Soil & Tillage Research最新文献

{"title":"Biochar application enhances tolerance to boron toxicity in rice (Oryza sativa) seedlings","authors":"Muhammad Riaz ,&nbsp;Lei Yan ,&nbsp;Xia Hao","doi":"10.1016/j.still.2025.107048","DOIUrl":"10.1016/j.still.2025.107048","url":null,"abstract":"<div><div>Boron (B) is an essential micronutrient for plant physiological processes, yet excessive soil concentrations can severely impair plant health, particularly in sensitive crops such as rice. Although biochar is known to improve soil conditions and mitigate various environmental stressors, its capacity to alleviate B toxicity remains insufficiently studied. This research examined the effects of biochar application on rice seedling growth and soil microbial communities under boron toxicity (BT). The treatments were designated as CK (control), BC (biochar with normal boron), BT (B toxicity), and BC+BT (biochar with B toxicity). Boron stress significantly reduced shoot length, fresh and dry biomass, and leaf chlorophyll content. In contrast, BC+BT markedly improved these growth traits relative to BT alone. Biochar also altered the distribution of B fractions in soil by lowering easily soluble and residual B while increasing organically bound B. Changes in soil properties under BC included higher total nitrogen (TN), available potassium (AK), and soil organic matter (SOM). Furthermore, the study revealed clear differences in soil bacterial diversity, with the BC+BT treatment showing higher alpha-diversity metrics than the other treatments, while fungal diversity remained largely unchanged. Community composition analyses indicated that biochar application reshaped both bacterial and fungal community structures. These findings highlight the potential of biochar as an effective soil amendment for mitigating the adverse effects of B contamination on rice seedlings and improving overall soil health.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107048"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The thickness and variation rate of mollic epipedon in the drylands of northeastern China over the past 40 years","authors":"Lixia Ma ,&nbsp;Zhang Gao ,&nbsp;Wenyou Hu ,&nbsp;Dongsheng Yu ,&nbsp;Jun Jiang ,&nbsp;Decheng Li ,&nbsp;Lei Gao ,&nbsp;Feng Liu ,&nbsp;Changkun Wang ,&nbsp;Yongcun Zhao ,&nbsp;Yuguo Zhao ,&nbsp;Zhongjun Jia ,&nbsp;Xinhua Peng","doi":"10.1016/j.still.2026.107058","DOIUrl":"10.1016/j.still.2026.107058","url":null,"abstract":"<div><div>Clarifying the thickness and its temporal variation rate of the mollic epipedon across cultivated lands in northeastern China is crucial for the protection of Mollisols and food security. However, accurately determining the thickness and its variation of the mollic epipedon is challenging due to the lack of comprehensive datasets and the spatial mismatch of sampling sites from different time periods. This study mainly aimed to determine the spatiotemporal variation in mollic epipedon thickness in the drylands of northeastern China over the past 40 years. We developed a method to identify the thickness of the mollic epipedon from 4410 soil profiles collected in the 1980s. In the 2020s, a rapid survey method was proposed to measure the thickness of the mollic epipedon. We then developed spatial predictive models of mollic epipedon thickness for the 2020s and 1980s, respectively, using random forest algorithms. Finally, we evaluated the thickness and variation of the mollic epipedon for drylands over the past 40 years by combining data from sampling sites and spatial distributions. Results indicate that both the identification method (R² = 0.80, N = 69) and the rapid survey method (R² = 0.91, N = 69) for mollic epipedon thickness perform well. The spatial prediction models also perform well for both the 2020s and 1980s, with R² (RMSE) values of 0.94 (9.1 cm, N = 732) and 0.94 (8.8 cm, N = 4410), respectively. The spatial distributions indicate a decreasing trend in mollic epipedon thickness from north to south in both periods, with an average thickness of 45.0 cm in the 2020s and a thinning rate of 0.25 cm per year over the past 40 years. Findings from sampling sites support the spatial distribution of variation rate for mollic epipedon thickness (R² = 0.78, N = 69). The thickness and variation rate of the mollic epipedon are related to soil type and slope position. The mollic epipedon thickness is largest for the soil type of Hapli-Udic Isohumosols and smallest for Hapli-Udic Argosols, with the thinning rate largest for the former soil type (0.38 cm/y). The thinning rate decreases with slope position, with average rates of 0.38 cm/y, 0.27 cm/y, and 0.13 cm/y for upper, middle, and lower slope, respectively. This is the first large-scale assessment of thickness and variation of the mollic epipedon in northeastern China over the past 40 years, utilizing extensive sampling data and machine learning methods. These findings provide valuable technical and data support for the conservation of Mollisols.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107058"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145925509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing farmland soil carbon mapping: Integrating radar backscatter model and machine learning","authors":"Yujiao Wei ,&nbsp;Yiyun Chen ,&nbsp;Jiaxue Wang ,&nbsp;Zheng Sun ,&nbsp;Bo Wang ,&nbsp;Chi Zhang ,&nbsp;Chen Wu ,&nbsp;Tianjie Zhao ,&nbsp;Huanfeng Shen","doi":"10.1016/j.still.2025.107055","DOIUrl":"10.1016/j.still.2025.107055","url":null,"abstract":"<div><div>Accurate farmland soil carbon mapping is essential for assessing soil health and monitoring carbon dynamics. Currently, most studies primarily rely on vegetation indicators (e.g., optical vegetation indices) or other surface features that are indirectly related to soil carbon. In contrast, surface soil properties beneath vegetation cover play a more direct and critical role in governing soil carbon dynamics and spatial distribution. Here, we developed an innovative soil carbon mapping framework based on machine learning, which integrates multi-source remote sensing data to leverage complementary vegetation and soil surface characteristics. Furthermore, the radar backscatter model was incorporated to enhance prediction accuracy by capturing additional soil structural properties. Specifically, Sentinel-2 (S2) optical data were used to derive comprehensive surface indicators including vegetation indices, brightness indices, and moisture indices. Sentinel-1 (S1) radar data provided complementary ground surface information beneath vegetation cover through its microwave penetration capability. To ensure that S1 backscatter accurately reflects soil physical properties, we applied the Water-Cloud Model (WCM) for vegetation correction, and compared correction results using NDVI and NDWI. A total of 154 topsoil samples were systematically collected from the central Songliao Plain, China, to validate the framework’s performance. By employing the XGBoost algorithm, we developed soil carbon prediction models under four distinct modeling strategies: (Ι) climatic conditions, topographical features, and S2-derived variables; (Ⅱ) adding uncorrected S1-derived variables; (Ⅲ) adding NDVI-corrected S1-derived variables; and (Ⅳ) adding NDWI-corrected S1-derived variables. The results indicated that compared with strategy Ι, strategy Ⅱ achieved an RMSE of 1.70 g/kg (9.09 % lower) and an R² of 0.47 (30.56 % higher), demonstrating the added value of radar information. The NDWI-corrected model (strategy Ⅳ) performed best, with an RMSE of 1.66 g/kg (11.23 % lower than strategy Ι) and an R² of 0.50 (38.89 % higher), highlighting the effectiveness of vegetation correction using NDWI. These findings emphasize how integrating optical and radar remote sensing can enrich the data dimensions used in soil carbon mapping. Proper vegetation correction is also crucial for improving mapping accuracy. Together, these approaches provide a scalable framework for precise farmland soil carbon prediction.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107055"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectra-based predictive mapping of soil erodibility and analysis of its influence mechanism: A typical case study for Northeast China","authors":"Yuling Shi ,&nbsp;Zihao Wu ,&nbsp;Pu Shi ,&nbsp;Yuanli Zhu","doi":"10.1016/j.still.2025.107044","DOIUrl":"10.1016/j.still.2025.107044","url":null,"abstract":"<div><div>Soil erosion in Northeast China’s black soil region poses serious challenges to agricultural productivity and ecosystem sustainability. This study proposes a novel framework for high-resolution (10 m) mapping of soil erodibility by integrating Sentinel-2 spectral data with a gradient boosting decision tree (GBDT) model. A comprehensive soil erodibility index (CSEI) was developed to represent the combined effects of soil texture, structure, and organic stability. The GBDT model was used to identify the dominant environmental drivers and their nonlinear relationships with CSEI. Results indicate that the normalized difference tillage index (NDTI), soil moisture, and mean annual precipitation are the key influencing factors, collectively explaining 69.3 % of the spatial variability in soil erodibility. Threshold effects were observed, including an inverse S-curve for soil moisture and an inverted-U response to precipitation, reflecting shifts in erosion mechanisms under varying surface conditions. These findings provide quantitative evidence for targeted soil conservation and land-use optimization, supporting management strategies such as conservation tillage, slope-specific terracing, and vegetation restoration to mitigate erosion risks in vulnerable landscapes.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107044"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cropping systems-induced microtopography in regulating soil erosion in alpine canyon regions of southwestern China","authors":"Xiaopeng Shi ,&nbsp;Zicheng Zheng ,&nbsp;Haiyan Yi ,&nbsp;Xinlan Liang ,&nbsp;Shuqin He","doi":"10.1016/j.still.2025.107041","DOIUrl":"10.1016/j.still.2025.107041","url":null,"abstract":"<div><div>The unique geography and climate of the Alpine Canyon Area make it highly susceptible to soil erosion. Quantitative assessment of how cropping system-induced microtopography affects runoff and sediment yield is essential for predicting the water conservation function of this region. Based on Structure-from-Motion (SfM) technology, this study quantified the changes in microtopography induced by different cropping systems through a field in-situ scouring test, aiming to clarify the response mechanisms of these changes to soil erosion on sloping farmland. Results showed that soil surface elevation varied between -80 mm and 40 mm for each cropping system, with rills observed on all slopes. The amplitude of soil surface roughness (<em>SSR</em>) variation in the intercropping system (-38.41–39.82 %) was smaller than that in the monocropping system (-4.64–162 %). The <em>D</em>(<em>q</em>) curve exhibited a decreasing nonlinear relationship with <em>q</em>, with values ranging from 1.94 to 2.34. Both total runoff and sediment yield were significantly lower in intercropping than in monocropping systems. Soil surface roughness was negatively correlated with sediment connectivity (<em>R</em>²=0.61). Redundancy analysis (RDA) showed that in maize-dominated systems, the first two axes cumulatively explained 68.49 % of runoff and sediment yield variance. Runoff showed significant positive correlations with <em>SSR</em>_<em>A</em> (<em>P</em> &lt; 0.05), while sediment yield was significantly positively correlated with <em>a</em>_<em>max</em> and significant negative correlations with Δ<em>f</em>(<em>a</em>) and <em>f</em>(<em>a</em>_<em>max</em>). In Zanthoxylum-dominated systems, the first two axes cumulatively explained 67.17 % of the variance, and sediment yield was significantly positively correlated with <em>SSR</em>_<em>A</em> and significantly negatively correlated with <em>f</em>(<em>a</em>)<em>max</em>. The results provide a theoretical basis for the scientific planning of soil and water conservation practices on sloping farmland, as well as for the development of a soil erosion model in the Alpine Canyon Area of southwestern China.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107041"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing rice-crayfish systems with direct seeding: Impacts on greenhouse gas emissions and economic performance","authors":"Yilin Liu ,&nbsp;Shaopeng Wang ,&nbsp;Yinghua Yin ,&nbsp;Limei Zhai ,&nbsp;FuLin Zhang ,&nbsp;Ying Xia ,&nbsp;Xianpeng Fan ,&nbsp;M. Haïssam Jijakli ,&nbsp;Hongbin Liu","doi":"10.1016/j.still.2025.107004","DOIUrl":"10.1016/j.still.2025.107004","url":null,"abstract":"<div><div>The rapid expansion of rice-crayfish (RC) systems has raised concerns about increased methane (CH₄) emissions due to prolonged field flooding, especially in long-term practices. While direct seeding (DS) is widely used to reduce CH₄ in rice cultivation, its efficacy and economic viability in RC systems remain unclear. This study aimed to compare DS versus transplanting (TP) in RC systems cultivated for 5 (RC5) and 15 (RC15) years. Results showed that under TP, CH₄ emissions were 22.0 % higher in RC15 than in RC5. Implementing DS reduced CH₄ emissions by 49.9 % in RC5 and 30.1 % in RC15—mainly during the initial drainage stage—reducing the global warming potential (GWP) by 44.5 % and 27.3 %, despite increased nitrous oxide emissions. Mechanistically, DS suppressed methanogenesis by increasing soil redox potential, as indicated by a 14.1–50.9 % reduction in <em>mcrA</em> gene abundance, while increasing the abundance of ammonia-oxidizing bacteria genes. The reduced effectiveness in RC15 reflected altered emission drivers, as significant CH₄-WFPS correlations observed in RC5 (R² = 0.96) were absent in RC15 (R² = 0.09), limiting water management benefits. Although DS reduced rice yields in RC5 (12.1–10.0 t ha⁻¹), yields remained stable in RC15 (11.8 vs 12.3 t ha⁻¹). Economically, DS improved net ecosystem economic benefits by 3.5 % in RC5 and 12.8 % in RC15 systems, driven by lower crop establishment costs and reduced GWP-associated environmental costs. This study demonstrates that DS is a viable strategy for balancing environmental sustainability with economic profitability in RC systems, though optimal management is modulated by system age.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107004"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-frequency SAR and optical data integration for continental-scale digital mapping of soil chemical properties across Europe","authors":"Tao Zhou ,&nbsp;Yajun Geng ,&nbsp;Huijie Li ,&nbsp;Hongmin Zhang ,&nbsp;Hongchen Li ,&nbsp;Junming Liu ,&nbsp;Shuang Li ,&nbsp;Tingting Liu ,&nbsp;Jianjun Pan ,&nbsp;Bingcheng Si ,&nbsp;Angela Lausch","doi":"10.1016/j.still.2025.107034","DOIUrl":"10.1016/j.still.2025.107034","url":null,"abstract":"<div><div>Timely and accurate spatial information on soil properties is essential for addressing global challenges, including climate change, food security, and ecosystem degradation. Despite advances in digital soil mapping (DSM), current approaches remain limited by reliance on optical satellite data and insufficient exploration of synthetic aperture radar (SAR) potential at continental scales. Here, we advance DSM by integrating multi-frequency SAR and optical satellite observations to map four key soil chemical properties—soil organic carbon, pH, extractable potassium, and total nitrogen—across Europe. Eleven scenarios with different data integrations, combined with two machine learners (support vector machine and random forest algorithms) and measurements from the LUCAS 2018 soil module, were employed to construct prediction models. The results confirm that continental-scale DSM is feasible using long-term optical and SAR observations. For all soil properties, C-band Sentinel-1 outperformed <span>L</span>-band PALSAR-1/2, and the integration of multi-frequency SAR data achieved prediction accuracies comparable to or even exceeding those of optical data, with R² improvements of approximately 29 %–87 % compared with using only <span>L</span>-band backscatter bands. The joint use of radar and optical observations produced the best performance, improving predictions of all soil properties compared to using optical data alone, with R² values ranging approximately from 0.31 to 0.60—highest for soil pH and lowest for soil total nitrogen. The relative importance of SAR features in the predictions varied with specific polarization modes and band frequencies, and radar indices were found to be more influential in models than backscatter bands. The generated soil property maps showed spatial patterns consistent with previous efforts based on multi-source environmental data. This study demonstrates that multi-frequency SAR data can both substitute for and complement optical data in DSM, offering new insights and practical directions for future model development.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107034"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing water use efficiency and crop production through shallow- and deep-rooted crop strip intercropping in semi-arid regions","authors":"Yuhuan Wu ,&nbsp;Qianhu Ma ,&nbsp;Yanan Liu ,&nbsp;Zikui Wang","doi":"10.1016/j.still.2025.107043","DOIUrl":"10.1016/j.still.2025.107043","url":null,"abstract":"<div><div>In semi-arid dryland farming, continuous cultivation of perennial deep-rooted pastures can excessively deplete soil moisture, whereas annual crops underutilize precipitation. We hypothesize that intercropping these two types of plants has great potential for water resource conservation and efficient utilization. A field experiment on wheat-alfalfa strip intercropping was conducted over four seasons from September 2017 to September 2021 to examine root development and water use in three intercrops with wheat-to-alfalfa row ratios of 2:1 (I21), 4:2 (I42), and 8:4 (I84). We observed that wheat roots were primarily distributed within the 0–2 m soil profile, whereas alfalfa roots extended to 5-m-depth. Intercropping reduced vertical penetration while facilitating the lateral extension of wheat roots into alfalfa strips and promoting alfalfa roots distribution laterally below 2-m-depth in the wheat strip. Intercropping also increased root length and surface area of both species. Root plasticity enhanced the complementary use of soil water. Wheat in I21, I42, and I84 absorbed an average of 39.0, 33.1, and 14.7 mm yr⁻¹ of soil water from the alfalfa strip. In the dry year, 2021, alfalfa in I21, I42, and I84 absorbed 19.5, 20.2, and 62.4 mm of soil water from the wheat strip below 2-m-depth. Intercropping increased wheat grain yield by 18.4–22.3 % while maintaining the alfalfa biomass production. The wide-strip pattern, I84, achieved the highest production and water use advantages, averaging 9 % and 13 % respectively, over monocultures, with peaks of 14 % and 31 % in 2021. Our research confirms the feasibility of intercropping shallow- and deep-rooted crops to enhance water use efficiency in semi-arid regions, demonstrating a replicable and scalable approach that can be applied globally.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107043"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145823022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ecological effects of nature-based solutions on degraded grassland restoration in China: A meta-analysis","authors":"Haoli Hu ,&nbsp;Zemin Ai ,&nbsp;Xiaohu Dang ,&nbsp;Yong Cao ,&nbsp;Huan Liu ,&nbsp;Qingqing Li ,&nbsp;Yuanyuan Zhang ,&nbsp;Tian Cao ,&nbsp;Lie Xiao","doi":"10.1016/j.still.2025.106998","DOIUrl":"10.1016/j.still.2025.106998","url":null,"abstract":"<div><div>Nature-based Solutions (NbS) for the restoration of the degraded grassland ecosystems gain considerable global attention. However, the ecological restoration performance still requires further clarification. A meta-analysis focuses on the degraded grasslands in China to systematically assess the restoration effectiveness of protection measures (PM), restoration measures (RM), and management measures (MM). The results show that all three measures significantly increase total nitrogen (TN), soil organic carbon (SOC), and microbial biomass carbon (MBC), with PM exhibiting the most pronounced improvement in TN (24.09 %), while RM exerts the strongest effects on SOC (26.89 %) and MBC (42.21 %). RM and PM significantly increase total phosphorus and potassium content in soil and significantly lower soil pH, and RM significantly increases microbial biomass nitrogen (75.96 %). MM and PM elevate soil water content, whereas MM also reduces soil bulk density. All three interventions significantly increase aboveground biomass (AGB), with RM inducing the greatest enhancement (100.97 %). MM (28.16 %) and RM (121.46 %) significantly promote belowground biomass (BGB). Only MM results in a significant increase in vegetation coverage (13.88 %). Under MM, both temperature and precipitation positively influence species diversity, and precipitation shows significant positive correlations with AGB and vegetation coverage. Under RM, temperature enhances both AGB and BGB, whereas precipitation promotes AGB, vegetation coverage, and species diversity but suppresses BGB. Under PM, temperature inhibits species diversity. Overall, RM is recommended for improving SOC, microbial biomass, and plant biomass, while MM is more suitable for enhancing soil structure and moisture conditions, and climatic drivers should be considered for targeted restoration.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 106998"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145659106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The conversion of natural grassland to cropland drives thermodynamic destabilization of subsoil DOM over decades","authors":"Yuxin Yan,&nbsp;Yumei Peng,&nbsp;Jia Shi,&nbsp;Chunpeng Huo,&nbsp;Zhongmin Fan,&nbsp;Xiang Wang","doi":"10.1016/j.still.2025.107051","DOIUrl":"10.1016/j.still.2025.107051","url":null,"abstract":"<div><div>The conversion of natural grassland to cropland is a widespread practice that threatens soil carbon stocks. However, its impact on the dynamics of dissolved organic matter (DOM), particularly the thermodynamic stability of subsoil DOM, remains poorly quantified. This study investigated the distribution and biochemical characterization of DOM and its transformation processes following 11 and 40 years of conversion from natural grassland to agricultural land on a Haplic Chernozems soil in northern China. The post-conversion agricultural management was no-tillage, focused on rain-fed cultivation of wheat and oats. The chemical characterization of DOM was conducted using UV–visible and fluorescence spectroscopy and Fourier-transform ion cyclotron resonance mass spectrometry combined with PARAFAC analysis and substrate-explicit modeling. The results showed a critical depth-dependent shift of DOM content and stability: while topsoil (0–20 cm) dissolved organic carbon (DOC) decreased by 88 %, its thermodynamic stability increased. Conversely, subsoil (80–100 cm) DOC increased by 1.8-fold, yet this accumulated pool was characterized by lower molecular weight, enrichment of a blue-shifted humic-like component (C2), and significantly higher thermodynamic degradability. Molecular-level evidence revealed that this destabilization was primarily driven by the transformation of complex subsoil organic matter into labile DOM, a process strongly linked to nutrient enrichment. Although derived from a single representative soil type, our findings provide a mechanistic framework for assessing carbon vulnerability in agroecosystems following land-use change.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"258 ","pages":"Article 107051"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145902299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}