Travis W. Nauman, Suzann Kienast-Brown, Stephen M. Roecker, Colby Brungard, David White, Jessica Philippe, James A. Thompson
Detailed soil property maps are increasingly important for land management decisions and environmental modeling. The US Soil Survey is investing in production of the Soil Landscapes of the United States (SOLUS), a new set of national predictive soil property maps. This paper documents initial 100-m resolution maps of 20 soil properties that include various textural fractions, physical parameters, chemical parameters, carbon, and depth to restrictions. Many of these properties have not been previously mapped at this resolution. A hybrid training strategy helped increase training data by roughly 10-fold over previous similar studies by combining commonly used laboratory data with underutilized field descriptions tied to soil survey map unit component property estimates (to help represent within polygon variability) as well as randomly selected soil survey map unit weighted average property estimates. Relative prediction intervals were used to help select which training data sources improved model performance. Conventional and spatial cross-validation strategies yielded generally strong coefficients of determination between 0.5 and 0.7, but with substantial variability and outliers among the various properties, types of training data, and depths. Internal review of the maps highlighted both strengths and weaknesses of the maps, but most of the critical comments were in areas with high model uncertainty that can be used to guide future improvements. Generally, previously glaciated areas and complex large alluvial basins were harder to model. The new SOLUS 100-m maps will be updated in the future to address identified issues and feedback as users interact with the data.
详细的土壤属性图对于土地管理决策和环境建模越来越重要。美国土壤普查局正在投资制作美国土壤地貌图(SOLUS),这是一套新的全国性预测土壤属性图。本文记录了 20 种土壤属性的 100 米分辨率初始地图,其中包括各种纹理成分、物理参数、化学参数、碳和限制深度。其中许多属性以前从未以这种分辨率绘制过。通过将常用的实验室数据与未充分利用的实地描述相结合,并与土壤勘测图单元成分属性估计值(以帮助表示多边形内的变异性)以及随机选择的土壤勘测图单元加权平均属性估计值相联系,混合训练策略帮助将训练数据比以前的类似研究增加了大约 10 倍。相对预测区间用于帮助选择哪种训练数据源可提高模型性能。常规和空间交叉验证策略得出的确定系数一般在 0.5 到 0.7 之间,但在各种属性、训练数据类型和深度之间存在很大的变异性和异常值。对地图的内部审查强调了地图的优点和缺点,但大多数批评意见都集中在模型不确定性较高的区域,可用于指导未来的改进工作。一般来说,以前的冰川地区和复杂的大型冲积盆地较难建模。新的 SOLUS 100 m 地图将在未来进行更新,以解决已发现的问题和用户与数据交互时的反馈。
{"title":"Soil landscapes of the United States (SOLUS): Developing predictive soil property maps of the conterminous United States using hybrid training sets","authors":"Travis W. Nauman, Suzann Kienast-Brown, Stephen M. Roecker, Colby Brungard, David White, Jessica Philippe, James A. Thompson","doi":"10.1002/saj2.20769","DOIUrl":"https://doi.org/10.1002/saj2.20769","url":null,"abstract":"<p>Detailed soil property maps are increasingly important for land management decisions and environmental modeling. The US Soil Survey is investing in production of the Soil Landscapes of the United States (SOLUS), a new set of national predictive soil property maps. This paper documents initial 100-m resolution maps of 20 soil properties that include various textural fractions, physical parameters, chemical parameters, carbon, and depth to restrictions. Many of these properties have not been previously mapped at this resolution. A hybrid training strategy helped increase training data by roughly 10-fold over previous similar studies by combining commonly used laboratory data with underutilized field descriptions tied to soil survey map unit component property estimates (to help represent within polygon variability) as well as randomly selected soil survey map unit weighted average property estimates. Relative prediction intervals were used to help select which training data sources improved model performance. Conventional and spatial cross-validation strategies yielded generally strong coefficients of determination between 0.5 and 0.7, but with substantial variability and outliers among the various properties, types of training data, and depths. Internal review of the maps highlighted both strengths and weaknesses of the maps, but most of the critical comments were in areas with high model uncertainty that can be used to guide future improvements. Generally, previously glaciated areas and complex large alluvial basins were harder to model. The new SOLUS 100-m maps will be updated in the future to address identified issues and feedback as users interact with the data.</p>","PeriodicalId":101043,"journal":{"name":"Proceedings - Soil Science Society of America","volume":"88 6","pages":"2046-2065"},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/saj2.20769","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher J. Burgess, David D. Myrold, Ryan S. Mueller, Thomas Wanzek, Jennifer M. Moore, Kristin D. Kasschau, Markus Kleber
The variation in the soil microbial community composition over time was assessed at monthly time steps for 1 year in three neighboring Mollisols spanning a drainage gradient. This was done to distinguish between natural oscillations in the community composition versus lasting adaptations to environmental factors such as soil water availability. To isolate soil water availability as a controlling factor, we selected three soils sharing the same soil order (fine-silty, superactive Argixerolls/Argialbolls); slope (0%–1%); temperature regime (mesic); moisture regime (xeric); and land use history (continuous grassland for the past 10 years) but differing in drainage class (well-drained vs. moderately well-drained vs. poorly drained). Changes in microbial diversity were quantified by monitoring the bacterial community at monthly intervals for 1 year. Within individual soils, α-diversity varied little with season and drainage classes. Despite the three soils experiencing the same climate regime and vegetation/land use, they exhibited distinct community composition and turnover, which we attribute to differences in moisture availability across drainage and seasons. We posit that a seasonal recurring drop in soil redox potential induced by seasonal water saturation in the poorly drained soil is the most probable cause setting the microbial community of that soil apart from those in the better drained soils. Our investigation suggests that not all indicators of microbial diversity share the same sensitivity to seasonal and drainage-related soil moisture variations.
{"title":"Drainage gradient versus seasonal cycles: Differential response of microbial community composition to variations in soil moisture","authors":"Christopher J. Burgess, David D. Myrold, Ryan S. Mueller, Thomas Wanzek, Jennifer M. Moore, Kristin D. Kasschau, Markus Kleber","doi":"10.1002/saj2.20780","DOIUrl":"https://doi.org/10.1002/saj2.20780","url":null,"abstract":"<p>The variation in the soil microbial community composition over time was assessed at monthly time steps for 1 year in three neighboring Mollisols spanning a drainage gradient. This was done to distinguish between natural oscillations in the community composition versus lasting adaptations to environmental factors such as soil water availability. To isolate soil water availability as a controlling factor, we selected three soils sharing the same soil order (fine-silty, superactive Argixerolls/Argialbolls); slope (0%–1%); temperature regime (mesic); moisture regime (xeric); and land use history (continuous grassland for the past 10 years) but differing in drainage class (well-drained vs. moderately well-drained vs. poorly drained). Changes in microbial diversity were quantified by monitoring the bacterial community at monthly intervals for 1 year. Within individual soils, α-diversity varied little with season and drainage classes. Despite the three soils experiencing the same climate regime and vegetation/land use, they exhibited distinct community composition and turnover, which we attribute to differences in moisture availability across drainage and seasons. We posit that a seasonal recurring drop in soil redox potential induced by seasonal water saturation in the poorly drained soil is the most probable cause setting the microbial community of that soil apart from those in the better drained soils. Our investigation suggests that not all indicators of microbial diversity share the same sensitivity to seasonal and drainage-related soil moisture variations.</p>","PeriodicalId":101043,"journal":{"name":"Proceedings - Soil Science Society of America","volume":"88 6","pages":"2123-2134"},"PeriodicalIF":0.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Understanding the effects of abandoned coal mine ecological restoration on soil quality and function is important to protect the regional ecological environment. This study aims to evaluate the ecological restoration effects of soil quality in abandoned coal mine area. Taking Fengcheng County, a typical coal-rich area in southern China, as a case, this study took 120 soil samples to investigate the influence of restoration years on soil quality by using an integrated soil quality index (SQI). Results indicated that restoration years had significant effects on the saturated hydraulic conductivity (Ks) by affecting the soil bulk density, clay content, and soil water content. Furthermore, clay, soil organic matter, Ks, and pH were selected to assess the effect of ecological restoration years on soil quality. It was found that the ecological restoration 8 years (ER8) site had higher SQI value, indicating ecological restoration years showed a positive correlation with SQI in abandoned coal mine area. Since there was a 4-year gap between ecological restoration 4 years site and ER8 site, the ecological restoration may be effective between 5 and 8 years. The results of this study are of great significance for improving the effects of ecological restoration and management in abandoned coal mine area.
{"title":"Changes in soil quality during different ecological restoration years in the abandoned coal mine area of southern China","authors":"Hao Li, Wenbo Chen, Kaixin Fu, Cheng Zhang, Haifen Liang","doi":"10.1002/saj2.20775","DOIUrl":"https://doi.org/10.1002/saj2.20775","url":null,"abstract":"<p>Understanding the effects of abandoned coal mine ecological restoration on soil quality and function is important to protect the regional ecological environment. This study aims to evaluate the ecological restoration effects of soil quality in abandoned coal mine area. Taking Fengcheng County, a typical coal-rich area in southern China, as a case, this study took 120 soil samples to investigate the influence of restoration years on soil quality by using an integrated soil quality index (SQI). Results indicated that restoration years had significant effects on the saturated hydraulic conductivity (Ks) by affecting the soil bulk density, clay content, and soil water content. Furthermore, clay, soil organic matter, Ks, and pH were selected to assess the effect of ecological restoration years on soil quality. It was found that the ecological restoration 8 years (ER8) site had higher SQI value, indicating ecological restoration years showed a positive correlation with SQI in abandoned coal mine area. Since there was a 4-year gap between ecological restoration 4 years site and ER8 site, the ecological restoration may be effective between 5 and 8 years. The results of this study are of great significance for improving the effects of ecological restoration and management in abandoned coal mine area.</p>","PeriodicalId":101043,"journal":{"name":"Proceedings - Soil Science Society of America","volume":"88 6","pages":"2311-2328"},"PeriodicalIF":0.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information on water absorption from the air by urea fertilizers and on NH3 loss when applied to grasslands is limited. Urea application to grassland is typically broadcast (Bcast), whereas urea-ammonium nitrate (UAN) is applied either Bcast or in bands (dribble). This work was conducted to (1) evaluate water absorption from the air by Bcast granular urea, Bcast UAN, and dribble UAN under laboratory conditions, and (2) compare NH3 losses from Bcast urea, Bcast UAN, and dribble UAN when applied to a grassland. Six field studies were conducted from 2017 to 2019. In the laboratory, Bcast UAN exposed to 100% relative humidity absorbed water from air at a faster rate than dribble UAN and Bcast urea. In the field, all three fertilizers lost similar amounts of NH3 when applied to relatively wet soil (> −0.1 MPa). In contrast, when the fertilizers were applied to dry soil (≤ −1.2 MPa), Bcast UAN lost the most NH3 (17.3% and 19.8%) likely because of its capacity to absorb water from the air. Also, at −1.2 MPa, dribble UAN lost more NH3 than Bcast urea (15.3 vs. 10.7%, p < 0.05), probably because the low osmotic potential of UAN (−55 MPa) allowed it to absorb water from the soil at a faster rate than urea could absorb water from the air. In contrast, when the soil water potential was −5.7 MPa, dribble UAN lost less NH3 than Bcast urea (4.4 vs. 17.3%, p < 0.05), likely because the low soil water potential reduced its water absorption.
{"title":"Water absorption from air and ammonia loss from urea fertilizers applied to grassland in southeastern United States","authors":"Miguel L. Cabrera, Dorcas Franklin, David Kissel","doi":"10.1002/saj2.20778","DOIUrl":"https://doi.org/10.1002/saj2.20778","url":null,"abstract":"<p>Information on water absorption from the air by urea fertilizers and on NH<sub>3</sub> loss when applied to grasslands is limited. Urea application to grassland is typically broadcast (Bcast), whereas urea-ammonium nitrate (UAN) is applied either Bcast or in bands (dribble). This work was conducted to (1) evaluate water absorption from the air by Bcast granular urea, Bcast UAN, and dribble UAN under laboratory conditions, and (2) compare NH<sub>3</sub> losses from Bcast urea, Bcast UAN, and dribble UAN when applied to a grassland. Six field studies were conducted from 2017 to 2019. In the laboratory, Bcast UAN exposed to 100% relative humidity absorbed water from air at a faster rate than dribble UAN and Bcast urea. In the field, all three fertilizers lost similar amounts of NH<sub>3</sub> when applied to relatively wet soil (> −0.1 MPa). In contrast, when the fertilizers were applied to dry soil (≤ −1.2 MPa), Bcast UAN lost the most NH<sub>3</sub> (17.3% and 19.8%) likely because of its capacity to absorb water from the air. Also, at −1.2 MPa, dribble UAN lost more NH<sub>3</sub> than Bcast urea (15.3 vs. 10.7%, <i>p</i> < 0.05), probably because the low osmotic potential of UAN (−55 MPa) allowed it to absorb water from the soil at a faster rate than urea could absorb water from the air. In contrast, when the soil water potential was −5.7 MPa, dribble UAN lost less NH<sub>3</sub> than Bcast urea (4.4 vs. 17.3%, <i>p</i> < 0.05), likely because the low soil water potential reduced its water absorption.</p>","PeriodicalId":101043,"journal":{"name":"Proceedings - Soil Science Society of America","volume":"88 6","pages":"2266-2276"},"PeriodicalIF":0.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/saj2.20778","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study investigates the utility of plant δ¹3C natural labeling in predicting the impacts of environmental shifts on carbon cycling within ecosystems, particularly focusing on paddy fields treated with maize (Zea mays L.) residues and biochar. Specifically, it examines how soil δ¹3C and the sources of soil organic carbon (SOC), respond in paddy fields (which cultivate C3 plants like rice) when amended with maize residues, maize biochar, and silica-enriched biochar (derived from C4 plants). Conducted in the Fuzhou paddy fields, the experiment included control groups and treatment groups with maize residue (4 t ha⁻¹), maize biochar (4 t ha⁻¹), and silicon-modified maize biochar (4 t ha⁻¹) during both the early and late rice growth periods. The results indicate that all soil treatments increased soil δ¹3C. The application of maize residues notably affected the δ¹3C of the upper soil profile (0–15 cm) differently from the deeper layers (15–30 cm), and it increased soil organic C more than biochar or silicon-modified maize biochar. Soil available P (AP) and pH emerged as significant factors linking δ¹3C, influencing rice yield through changes in soil physicochemical properties. Unlike maize residues, which reduced rice yields, applications of biochar and silicon-modified maize biochar increased rice yields. The latter, which was particularly effective in lowering SOC decomposition rates and addressing rice's silica needs, emerged as the preferred option. The study highlights maize biochar and silicon-modified maize biochar as sustainable alternatives to maize residues for rice cultivation, enhancing soil fertility, carbon pool stability, and yields.
{"title":"Effects of maize residue and biochar applications on soil δ13C and organic carbon sources in a subtropical paddy rice ecosystem","authors":"Qiang Jin, Weiqi Wang, Xuyang Liu, Shaoying Lin, Jordi Sardans, Yunying Fang, Tony Vancov, Akash Tariq, Fanjiang Zeng, Josep Peñuelas","doi":"10.1002/saj2.20773","DOIUrl":"https://doi.org/10.1002/saj2.20773","url":null,"abstract":"<p>This study investigates the utility of plant δ¹<sup>3</sup>C natural labeling in predicting the impacts of environmental shifts on carbon cycling within ecosystems, particularly focusing on paddy fields treated with maize (<i>Zea mays</i> L.) residues and biochar. Specifically, it examines how soil δ¹<sup>3</sup>C and the sources of soil organic carbon (SOC), respond in paddy fields (which cultivate C<sub>3</sub> plants like rice) when amended with maize residues, maize biochar, and silica-enriched biochar (derived from C<sub>4</sub> plants). Conducted in the Fuzhou paddy fields, the experiment included control groups and treatment groups with maize residue (4 t ha⁻¹), maize biochar (4 t ha⁻¹), and silicon-modified maize biochar (4 t ha⁻¹) during both the early and late rice growth periods. The results indicate that all soil treatments increased soil δ¹<sup>3</sup>C. The application of maize residues notably affected the δ¹<sup>3</sup>C of the upper soil profile (0–15 cm) differently from the deeper layers (15–30 cm), and it increased soil organic C more than biochar or silicon-modified maize biochar. Soil available P (AP) and pH emerged as significant factors linking δ¹<sup>3</sup>C, influencing rice yield through changes in soil physicochemical properties. Unlike maize residues, which reduced rice yields, applications of biochar and silicon-modified maize biochar increased rice yields. The latter, which was particularly effective in lowering SOC decomposition rates and addressing rice's silica needs, emerged as the preferred option. The study highlights maize biochar and silicon-modified maize biochar as sustainable alternatives to maize residues for rice cultivation, enhancing soil fertility, carbon pool stability, and yields.</p>","PeriodicalId":101043,"journal":{"name":"Proceedings - Soil Science Society of America","volume":"88 6","pages":"2254-2265"},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Researchers in urban environments sample where people live and work. However, there is limited extant guidance available to scientists engaging with community stakeholders to sample soils in urban settings. Leveraging our cumulative experiences, insights gained from community collaborations, and interdisciplinary literature, we present a community-engaged framework for urban soils research. Community-engaged research frameworks emerged over the past two decades to foster trust and respect between communities and researchers as a response to historical exploitation of communities by the academy. Today, these frameworks have become standard for social and public health researchers investigating the physical well-being of communities. However, there is no equivalent framework for scientists studying the soils that underpin the physical and ecological well-being of the same communities. Here, we present the first such framework for soil scientists that incorporates nuanced aspects that are often overlooked. Our proposed framework recognizes the iterative nature of collaboration with community stakeholders and highlights the significance of ethical considerations throughout the research process by emphasizing protection of community stakeholders from harm, involvement of all parties in decision-making processes, maintaining informed consent, and fostering mutual accountability among researchers throughout the research and sampling process.
{"title":"Toward a community-engaged framework for urban soil research","authors":"Tiffany A. Legg, Caitlin Hodges","doi":"10.1002/saj2.20776","DOIUrl":"https://doi.org/10.1002/saj2.20776","url":null,"abstract":"<p>Researchers in urban environments sample where people live and work. However, there is limited extant guidance available to scientists engaging with community stakeholders to sample soils in urban settings. Leveraging our cumulative experiences, insights gained from community collaborations, and interdisciplinary literature, we present a community-engaged framework for urban soils research. Community-engaged research frameworks emerged over the past two decades to foster trust and respect between communities and researchers as a response to historical exploitation of communities by the academy. Today, these frameworks have become standard for social and public health researchers investigating the physical well-being of communities. However, there is no equivalent framework for scientists studying the soils that underpin the physical and ecological well-being of the same communities. Here, we present the first such framework for soil scientists that incorporates nuanced aspects that are often overlooked. Our proposed framework recognizes the iterative nature of collaboration with community stakeholders and highlights the significance of ethical considerations throughout the research process by emphasizing protection of community stakeholders from harm, involvement of all parties in decision-making processes, maintaining informed consent, and fostering mutual accountability among researchers throughout the research and sampling process.</p>","PeriodicalId":101043,"journal":{"name":"Proceedings - Soil Science Society of America","volume":"88 6","pages":"1911-1918"},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}