Geoderma最新文献

{"title":"Adsorption of extracellular enzymes by biochar: Impacts of enzyme and biochar properties","authors":"","doi":"10.1016/j.geoderma.2024.117082","DOIUrl":"10.1016/j.geoderma.2024.117082","url":null,"abstract":"<div><div>Extracellular enzymes play a key role in mediating organic matter decomposition in soils and the mobility of enzymes is largely controlled by their interaction with soil surfaces. The introduction of pyrogenic products, including biochar produced for the purpose of carbon sequestration or soil health management, may alter the ecological functioning of soil. In this work, we studied the adsorption of four representative soil extracellular enzymes (urease, invertase, α-amylase and protease) to biochar (derived from wood biomass and wheat straw produced at different pyrolysis temperatures, and a wildfire pine char) and soil mixed with biochar. A pH-edge adsorption experiment showed that, for all biochar/enzyme combinations, adsorption of all extracellular enzymes decreased as pH increased from 4 to 9. This pH dependency suggests that electrostatic interaction was the primary adsorption mechanism. Equilibrium enzyme adsorption data was best fit by the Langmuir isotherm and adsorption capacity varied significantly with enzyme type, ranging from 67 to 232 mg·g⁻¹ for urease and 0 to 11 mg·g⁻¹ for the others at pH 5.0. Enzyme adsorption also differed among biochars with or without surface oxidation treatment. Correlations between enzyme adsorption data and biochar properties demonstrated the relevance of enzyme sizes, biochar surface porous structure, and surface chemical functionality in determining biochar adsorption capacity and affinity for enzymes. Soil adsorption experiment showed that biochar addition can enhance or reduce soil adsorption of enzymes, depending on the relative enzyme affinity between the soil and biochar. These findings indicate that pyrogenic organic matter has varying impacts on the mobility of soil extracellular enzymes through direct adsorption and potentially affect the activity and stability of enzymes, and ultimately soil carbon and nutrient cycling.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560786","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":"Effects of slope shape on soil erosion and deposition patterns based on SfM-UAV photogrammetry","authors":"","doi":"10.1016/j.geoderma.2024.117076","DOIUrl":"10.1016/j.geoderma.2024.117076","url":null,"abstract":"<div><div>Slope shape as a consequence of erosional landform development plays a prominent role in soil erosion. Clarifying the distribution of soil erosion and deposition patterns on different shaped slopes is crucial for soil erosion control. The aim of this study was to decipher the effects of slope shape on soil erosion and deposition patterns under natural rainfall conditions based on high-resolution unmanned aerial vehicle (UAV) data and geographic information system technology. Structure from motion (SfM)-UAV photogrammetry was carried out in four runoff plots with various slope shapes during the rainy season in 2021. Digital elevation models (DEMs) were developed for each slope shape before and after the rainy season. In addition to collecting runoff and sediment, the DEMs of difference were analyzed to quantify soil erosion and deposition patterns on various slope shapes in the rainy season. Results showed that the runoff volumes and sediment yields induced by rainfall were markedly different among various slope shapes. The mean runoff volume and sediment yield from the concave-convex slope were 1.09 ∼ 2.69 and 1.33 ∼ 27.16 times those of the other three slopes, respectively, with less sediment loss from the convex-concave slope and its combination slope. Slope shape exhibited a notable effect on the type of slope erosion and deposition. All four slopes showed considerable changes in surface elevation after the rainy season. The increase and decrease in surface elevation were concentrated in the range of –0.02 to –0.007 m and 0.007 to 0.02 m, respectively, with a low proportion of changes less than –0.03 m and greater than 0.03 m. The effectiveness of SfM-UAV in monitoring the microgeomorphic changes of slopes was verified by the consistency of soil erosion amounts based on sediment collection and SfM-UAV measurements. Reference values were provided to solve the threshold problem of slope length cutoff in soil erosion prediction models based on runoff plot experiments. Findings of this study could be useful for decision-making in soil erosion control and slope reconstruction.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531668","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":"Environmental drivers of soil carbon and nitrogen accumulation in global drylands","authors":"","doi":"10.1016/j.geoderma.2024.117075","DOIUrl":"10.1016/j.geoderma.2024.117075","url":null,"abstract":"<div><div>We are far from understanding the spatial patterns of dryland soil carbon and nitrogen stocks and how they vary among different land cover types. We used data from 12,000 sites from 129 countries in global drylands to estimate soil organic carbon (SOC) and total nitrogen (STN) stocks in different land cover types, explore the factors driving their spatial distribution, and predict the trends under different climate scenarios in global drylands. SOC and STN stocks in the upper 100 cm reached 419.5 and 38.2 Pg, respectively, with the upper 0–30 cm accounting for half of them. The largest SOC stocks were found in forests, shrublands and grasslands, while STN stocks peaked in forests, bare areas and croplands. The factors driving the spatial patterns of SOC and STN varied among soil depths, with mean annual temperature, pH and aridity being the main factors driving the spatial patterns in SOC and STN density for 0–30 cm, and soil texture the strongest factor for 60–100 cm. Under the Representative Concentration Pathways (RCP) 4.5 scenario, SOC and STN stocks were predicted to decrease by 3.6 % and 4.0 %, respectively, from 2020 to 2100, whereas under the RCP 8.5 scenario, the projected decreases were 5.9 % and 6.4 % respectively. Our results indicate that if we want to accurately predict C and N accumulation, and design effective mitigation measures in terrestrial ecosystems under future climatic scenarios, we need to better explore the drivers that operate at the deeper soil depths, which also accumulate a significant amount of SOC and STN.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531665","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":"Including soil spatial neighbor information for digital soil mapping","authors":"","doi":"10.1016/j.geoderma.2024.117072","DOIUrl":"10.1016/j.geoderma.2024.117072","url":null,"abstract":"<div><div>Digital soil mapping (DSM) is transforming how we understand and manage soil resources, offering high-resolution spatial–temporal soil information essential for addressing environmental challenges. The integration of environmental covariates has advanced soil mapping accuracy, while the potential of neighboring soil sample data has been largely overlooked. This study introduces soil spatial neighbor information (SSNI) as a novel approach to enhance the predictive power of spatial models. Utilizing two open-access datasets from LUCAS Soil and Meuse, our findings showed that incorporating SSNI improved the accuracy of random forest models in mapping soil organic carbon density (reduced %RMSE of 3.1%), cadmium (reduced %RMSE of 3.6%), copper (reduced %RMSE of 5.9%), lead (reduced %RMSE of 11.5%), and zinc (reduced %RMSE of 7.4%). Compared to the inclusion of buffer distance or oblique geographic coordinates for modelling, SSNI also performed better for both LUCAS Soil and Meuse datasets. This study underscores the value of SSNI in improving digital soil maps by capturing the neighboring information. Embracing SSNI could lead to more informed decision-making in soil management and its potential applicability across other disciplines also remains open for exploration in future research endeavors.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531667","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":"Using combustion analysis to simultaneously measure soil organic and inorganic carbon","authors":"","doi":"10.1016/j.geoderma.2024.117066","DOIUrl":"10.1016/j.geoderma.2024.117066","url":null,"abstract":"<div><div>Soil organic carbon (SOC) and soil inorganic carbon (SIC) are of longstanding interest due to their relationship with other key soil properties and indications for soil health and carbon storage. At the USDA-NRCS Kellogg Soil Survey Laboratory (KSSL), total carbon (SOC + SIC) is determined via dry combustion analysis, while calcium carbonate (CaCO₃) equivalent is determined via manocalcimetry. For calcareous (carbonate bearing) samples, SIC is estimated as 12 % of CaCO₃ equivalent, while SOC is estimated as the difference between measured total carbon and estimated SIC. An alternative dry combustion method for the measurement of SOC and SIC pools was evaluated with the goal of directly measuring – not estimating – inorganic and organic carbon on calcareous samples. The alternative temperature ramp dry combustion (TRDC) method comprises two variants that differ in ramp cycle and carrier gases used. One variant operates under continuous oxygen and has temperature ramp plateaus of 400, 600 and 900 °C; thus, it is referred to as the non-gas switching variant or TRDC_NGS. The other variant operates under oxygen until 400 °C, then switches to nitrogen gas for a ramp to 900 °C, then reintroduces oxygen at 900 °C; thus, it is referred to as the gas switching variant or TRDC_GS. Both variants were applied in duplicate to 110 diverse samples, including 32 calcareous samples, from across the USA that had been previously characterized by the KSSL. Samples were selected to capture wide variability in carbon contents. Comparing carbon data outcomes with data from the legacy KSSL methods revealed the TRDC_GS variant as best for calcareous samples, whereas the TRDC_NGS variant was preferred for non-calcareous samples. A combination of the two method variants offers an accurate and direct measurement of SOC and SIC. For calcareous samples, mid-infrared (MIR) spectral analysis demonstrated TRDC method as slightly more accurate than legacy KSSL methods for estimating SOC and SIC.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531666","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":"Drainage estimation across mountainous regions from large-scale soil moisture observations","authors":"","doi":"10.1016/j.geoderma.2024.117077","DOIUrl":"10.1016/j.geoderma.2024.117077","url":null,"abstract":"<div><div>Drainage is a crucial soil hydrological process that governs the partitioning of rainfall into runoff, groundwater recharge, soil water storage and evapotranspiration. Despite its significance, the drainage process is poorly understood due to the difficulty in direct measurements and insufficient understanding of its underlying physical mechanisms. To address these challenges, we present an innovative, physically-based, data-driven approach, SM2D (Soil Moisture to Drainage), to estimate drainage. SM2D was applied and examined using soil moisture data from a large-scale observation network over mountainous areas during 2014–2020. The soil moisture threshold governing drainage initiation proves to be significantly lower than the commonly employed field capacity metric in hydrological models. This threshold is influenced by factors such as mean soil moisture, bulk density, residual soil moisture, soil organic carbon, and parameters <em>n</em> and <em>α</em> of soil retention curve. Notably, field capacity has minimal impact on this threshold. Additionally, our analysis reveals that the drainage process is more influenced by the Soil Water Storage Increment (SWSI) than by mean soil moisture (MSM) that has traditionally been recognized as a key factor in drainage control. In comparison to commonly used exponential equations and those in models such as the Soil &amp; Water Assessment Tool (SWAT), SM2D demonstrates superior performance in estimating drainage. The exponential equation derived from the SWSI outperforms those derived from other soil moisture metrics, including the commonly utilized MSM, challenging prevailing norms in drainage equations. SM2D holds the potential to generate extensive drainage datasets from satellite or large-scale soil moisture observations, advancing large-scale hydrological studies.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531664","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":"Space-time modelling of soil organic carbon stock change at multiple scales: Case study from Hungary","authors":"","doi":"10.1016/j.geoderma.2024.117067","DOIUrl":"10.1016/j.geoderma.2024.117067","url":null,"abstract":"<div><div>The role of soil organic carbon (SOC) is crucial not only for numerous soil functions and processes but also for addressing various environmental crises and challenges we face. Consequently, the demand for information on the spatiotemporal variability of SOC is increasing, posing new methodological challenges, such as the need for information on SOC and SOC changes with quantified uncertainty across a wide variety of spatial scales and temporal periods. Our objective was to present a methodology based on a combination of machine learning and space–time geostatistics to predict the spatiotemporal variability of SOC stock with quantified uncertainty at various spatial supports (i.e., point support, 1 × 1 km, 5 × 5 km, 10 × 10 km, 25 × 25 km, counties, and the entire country) for Hungary, between 1992 and 2016. The role of geostatistics is pivotal, as it accounts for the spatiotemporal correlation of the interpolation errors, which is essential for reliably quantifying the uncertainty associated with spatially aggregated SOC stock and SOC stock change predictions. Five times repeated 10-fold leave-location-out cross-validation was used to evaluate the point support predictions and uncertainty quantifications, yielding acceptable results for both SOC stock (ME = −0.897, RMSE = 19.358, MEC = 0.321, and G = 0.912) and SOC stock change (ME = 0.414, RMSE = 16.626, MEC = 0.160, and G = 0.952). We compiled a series of maps of SOC stock predictions between 1992 and 2016 for each support, along with the quantified uncertainty, which is unprecedented in Hungary. It was demonstrated that the larger the support, the smaller the prediction uncertainty, which facilitates the identification and delineation of larger areas with statistically significant SOC stock changes. Moreover, the methodology can overcome the limitations of recent approaches in the spatiotemporal modelling of SOC, allowing the prediction of SOC and SOC changes, with quantified uncertainty, for any year, time period, and spatial scale. This methodology is capable of meeting the current and anticipated demands for dynamic information on SOC at both national and international levels.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531657","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":"Sulfur biogeochemical dynamics of grassland soils in northern China transect along an aridity gradient","authors":"","doi":"10.1016/j.geoderma.2024.117073","DOIUrl":"10.1016/j.geoderma.2024.117073","url":null,"abstract":"<div><div>As an essential nutrient element for biological growth and metabolism, sulfur is closely interlinked with the carbon and nitrogen cycles, and it is one of the limiting elements for grassland productivity. Here we investigated the spatial distribution of sulfur contents and ³⁴S stable isotope along the North China Transect (NCT), with the aim to explore the shaping role of the aridity index (AI) gradient on sulfur cycling dynamic in arid and semi-arid grasslands. In the area with AI &lt; 0.12, soil sulfur contents and sulfur isotopic compositions (δ³⁴S) showed no correlation with AI, indicating that abiotic processes predominantly govern the sulfur cycle in this area. In the area where 0.12 ≤ AI &lt; 0.32, both sulfur contents and δ³⁴S values increased with rising AI, with microbial-mediated reduction being the primary sulfur cycling process. In the area with 0.32 ≤ AI &lt; 0.60, soil sulfur contents continued to increase with higher AI, but δ³⁴S significantly decreased as AI increased, suggesting plant uptake as the dominant sulfur cycling process in this area. This study demonstrated the significant impact of AI on sulfur dynamics, providing insights into the different drivers of sulfur cycling along the aridity gradient, and offering guidance for developing targeted strategies under global climate change.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531663","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":"Characterization and modeling of exogenous selenite aging in soils using machine learning and traditional data analysis","authors":"","doi":"10.1016/j.geoderma.2024.117074","DOIUrl":"10.1016/j.geoderma.2024.117074","url":null,"abstract":"<div><div>Understanding and predicting the aging process of exogenous selenium (Se) in soil is crucial for Se biofortification. However, the long-term aging of selenite in various soils has rarely been reported, and the key factors influencing this aging process remain unclear. Our study involved nineteen typical Chinese soils with varying physiochemical properties, all spiked with potassium selenite (1.0 mg kg⁻¹ Se) and incubated for 180 days. Soil available Se extracted using a 0.1 M K₂HPO₄-KH₂PO₄ solution was measured through the whole aging process. The average available Se% (the percentage of available Se in aged soils to total added Se) of all soils decreased from 55.4 % on the day 1 to 32.6 % on day 60, remaining stable thereafter. Pseudo-second-order equation provided the optimal fit (R² &gt; 0.989, P &lt; 0.01) for characterizing the dynamic process of selenite aging in soil, indicating that chemisorption, rather than internal diffusion, controlled the main rate-limiting step in the selenite aging process. Both machine learning and traditional correlation analysis indicated aging time was the most critical feature and the key soil property that contributed to available Se was pH. Empirical models incorporating soil properties and aging time were developed to predict changes of available Se in soil during aging under aerobic conditions. The reliability of the prediction model was further validated using data collected from previous studies. The developed aging model could potentially be used to scale biofortification data of Se generated from different soils under different aging times.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531752","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":"Responses in different levels of biological organization in the soil invertebrate Enchytraeus crypticus exposed to field-contaminated soils from a mining area","authors":"","doi":"10.1016/j.geoderma.2024.117069","DOIUrl":"10.1016/j.geoderma.2024.117069","url":null,"abstract":"<div><div>The sub-lethal ecotoxicity of field-contaminated soils toward small soil fauna, such as enchytraeids, remains understudied but holds paramount importance in soil pollution assessment. This study employed <em>Enchytraeus crypticus</em> to evaluate metal-contaminated soils from a mining area across various levels of biological organization, including individual level responses (survival, growth, reproduction, Cd/Pb/Zn accumulation), cellular level effects (peroxidase (POD), superoxide dismutase (SOD), glutathione (GSH), catalase (CAT), acetylcholinesterase (AChE), lipid peroxidation malondialdehyde (MDA)) and genetic alterations (olive tail moment (OTM) and tail DNA%). The study revealed considerable Cd and Pb accumulation, exerting adverse impacts on the reproduction and growth of the enchytraeids after a 21-day exposure. Changes in cellular and genetic parameters occurred with increasing exposure concentration and duration, indicating heightened lipid peroxidation and DNA damage in enchytraeids. A noteworthy metal detoxification process, evident at a physical level, was identified in <em>E. crypticus</em>, characterized by an initial escalation in toxicity followed by a subsequent decline. A distinctive complementary mechanism governing oxidative damage was detected in the enchytraeids, with an initial suppression of CAT activity, followed by inductions in SOD, POD, and GSH activity. Over the exposure duration, MDA content and DNA damage in the enchytraeids exhibited concentration-dependent shifts indicating their potential as efficient early-warning indicators for assessing the impact of Pb-Zn mining soils. This study contributes to a comprehensive understanding of the toxicological implications of metal-contaminated soils within the soil-enchytraeid framework.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446393","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}