Pub Date : 2024-11-12DOI: 10.1016/j.still.2024.106359
Runze Zhang , Jiaxing Xu , Panxin Zhang , Yan Han , Changlu Hu , Victor Sadras , Xueyun Yang , Shulan Zhang
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, 0.20.4 m, 0.41.2 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 0.42.0 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 0.43.0 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.
{"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 , Jiaxing Xu , Panxin Zhang , Yan Han , Changlu Hu , Victor Sadras , Xueyun Yang , 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 (δ<sup>18</sup>O) 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}
Pub Date : 2024-11-09DOI: 10.1016/j.still.2024.106354
Ming Gao , Wei Hu , Xingyi Zhang , Meng Li , Yongsheng Yang , Renfeng Che
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 (P < 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.
{"title":"Land degradation decreased crop productivity by altering soil quality index generated by network analysis","authors":"Ming Gao , Wei Hu , Xingyi Zhang , Meng Li , Yongsheng Yang , 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> < 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}
Pub Date : 2024-11-06DOI: 10.1016/j.still.2024.106349
Andre Peters , Kai Germer , Mahyar Naseri , Lennart Rolfes , Marco Lorenz
Soil compaction leads to an increase in bulk density () 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 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 . 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.
{"title":"Modeling compaction effects on hydraulic properties of soils using limited information","authors":"Andre Peters , Kai Germer , Mahyar Naseri , Lennart Rolfes , 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}
Pub Date : 2024-11-05DOI: 10.1016/j.still.2024.106352
Ming Gao , Wei Hu , Meng Li , Shuli Wang , Lin Chu
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.
{"title":"Network analysis was effective in establishing the soil quality index and differentiated among changes in land-use type","authors":"Ming Gao , Wei Hu , Meng Li , Shuli Wang , 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}
Pub Date : 2024-11-05DOI: 10.1016/j.still.2024.106350
Nana Wang , Zicheng Zheng , Tingxuan Li , Shuqin He , Xizhou Zhang , Yongdong Wang , Haiying Yu , Huagang Huang , Daihua Ye
Soil surface roughness (SSR) impacts runoff dynamics of surface-subsurface and the magnitude of soil erosion, limited attention has been paid to how SSR governs runoff hydrodynamics to affect erosion behavior and the effectiveness of erosion reduction under rainfall-seepage scenarios on low-permeability purple soil slopes. Herein the seepage rates of 2, 4, and 8 L min⁻¹ were sequentially simulated under a rainfall intensity of 1.0 mm min⁻¹ among different microrelief treatments (CT: conventional tillage; AD: artificial digging; RT: ridge tillage) on purple soil slopes with gradients of 5°, 10°, and 15°. These simulations aimed to investigate the mechanisms underlying the erosion reduction benefits associated with flow properties due to microrelief. The results showed that increased SSR altered erosion kinetic energy under rainfall-seepage conditions. The benefits of rough slopes to control erosion decreased as rainfall-seepage intensity and slope gradient increased. During rainfall-seepage events, the variation in runoff behavior was regulated positively by the effect of SSR on unit stream power. However, the increasing net output power of runoff due to flow turbulence altered sediment output, thereby affecting sediment control benefits. Overall, the impact of rainfall-seepage intensity on surface roughness became more significant with increasing slope gradient. Our findings suggest the capable of integrating for interrelated microrelief and runoff processes in factors analysis of driving soil erosion at rainfall-seepage hydrologic states to elucidate erosion effect.
土壤表面粗糙度（SSR）影响表层-次表层径流动力学和土壤侵蚀程度，但人们对 SSR 如何调节径流流体力学以影响侵蚀行为以及在低渗透性紫色土斜坡上降雨-渗流情况下减少侵蚀效果的关注还很有限。本文模拟了在梯度为 5°、10° 和 15°的紫色土壤斜坡上，在降雨强度为 1.0 mm min-¹ 的情况下，不同微灌处理（CT：常规耕作；AD：人工挖掘；RT：脊耕）的渗流率依次为 2、4 和 8 L min-¹。这些模拟旨在研究微疏松带来的与流动特性相关的侵蚀减少效益的内在机制。结果表明，在降雨-渗流条件下，SSR 的增加改变了侵蚀动能。随着降雨-渗流强度和坡度的增加，糙面斜坡对控制侵蚀的益处也在减少。在降雨-渗流事件中，径流行为的变化受 SSR 对单位水流功率影响的正向调节。然而，由于水流湍动导致径流净输出功率增加，从而改变了沉积物的输出量，从而影响了沉积物控制效益。总体而言，降雨-渗流强度对地表粗糙度的影响随着坡度的增加而变得更加显著。我们的研究结果表明，在对降雨-渗流水文状态下的土壤侵蚀驱动因素进行分析时，可以综合考虑相互关联的微解脱过程和径流过程，以阐明侵蚀效应。
{"title":"Soil surface roughness impacts erosion behavior through selective regulation of flow properties in rainfall-seepage scenarios","authors":"Nana Wang , Zicheng Zheng , Tingxuan Li , Shuqin He , Xizhou Zhang , Yongdong Wang , Haiying Yu , Huagang Huang , Daihua Ye","doi":"10.1016/j.still.2024.106350","DOIUrl":"10.1016/j.still.2024.106350","url":null,"abstract":"<div><div>Soil surface roughness (SSR) impacts runoff dynamics of surface-subsurface and the magnitude of soil erosion, limited attention has been paid to how SSR governs runoff hydrodynamics to affect erosion behavior and the effectiveness of erosion reduction under rainfall-seepage scenarios on low-permeability purple soil slopes. Herein the seepage rates of 2, 4, and 8 L min⁻¹ were sequentially simulated under a rainfall intensity of 1.0 mm min⁻¹ among different microrelief treatments (CT: conventional tillage; AD: artificial digging; RT: ridge tillage) on purple soil slopes with gradients of 5°, 10°, and 15°. These simulations aimed to investigate the mechanisms underlying the erosion reduction benefits associated with flow properties due to microrelief. The results showed that increased SSR altered erosion kinetic energy under rainfall-seepage conditions. The benefits of rough slopes to control erosion decreased as rainfall-seepage intensity and slope gradient increased. During rainfall-seepage events, the variation in runoff behavior was regulated positively by the effect of SSR on unit stream power. However, the increasing net output power of runoff due to flow turbulence altered sediment output, thereby affecting sediment control benefits. Overall, the impact of rainfall-seepage intensity on surface roughness became more significant with increasing slope gradient. Our findings suggest the capable of integrating for interrelated microrelief and runoff processes in factors analysis of driving soil erosion at rainfall-seepage hydrologic states to elucidate erosion effect.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106350"},"PeriodicalIF":6.1,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586806","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}
Pub Date : 2024-11-04DOI: 10.1016/j.still.2024.106348
Weiting Ding , Liangjie Sun , Yihan Fang , Francis Zvomuya , Xiaotong Liu , Hailong He
Cover crops (CC) have been widely recognized and implemented as one of the most effective agronomic practices for enhancing soil organic carbon (SOC) sequestration in orchard ecosystems. However, considerable uncertainty remains regarding the effect of CC on specific SOC fractions, posing challenges for accurate prediction of carbon (C) dynamics, which requires further comprehensive study at regional and national scales. Based on 615 paired-comparisons from 47 studies across China, we investigated the effects of CC management on SOC fractions, including microbial biomass C (MBC), dissolved organic C (DOC), particulate organic C (POC), easily oxidizable organic C (EOC), light fraction organic C (LFOC), and heavy fraction organic C (HFOC). In addition, we quantified the effects of various environmental factors (e.g., climatic conditions), soil properties (e.g., soil characteristics and depth), and agronomic variables (e.g., experiment duration, tree age, cover type, source and species of grass, cover pattern, mowing practices, and residue management) on the changes in SOC fractions. Compared to conventional clean (bare ground) tillage, CC significantly increases MBC (35.4 %), DOC (23.7 %), POC (36.2 %), EOC (18.4 %), LFOC (99.9 %), and HFOC (5.4 %). Random forest modeling demonstrates that soil depth is the dominant driver of SOC fractions responses to CC, and the CC effects are weakened with soil depth. It is therefore crucial to consider the various drivers of SOC fractions between soil depths in order to accurately forecast soil C dynamics and its potential feedback on global warming. Overall, this study systematically assessed the effects of CC on SOC fractions changes in China and identified CC as a promising practice for increasing SOC in orchards. These findings further indicate that the response of SOC fractions to CC is predominantly influenced by specific climatic, edaphic, and agronomic variables. These results not only reveal the ecological benefits of CC, but also highlight the importance of developing site-specific CC practices for the sustainability of agroecosystems.
覆盖作物（CC）作为提高果园生态系统土壤有机碳（SOC）固存的最有效农艺措施之一，已得到广泛认可和实施。然而，CC对特定SOC组分的影响仍存在相当大的不确定性，为准确预测碳（C）的动态变化带来了挑战，这需要在区域和国家尺度上进行进一步的综合研究。基于全国 47 项研究中的 615 项配对比较，我们调查了 CC 管理对 SOC 分馏的影响，包括微生物生物量碳（MBC）、溶解有机碳（DOC）、颗粒有机碳（POC）、易氧化有机碳（EOC）、轻组分有机碳（LFOC）和重组分有机碳（HFOC）。此外，我们还量化了各种环境因素（如气候条件）、土壤特性（如土壤特性和深度）和农艺变量（如实验持续时间、树龄、覆盖类型、草的来源和种类、覆盖模式、除草方法和残留物管理）对 SOC 分数变化的影响。与传统的清洁（裸地）耕作相比，CC 能显著增加 MBC（35.4%）、DOC（23.7%）、POC（36.2%）、EOC（18.4%）、LFOC（99.9%）和 HFOC（5.4%）。随机森林建模表明，土壤深度是 SOC 分量对 CC 响应的主要驱动因素，CC 的影响随土壤深度的增加而减弱。因此，为了准确预测土壤碳动态及其对全球变暖的潜在反馈，考虑不同土壤深度之间 SOC 分量的各种驱动因素至关重要。总之，本研究系统地评估了 CC 对中国 SOC 分量变化的影响，并确定 CC 是增加果园 SOC 的有效方法。这些发现进一步表明，SOC组分对CC的响应主要受特定气候、土壤和农艺变量的影响。这些结果不仅揭示了CC的生态效益，还强调了因地制宜地发展CC实践对农业生态系统可持续性的重要性。
{"title":"Depth-driven responses of soil organic carbon fractions to orchard cover crops across China: A meta-analysis","authors":"Weiting Ding , Liangjie Sun , Yihan Fang , Francis Zvomuya , Xiaotong Liu , Hailong He","doi":"10.1016/j.still.2024.106348","DOIUrl":"10.1016/j.still.2024.106348","url":null,"abstract":"<div><div>Cover crops (CC) have been widely recognized and implemented as one of the most effective agronomic practices for enhancing soil organic carbon (SOC) sequestration in orchard ecosystems. However, considerable uncertainty remains regarding the effect of CC on specific SOC fractions, posing challenges for accurate prediction of carbon (C) dynamics, which requires further comprehensive study at regional and national scales. Based on 615 paired-comparisons from 47 studies across China, we investigated the effects of CC management on SOC fractions, including microbial biomass C (MBC), dissolved organic C (DOC), particulate organic C (POC), easily oxidizable organic C (EOC), light fraction organic C (LFOC), and heavy fraction organic C (HFOC). In addition, we quantified the effects of various environmental factors (e.g., climatic conditions), soil properties (e.g., soil characteristics and depth), and agronomic variables (e.g., experiment duration, tree age, cover type, source and species of grass, cover pattern, mowing practices, and residue management) on the changes in SOC fractions. Compared to conventional clean (bare ground) tillage, CC significantly increases MBC (35.4 %), DOC (23.7 %), POC (36.2 %), EOC (18.4 %), LFOC (99.9 %), and HFOC (5.4 %). Random forest modeling demonstrates that soil depth is the dominant driver of SOC fractions responses to CC, and the CC effects are weakened with soil depth. It is therefore crucial to consider the various drivers of SOC fractions between soil depths in order to accurately forecast soil C dynamics and its potential feedback on global warming. Overall, this study systematically assessed the effects of CC on SOC fractions changes in China and identified CC as a promising practice for increasing SOC in orchards. These findings further indicate that the response of SOC fractions to CC is predominantly influenced by specific climatic, edaphic, and agronomic variables. These results not only reveal the ecological benefits of CC, but also highlight the importance of developing site-specific CC practices for the sustainability of agroecosystems.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106348"},"PeriodicalIF":6.1,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578405","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}
Pub Date : 2024-11-04DOI: 10.1016/j.still.2024.106345
Carolina Bilibio , Tobias Karl David Weber , Markus Hammer-Weis , Stephan Martin Junge , Simeon Leisch-Waskoenig , Janos Wack , Wiebke Niether , Andreas Gattinger , Maria Renate Finckh , Stephan Peth
Regenerative agriculture has been associated with improved soil structure and soil fertility. However, conclusive evidence of its efficacy has remained elusive owing to a lack of long-term experimental studies. In this study, we assessed the impact of diverse regenerative agricultural measures on soil mechanical and hydraulic properties and indicators. Tested treatment factors included reduced tillage versus plowing, along with different levels of compost, mulch, and the application of ferments and compost tea. We measured in situ soil strength via soil penetration (from 0 to 0.8 m depth) and shear resistance (at 0.08 and 0.23 m depth) and assessed field-saturated hydraulic conductivity and ex situ soil aggregate stability (at 0.07 and 0.23 m depth). The experiments were conducted at five sites in Hesse, Germany, including one organic long-term experiment (LTE, since 2010) in Neu-Eichenberg and three organic and one conventional on-farm experiments to cover different soil types, weather conditions, and field practices. The soil types are classified as Luvisol and Vertic Cambisols, and the soil texture ranges from silt loam to silty clay loam. In the LTE, significant differences in aggregate stability and shear resistance were noted between treatments, with a higher geometric mean aggregate diameter at 0.07 m depth in 2021 and 2022 and a higher shear resistance at 0.19 m and 0.23 m in 2020 and in 2021, respectively, in the reduced tillage systems. However, no significant differences were observed among treatments for field-saturated hydraulic conductivity, which was overall very high, showing that reduced tillage did not negatively influence saturated infiltration, albeit bulk density is higher than in the conventionally plowed system. The soil penetration resistance was generally higher for the reduced tillage treatments across depths of 0.0–0.30 m, albeit not statistically significant (p > 0.05). Significantly higher water-stable aggregates and geometric mean diameters were observed for regenerative agricultural treatments in three of the on-farm experiments at a depth of 0.07 m. The shear resistance was significantly higher in regenerative agriculture units in specific years and depths. Although the outcomes are encouraging, the variability of the effects of reduced tillage and organic amendments in affecting soil properties highlights the need for further long-term research including farm trials. This is essential to fully understand the effects of regenerative practices on soil physical quality.
{"title":"Changes in soil mechanical and hydraulic properties through regenerative cultivation measures in long-term and farm experiments in Germany","authors":"Carolina Bilibio , Tobias Karl David Weber , Markus Hammer-Weis , Stephan Martin Junge , Simeon Leisch-Waskoenig , Janos Wack , Wiebke Niether , Andreas Gattinger , Maria Renate Finckh , Stephan Peth","doi":"10.1016/j.still.2024.106345","DOIUrl":"10.1016/j.still.2024.106345","url":null,"abstract":"<div><div>Regenerative agriculture has been associated with improved soil structure and soil fertility. However, conclusive evidence of its efficacy has remained elusive owing to a lack of long-term experimental studies. In this study, we assessed the impact of diverse regenerative agricultural measures on soil mechanical and hydraulic properties and indicators. Tested treatment factors included reduced tillage versus plowing, along with different levels of compost, mulch, and the application of ferments and compost tea. We measured <em>in situ</em> soil strength via soil penetration (from 0 to 0.8 m depth) and shear resistance (at 0.08 and 0.23 m depth) and assessed field-saturated hydraulic conductivity and <em>ex situ</em> soil aggregate stability (at 0.07 and 0.23 m depth). The experiments were conducted at five sites in Hesse, Germany, including one organic long-term experiment (LTE, since 2010) in Neu-Eichenberg and three organic and one conventional on-farm experiments to cover different soil types, weather conditions, and field practices. The soil types are classified as Luvisol and Vertic Cambisols, and the soil texture ranges from silt loam to silty clay loam. In the LTE, significant differences in aggregate stability and shear resistance were noted between treatments, with a higher geometric mean aggregate diameter at 0.07 m depth in 2021 and 2022 and a higher shear resistance at 0.19 m and 0.23 m in 2020 and in 2021, respectively, in the reduced tillage systems. However, no significant differences were observed among treatments for field-saturated hydraulic conductivity, which was overall very high, showing that reduced tillage did not negatively influence saturated infiltration, albeit bulk density is higher than in the conventionally plowed system. The soil penetration resistance was generally higher for the reduced tillage treatments across depths of 0.0–0.30 m, albeit not statistically significant (p > 0.05). Significantly higher water-stable aggregates and geometric mean diameters were observed for regenerative agricultural treatments in three of the on-farm experiments at a depth of 0.07 m. The shear resistance was significantly higher in regenerative agriculture units in specific years and depths. Although the outcomes are encouraging, the variability of the effects of reduced tillage and organic amendments in affecting soil properties highlights the need for further long-term research including farm trials. This is essential to fully understand the effects of regenerative practices on soil physical quality.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106345"},"PeriodicalIF":6.1,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578403","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}
Pub Date : 2024-11-02DOI: 10.1016/j.still.2024.106341
Simon Ian Futerman , Yafit Cohen , Yael Laor , Eli Argaman , Shlomi Aharon , Gil Eshel
Cover crops (CC) effectively reduce soil erosion, a significant threat to farmers and the environment. Yet, there is lack of data quantifying their effect on rill erosion in the field scale. The major objective of this study was to use UAV-RGB images to estimate the effects of CC on rill erosion in the field scale and to characterize rill parameters in areas with and without CC. Images were collected from a 20-ha field in the "Model Farm for Sustainable Agriculture", consisting of plots with and without CC. Images were captured 33 days after CC sowing and following substantial rainfall events that formed three prominent rills. Following the elimination of vegetation pixels, structure from motion algorithm was used to generate a post-erosion digital surface model (DSM) and a baseline DSM simulating the pre-erosion soil surface (DSM reconstructed baseline). Change-detection analysis revealed that CC significantly reduced rill erosion. Average soil loss per m2 was 48 %, 58 %, and 29 % lower in CC compared to bare soil plots in the three studied rills. Additionally, rill maximum depth was 74 %, 74 %, and 24 %, and cross-sectional surface area was 67 %, 87 %, and 43 % lower in CC, compared to bare soil plots. The findings highlight CC's effectiveness in mitigating field-scale rill erosion even in their early growth stages. However, creating a DSM reconstructed baseline in CC plots is currently confined to partial CC vegetation coverage (leaving enough soil pixels visible), necessitating additional studies to determine the maximal coverage that won't compromise accuracy. Further assessments of the methods' quantitative accuracy require studies incorporating extensive ground truth data.
覆盖作物（CC）能有效减少土壤侵蚀，这对农民和环境都是一个重大威胁。然而，目前还缺乏数据来量化覆盖作物在田间尺度上对土壤流失的影响。本研究的主要目的是利用无人机 RGB 图像估算 CC 对田间尺度的辙蚀的影响，并描述有 CC 和无 CC 区域的辙蚀参数特征。图像采集自 "可持续农业示范农场 "的一块 20 公顷的田地，由有 CC 和无 CC 的地块组成。图像拍摄于 CC 播种 33 天后，在降雨量较大的情况下形成了三条明显的溪流。剔除植被像素后，使用运动结构算法生成侵蚀后数字地表模型（DSM）和模拟侵蚀前土壤表面的基线数字地表模型（DSM 重建基线）。变化检测分析表明，CC 能显著减少土壤流失。在所研究的三个溪流中，与裸露土壤地块相比，CC 每平方米的平均土壤流失量分别减少了 48%、58% 和 29%。此外，与裸露土壤地块相比，CC 地块的溪流最大深度分别减少了 74%、74% 和 24%，横截面积分别减少了 67%、87% 和 43%。这些研究结果突出表明，CC 即使在早期生长阶段也能有效减轻田间尺度的溪流侵蚀。然而，在 CC 地块创建 DSM 重建基线目前仅限于 CC 植被的部分覆盖范围（留下足够的土壤像素），因此有必要进行更多研究，以确定不会影响精度的最大覆盖范围。要进一步评估这些方法的定量准确性，需要结合大量地面实况数据进行研究。
{"title":"Assessing field-scale rill erosion mitigation by cover crops in arable land using drone image analysis","authors":"Simon Ian Futerman , Yafit Cohen , Yael Laor , Eli Argaman , Shlomi Aharon , Gil Eshel","doi":"10.1016/j.still.2024.106341","DOIUrl":"10.1016/j.still.2024.106341","url":null,"abstract":"<div><div>Cover crops (CC) effectively reduce soil erosion, a significant threat to farmers and the environment. Yet, there is lack of data quantifying their effect on rill erosion in the field scale. The major objective of this study was to use UAV-RGB images to estimate the effects of CC on rill erosion in the field scale and to characterize rill parameters in areas with and without CC. Images were collected from a 20-ha field in the \"Model Farm for Sustainable Agriculture\", consisting of plots with and without CC. Images were captured 33 days after CC sowing and following substantial rainfall events that formed three prominent rills. Following the elimination of vegetation pixels, structure from motion algorithm was used to generate a post-erosion digital surface model (DSM) and a baseline DSM simulating the pre-erosion soil surface (DSM <sub>reconstructed baseline)</sub>. Change-detection analysis revealed that CC significantly reduced rill erosion. Average soil loss per m<sup>2</sup> was 48 %, 58 %, and 29 % lower in CC compared to bare soil plots in the three studied rills. Additionally, rill maximum depth was 74 %, 74 %, and 24 %, and cross-sectional surface area was 67 %, 87 %, and 43 % lower in CC, compared to bare soil plots. The findings highlight CC's effectiveness in mitigating field-scale rill erosion even in their early growth stages. However, creating a DSM <sub>reconstructed baseline</sub> in CC plots is currently confined to partial CC vegetation coverage (leaving enough soil pixels visible), necessitating additional studies to determine the maximal coverage that won't compromise accuracy. Further assessments of the methods' quantitative accuracy require studies incorporating extensive ground truth data.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106341"},"PeriodicalIF":6.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572804","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}
Pub Date : 2024-11-01DOI: 10.1016/j.still.2024.106342
G. Vazquez Amabile , G. Studdert , S.M. Ogle , M. Beltrán , A.D. Said , S. Galbusera , F. Montiel , R. Moreno , M.F. Ricard
The estimation of changes in soil organic carbon (SOC) is a key issue for national green-house gasses (GHG) inventories, climate change mitigation programs and the estimation of carbon footprint of farm products in life cycle assessments. Any strategy related to net-zero carbon in agricultural systems needs to quantify the SOC balance. In this way, SOC models help decision makers involved in agriculture to understand the dynamics of the SOC and the interaction between all variables related to soil, climate, land use, and management, to design the best solution to reduce emissions or enable carbon sequestration. Likewise, it is important to identify suitable models for the region. This study aims to address three main subjects: a) a discussion on the importance of SOC estimation for GHG inventories and the carbon footprint of crops, using the Intergovernmental Panel on Climate Change (IPCC) Tier 1 method and AMG model; b) an evaluation and brief description of the IPCC “Steady State Method” (SSM), using experimental data from two sites in Argentina, comparing these results to AMG and RothC models (both previously validated at those sites); and c) a brief discussion about the potential use of SOC models for what-if management scenarios, their real limitations and future research needs. The three models were consistent in predicting the impact of tillage and the long-term trends in changes in SOC stocks under different management practices. The SSM model was evaluated for the first time in Argentina and performed even better than the other two models. It was consistent with the observed values, when predicting the effect of tillage system under different crop rotations, including pasture systems. Regarding efficiencies of the models, they showed acceptable Nash-Sutcliffe Efficiency (NSE) values, and the root mean square error (RMSE) was also acceptable between 3 % and 7 %, within a range of 4–5 Mg C.ha−1. Therefore, the SSM model proved to be a valuable tool to estimate SOC trends for crop and pasture rotations under different management scenarios (i.e., tillage systems and fertilization), to identify best practices that allow for a zero or positive SOC balance, in two different soil and climate conditions of the Pampean Region of Argentina. In our study, the SSM did have a better fit to the data and, furthermore, this Tier 2 method is simpler than the Tier 3 models, and, therefore, is advantageous for conducting regional assessments and GHG inventories.
{"title":"An evaluation of soil carbon models and their role on finding ways to net-zero carbon in agricultural systems","authors":"G. Vazquez Amabile , G. Studdert , S.M. Ogle , M. Beltrán , A.D. Said , S. Galbusera , F. Montiel , R. Moreno , M.F. Ricard","doi":"10.1016/j.still.2024.106342","DOIUrl":"10.1016/j.still.2024.106342","url":null,"abstract":"<div><div>The estimation of changes in soil organic carbon (SOC) is a key issue for national green-house gasses (GHG) inventories, climate change mitigation programs and the estimation of carbon footprint of farm products in life cycle assessments. Any strategy related to net-zero carbon in agricultural systems needs to quantify the SOC balance. In this way, SOC models help decision makers involved in agriculture to understand the dynamics of the SOC and the interaction between all variables related to soil, climate, land use, and management, to design the best solution to reduce emissions or enable carbon sequestration. Likewise, it is important to identify suitable models for the region. This study aims to address three main subjects: a) a discussion on the importance of SOC estimation for GHG inventories and the carbon footprint of crops, using the Intergovernmental Panel on Climate Change (IPCC) Tier 1 method and AMG model; b) an evaluation and brief description of the IPCC “Steady State Method” (SSM), using experimental data from two sites in Argentina, comparing these results to AMG and RothC models (both previously validated at those sites); and c) a brief discussion about the potential use of SOC models for what-if management scenarios, their real limitations and future research needs. The three models were consistent in predicting the impact of tillage and the long-term trends in changes in SOC stocks under different management practices. The SSM model was evaluated for the first time in Argentina and performed even better than the other two models. It was consistent with the observed values, when predicting the effect of tillage system under different crop rotations, including pasture systems. Regarding efficiencies of the models, they showed acceptable Nash-Sutcliffe Efficiency (NSE) values, and the root mean square error (RMSE) was also acceptable between 3 % and 7 %, within a range of 4–5 Mg C.ha<sup>−1</sup>. Therefore, the SSM model proved to be a valuable tool to estimate SOC trends for crop and pasture rotations under different management scenarios (i.e., tillage systems and fertilization), to identify best practices that allow for a zero or positive SOC balance, in two different soil and climate conditions of the Pampean Region of Argentina. In our study, the SSM did have a better fit to the data and, furthermore, this Tier 2 method is simpler than the Tier 3 models, and, therefore, is advantageous for conducting regional assessments and GHG inventories.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106342"},"PeriodicalIF":6.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572803","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}
Pub Date : 2024-10-31DOI: 10.1016/j.still.2024.106347
Otávio dos Anjos Leal , Pablo Miguel , Mateus Fonseca Rodrigues , Rachel Muylaert Locks Guimarães , Luiz Fernando Spinelli Pinto , Thais Palumbo Silva , Marilia Alves Brito Pinto , Stephan Domingues Nachtigall , Lizete Stumpf
Topsoil compaction is a persistent problem in minesoils, jeopardizing the revegetation and ecological reclamation of the mined land. Evaluation of soil structural quality (Sq) through quantitative methods is usually labor-intensive and/or costly, especially if a large area has to be examined. Therefore, reconciling cost-effective and accurate diagnose of minesoil Sq is crucial. The Visual Evaluation of Soil Structure (VESS) is a spade-based method scoring the soil Sq from 1 (good) to 5 (poor), which has not yet been validated for minesoils, and this was exactly the aim of this study. We made use of our long-term field experiment where quantitative physical attributes differed between perennial grasses used for minesoil revegetation, creating a Sq range to be screened by VESS. The minesoil, located in Southern Brazil, was revegetated for 14.3 years with Hemarthria altissima, Paspalum notatum, Cynodon dactylon, and Urochloa brizantha. The Sq of the minesoil (0.00–0.10 and 0.10–0.20 m layer) was evaluated by VESS and tensile strength of aggregates (TS), soil macroaggregates and microaggregates (%), soil organic matter (SOM) content, bulk density (BD), macroporosity (MaP), microporosity, total porosity (TP), and soil penetration resistance (PR). Through significant correlations between VESS scores and TS, MaP, macroaggregates (%), microaggregates (%), TP, SOM and especially BD (r = 0.60) and PR (r = 0.56), we found VESS to be a suitable method for reliable assessment of minesoil Sq. VESS scores 2.0–3.1 confirmed improved Sq at 0.00–0.10 m compared to 0.10–0.20 m (2.7–3.5), and this was supported by the ordination of 0.00–0.10 m samples together with SOM, macroaggregates (%), MaP and TP by principal component analysis. Moreover, VESS confirmed improved Sq in H. altissima (2.7) compared to C. dactylon (3.6) at 0.10–0.20 m, likely due to gains in soil MaP, TP, macroaggregates (%) and SOM. In this pioneering study we validated VESS as a practical and science-grounded method to monitor the Sq of a clayey subtropical minesoil.
{"title":"First validation of the method Visual Evaluation of Soil Structure in coal mining area using a long-term field revegetation experiment as testbed","authors":"Otávio dos Anjos Leal , Pablo Miguel , Mateus Fonseca Rodrigues , Rachel Muylaert Locks Guimarães , Luiz Fernando Spinelli Pinto , Thais Palumbo Silva , Marilia Alves Brito Pinto , Stephan Domingues Nachtigall , Lizete Stumpf","doi":"10.1016/j.still.2024.106347","DOIUrl":"10.1016/j.still.2024.106347","url":null,"abstract":"<div><div>Topsoil compaction is a persistent problem in minesoils, jeopardizing the revegetation and ecological reclamation of the mined land. Evaluation of soil structural quality (Sq) through quantitative methods is usually labor-intensive and/or costly, especially if a large area has to be examined. Therefore, reconciling cost-effective and accurate diagnose of minesoil Sq is crucial. The Visual Evaluation of Soil Structure (VESS) is a spade-based method scoring the soil Sq from 1 (good) to 5 (poor), which has not yet been validated for minesoils, and this was exactly the aim of this study. We made use of our long-term field experiment where quantitative physical attributes differed between perennial grasses used for minesoil revegetation, creating a Sq range to be screened by VESS. The minesoil, located in Southern Brazil, was revegetated for 14.3 years with <em>Hemarthria altissima</em>, <em>Paspalum notatum</em>, <em>Cynodon dactylon</em>, and <em>Urochloa brizantha</em>. The Sq of the minesoil (0.00–0.10 and 0.10–0.20 m layer) was evaluated by VESS and tensile strength of aggregates (TS), soil macroaggregates and microaggregates (%), soil organic matter (SOM) content, bulk density (BD), macroporosity (MaP), microporosity, total porosity (TP), and soil penetration resistance (PR). Through significant correlations between VESS scores and TS, MaP, macroaggregates (%), microaggregates (%), TP, SOM and especially BD (r = 0.60) and PR (r = 0.56), we found VESS to be a suitable method for reliable assessment of minesoil Sq. VESS scores 2.0–3.1 confirmed improved Sq at 0.00–0.10 m compared to 0.10–0.20 m (2.7–3.5), and this was supported by the ordination of 0.00–0.10 m samples together with SOM, macroaggregates (%), MaP and TP by principal component analysis. Moreover, VESS confirmed improved Sq in <em>H. altissima</em> (2.7) compared to <em>C. dactylon</em> (3.6) at 0.10–0.20 m, likely due to gains in soil MaP, TP, macroaggregates (%) and SOM. In this pioneering study we validated VESS as a practical and science-grounded method to monitor the Sq of a clayey subtropical minesoil.</div></div>","PeriodicalId":49503,"journal":{"name":"Soil & Tillage Research","volume":"246 ","pages":"Article 106347"},"PeriodicalIF":6.1,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561448","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}
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