Soil & Tillage Research最新文献

{"title":"The coupling of bacterial and fungal diversity under land-use conversion in global grassland regions is limited by perturbation intensity","authors":"Tongrui Zhang ,&nbsp;Shucheng Li ,&nbsp;Tingting Xing ,&nbsp;Jiayue Liu ,&nbsp;Zhaokai Sun ,&nbsp;Zhenyu Yao ,&nbsp;Shiming Tang ,&nbsp;Ke Jin","doi":"10.1016/j.still.2025.106751","DOIUrl":"10.1016/j.still.2025.106751","url":null,"abstract":"<div><div>The dynamics of bacterial and fungal communities in grasslands are strongly affected by land-use conversion, but their large-scale diversity responses remain unclear. We quantified the effects of grassland-use conversion (i.e., native grassland converted to cropland, forest, or artificial grassland) on soil microbial alpha diversity (Chao1 richness and Shannon diversity) using 422 observations from 94 publications. Overall, grassland-use conversion significantly reduced fungal Shannon diversity (5.1 %), whereas it marginally increased bacterial Shannon diversity (2.0 %) and Chao1 richness (6.0 %). These effects were driven by conversion types associated with high perturbation, namely conversion to cropland or forest, and by cultivation or succession management. The responses of bacterial and fungal Chao1 richness were positively coupled under land-use conversion but decoupled in cropland ecosystems and under cultivation management. The positive coupling of bacterial and fungal Shannon diversity was not statistically significant until the perturbation associated with conversion converged at a lower level: when the bacterial diversity change induced by land-use conversion was within ± 30 %. This coupling was regulated by nutrient availability in soil (nitrate and available phosphorus). Our findings highlight the limited and coupled responses of bacterial and fungal diversity to grassland-use conversion, in a manner regulated by perturbation intensity. Land-use conversion and management should be undertaken cautiously with the goals of conserving biodiversity and soil function potential in grassland regions.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106751"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623482","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":"Unified modeling of longitudinal slip and longitudinal skid for grouser-wheeled rovers without slip ratio","authors":"Yakuan Li ,&nbsp;Junlong Guo ,&nbsp;Chenghua Tian ,&nbsp;Liang Ding ,&nbsp;Chao Chen ,&nbsp;Rujun Song ,&nbsp;Bo Huang ,&nbsp;Haibo Gao","doi":"10.1016/j.still.2025.106753","DOIUrl":"10.1016/j.still.2025.106753","url":null,"abstract":"<div><div>When planetary rovers traverse across extensive megaripple deposits, some planetary rover’s wheels climbing up a slope will experience longitudinal slip, while others moving down a slope simultaneously will suffer longitudinal skid. It is important to establish a unified model of longitudinal slip and longitudinal skid for online control optimization and terrain mechanical parameters estimation. However, when the wheel running state changes from longitudinal skid to longitudinal slip, the equivalent shear deformation modulus of a same terrain estimated using traditional terramechanics models is different, while the estimated modified sinkage exponent of a same terrain suffers an unexpected break. It is difficult to establish a unified model with traditional terramechanics theories. A unified model without slip ratio for smooth wheels was first established using a switching function, and named as smooth unified model. The relative error of the drawbar pull estimated using the smooth unified model is less than 19.7 % compared with the experimental data. And a unified terramechanics model without slip ratio for grouser wheels was established by introducing the grouser effect coefficient and equivalent radius to the smooth unified model, and named as grouser unified model. The equivalent terrain mechanical parameters estimated using the grouser unified model change continuously without break, and the relative error of the estimated drawbar pull can be captured within 22.37 % compared with the experimental data. Finally, field experiments were conducted to validate the performance of the grouser unified model.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106753"},"PeriodicalIF":6.1,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604544","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":"Changes in cropland soil color in Northeast China's black soils region over the past 30 years","authors":"Yang Lu ,&nbsp;Xiang Wang ,&nbsp;Mingchang Wang ,&nbsp;Kaishan Song ,&nbsp;Bingxue Zhu ,&nbsp;Z. Tao ,&nbsp;CM Wang","doi":"10.1016/j.still.2025.106750","DOIUrl":"10.1016/j.still.2025.106750","url":null,"abstract":"<div><div>Cultivation has led to soil degradation, with soil color being the most direct indicator. This study examined the impact of nearly 30 years of cultivation on soil color. A total of 1273 topsoil samples were collected from cropland in Northeast China, resulting in seven Munsell soil colors. Combined with Landsat remote sensing images and soil formation factors, soil color predictions were made for every five-year period from 1990 to 2020. A stepwise classification method was introduced for modeling, with classification validation accuracy ranging from 0.61 to 0.72, and the overall average color difference was 1.60. Based on the definition of \"black soils,\" the seven soil colors were classified into two groups: black soils color and non-black soils color, leading to four types of changes: consistently black soils color, positive change (non-black soils color transitioning to black soils color), negative change (black soils color transitioning to non-black soils color), and consistently non-black soils color. Using existing reclamation history and soil organic carbon (SOC) datasets, soil color change trends were analyzed. The experimental results show that: 1. After 30 years of continuous cultivation, 23.16 % of cropland in Northeast China experienced negative changes in soil color; 2. In areas of long-term negative soil color changes after 30 years of continuous cultivation, SOC changes ranged from −1.45 g kg⁻¹ to −3.38 g kg⁻¹, while in areas with long-term positive changes, SOC changes ranged from 7.4 g kg⁻¹ to 11.68 g kg⁻¹; 3. The proportion of black soils color decreased after the conversion of natural land to cropland, with the most significant reduction occurring when forests were converted. In areas that had been cultivated for 11 to 15 years, the proportion of black soils color decreased by an average of 8.09% every five years.4. Soil color changes were primarily in the Chroma dimension, followed by the Value dimension. This study shows that cropland reclamation has had a significant impact on soil color changes. To better protect black soils, appropriate agricultural policies and management measures are recommended. The findings provide an important reference for soil color changes in the black soils region of Northeast China and highlight the crucial role of soil color in black soils conservation. These results offer a scientific basis for formulating effective soil management strategies.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106750"},"PeriodicalIF":6.1,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611647","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":"Estimating cropland soil organic carbon stock in Erhai Lake basin: Contribution of temporal-spatial-spectral information","authors":"Xinran Ji ,&nbsp;Bo-Hui Tang ,&nbsp;Liang Huang ,&nbsp;Guokun Chen ,&nbsp;Weipeng Le ,&nbsp;Dong Fan","doi":"10.1016/j.still.2025.106747","DOIUrl":"10.1016/j.still.2025.106747","url":null,"abstract":"<div><div>Traditional soil organic carbon (SOC) prediction methods exhibit significant uncertainty when applied to croplands in plateau lake basins, which are characterized by complex terrain, fragmented plots, and diverse cropping structures. In this study, we endeavored to overcome the limitations of traditional methods in predicting SOC content in the ecologically fragile and agriculturally vital plateau lake basins. This study effectively integrates dispersed soil data, spatial features, and temporal-spatial variations into seven categories of soil-forming factors by combining multi-source remote sensing data and a soil-pedogenic model. Furthermore, to extract the temporal-spatial-spectral (TSS) features of soil-forming factors and calculate the weights of input variables by integrating the convolutional neural networks, long short-term memory networks, and attention mechanism (CNN-LSTM_A), thereby enhancing the predictive accuracy and interpretability of SOC content. Finally, based on two periods of measured topsoil (0–20 cm) sample data, we constructed a precise estimation framework for interannual variations in cropland SOC stocks in the plateau lake basin. The results showed that CNN-LSTM_A outperformed six comparison models in both prediction accuracy and temporal transferability: reducing the RMSE_mean and MAE_mean by 1.6796–1.9558 g kg⁻¹ and 0.7835–1.2400 g kg⁻¹, increasing the R²_mean, RPIQ_mean, and CCC_mean by 0.0970–0.1273, 0.3863–0.5778, and 0.0773–0.1100, respectively. Additionally, the results confirmed that long-term crop growth information indirectly reflects the SOC accumulation process, contributing to improved prediction accuracy. From 2007–2016, the spatial heterogeneity of cropland SOC content in the Erhai Lake basin was jointly driven by vegetation and topography, with vegetation being the more influential factor. Higher SOC content was observed in regions on the western and northern sides of Erhai Lake, exhibiting certain temporal dynamics. During this period, cropland SOC content exhibited an overall increasing trend, with significant increases concentrated in the northern basin. However, due to a reduction in cropland area, total SOC stocks showed a decreasing trend (4.366 Tg C and 4.136 Tg C). Specifically, 0.475 Tg C was indirectly lost due to land use changes, while areas of unchanged cropland directly contributed a gain of 0.245 Tg C due to increasing SOC content. This research not only provides critical data support for ecological management and sustainable agricultural development in the Erhai Lake basin but also offers scientific backing for ecological protection and broader-scale carbon cycling studies in other ecologically fragile areas.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106747"},"PeriodicalIF":6.1,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144611791","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":"Nitrogen-induced soil acidification mitigates the negative effects of nitrogen addition on SOC stability","authors":"Xinsheng Zhang ,&nbsp;Shibing Jia ,&nbsp;Chengming You ,&nbsp;Hongwei Xu ,&nbsp;Yaling Yuan ,&nbsp;Jiao Li ,&nbsp;Sining Liu ,&nbsp;Bo Tan ,&nbsp;Zhenfeng Xu ,&nbsp;Jordi Sardans ,&nbsp;Josep Peñuelas","doi":"10.1016/j.still.2025.106752","DOIUrl":"10.1016/j.still.2025.106752","url":null,"abstract":"<div><div>While nitrogen (N) deposition is a well-established driver of soil organic carbon (SOC) stability, quantitative syntheses assessing its global-scale impacts remain surprisingly limited. This study conducted a meta-analysis of 4418 observations from 131 independent studies to investigate how SOC, particulate organic carbon (POC), and mineral-associated organic carbon (MAOC) response to N addition. Our findings showed that N addition increased SOC (6.53 %), POC (12.59 %) and MAOC (3.45 %) pools. Nevertheless, the POC:SOC ratio increased by 5.46 %, whereas the MAOC:SOC ratio decreased by 2.2 %, indicating that N addition reduced SOC stability. Under N addition, soil acidification was categorized into three levels based on the magnitude of soil pH decline: non-acidified [≥ 0], mildly acidified [-0.5–0] and severely acidified [≤ -0.5]. Soil acidification inhibited the positive responses of SOC and POC to N addition. With increasing acidification, both SOC and POC declined progressively. In contrast, Soil acidification generally promoted the accumulation effect of N addition on MAOC, as the 4.21 % increase in MAOC under mild acidification exceeded the 0.25 % loss under severe acidification. Furthermore, the MAOC:SOC ratio steadily increased under N-addition treatments, indicating that N-induced soil acidification contributed to SOC stability. Overall, our study demonstrated that N-induced soil acidification mitigated the negative effects of N addition on SOC stability by regulating the POC and MAOC response to N addition. These findings underscore the crucial role of soil acidification in regulating SOC dynamics under N addition and offer new insights into the interactions between soil C and N.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106752"},"PeriodicalIF":6.1,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604657","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":"Inversion and mapping of soil alkali-hydrolyzable nitrogen in farmland using satellite remote sensing and machine learning","authors":"Jinkai Qiu ,&nbsp;Wei Zhang ,&nbsp;Xiuying Xu ,&nbsp;Yongcai Ma ,&nbsp;Xiaoming Fu ,&nbsp;Wenqiang Shi","doi":"10.1016/j.still.2025.106748","DOIUrl":"10.1016/j.still.2025.106748","url":null,"abstract":"<div><div>Soil alkali-hydrolyzable nitrogen (SAN) is a crucial indicator of soil nutrient status. Quickly and accurately obtaining the spatial distribution of SAN content is essential for the effective implementation of precision variable fertilization. To efficiently estimate SAN content at the field scale and improve the model's accuracy and stability, the basic farmland of Jianshan Farm in Heilongjiang Province was selected as the study area. Remote sensing factors and topographic variables were extracted from Sentinel-2 satellite imagery and Copernicus digital elevation model. Simultaneously, SAN content was measured during different bare soil periods in spring and autumn. This study employed support vector regression (SVR), extreme gradient boosting (XGBoost) and BP neural network (BPNN) to establish SAN content inversion models for different bare soil periods. Then, the zebra optimization algorithm (ZOA) was used to optimize the hyperparameters of the best-performing model, and the experimental results were analyzed. Finally, the model's interpretability and reliability were validated through feature importance analysis and statistical significance tests. The results indicated that the correlation between the raw bands of remote sensing data in autumn and SAN content was generally higher than that in spring. The spring SAN inversion model, ZOA-XGBoost-2, which incorporates raw bands and topographic variables demonstrated the best predictive performance (R²=0.3416, r = 0.6153, RMSE=31.1616 mg/kg, MAE=21.2132 mg/kg, MAPE=7.5184 %). The autumn SAN inversion model, ZOA-BPNN-6, based on raw bands, vegetation indices and topographic variables demonstrated the best predictive performance (R²=0.7304, r = 0.8664, RMSE=20.3511 mg/kg, MAE=15.5451 mg/kg, MAPE=5.2008 %). Compared with the unoptimized inversion model, R² increased by 6.32 percentage points and 1.12 percentage points, and r increased by 3.99 percentage points and 1.01 percentage points, respectively, while RMSE, MAE and MAPE decreased. In the spring model, vegetation indices and raw bands accounted for 52.82 % and 47.18 % of the total importance, respectively, while in the autumn model, raw bands, vegetation indices, and topographic variables contributed 46.15 %, 30.72 %, and 23.13 %, respectively. In addition, ANOVA confirmed that the model performance differed significantly between the two seasons, validating the superiority of the autumn model in SAN prediction. The proposed inversion model yielded better prediction results, which closely aligned with the actual SAN data. It can provide a theoretical basis and technical support for the rapid and dynamic monitoring of soil nitrogen content at the farm scale, as well as for variable fertilization decision-making.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106748"},"PeriodicalIF":6.1,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144604656","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":"Cover cropping shifts microbial life-history strategies to promote necromass carbon accumulation through soil metabolite mediation in orchard systems","authors":"Yutao Zhang ,&nbsp;Jia Liu ,&nbsp;Kailou Liu ,&nbsp;Daming Li ,&nbsp;Rong Cui ,&nbsp;Yaxin Liu ,&nbsp;Xingjia Xiang ,&nbsp;Ming Liu","doi":"10.1016/j.still.2025.106749","DOIUrl":"10.1016/j.still.2025.106749","url":null,"abstract":"<div><div>Preliminary studies suggest that cover cropping (CC) enhances necromass carbon (C) accumulation, but the specific mechanisms linking microbial life-history strategies and soil biochemical pathways remain unclear. This study investigated these processes in orchard systems under hairy vetch (<em>Vicia villosa</em> Roth) cover in southern China, focusing on quantifying necromass C using biomarker analysis and examining the contributions of microbial assembly, life-history strategies, and soil metabolites to necromass C. Compared to clean tillage (CT), CC increased necromass C by 33.90 % and soil organic carbon (SOC) by 27.36 %. CC also enhanced homogeneous selection (HS), boosting bacterial community assembly by 12.85 % compared to CT, reinforcing deterministic processes. Additionally, CC shifted microbial life-history strategies toward the Y-strategy, enriching certain Proteobacteria with strong growth potential, leading to a 40.87 % increase in their relative abundance. Metabolites from the lipid and nucleic acid metabolic pathways, including lipids and lipid-like molecules (LL) as well as nucleosides, nucleotides, and analogues (NN), were significantly enhanced under CC, with relative abundances increasing by 94.85 % and 27.73 %, respectively, and positively correlating with necromass C. Partial least squares path modeling indicated that CC altered the bacterial community composition, ultimately increasing necromass C content, with this effect primarily mediated by soil metabolites. Overall, these findings demonstrate that CC promotes Y-strategist dominance through HS, which regulates LL and NN metabolism to promote necromass C accumulation. This study reveals novel perspectives on the microbial-mediated biochemical processes governing necromass C dynamics in orchard ecosystems, offering practical implications for sustainable agricultural management.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106749"},"PeriodicalIF":6.1,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144587790","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":"Effects of microplastics on the hydraulic properties and pore characteristics of compacted soil","authors":"Lisheng Guo ,&nbsp;Xin Xu ,&nbsp;Qing Wang ,&nbsp;Junboum Park ,&nbsp;Lu Zhou ,&nbsp;Haomin Lei ,&nbsp;Xinhai Wang","doi":"10.1016/j.still.2025.106742","DOIUrl":"10.1016/j.still.2025.106742","url":null,"abstract":"<div><div>As emerging persistent pollutants, microplastics have become widely distributed in natural environments. Current research primarily focuses on the effects of microplastics on uncompacted or lightly compacted soils. However, the effects of microplastics on compacted soils remain unclear and require an urgent investigation. Therefore, this study used polyethylene particles as microplastics to investigate their effects on the hydraulic properties (saturated hydraulic conductivity, water retention capacity, and water stability) and pore characteristics (porosity and pore size distribution) of compacted clayey soil. As the concentration of microplastics increased, the saturated hydraulic conductivity of compacted soil decreased, while the water retention capacity and water stability increased. The addition of microplastics reduced the porosity of compacted soil, decreasing the volume of inter-aggregate pores and increasing the volume of intra-aggregate pores. The percentage of macropores (&gt;4 μm) decreased, while the percentage of micropores (&lt;0.04 μm) increased. The changes in the hydraulic properties of compacted soil were mainly due to the alteration of its pore characteristics by microplastics. Overall, large-sized microplastics exhibited a greater impact than small-sized microplastics. In contrast to uncompacted or lightly compacted soils, the properties of compacted soils were significantly affected by microplastics at the environmentally relevant concentrations (0.5 wt%). This study reveals the mechanisms by which microplastics affect the hydraulic properties and pore characteristics of compacted soil, providing insights into the potential impacts and risks of microplastic pollution in the soil environment.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106742"},"PeriodicalIF":6.1,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144587791","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":"Effects of soil porosity on water stability of aggregates","authors":"Hairu Li ,&nbsp;Gang Liu ,&nbsp;Chenxi Dan ,&nbsp;Zongjiang Zhou ,&nbsp;Ya Liu ,&nbsp;Chang Liu ,&nbsp;Enshuai Shen ,&nbsp;Qiong Zhang ,&nbsp;Xiaolin Xia ,&nbsp;Dandan Liu ,&nbsp;Zhen Guo ,&nbsp;Xining Zhao","doi":"10.1016/j.still.2025.106741","DOIUrl":"10.1016/j.still.2025.106741","url":null,"abstract":"<div><div>Soil pore structure is a fundamental determinant of water infiltration, flow, and storage, and it is intricately linked to soil stability and erodibility. Understanding the interplay between soil pore structure and aggregate disintegration is vital for refining the erodibility factor in soil erosion prediction models. This study aimed to examine the differential impacts of pore volume on aggregate disintegration by employing three soil samples with controlled internal pore spaces at various initial moisture contents (air-dried aggregates with 3 %, 5 %, 10 %, 15 %, and 20 %). Computerized Tomography (CT) scanning technology was utilized to visualize and quantitatively assess the aggregate pore structure. The results indicated that the number of pores, as measured in three-dimensional (3D) space and fractal dimension (FD), initially increased and then subsequently decreased with rising moisture content. An increase in moisture content was associated with a decline in aggregate anisotropy values. The resistance of aggregates to slaking (<em>RSI</em>) diminished progressively with increasing moisture content. A significant negative correlation was observed between moisture content and anisotropy, mean weight diameter in the slow wetting (<em>MWD</em>_<em>sw</em>), <em>MWD</em> in the pre-wetting followed by shaking (<em>MWD</em>_<em>ws</em>), and <em>RSI</em>. Conversely, anisotropy, <em>MWD</em>_<em>ws</em>, and <em>RSI</em> exhibited significant positive correlations. This study not only enhances our understanding of the relationship between soil pore structure and stability but also has substantial practical implications for predicting water infiltration, flow, and storage in soil during natural rainfall events, as well as for assessing the stability and erodibility of soil aggregates under varying humidity conditions and improving soil erosion prediction models.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106741"},"PeriodicalIF":6.1,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144579674","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":"Identifying the critical potassium inputs for optimum yield, potassium use efficiency and soil fertility through potassium balance in a winter wheat-summer maize rotation system in North China","authors":"Mengze Xu,&nbsp;Lei Wang,&nbsp;Yanli Lu,&nbsp;Youlu Bai","doi":"10.1016/j.still.2025.106743","DOIUrl":"10.1016/j.still.2025.106743","url":null,"abstract":"<div><div>Potassium (K) is a primary limiting macronutrient for plant growth. Inappropriate K application decisions can lead to reduced yield and potassium use efficiency (KUE). Given the scarcity and non-renewable nature of K resources, developing an indicator for critical K input is essential. The apparent K balance is a simplified method calculated from fertilizer inputs and crop K uptake, enabling straightforward agronomic evaluation. Here, we hypothesize that the apparent K balance serves as a valuable indicator for determining critical K input. A twelve-year field trial with six K treatments (0, 30, 60, 90, 120, and 150 kg K ha^–1 per year) was conducted to assess grain yield response to apparent K balance, establish a K input-output framework, and determine critical K input in a winter wheat-summer maize rotation system in North China. The crop yield, K uptake, and K fertilizer recovery efficiency initially increased but then declined with increasing K fertilizer rates, likely due to excessive K-induced nutrient imbalance and salt stress. The K balance threshold can be determined based on the target yield to be pursued. A K balance of 0 –9.77 kg K ha^–1 per year achieved optimal yield and maintained soil fertility. The K input-output framework provided a clear visualization of the K balance and KUE relationships. The critical K input range of 56.6 –62.5 kg K ha^–1 achieved high yields with KUE improving to 85 –100 %, while sustaining high levels of soil available K and organic matter. Overall, optimizing K input within appropriate K balance thresholds enhances crop yield, KUE and soil quality simultaneously. This study provides new insights for determining critical K balance and K input, offering guidance for field-scale K management.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"254 ","pages":"Article 106743"},"PeriodicalIF":6.1,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144572548","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}