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Soil organic carbon (C) and aggregates are the important components of soil fertility and the foundation of sustainable agriculture. The storage and protection of SOC in aggregates is widely regarded as the material basis of soil organic C accumulation. However, current understanding of soil aggregate and its associated organic C is insufficient to elucidate the regulation mechanism of soil organic C. A nine-year field experiment including chemical fertilizer (FR) and organic manure (OM) treatments was set up in the eastern plain of Funiu Mountain, central China. Using chemical analysis, physical sieving as well as nuclear magnetic resonance (NMR) methods, we mainly probed into the response of soil organic C concentration and composition, and C functional groups, water-stable aggregates to different treatments. Furthermore, scanning electronic microscopy (SEM) and partial least square structural equation modelling (PLS-SEM) was conducted to characterise the different size aggregates and to analyse the mechanism of soil organic C accumulation and stabilisation at aggregate scales. After nine years of farming, OM treatment substantially increased soil organic C content (by 3.77 g kg−1) and significantly enhanced the formation of macro-aggregates (> 250 μm), while FR had no significant influence on soil organic C. At the aggregate scale, the amounts of soil organic C, C physical fractions (particulate and mineral-associated organic C), total nitrogen and microbial biomass carbon associated in macro-aggregates (> 250 μm) were obviously higher than that in micro-aggregates and silt + clay fraction, and OM treatment greatly increased the accumulation of soil organic C and its components in macro-aggregates. Moreover, microbial biomass carbon (MBC) amounts in aggregates were remarkably increased (27–116%) by the application of OM. And MBC had a positively effect on the physical fractions of SOC but not on the C chemical structure within aggregates. The present study indicated that soil organic C accumulation mainly rely on macro-aggregates (> 250 μm). Intra–particulate organic carbon (POC) and mineral-associated organic carbon (MOC) within macro-aggregates played an important role in soil organic C accumulation. Meanwhile, soil microbes were a driving force for the accumulation of soil organic C physical fractions (POC and MOC). We concluded that OM treatment accelerated the synergistic process between organic C sequestration and soil aggregation, and showed great potential to increase soil organic C accumulation. [ABSTRACT FROM AUTHOR]

The accurate estimation of the soil organic carbon (SOC) sequestration rate is very important for studying farmland soil fertility and environmental effects. In this research, a typical fluvor-aquic soil area, Fengqiu county, located in the Yellow River basin of the Huang-Huai-Hai Plain of China, was chosen as a study area. The physicochemical properties of 70 soil samples collected from the surface layer (at a depth of 0–20 cm) in 2011 were analyzed, and related data about the sampling sites were also collected from the Second State Soil Survey of China (SSSSC), conducted in 1981. The results revealed that the SOC density (SOCD) in Fengqiu county increased greatly on a spatio-temporal scale. The average SOCD increased from 15.66 to 26.09 Mg ha−1, and the SOCD sequestration rate was more than 0.20 Mg C ha−1 year−1 in most regions. Few areas showed lost carbon in the past 30 years (1981–2011). In addition, the study suggested that all the areas present strong carbon sequestration potential in the coming decades from 2011, and the carbon sequestration potential was mainly between 32–40 Mg ha−1. Finally, the SOCD sequestration rate was not only affected by natural factors, such as soil type and pH, but also positively correlated with artificial soil management measures, such as fertilization and straw returning. Therefore, we concluded that the farmland in Fengqiu county showed significant carbon sequestration characteristics in the past 30 years (1981–2011). Considering that soil has a great potential for carbon sequestration in the future, the trend of carbon sequestration in farmland soil might continue for a period of time. Furthermore, the results of this study emphasized that strengthening soil scientific management may play a positive role in improving soil carbon sequestration. [ABSTRACT FROM AUTHOR]

• The application of reduced tillage plus organic manure promoted soil aggregation. • SOC and its active fractions were preferentially fixed in macroaggregates. • Reduced tillage plus organic manure improved the quantity and quality of SOC. Studying the impact of tillage and fertilization on soil organic carbon (SOC) content and aggregate is essential to define better strategies for improving soil structure and SOC sequestration. A field experiment was conducted for 9 years to investigate effects of different tillage and fertilization management practices on SOC and its active fractions [labile organic carbon (LOC), dissolved organic carbon (DOC) and microbial biomass carbon (MBC)] within the bulk soil and in soil aggregates under rice (Oryza sativa L.)–wheat (Triticum aestivum L.)-based cropping systems. Five treatments were included: conventional tillage with no fertilizer (CT), conventional tillage with chemical fertilizer (CTFR), reduced tillage with chemical fertilizer (RTFR), conventional tillage with organic manure (CTOM), and reduced tillage with organic manure (RTOM). The results showed that the organic manured plots (CTOM and RTOM) significantly increased the concentrations of SOC and active carbon fractions (LOC, DOC and MBC) within the bulk soil and soil macroaggregates, and increased the mass proportion of macroaggregates (>250 μm) compared with chemical fertilizer treatments (CTFR and RTFR) or CT. The highest SOC concentration and macroaggregates (>250 μm) were observed in CTOM. The increased SOC, especially active carbon fractions, was mainly concentrated in soil macroaggregates (>250 μm). Soil aggregates were dominated by macroaggregates (>250 μm), which had higher MBC and lower PAOC (the percentage of slow plus passive carbon fractions) after 9 years of RTOM treatment than after CT or CRFR treatment. The results indicated that RTOM played a positive role in promoting the formation of the soil macroaggregate structure. By studying the responses of SOC and water-stable aggregate contents to different tillage and fertilization managements, the continual application of organic manure may be feasible and the periodic organic manure addition may be combined with reduced tillage practice to produce an integrated soil management strategy for the paddy–upland rotation region in Middle China. [ABSTRACT FROM AUTHOR]

Corporate financial distress prediction research has been ongoing for more than half a century, during which many models have emerged, among which ensemble learning algorithms are the most accurate. Most of the state-of-the-art methods of recent years are based on gradient boosted decision trees. However, most of them do not consider using feature importance for feature selection, and a few of them use the feature importance method with bias, which may not reflect the true importance of features. To solve this problem, a heuristic algorithm based on permutation importance (PIMP) is proposed to modify the biased feature importance measure in this paper. This method ranks and filters the features used by machine learning models, which not only improves accuracy but also makes the results more interpretable. Based on financial data from 4,167 listed companies in China between 2001 and 2019, the experiment shows that compared with using the random forest (RF) wrapper method alone, the bias in feature importance is indeed corrected by combining the PIMP method. After the redundant features are removed, the performance of most machine learning models is improved. The PIMP method is a promising addition to the existing financial distress prediction methods. Moreover, compared with traditional statistical learning models and other machine learning models, the proposed PIMP-XGBoost offers higher prediction accuracy and clearer interpretation, making it suitable for commercial use. • The model Combines a corrected feature selection measure and XGBoost. • Permutation importance can correct the bias of feature importance. • The model is validated on Chinese listed companies datasets over five metrics. • The model is proved to outperform several benchmark techniques. • The feature importance and partial dependence plot enhance model interpretation. [ABSTRACT FROM AUTHOR]

Background and Aims: This paper was primarily devoted to understand the interactions of soil aggregates, organic carbon (C) and carbon cycle enzymes in aggregates under different fertilization managements, aiming to identify the effects of organic and inorganic fertilizer amendments on soil organic C accumulation and the activities of carbon cycle enzymes within aggregates in Vertisol., Methods: A Vertisol soil following 4-year compost and inorganic fertilizer amendments, i.e. no fertilizer (CK), mineral fertilizer (FR) and 60% compost N plus 40% fertilizer N (FRM), was collected to identify the dynamics of organic C, enzymes activities and their associations with macroaggregation using aggregate fractionation techniques., Results: The organic C content in all FR and FRM treatments was 8.24-41.15% higher than that in CK. An increased amounts of carbon cycle enzymes in aggregates or 0-20 cm bulk soil were also observed in FRM plots. Compared to FR, FRM significantly strengthened the structural stability of macroaggregates and the intimate connection between enzyme activities and macroaggregates., Conclusions: As a recommended measure, supplementation with organic manure such as compost strengthened the process of mutual promotion between carbon cycle enzymes and macroaggregates, and the synergistic effect would be highly beneficial to soil organic C sequestration., Competing Interests: The authors have declared that no competing interests exist.