Soil & Tillage Research最新文献

{"title":"Drivers of soil quality and maize yield under long-term tillage and straw incorporation in Mollisols","authors":"Chunzhu Liu ,&nbsp;Bingcheng Si ,&nbsp;Ying Zhao ,&nbsp;Zhimin Wu ,&nbsp;Xinchun Lu ,&nbsp;Xu Chen ,&nbsp;Xiaozeng Han ,&nbsp;Yuanchen Zhu ,&nbsp;Wenxiu Zou","doi":"10.1016/j.still.2024.106360","DOIUrl":"10.1016/j.still.2024.106360","url":null,"abstract":"<div><div>Proper tillage combined with straw management is crucial for maintaining agroecosystem sustainability and crop yield, especially under intensified agricultural activities. However, the optimal depth for tillage in combination with straw incorporation remains unclear. To address this, we established a field experiment in 2011 in Mollisols with five treatments: conventional tillage (CT, tillage depth 20 cm), no-tillage combined with straw return (SNT), conventional tillage combined with straw return (SCT), inversion tillage combined with straw return (SIT, tillage depth 35 cm), and subsoil tillage combined with straw return (SST, straw depth 20–35 cm). We assessed the effects of these treatments on soil quality by evaluating the Soil Physical Property Index (SPI), Soil Chemical Property Index (SCI), and Soil Microbial Property Index (SMI) in relation to the Soil Quality Index (SQI) and crop yield. Our findings shown that tillage combined with straw return significantly improved soil properties. Compared to the CT, SNT, and SST treatments, the SCT and SIT treatments increased SPI and SQI in the 0–20 cm soil layer by 43.9–845.4 %. While the SIT and SST treatments enhanced SPI, SCI, and SMI in the 20–35 cm soil layer by 69.2–307.7 % more than the CT, SNT, and SCT treatments. Among all treatments, SIT treatment resulted in the highest SPI, SCI, and SMI in the 0–35 cm soil layer. Additionally, SQI and maize yield under the SIT treatment were 11.7–140.5 % and 15.6–78.0 % higher, respectively, compared to other treatments. Linear regression analysis revealed that SPI in all layers had a significant impact on maize yield, while SCI and SMI were significantly correlated with yield only in the 20–35 cm layer (<em>P</em> &lt; 0.05). SPI's contribution to maize yield was 18.6–156.8 % higher than that of SCI and SMI. Partial least-squares path modeling identified SPI as a direct influence on SMI and SCI, making it the largest driver indirectly improving SQI and maize yield in Mollisols. Therefore, SIT treatment is a highly effective soil management practice for improving soil quality and crop yields in the Mollisols region. Our study provides guidance for enhancing soil environmental quality and designing sustainable agricultural policies in the Mollisols region and other arable soils.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106360"},"PeriodicalIF":6.1,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643017","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":"Significant increases in nitrous oxide emissions under simulated extreme rainfall events and straw amendments from agricultural soil","authors":"Xiaogang Li ,&nbsp;Rui Wang ,&nbsp;Yanling Du ,&nbsp;Hui Han ,&nbsp;Shengli Guo ,&nbsp;Xiaotong Song ,&nbsp;Xiaotang Ju","doi":"10.1016/j.still.2024.106361","DOIUrl":"10.1016/j.still.2024.106361","url":null,"abstract":"<div><div>Pulsed N₂O emissions resulting from field management practices (N fertilization addition and straw return) or rainfall events make for a significant proportion of the total annual N₂O budget from croplands. However, it remains unclear whether altered rainfall patterns induced by climate change will stimulate the responses of pulsed N₂O emissions to various field practices. In this study, we aimed to elucidate the underlying mechanisms driving pulsed N₂O emissions in response to extreme rainfall events and examine their interaction with carbon and nitrogen availability. We hypothesized that highly available substrates rapidly induce an anaerobic environment and N₂O pulses during extreme rainfall events. A soil column experiment under simulating extreme rainfall events was conducted to investigate the responses of pulsed N₂O emissions to three common farming practices: nitrogen fertilization (N), nitrogen fertilization coupled with low straw return (N+LS), and nitrogen fertilization coupled with high straw return (N+HS). We frequently monitored surface emissions and soil concentrations of N₂O and CO₂, and measured O₂, NH₄⁺, NO₃^- and DOC concentrations. N and straw amendments together under simulated rainfall events significantly depleted O₂, and simultaneously increased pulsed N₂O emissions. The N+HS treatment exhibited the highest soil N₂O concentration (51.9 µL L⁻¹) and lowest O₂ concentration (4.3 %), along with high soil moisture levels (24.8 %–32.2 %). Correspondingly, the highest cumulative N₂O emissions were observed in the N+HS treatment (117.8 mg m⁻²), followed by 52.2, 31.9, and 11.0 mg m⁻² for the N+LS, N, and CK treatments, respectively. The promotion of N₂O production by highly available substrates confirms our hypothesis. Our work contributes to the refinement of global climate models and field mitigation practices, as pulsed N₂O emissions from croplands will increase under future extreme rainfall events owing to climate change.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106361"},"PeriodicalIF":6.1,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643025","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":"Straw incorporating in shallow soil layer improves field productivity by impacting soil hydrothermal conditions and maize reproductive allocation in semiarid east African Plateau","authors":"Sylvia Ngaira Indoshi ,&nbsp;Wesly Kiprotich Cheruiyot ,&nbsp;Muhammad Maqsood Ur Rehman ,&nbsp;Fu-Jian Mei ,&nbsp;Qing-Hui Wen ,&nbsp;Alex Ndolo Munyasya ,&nbsp;Kiprotich Koskei ,&nbsp;David Mwehia Mburu ,&nbsp;Aggrey Bernard Nyende ,&nbsp;Levis Kavagi ,&nbsp;Delphine Nyanchera Gisacho ,&nbsp;Eliyas Feyisa Sori ,&nbsp;Yi-Bo Wang ,&nbsp;Hong-Yan Tao ,&nbsp;You-Cai Xiong","doi":"10.1016/j.still.2024.106351","DOIUrl":"10.1016/j.still.2024.106351","url":null,"abstract":"<div><div>Ridge-furrow plastic film mulching (RFM) planting system can conserve soil water and boost crop yield in semi-arid rainfed agricultural areas. In the east African Plateau (EAP), the RFM system has shown significant promoting effects on the yield and water use efficiency in maize (<em>Zea mays</em> L.) and wheat (<em>Triticum aestivum</em> L.). Although the RFM system is effective and efficient, it is unclear how to further increase crop productivity under RFM in EAP where soil moisture is limited. This study advocates for an integrated practice (maize straw returning) in the RFM system. Field trials were conducted using maize cultivar DK8031 to investigate the effects of maize straw returning in the shallow soil layer on soil hydrothermal conditions from 2021 to 2022. Maize productivity, water use efficiency, soil organic carbon, and soil total nitrogen were determined under RFM in Kenya, EAP. Three treatments were designed as follows: 1) conventional bare flat planting, CK; 2) RF with full plastic film mulching, RFM; and 3) RFM with maize straw piece (9 t ha⁻¹) returning to 0–30 cm soil layer, RFMR. The results indicated that soil water storage (SWS) was substantially improved by 40.8 mm in 2021 and 30.9 mm in 2022 in RFMR, respectively, than that of CK, which was also significantly greater than that of RFM (<em>p</em>&lt;0.05). Under relatively high air temperature at the silking stage, soil temperature at 15 cm soil depth was averagely reduced by 0.85 °C in RFMR and 0.15 °C in RFM, respectively, compared with CK. Across two growing seasons, grain yield and water use efficiency increased by 470 kg ha⁻¹ and 1.5 kg ha⁻¹mm⁻¹ in RFMR compared to RFM and 2407 kg ha⁻¹ and 7.1 kg ha⁻¹mm⁻¹ compared with CK, respectively., The highest economic benefit was found in RMFR, relative to RFM and CK. The above trend was positively associated with the improvements in hydrothermal conditions in the shallow soil layer. Additionally, soil organic carbon was increased by 0.88 g kg⁻¹ in RFMR relative to CK due to improved soil structure and physiochemical traits. For the first time, we found that straw pieces returning to the shallow soil layer can further boost maize productivity on the basis of RFM, which was intended to improve soil texture in EAP.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106351"},"PeriodicalIF":6.1,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643020","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":"Improving the accuracy of soil organic matter mapping in typical Planosol areas based on prior knowledge and probability hybrid model","authors":"Deqiang Zang ,&nbsp;Yinghui Zhao ,&nbsp;Chong Luo ,&nbsp;Shengqi Zhang ,&nbsp;Xilong Dai ,&nbsp;Yong Li ,&nbsp;Huanjun Liu","doi":"10.1016/j.still.2024.106358","DOIUrl":"10.1016/j.still.2024.106358","url":null,"abstract":"<div><div>The use of remote sensing techniques for mapping soil organic matter (SOM) in black soil regions is well established. However, in areas where Planosols are interspersed with non-Planosols, tilling impacts the soil spectra of tilled soils at varying times and to different extents. As a result, errors may arise when modeling Planosols and non-Planosols collectively using conventional methods. This study developed a probability hybrid model specifically designed for the interlayered zones of Planosol and non-Planosol soils to accurately reflect the content and spatial distribution of SOM. A total of 712 topsoil samples were collected from the 852 Farm, a typical area with the interlayered zones of Planosol and non-Planosol soils in northeastern China. Cloud-free Sentinel-2 images were obtained during the bare soil period from April to May between 2021 and 2023. The spatial distribution of Planosol was detected, and the probability of soil classification was calculated using a random forest model. Based on soil classification probabilities, global models, multi-temporal ordinary hybrid models, and multi-temporal probability hybrid models were developed respectively. The results of SOM mapping using these different strategies were compared. Under seasonal reductive leaching, Planosol exhibits a distinct eluvial horizon beneath the topsoil. Long-term tilling leads to the mixing of this eluvial horizon with the topsoil in Planosol, resulting in spectral characteristics that differ significantly from those of other soil types. Accordingly, we propose a new remote sensing index—the Normalized Difference Planosol Index (NDPI), to reflect the upturning degree of the eluvial horizon and get “whiteness degree” information. We evaluated the effect of adding this index as an input on the detection of Planosol and the accuracy of SOM mapping. The results of the study show that (1) May is the optimal time window for SOM mapping and Planosol detection in the typical interlayered area of Planosol and non-Planosol soils. (2) Based on the random forest model combined with multi-period May bare soil images can accurately detect the spatial distribution of Planosol with the highest accuracy, the overall accuracy is 97.66 %; (3) The hybrid models outperform the global model, with the probability hybrid model achieving the highest accuracy (R²=0.8056, RMSE=4.2869 g/kg) and the mapping is more continuous and smoother. (4) The inclusion of NDPI improves the accuracy of Planosol spatial distribution detection and SOM mapping in Planosol areas, resulting in an increase in the Kappa coefficient by 0.0168 and an improvement in R² by 0.0122. The present study innovatively utilizes remote sensing imagery to monitor Planosol, thus expanding the application of remote sensing technology in digital soil mapping.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106358"},"PeriodicalIF":6.1,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643019","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":"Improved soil organic matter monitoring by using cumulative crop residue indices derived from time-series remote sensing images in the central black soil region of China","authors":"Mei-Wei Zhang ,&nbsp;Xiao-Lin Sun ,&nbsp;Mei-Nan Zhang ,&nbsp;Hao-Xuan Yang ,&nbsp;Huan-Jun Liu ,&nbsp;Hou-Xuan Li","doi":"10.1016/j.still.2024.106357","DOIUrl":"10.1016/j.still.2024.106357","url":null,"abstract":"<div><div>Soil organic matter (SOM) determines soil fertility and functions, playing a key role in agriculture, the environment and climate change. During the past century, the SOM of the world, e.g., the black soil (Mollisol) in croplands of Northeast China, experienced extensive changes, making SOM monitoring crucial. Recently, digital soil mapping (DSM) with time-series remote sensing images has become a mainstream method for SOM monitoring, but there is room for its accuracy to be improved. To fulfill this purpose, we propose utilizing crop residue indices (CRIs) derived from remote sensing images within the method, as crop residues are a main source of the SOM. In this study, performances of five commonly used CRIs, e.g., normalized difference tillage index (NDTI), on SOM monitoring was evaluated based on a series of topsoil samples collected from 2014 to 2018 in croplands of the center black soil region in Northeast China. The performances and those of cumulative CRIs computed over some years were compared to those of basic climate and terrain attributes, spectral bands, an empirical index, and commonly used vegetation indices (VIs, e.g., normalized difference vegetation index (NDVI)). Results showed that temporal CRIs had a stronger correlation with SOM content (0.52–0.73) than did the others (0.04–0.69). Integrating CRIs with basic soil covariates increased prediction accuracy by 7.27 % in Lin’s concordance correlation coefficient (CCC). Further, the CRIs and VIs accumulated over 3 and 4 years, respectively, had a much stronger correlation with SOM (0.65–0.73 and 0.67–0.69, respectively) and led to better accuracies with an average increase of 2.62 % in CCC compared to indices of the current sampling year. While annual SOM maps predicted with and without the optimal cumulative CRI showed similar spatial patterns, they were statistically significantly different. It is recommended to utilize the cumulative NDTI for monitoring SOM.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106357"},"PeriodicalIF":6.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643021","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":"Soil mineral–associated organic carbon fraction maintains quantitatively but not biochemically after cropland abandonment","authors":"Bin Jia ,&nbsp;Yanmei Liang ,&nbsp;Xiaoming Mou ,&nbsp;Han Mao ,&nbsp;Li Jia ,&nbsp;Jie Chen ,&nbsp;Kuzyakov Yakov ,&nbsp;Xiao Gang Li","doi":"10.1016/j.still.2024.106355","DOIUrl":"10.1016/j.still.2024.106355","url":null,"abstract":"<div><div>Abandonment is a strategy applied to increase soil organic C (SOC) in degraded cropland, but such efforts may fail because of microbial N limitation after abandonment in the absence of fertilization. In this study, we investigated the associations between SOC and microbial necromass C (MNC) dynamics in bulk soil and particle-size pools with N availability in a cropland abandonment chronosequence on the Loess Plateau. The total SOC, total MNC, and their particulate fractions (&gt; 0.05 mm) in soil declined in the first eight years after cropland abandonment, but increased thereafter. By the 23rd year, the SOC content in abandoned soils increased towards the levels of cropland (16.5 g kg^–1) but were still far lower than those of natural vegetation (21.5 g kg^–1). The mineral–associated SOC (&lt; 0.05 mm) content maintained after abandonment; but by contrast, the mineral-associated MNC profoundly decreased. This indicated that the reduction in MNC in this fraction was compensated for by plant-derived substances from the particulate fraction. Enzymatic stoichiometry analysis identified microbial N limitations in abandoned soils compared with cropland soils. As such, microbial N limitation led to increases in mineralization and/or decreases in synthesis of MNC in both particulate and mineral-associated fractions after abandonment, attributable to the decreased total SOC. Across the abandonment chronosequence, up to 20 % of particulate SOC was derived from microbes, whereas more than half of mineral-associated SOC came from plants. These findings challenge the general consensus that particulate SOC is dominated by plant residues whereas the mineral-associated fraction contains mainly microbially derived substances. The MNC contained a smaller proportion of fungal substances in mineral-associated fractions compared to particulate fractions, reflecting microbial ecological niche differentiation in the SOC formation between particle-size fractions. In conclusion, cropland abandonment decreased MNC accumulation because of microbial N limitation, and the mineral-associated SOC was stable in quantity but not in its source composition.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106355"},"PeriodicalIF":6.1,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643022","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":"Combined measurement of roots, δ18O and δ2H, and a Bayesian mixed model capture the soil profiles of wheat water uptake in a deep loamy soil","authors":"Runze Zhang ,&nbsp;Jiaxing Xu ,&nbsp;Panxin Zhang ,&nbsp;Yan Han ,&nbsp;Changlu Hu ,&nbsp;Victor Sadras ,&nbsp;Xueyun Yang ,&nbsp;Shulan Zhang","doi":"10.1016/j.still.2024.106359","DOIUrl":"10.1016/j.still.2024.106359","url":null,"abstract":"<div><div>The profile of crop water uptake from the soil depends on rainfall regime (amount, seasonality, frequency distribution of rainfall event size), soil, crop, and management. This study, with a focus on winter wheat in a wheat-fallow system, combines measurements of hydrogen (δD) and oxygen (δ¹⁸O) isotopes with a Bayesian mixing model (MixSIAR), and measurements of root length density to (i) quantify crop water uptake from soil down to 3 m depth, (ii) to assess the influence of soil water at sowing, soil mulching, seasonal conditions and their interaction on the profiles of soil water uptake, and (iii) to probe for relations between yield and the profiles of soil water uptake. Across treatments and seasons, water uptake at jointing featured a ratio 2.1: 1.0: 1.8: 2.2 in four soil layers, top 0.2 m, 0.2<img>0.4 m, 0.4<img>1.2 m, and 1.2–3.0 m. At anthesis, the ratios shifted to 5.2: 1.0: 1.7: 2.0. Water uptake at jointing was higher from top-soil in dry (∼60 %) than in wet condition (∼30 %), and the opposite was true in deeper layers; water supply had a smaller effect on the profiles of water uptake at anthesis. Compared to bare ground, mulch favored root proliferation and water uptake in 0.4<img>2.0 m soil layer. For a given soil layer, soil moisture correlated negatively with root length density. Yield correlated positively and linearly with water uptake from 0.4<img>3.0 m soil at jointing, indicating that faster root development at early stages favors water uptake from deep soil in the critical period of grain yield formation. We discuss the implications of our findings for agronomic management and breeding.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106359"},"PeriodicalIF":6.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643023","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":"Land degradation decreased crop productivity by altering soil quality index generated by network analysis","authors":"Ming Gao ,&nbsp;Wei Hu ,&nbsp;Xingyi Zhang ,&nbsp;Meng Li ,&nbsp;Yongsheng Yang ,&nbsp;Renfeng Che","doi":"10.1016/j.still.2024.106354","DOIUrl":"10.1016/j.still.2024.106354","url":null,"abstract":"<div><div>Soil erosion is a principal mechanism of land degradation, and wind erosion is particularly marked in northeast China due to its ecological characteristics. However, most investigations on the implications of land degradation on soil quality and crop productivity have concentrated on water-erosion regions, and little focus has been placed on the wind-erosion region. Therefore, we examined the impacts of land degradation on soil quality and crop productivity in the degradation area of Horqin Sandy Land, the wind-eroded region of northeast China, which suffers from varying intensities of land degradation, that is, no degraded grassland, lightly, moderately, and severely degraded croplands. In our study, network analysis (NA) was applied as a novel approach to calculate the soil quality index (SQI), which covered 11 physical, 12 chemical, and 6 biological variables measured in the 0–20 cm soil layer as indicators of soil quality. Results showed that land degradation resulted in adverse effects on soil properties. SQI, crop yield, and above-ground biomass significantly decreased with land degradation increasing (<em>P</em> &lt; 0.05). Specifically, the result of NA showed soil organic carbon, microbial biomass carbon, and bulk density (BD) were the most responsive factors impacting SQI under land degradation. Structural equation modeling showed that land degradation led to the reduction of crop productivity by altering soil properties and then changing SQI. Soil physical properties were the best mediator for the indirect effects of land degradation on SQI. In addition, the BD increased, but clay, soil total nitrogen, and organic matter content decreased from 1981 to 2022, which reveals land degradation in this area. Our investigation provides a theoretical foundation for preserving cropland in wind-eroded areas of northeast China.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106354"},"PeriodicalIF":6.1,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142643024","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":"Modeling compaction effects on hydraulic properties of soils using limited information","authors":"Andre Peters ,&nbsp;Kai Germer ,&nbsp;Mahyar Naseri ,&nbsp;Lennart Rolfes ,&nbsp;Marco Lorenz","doi":"10.1016/j.still.2024.106349","DOIUrl":"10.1016/j.still.2024.106349","url":null,"abstract":"<div><div>Soil compaction leads to an increase in bulk density (<span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span>) and a shift in the pore-size distribution towards smaller pores. This in turn changes the soil hydraulic properties (SHP), i.e., the water retention curve (WRC) and the hydraulic conductivity curve (HCC). Up to now, attempts to model the effect of altered <span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span> on SHP has been limited to SHP models that account only for capillary water, neglecting water stored and transmitted in adsorbed films (non-capillary water). We combine a recently developed model for compaction effects on SHP with a SHP model system, which accounts for both capillary and non-capillary water (Peters-Durner-Iden model system - PDI). Due to a plausible course of the PDI-WRC towards oven dryness and a physically based prediction scheme of the PDI-HCC based on the WRC, the new combined approach can fully predict both soil hydraulic functions of compacted soils, even with limited information. The new approach is analyzed via a sensitivity analysis and tested with a large dataset from a silty arable soil. A comparison with an established prediction approach showed that our new approach has slightly better predictive performance within the measurement range and a more plausible course in the dry range. For our field data, the new approach performed best when only 2 of the water retention parameters were scaled based on the known <span><math><msub><mrow><mi>ρ</mi></mrow><mrow><mi>b</mi></mrow></msub></math></span>. One of them determines the adsorptive water content and the other the shift of the capillary retention function on suction axis. Both parameters can be considered model independent, indicating that the new approach may not need calibration for each capillary retention model within the PDI model system.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106349"},"PeriodicalIF":6.1,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network analysis was effective in establishing the soil quality index and differentiated among changes in land-use type","authors":"Ming Gao ,&nbsp;Wei Hu ,&nbsp;Meng Li ,&nbsp;Shuli Wang ,&nbsp;Lin Chu","doi":"10.1016/j.still.2024.106352","DOIUrl":"10.1016/j.still.2024.106352","url":null,"abstract":"<div><div>Understanding the implications of land-use type on soil quality and function is critical to the adoption of suitable agricultural management practices in a specific region. Principal component analysis (PCA) is a widespread technique for calculating soil quality index (SQI), but it cannot correctly evaluate soil quality in some cases. Network analysis (NA) is a novel and effective technique for calculating SQI for determining susceptibility in different land uses but it is still limited. Moreover, few studies have compared NA and PCA to quantify soil quality. This study aimed to develop valid and accurate SQIs through NA and PCA to estimate the impacts of land-use types (cropland, forest, and grassland) on SQIs in Tongliao and Qiqihar, which are the two regions subject to frequent wind erosion in northeast China. A total of 27 soil physical, chemical, and biological properties were measured for the selection of the minimum data set (MDS), and eight SQI values were determined for each study site using additive or weighted methods and linear or nonlinear scoring functions. Results indicated that most soil attributes and SQIs varied markedly among three land-use types and were greater in grasslands or forests than in croplands. The amount of MDS generated using NA was considerably low, but soil physicochemical and biological properties were comprehensively covered. SOC in Tongliao and SHC in Qiqihar were selected by both methods and were considered the most sensitive soil quality indicators for detecting the effects of land-use types. The soil sensitivity index of the SQI calculated by NA (1.34–2.02) was higher than that of the SQI calculated by PCA (1.30–1.80). Thus, NA was more effective than PCA in computing the SQI and differentiated among changes in land use better as a simple and stable tool. The SQI developed through NA using the weighted method and nonlinear scoring function is a suitable and practical quantitative tool for SQI assessment, which is proposed to be used for soil quality assessment for various land-use types in northeast China.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106352"},"PeriodicalIF":6.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586807","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}