Soil & Tillage Research最新文献_第10页

Fine-scale remobilization of phosphorus around rice roots affected by biochar and water-saving irrigation: Evidence from in-situ, high-resolution observations 生物炭和节水灌溉对水稻根系周围磷的精细再移动影响：来自原位高分辨率观测的证据

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-18 DOI: 10.1016/j.still.2025.106961

Suting Qi , Shihong Yang , Chenggaoge Yang , Yi Xu , Zewei Jiang , Yupu He

Phosphorus (P) release is key to improving P availability in paddy soil, but the effects of water-saving irrigation and biochar on paddy P release remain unclear. To address this gap, we used high-resolution techniques (diffusive gradients in thin films (DGT), high-resolution dialysis (HR-Peeper), zymography, planar optoelectronic technology) and two models (DGT-induced fluxes in soil (DIFS), sediment P release risk index (SPRRI)) to evaluate P release kinetics and its mechanisms under different treatments: biochar application rates (0, 20, 40 t ha⁻¹) and irrigation regimes (water-saving irrigation, flooding irrigation). We also assessed the risk grade of P release. Results showed that flooding irrigation caused significantly more P release than water-saving irrigation, due to the strong reducing effect of Fe (hydr) oxides. This was supported by higher average concentrations of soluble P/Fe and labile P/Fe, higher desorption rates, a higher ratio of labile P to soluble P, and strong correlations between soluble P and soluble Fe, as well as labile P and labile Fe in flooded paddies. However, this intense P release led to a moderate P release risk grade, increasing the risk of P loss. Under water-saving irrigation, 40 t ha⁻¹ biochar increased labile P by 10.24%–34.48 % and soluble P by 31.28 %–55.43 %, while reducing P release risk compared to no biochar addition. In conclusion, combining 40 t ha⁻¹ biochar with water-saving irrigation is an effective strategy to simultaneously "enhance P availability and reduce P loss risk". This study provides new insights into the biogeochemical dynamics of P in paddies under combined biochar and water-saving irrigation.

磷释放是提高水稻土磷有效性的关键，但节水灌溉和生物炭对水稻磷释放的影响尚不清楚。为了解决这一空白，我们使用高分辨率技术（薄膜扩散梯度（DGT）、高分辨率透析（HR-Peeper）、酶谱法、平面光电技术）和两个模型（DGT诱导土壤通量（DIFS）、沉积物P释放风险指数（SPRRI））来评估不同处理下P释放动力学及其机制：生物炭施用量（0,20,40 t ha - 1）和灌溉方式（节水灌溉、漫灌）。我们还评估了P释放的风险等级。结果表明，由于铁（氢）氧化物的强还原作用，漫灌比节水灌溉释放出更多的磷。这与水淹稻田中较高的可溶性磷/铁和不稳定磷/铁平均浓度、较高的解吸速率、较高的不稳定磷与可溶性磷的比值以及可溶性磷与可溶性铁、不稳定磷与不稳定铁之间的强相关性有关。然而，这种强烈的P释放导致中等P释放风险等级，增加了P损失的风险。节水灌溉条件下，40 t ha−1生物炭与不添加生物炭相比，增加了10.24% ~ 34.48 %的活性磷和31.28 % ~ 55.43 %的可溶性磷，降低了磷的释放风险。综上所述，40 t ha - 1生物炭与节水灌溉相结合是同时“提高磷有效性和降低磷损失风险”的有效策略。本研究为生物炭与节水联合灌溉下稻田磷的生物地球化学动态提供了新的认识。

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引用次数: 0

Enhanced mapping of soil organic carbon in China’s Black Soil Region using spectral-temporal-spatial fusion of multi-sensor satellite data 基于多传感器卫星数据光谱-时空融合的中国黑土区土壤有机碳增强制图

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-17 DOI: 10.1016/j.still.2025.106965

Junwei Lv , Jing Geng , Yi Wu , Huajun Fang , Shulan Cheng , Jie Pei , Tianxing Wang

Soil organic carbon (SOC) is a critical determinant of soil health and agricultural sustainability in China’s Black Soil Region, a vital grain production base facing severe SOC depletion due to intensive farming. However, large-scale SOC monitoring remains challenging, as single-sensor satellite data fail to simultaneously capture fine spectral features and dynamic temporal changes in croplands. To address this, we propose a novel spectral-temporal-spatial (STS) fusion framework for SOC mapping, which integrates hyperspectral satellite imagery (166 bands, ZY-1 02D) with multi-temporal Landsat-8 multispectral data. We introduce a semi-supervised spectral-temporal-spatial fusion network based on regional energy-weighted discrete wavelet transform (RDWT-SSTSFN) to optimize the fusion process. This method first extracts temporal features from multi-temporal multispectral data using RDWT, then combines them with hyperspectral data in a dual-branch interactive learning model that captures complex spectral, temporal, and spatial relationships. Our results demonstrate that the RDWT-SSTSFN framework significantly reduces spectral uncertainty by approximately 20 % compared to using hyperspectral imagery alone (mean standard deviation reduced from 0.0588 to 0.0468). Meanwhile, the spectral features of the STS fusion data show stronger correlations with SOC, compared to single-source data. By evaluating four predictive models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and 1D Convolutional Neural Network (1D CNN), we demonstrate that RF models constructed with STS-fused data achieve the optimal SOC prediction and mapping performance. The framework enables high-resolution SOC mapping at 30 m, revealing spatially heterogeneous carbon patterns critical for targeted soil management. This study provides a scalable, satellite-based solution for monitoring SOC dynamics in intensive agricultural systems, directly supporting precision soil conservation and climate-smart farming practices.

土壤有机碳（SOC）是中国黑土地区土壤健康和农业可持续性的关键决定因素，黑土地区是中国重要的粮食生产基地，由于集约化耕作而面临严重的SOC损耗。然而，由于单传感器卫星数据无法同时捕获农田的精细光谱特征和动态时间变化，因此大规模SOC监测仍然具有挑战性。为了解决这个问题，我们提出了一种新的光谱-时空（STS）融合框架，用于SOC制图，该框架将高光谱卫星图像（166波段，ZY-1 02D）与多时相Landsat-8多光谱数据相结合。为了优化融合过程，提出了一种基于区域能量加权离散小波变换（RDWT-SSTSFN）的半监督谱-时-空融合网络。该方法首先利用RDWT从多时相多光谱数据中提取时间特征，然后将其与高光谱数据结合在一个双分支交互学习模型中，该模型可以捕获复杂的光谱、时间和空间关系。我们的研究结果表明，与单独使用高光谱图像相比，RDWT-SSTSFN框架显著降低了大约20 %的光谱不确定性（平均标准差从0.0588降低到0.0468）。与此同时，与单源数据相比，STS融合数据的光谱特征与有机碳的相关性更强。通过对随机森林（RF）、极端梯度增强（XGBoost）、分类增强（CatBoost）和一维卷积神经网络（1D CNN）四种预测模型的评估，我们证明了基于sts融合数据构建的RF模型具有最佳的SOC预测和映射性能。该框架实现了30 m的高分辨率碳含量映射，揭示了对目标土壤管理至关重要的空间异质性碳模式。该研究提供了一个可扩展的、基于卫星的解决方案，用于监测集约化农业系统的有机碳动态，直接支持精确的土壤保持和气候智能型农业实践。

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引用次数: 0

Assessment of gully erosion susceptibility in Northeast China's black soil region using new stacking model with multiple machine learning algorithms 基于多机器学习叠加模型的东北黑土区沟壑侵蚀敏感性评价

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-15 DOI: 10.1016/j.still.2025.106964

Zhang Minghao , Qin Wei , Wang Xiangdong , Yin Zhe , Xu Xiaohong , Zhou Liheng , Han Xing

Gully erosion is a severe, globally widespread manifestation of soil erosion, threatening land, food, ecological, and human settlement security. Recently, machine learning methods have been increasingly applied to Gully erosion susceptibility (GES) assessment; however, most studies mainly focus on algorithm comparison, with limited attention to result rationality, classification suitability, and factor interpretability. Moreover, ensemble models remain underexplored. This study uses multisource data from a typical watershed, including UAV and field-surveyed gullies and environmental variables, to assess gully erosion susceptibility. Through factor selecting methods, 12 influencing factors were identified. Seven machine learning models (Random Forest, Extremely Randomized Trees, Light Gradient Boosting Machine, Extreme Gradient Boosting, K-Nearest Neighbors, Support Vector Machine and stacking), combined with 3 classification methods, namely, Equal Interval Method (EIM), Geometric Interval Method (GIM), and Natural Breaks Method (NBM), were used to classify the GES results through different grading approaches. Model and classification effectiveness were analyzed using standard metrics and rationality validation, followed by interpretability analysis of the best-performing model. The following results were obtained: (1) Among the 3 classification methods, the GIM yields a larger range of high susceptibility, and NBM provided more balanced result; both are more suitable than the EIM. (2) The stacking model outperformed all 6 single algorithms, with improvements ranging from 0.2 % to 27.8 %. (3) Rationality validation revealed that the classification performance of 7 models was mainly affected by gully target omission. The stacking model exhibited the highest congruence with field observations. (4) NDVI, elevation, distance to residence, land use, topographic wetness index, ridge direction, and distance to cropland were identified as the key factors. The interpretability analysis results consistent with gully development patterns in the study area, supporting the model's rationality. (5) The GES performance depended more on selecting key independent factors than on factor numbers. These findings support for improving GES and disaster early warning and prevention.

沟蚀是一种严重的、全球普遍存在的土壤侵蚀现象，威胁着土地、粮食、生态和人类住区安全。近年来，机器学习方法越来越多地应用于沟蚀敏感性评估；然而，大多数研究主要集中在算法比较上，对结果的合理性、分类的适宜性和因素的可解释性关注较少。此外，集成模型仍未得到充分探索。本研究利用典型流域的多源数据，包括无人机和野外调查的沟道和环境变量，对沟道侵蚀敏感性进行了评估。通过因素选择法，确定了12个影响因素。采用随机森林、极度随机树、光梯度增强机、极端梯度增强机、k近邻、支持向量机和堆叠7种机器学习模型，结合等区间法（EIM）、几何区间法（GIM）和自然断裂法（NBM） 3种分类方法，对GES结果进行不同分级方法的分类。采用标准度量和合理性验证对模型和分类有效性进行分析，然后对表现最佳的模型进行可解释性分析。结果表明：(1)3种分类方法中，GIM的高敏感性范围更大，NBM的高敏感性范围更均衡；两者都比EIM更合适。(2)叠加模型优于所有6种单一算法，改进幅度在0.2 % ~ 27.8 %之间。(3)合理性验证表明，7种模型的分类性能主要受沟靶遗漏的影响。叠加模型与野外观测结果吻合度最高。(4) NDVI、高程、距居民点距离、土地利用、地形湿度指数、山脊方向和距农田距离是主要影响因子。可解释性分析结果与研究区沟壑发育规律一致，支持模型的合理性。(5) GES绩效更依赖于关键独立因子的选择，而不是因子数量。这些发现为改善GES和灾害早期预警和预防提供了支持。

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引用次数: 0

Effects of spatial distribution of slope erosion-deposition on soil quality degradation in the Mollisol region of Northeast China 东北Mollisol地区坡面侵蚀沉积空间分布对土壤质量退化的影响

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-14 DOI: 10.1016/j.still.2025.106966

Xuesong Wang , Fenli Zheng , Rui Liang , Xinyue Yang , Shuaihao Mo , Xiaobing An

Soil erosion is a major driver of soil quality degradation on sloping farmlands in the Mollisol region of Northeast China. However, the spatial interplay between erosion–deposition processes and the subsequent deterioration in soil quality has not been fully elucidated. This study introduces a novel framework that integrates the Soil Quality Index (SQI) with multiscale spatial analysis methods, specifically Moran's I and Principal Coordinates of Neighbor Matrices (PCNM), to assess the spatial relationship between soil erosion and quality. Erosion–deposition rates were quantified using ¹³⁷Cs tracer technology on two gently sloping farmlands, and 18 soil property indicators were analyzed to construct the SQI. The results revealed a weak–strong–weak pattern of erosion rates along the slopes and a clear negative correlation between erosion intensity and soil quality, with Moran’s I values ranging from –0.18 to –0.23. Moreover, soil erosion, spatial location, and topographic factors together explain 52.6–63.0 % of the variability in soil quality, with spatial location independently accounting for 20.6–52.6 % of this variance. These findings suggest that erosion degrades soil quality by reducing soil carbon and nitrogen nutrients and impairing microbial nutrient acquisition. Such effects are strongly modulated by spatial and topographic characteristics. This integrated approach advances the understanding of the spatial dynamics of erosion-induced soil degradation and provides a robust scientific foundation for developing targeted land management and conservation strategies to mitigate soil quality decline on sloping farmlands.

土壤侵蚀是东北Mollisol地区坡耕地土壤质量退化的主要驱动因素。然而，侵蚀-沉积过程与随后的土壤质量恶化之间的空间相互作用尚未完全阐明。本文提出了一种新的框架，将土壤质量指数（SQI）与多尺度空间分析方法（特别是Moran’s I和邻域矩阵主坐标（PCNM））相结合，来评估土壤侵蚀与土壤质量之间的空间关系。利用¹³⁷Cs示踪剂技术对2个缓坡农田的侵蚀沉积速率进行量化，并分析18个土壤性质指标以构建SQI。结果表明，坡面侵蚀速率呈弱-强-弱模式，侵蚀强度与土壤质量呈明显负相关，Moran’s I值在-0.18 ~ -0.23之间。此外，土壤侵蚀、空间位置和地形因素共同解释了52.6-63.0 %的土壤质量变异，空间位置单独解释了20.6 - 52.6% %的土壤质量变异。这些结果表明，侵蚀通过减少土壤碳氮养分和损害微生物养分获取来降低土壤质量。这种效应受到空间和地形特征的强烈调节。这种综合方法促进了对侵蚀引起的土壤退化空间动态的理解，并为制定有针对性的土地管理和保护策略以减轻坡耕地土壤质量下降提供了坚实的科学基础。

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引用次数: 0

Forest residue removal undermines soil health and micronutrient transfer to trees, compromising sustainable productivity of Eucalyptus plantations 森林残留物的清除破坏了土壤健康和微量营养素向树木的转移，损害了桉树人工林的可持续生产力

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-14 DOI: 10.1016/j.still.2025.106955

Antonio L. Florentino , Nariane de Andrade , Nikolas S. Mateus , Bruna E. Schiebelbein , Adam C. Rodrigues , Liamara S. Masullo , Alexandre V. Ferraz , Eduardo Mariano , Fernando D. Andreote , Carlos E.P. Cerri , Maurício R. Cherubin , Timothy R. Filley , José L.M. Gonçalves , José Lavres

There is rising interest within the timber industry in using forest residues, such as leaves, branches, and bark, for bioenergy. However, environmental benefits of bioenergy production may be offset by negative effects on soil health (SH), plant nutrition, and forest productivity induced by intensive residue management. These trade-offs remain poorly quantified in tropical systems. We investigated the effects of forest residue removal (leaves, branches, bark, and litterfall) on SH by integrating physical, chemical, and biological indicators (at 0–20 cm depth) into SH index (SHI) and correlating them with soil C and N stocks, micronutrient (B, Cu, and Zn) accumulation, and biomass production in a 6.5–yr–old Eucalyptus plantation established on a tropical Rhodic Ferralsol. Overall, residue removal influenced 16 of 31 soil variables, decreased the SHI by 37 % compared with the residue maintenance treatment, reduced B, Cu, and Zn transfer within the soil–plant system, and lowered biomass production by 5–11 %, mainly in leaves, branches, and bark. Low SHI was more strongly associated with changes in soil chemical and biological indicators than with physical indicators. The SHI correlated positively with soil C stocks, total B, Cu, and Zn accumulation in trees, and biomass production. Forest residue removal negatively affected site quality for Eucalyptus cultivation, since residues supply nutrients and sustain essential soil functions, including nutrient cycling and C–N transformations. These effects are expected to intensify over successive rotations, demonstrating that intensive residue removal (e.g., full-tree harvesting) compromises the long-term productivity and sustainability of Eucalyptus plantations.

在木材工业中，利用森林残留物，如树叶、树枝和树皮，作为生物能源的兴趣越来越大。然而，生物能源生产的环境效益可能被集约化残留物管理对土壤健康、植物营养和森林生产力造成的负面影响所抵消。在热带系统中，对这些权衡的量化仍然很差。通过将物理、化学和生物指标（0-20 cm深度）整合到SH指数（SHI）中，并将其与土壤C和N储量、微量营养素（B、Cu和Zn）积累和生物量生产相关联，研究了森林残留物去除（叶、枝、树皮和凋落物）对SH的影响。总体而言，残渣去除影响了31个土壤变量中的16个，与残渣维持处理相比，SHI降低了37% %，减少了土壤-植物系统中B、Cu和Zn的转移，生物量产量降低了5 - 11% %，主要是在叶片、树枝和树皮中。低SHI与土壤化学和生物指标的关系大于与土壤物理指标的关系。SHI与土壤C储量、树木总B、Cu、Zn积累和生物量产量呈正相关。森林残渣清除对桉树种植的立地质量有负面影响，因为残渣提供养分并维持基本的土壤功能，包括养分循环和碳氮转化。这些影响预计将在连续的轮作中加剧，表明密集的残留物清除（例如，全树采伐）会损害桉树人工林的长期生产力和可持续性。

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引用次数: 0

Aeolian sand flow characteristics and erosion mechanism of the disturbed stubble-soil complex after straw harvesting 秸秆采收后扰动残茬土壤复合体风沙流特征及侵蚀机理

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-13 DOI: 10.1016/j.still.2025.106958

Chunxiang Zhuo , Haiqing Tian , Ziqing Xiao , Ruiyi Xu , Jinghao Fan , Kai Zhao

With the growing threat of wind erosion in global dryland agricultural systems, the microscale mechanisms by which mechanical operations disturb soil and reshape near-surface aeolian sand flow remain insufficiently understood. To address this issue, this study investigates the stubble–soil complex (SSC) under different disturbance states following straw harvesting. A combined laser-scattering and long-exposure imaging technique was applied to capture the trajectories of wind-driven sand particles over SSC surfaces. Wind tunnel experiments were conducted to obtain data on vertical sand transport, particle-size distributions, and surface erosion–deposition morphology. In turn, computational fluid dynamics (CFD) simulations were integrated with the experiments to enable a multidimensional analysis of SSC surface responses across disturbance states. Results show that SSC disturbance exposes subsurface soil, generating new sand-dust sources that increase erosion risk and drive the near-surface sand flow toward bare-soil characteristics. Under strong winds, the maximum saltation height decreased from 9.53 cm to 4.09 cm, while the ejection angle declined from 70.46° to 34.55°. Sand transport was concentrated in the 0–8 cm near-surface high-flux layer, exhibiting a typical power-law relationship with height; the dominant sources were unconsolidated particles of 50–250 μm. Maximum surface erosion depth exceeded 5 mm, and the proportion of high-threshold (≥5 mm) deposition areas increased with disturbance intensity. This study elucidates the response mechanisms of SSC disturbance induced by mechanical operations on farmland wind erosion, and highlights the importance of controlling soil disturbance at the source and maintaining stubble-soil structural integrity. The findings provide significant guidance for improving farming practices and developing precise farmland conservation policies in dryland agricultural systems.

随着全球旱地农业系统中风蚀的威胁日益严重，机械操作扰乱土壤和重塑近地表风沙流的微观机制仍未得到充分了解。为解决这一问题，本研究对秸秆收获后不同扰动状态下的残茬-土壤复合体进行了研究。结合激光散射和长时间曝光成像技术，捕捉了SSC表面风沙颗粒的运动轨迹。通过风洞实验获得了垂直输沙、粒径分布和地表侵蚀-沉积形态的数据。反过来，计算流体动力学（CFD）模拟与实验相结合，以实现跨干扰状态的SSC表面响应的多维分析。结果表明，SSC扰动暴露了地下土壤，产生了新的沙尘源，增加了侵蚀风险，推动近地表沙流向裸露土壤特征发展。在大风条件下，最大跃变高度从9.53 cm下降到4.09 cm，弹射角从70.46°下降到34.55°。输沙主要集中在0 ~ 8 cm近地表高通量层，与高度呈典型的幂律关系；50 ~ 250 μm的松散颗粒是主要来源。地表最大侵蚀深度超过5 mm，高阈值（≥5 mm）沉积区比例随扰动强度增加而增加。本研究阐明了机械操作引起的SSC扰动对农田风蚀的响应机制，强调了从源头控制土壤扰动和保持茬土结构完整性的重要性。这些发现为改善旱地农业系统的耕作方式和制定精确的农田保护政策提供了重要的指导。

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引用次数: 0

Cyclical erosion-deposition patterns on long gentle slopes: Evidenced by the longitudinal ridge farmland in northeastern China 长缓坡的周期性侵蚀-沉积模式：以东北纵向脊田为例

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-13 DOI: 10.1016/j.still.2025.106967

Qiuxing Yue , Yaxian Hu , Qiqi Chang , Yixue Ma , Baoyuan Liu

Rolling topography is commonly used as farmland. However, the erosion-deposition patterns on long gentle slopes are not always linearly extended, but often prone to follow cyclical patterns over varying distances, invalidating all the approaches developed from short slopes or plot-scale settings. In this study, four long gentle slopes (two corn fields and two soybean fields) under longitudinal ridge tillage in the black soil region of northeastern China were compared through a two-year in situ investigation. For each slope, seven furrow erosion rates were investigated at intervals of 20–30 m (intervals as 5–10 m at slope tops). At each ridge-furrow cross-section, the relative elevation changes (referred to the undisturbed slope top) were in-situ measured at 27 points, in order to quantify the morphological variations and soil erosion rates over the two years. The results demonstrated that the erosion rates of this longitudinal ridge tillage study site averaged at 42.49 t·ha⁻¹ ·yr⁻¹ (exceeding the local soil loss tolerance), and followed a cyclical pattern of "increase-decrease-increase". The Morlet complex wavelet analysis further revealed the cyclical erosion patterns varied at multi-scales, where the predominant cycle length was approximately 129 m, and the secondary cycle length was 184 m and 85 m. Although soil erosion rates varied significantly across years and crop types, the erosion cycle lengths stayed consistent. Such discrepancies were probably because the soil erosion rates were mainly regulated by rainfall erosivity and crop coverage, whereas the erosion cycle length was more governed by the runoff erosivity. Overall, our findings highlight that the cyclical erosion intervals should not be ignored in similar regions with long gentle slopes. Local soil erosion modeling and conservation tillage management must take the potential impacts of erosion cycles on different slope segments into account.

起伏的地形通常被用作农田。然而，长缓坡上的侵蚀-沉积模式并不总是线性扩展的，而往往倾向于在不同的距离上遵循周期性模式，这使所有从短斜坡或地块尺度设置中开发的方法无效。本研究通过对东北黑土区4个长缓坡（2个玉米田和2个大豆田）进行为期2年的纵向垄作实地调查，比较了纵向垄作对土壤的影响。对每个坡面，以20-30 m的间隔（坡顶间隔5-10 m）调查7个沟蚀率。在每个垄沟剖面上，在27个点上测量相对高程变化（指未受干扰的坡顶），以量化两年来的形态变化和土壤侵蚀率。结果表明，纵向垄作研究点的土壤侵蚀速率平均为42.49 t·ha（⁻¹ ·yr⁻¹ ）（超出了当地的水土流失容忍度），并呈现“增加-减少-增加”的循环模式。Morlet复小波分析进一步揭示了不同尺度的循环侵蚀模式，其中主循环长度约为129 m，次循环长度为184 m和85 m。尽管土壤侵蚀速率在不同年份和作物类型之间存在显著差异，但侵蚀周期长度保持一致。这种差异可能是由于土壤侵蚀速率主要受降雨侵蚀力和作物盖度的调节，而侵蚀周期长度更多地受径流侵蚀力的控制。总的来说，我们的研究结果强调，在类似的长缓坡地区，周期性侵蚀间隔不应被忽视。局部土壤侵蚀模型和保护性耕作管理必须考虑不同坡段侵蚀循环的潜在影响。

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引用次数: 0

Nano-enabled phosphorus fertilizers: Mechanisms, applications, and environmental implications – A critical review 纳米磷肥：机制、应用和环境影响综述

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-10 DOI: 10.1016/j.still.2025.106959

Marimuthu Subramani , P. Balakrishnan

This critical review synthesizes recent advances in nano-enabled phosphorus (P) fertilizers, which represent a transformative approach to addressing the global phosphorus paradox where conventional fertilization exhibits alarmingly low nutrient use efficiency of only 10–30 %. These technologies drive efficacy by elucidating five core mechanisms, including overcoming soil fixation, synchronizing controlled release with plant demand, enhancing root-soil interactions, reducing environmental losses, and enabling smart stimuli-responsive delivery. An analysis of inorganic, polymeric, and hybrid composite systems reveals higher performance, with findings demonstrating that nano-hydroxyapatite increases Olsen-P concentrations 12.7-fold, while nano-DAP allows for a 25 % reduction in conventional phosphorus input without compromising wheat yields. Advanced composites like brushite-polyphosphate nano-fertilizers show exceptional performance improvements of 170 % higher root biomass, 240 % greater shoot biomass, and 280 % enhanced phosphorus uptake compared to conventional fertilizers. Tripolyphosphate-chitosan nano-fertilizers reduce cumulative phosphorus leaching by 84–91 % while enhancing wheat grain yield by 21 %. However, significant challenges persist including limited field-scale validation, incomplete mechanistic understanding of nanoparticle-soil-root interactions, scalability barriers from laboratory to mass production, and insufficient regulatory frameworks. Future research must prioritize comprehensive long-term field studies, mechanistic investigations, sustainable production methods through green synthesis approaches, and integration with precision agriculture technologies to realize the full potential of nano-enabled phosphorus management for global food security.

这篇重要的综述综合了纳米磷(P)肥料的最新进展，它代表了解决全球磷悖论的一种变革性方法，在全球磷悖论中，传统施肥显示出惊人的低养分利用效率，只有10 - 30% %。这些技术通过阐明五个核心机制来提高效率，包括克服土壤固定、与植物需求同步控释、加强根-土相互作用、减少环境损失和实现智能刺激响应输送。对无机、聚合物和杂交复合体系的分析显示出更高的性能，研究结果表明，纳米羟基磷灰石可将Olsen-P浓度提高12.7倍，而纳米dap可在不影响小麦产量的情况下将常规磷输入减少25% %。与传统肥料相比，先进的复合材料，如刷石-聚磷酸盐纳米肥料，其根系生物量提高170 %，茎部生物量提高240 %，磷吸收量提高280 %。三聚磷-壳聚糖纳米肥料可减少累积磷淋溶84-91 %，提高小麦籽粒产量21 %。然而，重大的挑战仍然存在，包括有限的现场规模验证，对纳米颗粒-土壤-根相互作用的机制理解不完整，从实验室到大规模生产的可扩展性障碍，以及监管框架不足。未来的研究必须优先考虑全面的长期实地研究、机械调查、通过绿色合成方法实现可持续生产方法，并与精准农业技术相结合，以充分发挥纳米磷管理对全球粮食安全的潜力。

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引用次数: 0

Pore architecture reshaping and microbial network restructuring drive sunflower yield gains in saline-alkali soil via straw-sand interlayer systems 孔隙结构重塑和微生物网络重构通过秸秆-砂层间系统驱动盐碱土向日葵产量增加

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-08 DOI: 10.1016/j.still.2025.106947

Xiaolong Bai , Na Liu , Jie Zhou , Jiashen Song , Guoli Wang , Aiping Chen , Yongliang Chen , Jing Wang , Hongyuan Zhang , Yuyi Li

Saline-alkali soils constrain dryland agriculture through high salinity, poor structure and low fertility. Interlayers can regulate soil moisture and salt, improve soil nutrients and alter microbial communities. However, little is known about how soil pore structure, microbial co-occurrence networks and assembly processes in respond to straw and sand interlayers in saline-alkali soil. A novel straw-sand interlayer system applied at 40 cm depth (treatments: JG=5 cm straw; SC=5 cm sand; JS=2.5 cm sand + 2.5 cm straw; CK=control) was assessed in a two-year field study. The results showed that integrated straw-sand interlayer increased topsoil (0–40 cm) moisture by 10–12 % after irrigation and reduced salt content by 15–36 % after harvest. Compared with CK, JG and JS treatments significantly elevated soil organic carbon, total nitrogen, available nitrogen, phosphorus, potassium within the 0–60 cm layer. Additionally, interlayer treatments enhanced total soil porosity by 74.3–247.4 % relative to CK. Interlayer treatments also increased the abundance of Acidobacteriota and Ascomycota and complexity of microbial co-occurrence networks, while decreased the abundance of Proteobacteria and Basidiomycota relative to CK treatment. Partial Least Squares Path Modeling demonstrated that soil nutrients and pore structure were primary drivers of yield enhancement under interlayers, with bacterial and fungal networks also exhibiting vital role in improving sunflower yield. Overall, this study demonstrated that interlayers enhances crop yield by regulating soil moisture & salt, nutrients, pore structure and microbial networks—with combined straw and sand interlayer showing the most pronounced effect on crop yield enhancement in saline-alkali soils.

盐碱土盐度高、结构差、肥力低，制约了旱地农业的发展。中间层可以调节土壤水分和盐分，改善土壤养分，改变微生物群落。然而，对于盐碱地土壤孔隙结构、微生物共生网络和组装过程如何响应秸秆和砂夹层的研究却知之甚少。在为期两年的实地研究中，对40 cm深度的新型秸秆-砂夹层系统进行了评价（处理：JG=5 cm稻草；SC=5 cm沙子；JS=2.5 cm沙子+ 2.5 cm稻草；CK=对照）。结果表明：灌水后秸秆-砂复合层使表层土壤（0 ~ 40 cm）含水量提高10 ~ 12% %，收获后含盐量降低15 ~ 36% %。与CK相比，JG和JS处理显著提高了0 ~ 60 cm层土壤有机碳、全氮、速效氮、磷、钾含量。此外，层间处理使土壤总孔隙度比对照提高了74.3 ~ 247.4 %。层间处理增加了酸菌门和子囊菌门的丰度，增加了微生物共生网络的复杂性，降低了变形菌门和担子菌门的丰度。偏最小二乘路径模型表明，土壤养分和孔隙结构是层间土壤增产的主要驱动因素，细菌和真菌网络对向日葵增产也有重要作用。综上所述，在盐碱地中，草沙复合层通过调节土壤水分、盐分、养分、孔隙结构和微生物网络来提高作物产量，其中秸秆复合层对作物增产的作用最为显著。

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引用次数: 0

Synergistic regulation of pH and organic materials on nitrate transformation pathways in facility vegetable soils under reductive soil disinfestation 还原性土壤除害条件下pH和有机质对设施蔬菜土壤硝酸盐转化途径的协同调节

IF 6.8 1区农林科学 Q1 SOIL SCIENCE

Soil & Tillage Research

Pub Date : 2025-11-08 DOI: 10.1016/j.still.2025.106963

Xiuxian Li , Mengqin Yan , Lingying Xu , Xu Zhao , Yongbo Xu

In facility vegetable systems, long-term continuous cropping with excessive nitrogen fertilization leads to soil nitrate accumulation, and while reductive soil disinfestation (RSD) effectively removes these nitrates, it often increases N₂O emissions, causing nitrogen loss and environmental concerns. This study used ¹⁵NO₃⁻ isotope labeling to trace nitrogen transformation pathways in nitrate-degraded soils under five treatments: waterlogging (CK); waterlogging + wheat bran (RSD₁); waterlogging + wheat straw (RSD₂); waterlogging + wheat bran, pH adjusted to 8 (RSD₃); and waterlogging + wheat straw, pH adjusted to 8 (RSD₄). The results showed that microbial activity and key nitrogen-transforming gene expression were stimulated by RSD₃, enhancing organic matter mineralization, driving denitrification, and converting nitrate nitrogen (NO₃⁻-N) into environmentally inert N₂, which significantly reduced N₂O emissions and improved the nitrate removal efficiency. During the initial phase (24 h), RSD₃ activated dissimilatory nitrate reduction to ammonium (DNRA) via the napA gene, increasing ammonium nitrogen (NH₄⁺-N) content compared to other treatments. From the middle stage until treatment completion (360 h), RSD₃ enhanced mineralization via the ureC gene, thereby continuously elevating NH₄⁺-N, and activated gdhA-mediated NO₃⁻-N immobilization, with dissolved and insoluble organic nitrogen being 0.31–3.51 times higher than in other treatments for effective nitrogen retention. This study reveals that during RSD, synergistic regulation of organic material C/N ratio and soil pH can direct the energy and electrons generated from mineralization towards specific pathways, thereby simultaneously driving complete denitrification (to N₂) and microbial nitrogen immobilization. This mechanism is key to achieving efficient nitrate removal while reducing environmental risks.

在设施蔬菜系统中，长期连作过量施氮会导致土壤硝酸盐积累，而还原性土壤消毒（RSD）虽然能有效去除这些硝酸盐，但往往会增加N2O的排放，造成氮的损失和环境问题。本研究采用15NO3−同位素标记法对5种处理下硝酸盐退化土壤的氮素转化途径进行了研究：渍水处理；内涝+ 麦麸（RSD1）；内涝+ 麦秸（RSD2）；内涝+ 麦麸，pH调至8 (RSD3)；涝渍+ 麦秸，pH调至8 （RSD4）。结果表明，RSD3刺激了微生物活性和关键氮转化基因表达，增强了有机质矿化，推动了反硝化作用，将硝态氮（NO3−-N）转化为环境惰性N2，显著减少了N2O排放，提高了硝酸盐去除效率。在初始阶段（24 h）， RSD3通过napA基因激活硝酸异化还原为铵态氮（DNRA），与其他处理相比，铵态氮（NH4+-N）含量增加。从处理中期到处理结束（360 h）， RSD3通过ureC基因增强矿化，从而持续升高NH4+-N，激活gdha介导的NO3−-N固定，溶出和不溶出有机氮比其他处理高0.31-3.51倍，有效留氮。本研究表明，在RSD过程中，有机质C/N比和土壤pH的协同调节可以将矿化产生的能量和电子导向特定途径，从而同时驱动完全反硝化（向N2）和微生物氮固定化。该机制是实现有效去除硝酸盐同时降低环境风险的关键。

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引用次数: 0