Search Results (47)

Accurate regional-scale mapping of soil organic matter (SOM) is crucial for land productivity management and global carbon pool monitoring. Current remote sensing inversion of SOM faces challenges, including the underutilization of temporal information and low feature selection efficiency. To address these limitations, this study developed an integrated framework combining multi-temporal Landsat imagery, field-measured SOM data, intelligent feature optimization, and machine learning. The framework employs two novel image-processing strategies: the Maximum Annual Bare-Soil Composite (MABSC) method to extract background spectral information and the Multi-temporal Feature Optimization Composite (MFOC) method to capture seasonal and environmental dynamics. These features, along with topographic covariates, were processed using an improved Feature-Optimized and Interpretable XGBoost (FOI-XGB) model for key variable selection and spatial mapping. Validation across two subtropical coastal mountainous regions at different scales in southeastern China demonstrated the framework’s effectiveness and robustness. Key findings include the following: (1) Both the MABSC-derived spectral bands and the MFOC-optimized indices significantly outperformed traditional single-season approaches. Their combined use achieved a moderate SOM inversion accuracy (R² = 0.42–0.44). (2) The FOI-XGB model substantially outperformed traditional feature selection methods (Pearson, SHAP, and CorrSHAP), achieving significant regional R² improvements ranging from 9.72% to 88.89%. (3) The optimal model integrating the MABSC-derived features, MFOC-optimized indices, and topographic covariates attained the highest accuracy (R² up to 0.51). This represents major improvements compared with using topographic covariates alone (R² increase of up to 160.11%) or the combined spectral features (MABSC + MFOC) alone (R² increase of up to 15.91%). This study provides a robust, scalable, and practical technical solution for accurate SOM mapping in complex environments, with significant implications for sustainable land management and carbon monitoring. Full article

Soil organic matter (SOM) content is a key indicator for assessing soil health, carbon cycling, and soil degradation. Traditional SOM detection methods are complex and time-consuming and do not meet the modern agricultural demand for rapid, non-destructive analysis. While significant progress has been made in spectral inversion for SOM prediction, its accuracy still lags behind traditional chemical methods. This study proposes a novel approach to predict SOM content by integrating spectral, texture, and color features using a three-branch convolutional neural network (3B-CNN). Spectral reflectance data (400–1000 nm) were collected using a portable hyperspectral imaging device. The top 15 spectral bands with the highest correlation were selected from 260 spectral bands using the Correlation Coefficient Method (CCM), Boruta algorithm, and Successive Projections Algorithm (SPA). Compared to other methods, CCM demonstrated superior dimensionality reduction performance, retaining bands highly correlated with SOM, which laid a solid foundation for multi-source data fusion. Additionally, six soil texture features were extracted from soil images taken with a smartphone using the gray-level co-occurrence matrix (GLCM), and twelve color features were obtained through the color histogram. These multi-source features were fused via trilinear pooling. The results showed that the 3B-CNN model, integrating multi-source data, performed exceptionally well in SOM prediction, with an R² of 0.87 and an RMSE of 1.68, a 23% improvement in R² compared to the 1D-CNN model using only spectral data. Incorporating multi-source data into traditional machine learning models (SVM, RF, and PLS) also improved prediction accuracy, with R² improvements ranging from 4% to 11%. This study demonstrates the potential of multi-source data fusion in accurately predicting SOM content, enabling rapid assessment at the field scale and providing a scientific basis for precision fertilization and agricultural management. Full article

High-latitude regions store substantial amounts of soil organic matter (SOM). Icelandic volcanic soils have exceptional capabilities for SOM accumulation, but recent changes in land use can significantly impact it. Water-extractable organic matter (WEOM) represents a labile SOM pool and serves as a reliable index of SOM dynamics. We assessed the stable carbon (C), stable nitrogen (N), and WEOC (water-extractable organic carbon), as well as WETN (water-extractable total nitrogen), concentrations in soils under different land uses—semi-natural habitats (tundra and wetland) and human-managed areas (intensively and extensively grazed pasturelands and formerly and presently fertilized meadows)—in southeastern Iceland. The results suggest that human-managed sites contain more total C and N but less WEOM per unit of total C or N than semi-natural habitats, except for wetlands. Wetlands exhibited the highest WEOM content. Extensive pasturelands and fertilized meadows are becoming more common in local ecosystems, highlighting the direction of changes in Icelandic grasslands management. Full article

Boreal forests have historically been regarded as some of the largest terrestrial carbon (C) sinks. However, increased soil organic matter (SOM) decomposition due to forest harvesting and post-harvest silviculture (e.g., site preparation, planting, and managing for competing vegetation) may exacerbate the effects of climate warming and shift boreal forests from being C sinks to C sources. We used an established stand-scale, fully replicated, experimental study to identify how two levels of forest management (harvesting = Harvest Only, and harvesting with post-harvest silviculture = Harvest Plus) influence SOC dynamics at three boreal forest sites varying in soil texture. Each site was surveyed for forest floor (litter and F/H horizons) and mineral soils pre-harvest (0) and 5, 14, and 20 years post-harvest. We predicted that sites harvested and left to revegetate naturally would have the lowest SOC stocks after 20 years, as sites that were planted and managed for competing vegetation would recover faster and contribute to a larger nutrient pool, and that the sand-dominated site would have the largest SOC losses following harvest due to the inherently lower ability of sand soils to chemically and/or physically protect SOC from decomposition following harvest. Over a 20-year period, both forest management treatments generally resulted in reduced total (litter, F/H, and mineral horizon) SOC stocks compared with the control: the Harvest Only treatment reduced overall SOC stocks by 15% at the silt-dominated site and 31% at the clay-dominated site but increased overall SOC stocks by 4% at the sand-dominated site, whereas the Harvest Plus treatment reduced overall SOC stocks by 32% at the sand- and silt-dominated sites and 5% at the clay-dominated site. This suggests that harvesting and leaving plots to revegetate naturally on sand-dominated sites and harvesting followed by post-harvest silviculture on clay-dominated sites may minimize total SOC losses at similar sites, though a full replicated field experiment is needed to test this hypothesis. Most treatment effects in this study were observed only in the second decade post-harvest (14 and 20 years post-harvest), highlighting the importance of long-term field experiments on the effects of forest harvesting and post-harvest silviculture. This research improves our understanding of the relationship between C dynamics, forest management, and soil texture, which is integral for developing sustainable management strategies that optimize C sequestration and contribute to the resilience of boreal forest ecosystems in the face of climate change. Full article

Mycorrhizal symbiosis has been the focus of research for more than a century due to the positive effect of fungi on the growth of the majority of woody plants. The extramatrical mycelium (EMM) of ectomycorrhiza (EMR) accounts for up to one-third of the total soil microbial biomass, whereas litter from this short-living pool accounts for 60% of the total litterfall mass in forest ecosystems. The functioning of EMR improves the nitrogen (N) nutrition of trees and thus contributes to the carbon (C) balance of forest soils. The model presented here is an attempt to describe these EMR functions quantitatively. It calculates the growth of EMM and the subsequent “mining” of additional nitrogen from recalcitrant soil organic matter (SOM) for EMR growth, with the associated formation of “dissolved soil carbon”. The decomposition of EMM litter is carried out by all organisms in the soil food webs, forming available ${\mathrm{N}\mathrm{H}}_4^{+}$ in the first phase and then solid-phase by-products (excretes) as a new labile SOM pool. These substances are the feedback that determines the positive role of EMR symbiosis for forest vegetation. A sensitivity analysis revealed a leading role of the C:N ratio of biotic components in the dynamics of EMM. The model validation showed a satisfactory agreement between simulated and observed data in relation to EMM respiration in larch forest plantations of different ages. Model testing within the EFIMOD3 model system allowed a quantitative assessment of the contribution of different components to forest soil and ecosystem respiration. The validation and testing of this model demonstrated the adequacy of the theoretical background used in this model, with a fast EMM decomposition cycle by all soil biota of the food webs and without direct resource exchange between plants and fungi. Full article

Active vegetation restoration plays an important role in the improvement in soil organic matter (SOM), including the carbon (C), nitrogen (N) and phosphorus (P) sequestration of degraded mining ecosystems. However, there is still a lack of understanding of the key drivers of SOM pool size and dynamics in active vegetation restoration. For this study, soil was collected from five different sites (Xiaoxian, Dingyuan, Chaohu, Tongling and Dongzhi), four habitats (platforms, slopes, steps and native areas) and two soil layers (0–20 cm and 20–40 cm) in limestone mines of Anhui province to quantify the spatial distribution of SOM contents and their stoichiometric characteristics and influential factors. It was found that the top soil in Chaohu had the highest significant C, N and P contents in the ranges of 14.95–17.97, 1.74–2.21 and 0.80–1.24 g/kg, respectively. Comparing the stoichiometric ratios of the different sites revealed significant differences in C:N and N:P ratios, but C:P ratios were relatively consistent. In particular, the C:N and C:P ratios in deep soil were higher than those in top soil, whereas the N:P ratio in deep soil was lower than that in top soil, suggesting that soil N is a major limiting factor in the top soil. The SOM content did not differ significantly between the three reclaimed habitats, but was significantly higher than that in the native habitat, suggesting that mine restoration has significantly enhanced SOM accumulation. Further analysis showed that nutrient availability and enzyme activity are important factors affecting soil C, N and P content in top soil, while the relationship gradually weakens in deep soil. This was attributed to active anthropogenic management and conservation measures during the early stages of reclamation. This study shows that the ecological recovery of the mining area can be enhanced by implementing differentiated vegetation planting strategies and anthropogenic management on different habitats in the mining area. Full article

Soil organic matter (SOM) is an important carbon pool in terrestrial ecosystems and plays a key role in soil functions. Nevertheless, the effects of fertilization practices on the physical, chemical, biological, and comprehensive stability of SOM are still unclear. We carried out a long-term field experiment in the northeast black soil region in China with four different fertilization practices: no fertilizer (CK), single chemical fertilizer (NPK), chemical fertilizer + straw (NPKJ), and chemical fertilizer + organic manure (NPKM). The content of particulate organic matter (POM) and mineral-associated organic matter (MAOM), compound composition of SOM, carbon mineralization characteristics, active soil organic matter (ASOM), and inert soil organic matter (ISOM) were tested. The results showed that the application of fertilizers significantly increased the contents of POM and MAOM to 2.59–4.65 g kg⁻¹ and 32.69–34.65 g kg⁻¹ (p < 0.05), but decreased the MAOM/POM values by 37.8–42.4%, indicating reduced the physical stability of SOM. Fertilization practices increased the contents of aromatic, nitrogen-containing compounds and decreased the oxygen compounds of SOM, representing enhancement of the chemical stability. The contents of ASOM and ISOM increased in fertilization practices, while the biological stability index (BSI) under the NPKJ and NPKM treatments was lower than the CK treatment, suggesting that the biological stability decreased under the manure and straw application. In addition, the comprehensive stability of SOM increased by 26–116% through a reduction in the physical and biological stability, coupled with an increase in the chemical stability. Collectively, our study demonstrated that the application of manure and straw enhanced both the comprehensive stability and content of SOM and reduced the physical and biological stabilities while increasing the chemical stability, which made the largest contribution to the comprehensive stability. Full article

The stability of soil organic matter (SOM) depends on its degree of physical protection, biochemical quality (q), and mineralogical features such as the abundance of iron or aluminum oxyhydroxides: All constraints stabilize SOM, but the relevance of each is herein discussed. We studied from this point of view the stability of SOM in four grassland soils. The SOM in these profiles was characterized for its physical protection (ultrasonic dispersion + size fractionation) and its q (acid hydrolysis, carbohydrates, phenolics, and unhydrolyzable carbon). The profiles were also analyzed for free iron forms extracted with several chemicals: dithionite-citrate-bicarbonate, citric acid, oxalic-oxalate (Tamm’s solution), and DTPA. Soil horizons were incubated under optimal conditions to obtain the C lost after 33 days (Cresp33) and basal respiration rate (BR_R). The microbial C was obtained at the end of the incubation. The microbial activity rate (MA_R: mg C respired per g microbial C per day) was obtained from these measures. The sum soluble + microbial C was taken as the active C pool. As expected, the stability of SOM depends on its distribution between the size fractions: The higher the proportion of particulate organic matter (POM: >20 µm size), the higher the soil respiration rate. In contrast, q barely affects SOM decomposition. Both physical availability (size fractionation) and q (acid hydrolysis) affect the size of the microbial C pool, but they barely affect MA_R. The effects of free iron on SOM stability are complex: While dithionite-extracted Fe negatively affected Cresp33, BR_R, and MA_R, the Fe extracted by smoother methods (Tamm’s reagent and DTPA) positively relates to Cresp33, BR_R, and MA_R. Free iron apparently modulates soil microbial metabolism because it is the only studied parameter that significantly affected MA_R; however, the precise effect depends on the precise free Fe fraction. From our data, SOM stability relies on a net of constraints, including physical availability and free Fe forms, with q being of minor relevance. Our dataset suggests a role for free iron as a modulator of microbial activity, deserving future research. Full article

The use of modern spectroscopic methods of analysis, which provide extensive information on the chemical nature of substances, significantly expands our understanding of the molecular composition and properties of soil organic matter (SOM) and its transformation and stabilization processes in various ecosystems and geochemical conditions. The aim of this review is to identify and analyze studies related to the application of nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopy techniques to study the molecular composition and transformation of organic matter in virgin and arable soils. This article is mainly based on three research questions: (1) Which NMR spectroscopy techniques are used to study SOM, and what are their disadvantages and advantages? (2) How is the NMR spectroscopy technique used to study the molecular structure of different pools of SOM? (3) How is ESR spectroscopy used in SOM chemistry, and what are its advantages and limitations? Relevant studies published between 1996 and 2024 were searched in four databases: eLIBRARY, MDPI, ScienceDirect and Springer. We excluded non-English-language articles, review articles, non-peer-reviewed articles and other non-article publications, as well as publications that were not available according to the search protocols. Exclusion criteria for articles were studies that used NMR and EPR techniques to study non-SOM and where these techniques were not the primary methods. Our scoping review found that both solid-state and solution-state NMR spectroscopy are commonly used to study the structure of soil organic matter (SOM). Solution-phase NMR is particularly useful for studying soluble SOM components of a low molecular weight, whereas solid-phase NMR offers advantages such as higher ¹³C atom concentration for stronger signals and faster analysis time. However, solution-phase NMR has limitations including sample insolubility, potential signal aggregation and reduced sensitivity and resolution. Solid-state NMR is better at detecting non-protonated carbon atoms and identifying heterogeneous regions within structures. EPR spectroscopy, on the other hand, offers significant advantages in experimental biochemistry due to its high sensitivity and ability to provide detailed information about substances containing free radicals (FRs), aiding in the assessment of their reactivity and transformations. Understanding the FR structure in biopolymers can help to study the formation and transformation of SOM. The integration of two- and three-dimensional NMR spectroscopy with other analytical methods, such as chromatography, mass spectrometry, etc., provides a more comprehensive approach to deciphering the complex composition of SOM than one-dimensional techniques alone. Full article

The stabilization mechanism of soil organic matter (SOM) has received considerable attention. It is widely accepted that mineral sorption/protection is important for SOM stabilization. However, it remains unclear which organic carbon component is beneficial for mineral protection. We collected soil samples from a paddy field (TP) to compare with natural soil (NS). To illustrate the behavior of different SOM pools and their protection by particles, we separated the soils into different particle-size fractions and then removed the active minerals using an acid mixture (1 M HCl/10% HF). The different carbon pools were analyzed using stable carbon isotopes and lipid biomarkers. Our study showed that acid treatment evidently increased the extractability of free lipids, usually over 60%, which confirmed the predominant role of minerals in SOM protection. For NS, the δ¹³C values increased with decreasing soil particle sizes and soil depths, indicating that ¹³C-enriched SOM was selectively preserved. However, this trend disappeared after cultivation, which was mainly attributed to the combined effects of the input of ¹³C-depleted fresh SOM and decomposition of the preserved ¹³C-enriched SOM. Meanwhile, based on the degradation parameters of the overall lipid biomarkers, SOM showed higher degradation states in clay and silt fractions than in the sand fraction before cultivation. It is possible that the small particle-size fractions could selectively absorb highly degraded SOM. The clay-associated SOM showed a low degradation state, but its carbon content was low after cultivation. We propose that the previously protected SOM was degraded after cultivation and was replaced by relatively fresh SOM, which should be carefully monitored during SOM management. Full article

Due to containing an abundance of essential nutrients, straw has significant potential to mitigate carbon (C), nitrogen (N), phosphorus (P), and potassium (K) deficits in soil. However, a lack of comprehensive and systematic reviews on C, N, P, and K release and conversion from straw and on the impact of available nutrients in soils supplemented using straw-returning (SR) practices is noticeable in the literature. Therefore, we investigated straw decomposition, its nutrient release characteristics, and the subsequent fate of nutrients in soils. At early stages, straw decomposes rapidly and then gradually slows down at later stages. Nutrient release rates are generally in the K > P > C > N order. Nutrient fate encompasses fractions mineralized to inorganic nutrients, portions which supplement soil organic matter (SOM) pools, and other portions which are lost via leaching and gas volatilization. In future research, efforts should be made to quantitatively track straw nutrient release and fate and also examine the potential impact of coordinated supply-and-demand interactions between straw nutrients and plants. This review will provide a more systematic understanding of SR’s effectiveness in agriculture. Full article

Soil is a vital component of the ecosystem that drives the holistic homeostasis of the environment. Directly, soil quality and health by means of sufficient levels of soil nutrients are required for sustainable agricultural practices for ideal crop yield. Among these groups of nutrients, soil carbon is a factor which has a dominating effect on greenhouse carbon phenomena and thereby the climate change rate and its influence on the planet. It influences the fertility of soil and other conditions like enriched nutrient cycling and water retention that forms the basis for modern ‘regenerative agriculture’. Implementation of soil sensors would be fundamentally beneficial to characterize the soil parameters in a local as well as global environmental impact standpoint, and electrochemistry as a transduction mode is very apt due to its feasibility and ease of applicability. Organic Matter present in soil (SOM) changes the electroanalytical behavior of moieties present that are carbon-derived. Hence, an electrochemical-based ‘bottom-up’ approach is evaluated in this study to track soil organic carbon (SOC). As part of this setup, soil as a solid-phase electrolyte as in a standard electrochemical cell and electrode probes functionalized with correlated ionic species on top of the metalized electrodes are utilized. The surficial interface is biased using a square pulsed charge, thereby studying the effect of the polar current as a function of the SOC profile. The sensor formulation composite used is such that materials have higher capacity to interact with organic carbon pools in soil. The proposed sensor platform is then compared against the standard combustion method for SOC analysis and its merit is evaluated as a potential in situ, on-demand electrochemical soil analysis platform. Full article

Fast and accurate SOM estimation and spatial mapping are significant for cultivated land planning and management, crop growth monitoring, and soil carbon pool estimation. It is a key problem to construct a fast and efficient estimation model based on hyperspectral remote sensing image data to realize the inversion mapping of SOM in large areas. In order to solve the problem that the estimation accuracy is not high due to the influence of hyperspectral image quality and soil sample quantity during the estimation model construction, this study explored a method for constructing an estimation model of SOM contents based on a new stacking ensemble learning algorithm and hyperspectral images. Surface soil samples in Huangzhong County of Qinghai Province were collected, and their ZY1-02D hyperspectral remote sensing images were investigated. As input data, a feature band dataset was constructed using the Pearson correlation coefficient and successive projections algorithm. Based on the dataset, a new SOM estimation model under the stacking ensemble learning framework combined with heterogeneous models was developed by optimizing the combination of base and meta-learners. Finally, the spatial distribution map of SOM was plotted based on the result of the model over the study area. The result suggested that the input data quality of the estimation model is improved by constructing a feature band dataset. The multi-class ensemble learning estimation model with the combination strategy of the base and meta-learners has better predictive effects and stability than the single-algorithm and single-level ensemble models with homogeneous learners. The coefficient of determination is 0.829, the residual prediction deviation is 2.85, and the predictive set root mean square error is 1.953. The results can provide new ideas for estimating SOM content using hyperspectral images and ensemble learning algorithms, and serve as a reference for mapping large-scale SOM spatial distribution using space-borne hyperspectral images. Full article

Background: Spheno-orbital meningiomas (SOMs) are rare tumors arising from the meninges surrounding the sphenoid bone and orbital structures. Surgical resection is the primary treatment approach for SOMs. Several surgical approaches have been described during the decades, including microsurgical transcranial (MTAs), endoscopic endonasal (EEAs), endoscopic transorbital (ETOAs), and combined approaches, and the choice of surgical approach remains a topic of debate. Purpose: This systematic review and meta-analysis aim to compare the clinical and surgical outcomes of different surgical approaches used for the treatment of SOMs, discussing surgical techniques, outcomes, and factors influencing surgical decision making. Methods: A comprehensive literature review of the databases PubMed, Ovid MEDLINE, and Ovid EMBASE was conducted for articles published on the role of surgery for the treatment of SOMs until 2023. The systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Meta-analysis was performed to estimate pooled event rates and assess heterogeneity. Fixed- and random-effects were used to assess 95% confidential intervals (CIs) of presenting symptoms, outcomes, and complications. Results: A total of 59 studies comprising 1903 patients were included in the systematic review and meta-analysis. Gross total resection (GTR) rates ranged from 23.5% for ETOAs to 59.8% for MTAs. Overall recurrence rate after surgery was 20.7%. Progression-free survival (PFS) rates at 5 and 10 years were 75.5% and 49.1%, respectively. Visual acuity and proptosis improvement rates were 57.5% and 79.3%, respectively. Postoperative cranial nerve (CN) focal deficits were observed in 20.6% of cases. The overall cerebro-spinal fluid (CSF) leak rate was 3.9%, and other complications occurred in 13.9% of cases. MTAs showed the highest GTR rates (59.8%, 95%CI = 49.5–70.2%; p = 0.001) but were associated with increased CN deficits (21.0%, 95%CI = 14.5–27.6%). ETOAs had the lowest GTR rates (23.5%, 95%CI = 0.0–52.5%; p = 0.001), while combined ETOA and EEA had the highest CSF leak rates (20.3%, 95%CI = 0.0–46.7%; p = 0.551). ETOAs were associated with better proptosis improvement (79.4%, 95%CI = 57.3–100%; p = 0.002), while anatomical class I lesions were associated with better visual acuity (71.5%, 95%CI = 63.7–79.4; p = 0.003) and proptosis (60.1%, 95%CI = 38.0–82.2; p = 0.001) recovery. No significant differences were found in PFS rates between surgical approaches. Conclusion: Surgical treatment of SOMs aims to preserve visual function and improve proptosis. Different surgical approaches offer varying rates of GTR, complications, and functional outcomes. A multidisciplinary approach involving a skull base team is crucial for optimizing patient outcomes. Full article

Maintaining soil health and sustainable crop production has been challenged by climate variability and wind erosion in semi-arid regions. To understand the initial effects of the transition of tilled cotton systems to no-tillage with winter wheat as a cover crop, we sampled 18 commercial grower sites from 2019 to 2022 in the Southern High Plains (SHP). We evaluated the soil biological component, which often responds rapidly to changes in residue additions or minimized soil disturbance providing an early indication of changes in soil health, especially in the low organic matter soils in this region. After two years, compared to tilled systems, no-till systems had significant increases in ester-linked fatty acid methyl ester (EL-FAME) bacterial and saprophytic and AMF fungal markers, enzyme activities of nutrient cycling, and various SOM pools, under both center-pivot irrigation and dryland. Similar increases were also observed in two dryland sites sampled before and up to two years after transition to no-till. Our study demonstrates the potential of no-tillage and cover crops to improve soil health in cotton production in semiarid regions, and a framework for a soil health assessment that links different soil health indicators with functions related to soil organic matter, soil water, and biogeochemical cycling. Full article