed the best simulation performance (RMSE = 7.3511, R2 = 0.8963, and RPD = 3.0139, RPIQ = 3.339), and obtained higher accuracy than Stack3 (16 combinations + XGBoost). Overall, our results suggested that the ensemble learning of spectral transformations and simulation models can improve the estimation accuracy of the SOC content. This study can provide useful suggestions for the high-precision estimation of SOC in the alpine ecosystem.

Effects of Stalk Incorporation on Soil Carbon Sequestration, Nitrous Oxide Emissions, and Global Warming Potential of a Winter Wheat-Summer Maize Field in Guanzhong Plain

The net greenhouse gas emissions from upland soils, as indicated by global warming potential (GWP), mainly depend on the soil carbon sequestration and nitrous oxide (N2O) emissions. The annual changes in surface (0-20 cm) soil organic carbon (SOC) content from 2010 to 2017 and the N2O emissions from 2014 to 2017 were measured within a long-term fertilization experiment. The objective was to quantify the effect of stalk incorporation on the soil carbon sequestration, annual N2O emissions, and GWP of a winter wheat-summer maize field in the Guanzhong Plain. The field experiment included three treatments:conventional fertilization (CF), conventional fertilization plus maize stalks (CFS), and an unfertilized control (CK). The CF and CFS treatments received the same amount of urea per year, with nitrogen (N) input at 165 kg·hm-2 and 188 kg·hm-2 in the winter wheat season and summer maize season, respectively. The CF treatment retained the stubbles (about 10 cm above ground) when harvesting the winter wheat and summer maize crops. The CFS treatment retained the same wheat stubbles and all maize stalks (containing approximately 40 kg·hm-2 of N). The CK treatment was unfertilized throughout the year, with the stubble management the same as that in the CF treatment. The results showed that the CK treatment displayed few changes in SOC content and low N2O emissions, with GWP varying from 0.04 to 0.11 t·(hm2·a)-1. The SOC contents in the CF and CFS treatments increased linearly with the fertilization years (P<0.001), and their SOC sequestration rates were 0.69 t·(hm2·a)-1 and 0.97 t·(hm2·a)-1, respectively. The N2O emissions from the CF and CFS treatments varied from 1.65 to 5.36 kg·(hm2·a)-1 and from 3.08 to 7.73 kg·(hm2·a)-1, respectively. The annual N2O emissions from the CFS treatment were 43%-94% higher than those from the CF treatment, whereas the difference was only significant between 2015 and 2016 (P<0.05). The GWP of the CF and CFS treatments varied from -1.95 to -0.28 t·(hm2·a)-1 and from -2.59 to -0.35 t·(hm2·a)-1, respectively. The cumulative GWP of the CFS treatment was 42% lower than that of the CF treatment between 2014 and 2017. In summary, the studied winter wheat-summer maize field acted as a sink of greenhouse gases under the conventional fertilization regime. The stalk incorporation further favored greenhouse gas mitigation despite the trade-offs between SOC sequestration and N2O emissions.

Effects of Organic Energy Crop Rotations and Fertilisation with the Liquid Digestate Phase on Organic Carbon in the Topsoil

Combining organic farming and biogas production from agricultural feedstocks has been suggested as a way of achieving carbon (C) neutrality in Europe. However, as the long-term effects of C removal for methane production on soil organic carbon (SOC) are unclear, organic farmers in particular have questioned whether farm biogas production will have a positive effect on soil fertility. Eight years of data from an organic long-term field trial involving digestate fertilisation and various crop rotations (CRs) with differing proportions of clover-grass leys were used to calculate C inputs based on the CANDY model, and these modelled changes compared with measured changes in SOC content (SOCc) over the same period. Measured SOCc increased by nearly 20% over the eight years. Digestate fertilisation significantly increased SOCc. Fertilised plots with the highest proportion of clover-grass in the CR had the highest SOCc. The C inputs from clover-grass leys, even if they only made up 25% of the CR, were high enough to increase SOCc, even with the removal of all aboveground biomass and without fertilisation. Our results show that biogas production based on clover-grass leys could be an important part of sustainable farming, improving or maintaining SOCc and improving nutrient flows, particularly in organic farming, while simultaneously providing renewable energy.