Geoderma最新文献

{"title":"Agricultural management-driven soil inorganic carbon dynamics: Evidence from Chinese field experiments","authors":"Weiting Ding ,&nbsp;Liangjie Sun ,&nbsp;Zihao Wang ,&nbsp;Zhidong Qi ,&nbsp;Chengwei Zheng ,&nbsp;Jinsong Huang ,&nbsp;Francis Zvomuya ,&nbsp;Zhenhong Hu ,&nbsp;Laura L. Van Eerd ,&nbsp;Hailong He","doi":"10.1016/j.geoderma.2025.117535","DOIUrl":"10.1016/j.geoderma.2025.117535","url":null,"abstract":"<div><div>Soil inorganic carbon (SIC) is a crucial component of soil carbon pool, impacting climate change and ecosystem functions. SIC is affected by drastic changes in agricultural practices, while its response remains uncertain. We synthesized 54 field studies in China to assess the impact of agricultural practices on soil carbon stock, focusing on SIC and its responses to environmental factors. Overall, agricultural practices significantly reduced SIC stock (3.37 %) while increasing soil organic carbon (SOC) stock (15.41 %) and total carbon stock (6.80 %). Carbon pool changes could be categorized as follows: synergistic increases in SIC and SOC; trade-offs between SOC increases and SIC decreases; and individual effects on either SOC or SIC. SIC varied significantly across practices and regions, driven by climate, field management, and soil properties. Mineral fertilizer and straw return caused SIC losses, particularly under low-temperatures (MAT &lt; 10 ℃), high-rainfall (MAP &gt; 400 mm), and after 30 years. Severe SIC losses were observed in Northeast and East China. Combining organic and mineral fertilizers optimized the balance between SIC and crop yield, especially in arid regions. Key factors affecting SIC stock included soil depth, nitrogen addition, and experimental duration. Furthermore, our <em>meta</em>-analysis revealed that the distinct responses of SIC and SOC to agricultural practices underscored the necessity of integrated management strategies that effectively balanced SOC sequestration with SIC conservation. This study enhances understanding of SIC cycle and provides scientific evidence for sustainable agricultural practices.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117535"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Water-based enzyme assays are more sensitive than buffer-based assays to tillage and site in the U.S. Corn Belt","authors":"Rosa E. Lopez ,&nbsp;Jordon Wade ,&nbsp;María B. Villamil ,&nbsp;Steve Culman ,&nbsp;Michel A. Cavigelli ,&nbsp;Matthew H.H. Fischel ,&nbsp;Jude E. Maul ,&nbsp;Morgan P. Davis ,&nbsp;Ezra Aberle ,&nbsp;Andrew J. Margenot","doi":"10.1016/j.geoderma.2025.117518","DOIUrl":"10.1016/j.geoderma.2025.117518","url":null,"abstract":"<div><div>Assay methodology can influence the sensitivity of soil enzyme activities to agroecosystem management practices. Using soils from six long-term tillage experiments encompassing maize-based agroecosystems and three soil orders (e.g., Mollisols, Alfisols, Ultisols) across the U.S., we quantified the sensitivity of acid phosphomonoesterase (AC-PME), alkaline phosphomonoesterase (AK-PME), β-glucosidase (BG), N-acetyl-β-D-glucosaminidase (NAG), and arylsulfatase (SUL) activities to tillage practices (conventional vs none) and site measured by water-based assays versus buffer-based assays. To explain soil enzyme activity sensitivity differences between assay methodologies, we assessed (1) relative differences in activities measured with buffer- rather relative to water-based assays, (2) differences between soil and assay pH, and (3) activities on a soil versus soil organic carbon (SOC) basis. On a soil mass basis, enzyme activities were ≈2-fold more sensitive to tillage and to site using water- relative to buffer-based assays. Water-based NAG activity was most sensitive to tillage and site, whereas buffer-based SUL activity was least sensitive to tillage and buffer-based AK-PME activity was least sensitive to site. The difference between assay pH and soil pH were 1.5- to 6-fold lower for water-based assays, though pH divergences did not fully explain differences between water- and buffer-based activities. Buffer-based assays produced lower AC-PME (−32%) and AK-PME (−53%) activities but higher BG (+23%), NAG (+43%) and SUL (+87%) activities relative to water-based assays. Tillage effects on activities were primarily driven by SOC, except for buffer-based AK-PME activities. However, water-based activities maintained an enhanced sensitivity to site. We recommend the use of water-based assays to maximize the sensitivity of soil enzyme activities to tillage and to site.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117518"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Liming enhances soil priming effect in Chinese fir plantation induced by glycine rather than glucose and oxalic acid","authors":"Xin Yu ,&nbsp;Ning Tian ,&nbsp;Liming Yin ,&nbsp;Xin Guan ,&nbsp;Weidong Zhang ,&nbsp;Qingpeng Yang ,&nbsp;Fuming Xiao ,&nbsp;Silong Wang ,&nbsp;Longchi Chen","doi":"10.1016/j.geoderma.2025.117520","DOIUrl":"10.1016/j.geoderma.2025.117520","url":null,"abstract":"<div><div>Liming is a widely adopted strategy to mitigate soil acidification and enhance forest productivity. However, the extent to which liming modulates forest soil priming effects, particularly those induced by distinct root exudate types, remains poorly understood. To address this, we conducted a 90-day incubation experiment using soils from a three-year field liming experiment in a <em>Cunninghamia lanceolata</em> plantation (treatments: control, soil pH = 4.4; low liming doses, soil pH = 4.7; high liming doses, soil pH = 5.4). We investigated priming effects by adding three major ¹³C-labeled root exudate components - ¹³C-glucose, ¹³C-glycine, and ¹³C-oxalic acid − each at 2 % of soil organic carbon. Results showed that all exudates consistently induced positive priming effects, with glycine eliciting the strongest response (51.6–89.8 μg C g⁻¹ soil), followed by glucose (37.0–41.5 μg C g⁻¹ soil) and oxalic acid (32.9–47.3 μg C g⁻¹ soil). High liming amplified significantly glycine-induced priming effect by 70 % compared to the control, while priming effects induced by glucose and oxalic acid had no change among different doses of liming. This differential response indicates a synergistic effect between liming and glycine additions on the priming effect. Correlation analysis showed that both soil pH and the soil organic carbon mineralization rate (CMR) were positively correlated only with glycine-induced priming, and that glycine addition was the only treatment that increased NAG activity under high liming. These results suggest that liming enhanced soil pH, thereby stimulating microbial activity, and that the combined C and N supplied by glycine further promoted microbial and exoenzyme activity, ultimately intensifying glycine-induced priming in limed soils. Our findings suggested that liming effects on forest soil priming are jointly governed by root exudate type and soil physicochemical properties, advancing our understanding of liming-mediated soil C cycling.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117520"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145228941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shapley values reveal geomorphic controls on exposed bedrock-gravel differentiation","authors":"Xin Zhang ,&nbsp;Jianrong Fan ,&nbsp;Xinglong Huang","doi":"10.1016/j.geoderma.2025.117525","DOIUrl":"10.1016/j.geoderma.2025.117525","url":null,"abstract":"<div><div>Accurate discrimination of exposed bedrock (EB) and gravel surfaces is essential for quantifying soil resources, understanding erosional controls on pedogenesis, and guiding conservation strategies in bedrock-dominated mountain ecosystems. Conventional methods based on manual visual interpretation are labor-intensive, costly, and typically classify both as a single “mixed bedrock–gravel surface,” leading to misestimation of soil resources. Here, we present a framework that integrates topographic features, remote sensing spectral indices, and interpretable machine learning to classify EB and gravel in the high-elevation, geomorphically complex mountains of southern Tibet, China (average elevation &gt; 4,500 m). A total of 7,798 samples were generated from Google Earth Pro high-resolution imagery. By combining Sentinel-2 spectral bands, soil- and vegetation-related indices, and DEM-derived topographic variables, a recursive feature elimination–random forest (RFE–RF) model achieved an overall accuracy of 95.64 %, significantly exceeding that of the legacy approach (overall accuracy = 88 %). Independent field validation confirmed the robustness of the predictions. Shapley analysis revealed slope height and topographic position index as the primary drivers of EB–gravel differentiation, reflecting denudation processes on ridges and deposition in valleys. Shortwave infrared bands (B11, B12) and derived indices (clay index, geological index) further enhanced separation. The resulting maps aligned closely with Gaofen imagery and manual interpretations. This study establishes a transferable paradigm for high-precision surface classification in alpine environments, enabling fine-scale identification of potential soil resources.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117525"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating drying-induced biases in soil biochemical properties: sensitivity patterns and texture controls","authors":"Xin Qin ,&nbsp;Weibo Kong ,&nbsp;Shulei Dong ,&nbsp;Liyun Wei ,&nbsp;Xiaorong Wei ,&nbsp;Yufei Yao ,&nbsp;Liping Qiu","doi":"10.1016/j.geoderma.2025.117544","DOIUrl":"10.1016/j.geoderma.2025.117544","url":null,"abstract":"<div><div>Soil pretreatment has a profound influence on measured properties and nutrient assessments, which in turn affect the accuracy of nutrient evaluation and ecological interpretation. In this study, we investigated the effects of air-drying and freeze-drying on organic matter (OM), pH, total nitrogen (TN), mineral nitrogen (NO₃⁻, NH₄⁺), available phosphorus (AP) and potassium (AK), available micronutrients (A_Fe, A_Mn, A_Cu, A_Zn), and nitrogen transformation rates (Ra, Rn, Rm) across land use types and soil textures in the Loess Plateau. Both drying treatments significantly increased OM, micronutrient availability, and nitrogen transformation rates—particularly under freeze-drying—highlighting the high sensitivity of these variables to drying pretreatment. Therefore, fresh or minimally disturbed samples are recommended for accurate measurement of these sensitive variables. Conversely, TN, AP, AK, and NH₄⁺ exhibited relatively minor alterations, indicating that conventional air-drying methods can still yield accurate measurements for these parameters. Furthermore, drying effects were strongly modulated by soil texture: silt- and clay-rich soils showed greater increases in OM and micronutrient availability, while sandy soils experienced more severe pH reductions. Clay-rich soils also suppressed Rm after freeze-drying. These findings provide empirical evidence that soil texture strongly modulates drying effects on key soil properties. Accordingly, pretreatment strategies should be tailored not only to the analytical targets but also to soil texture to reduce analytical bias, particularly in large-scale, cross-site, or long-term monitoring programs.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117544"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145268384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical modeling of ammonium and nitrate nitrogen transport in estuarine wetland sediments: a case study of the Minjiang Estuary","authors":"Lanqing Qiu ,&nbsp;Jun Xia ,&nbsp;Xingwei Chen ,&nbsp;Chuan Tong ,&nbsp;Zipeng Gu","doi":"10.1016/j.geoderma.2025.117514","DOIUrl":"10.1016/j.geoderma.2025.117514","url":null,"abstract":"<div><div>The transport and transformation of ammonium nitrogen (NH₄⁺-N) and nitrate nitrogen (NO₃^–-N) in estuarine wetland sediments are influenced by tidal fluctuations. However, current research on this topic primarily relies on field experiments, which are time-consuming and often lack continuity, particularly regarding the dynamic changes in nitrogen (N) transformation during tidal cycles. In this study, the Minjiang Estuary wetland in China was selected as the research area to investigate the transport and transformation of NH₄⁺-N and NO₃⁻-N in sediments under tidal influence. A numerical model based on HYDRUS was developed, and its simulation accuracy was within acceptable limits. Transformation parameters for N at different tidal flats and months were successfully obtained. Results suggested that nitrification, mineralization, and denitrification coefficients tended to be higher in summer (August) than in autumn (November), although the seasonal pattern varied across tidal flat positions and soil depths. Spatially, nitrification and mineralization often decreased with depth, whereas denitrification tended to increase. With greater inundation depth, denitrification and mineralization often showed an increasing trend. Model simulations indicated that sediment inundation depth and solute concentration were key factors controlling NO₃⁻-N leaching, which increased with tidal level but with a certain degree of lag, especially during spring tides, while neap tides showed greater variability at intermediate tidal flat. This study provides theoretical insights into N transport parameters in estuarine wetland sediments and offers a modeling approach exemplified by the Minjiang Estuary, contributing to the sustainable management of estuarine wetland ecosystems.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117514"},"PeriodicalIF":6.6,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping soil carbon content in two contrasting pedoclimatic regions using a deep learning approach with remote sensing imagery and laboratory spectral datasets","authors":"Hayfa Zayani ,&nbsp;Youssef Fouad ,&nbsp;Didier Michot ,&nbsp;Zeineb Kassouk ,&nbsp;Nicolas Baghdadi ,&nbsp;Maria José Marquez Perez ,&nbsp;Emmanuelle Vaudour ,&nbsp;Zohra Lili-Chabaane ,&nbsp;Christian Walter","doi":"10.1016/j.geoderma.2025.117513","DOIUrl":"10.1016/j.geoderma.2025.117513","url":null,"abstract":"<div><div>Mapping soil properties can help in monitoring spatial and temporal variability in soils. However, the accuracy of predictions based on optical remote sensing data depends on the availability of cloud-free images and the presence of bare soil under suitable surface conditions. The objective of this study was to produce maps of soil organic carbon (SOC) content or soil total carbon (STC) content for two study areas with contrasting pedoclimatic conditions: Naizin (1.5 km²), which has a temperate climate and mainly intensive mixed crop-livestock farms on Luvic Cambisols and Haplic Albeluvisols, and Merguellil (40 km²), which has a semi-arid climate and mainly intensive farms on Fluvisols. We used a deep learning approach that combined remote sensing and laboratory visible, near-infrared and short-wave infrared (Vis-NIR-SWIR) datasets. We developed deep neural network models using all available bare soil pixels from Sentinel-2 (S2) images over one farming year and by measuring soil properties at 58 and 73 soil sampling points in the Naizin and Merguellil study areas, respectively. We used two approaches: (1) using only S2 bands to calibrate models and (2) adding laboratory spectral indices incrementally to the S2 bands in decreasing order of their correlation with SOC or STC content. To compare and analyse the spatial patterns in the SOC and STC maps produced by the two approaches, we applied one model from approach 1 and one model from approach 2. The results showed that this method was able to adapt to the two pedoclimatic contexts. Adding the laboratory indices to the models increased prediction accuracy for both study areas. Although the two approaches yielded similar spatial patterns of SOC or STC content, some differences were observed. Adding the laboratory indices increased intra-field variability in the distribution of SOC content for Naizin but decreased inter- and intra-field variability in the distribution of STC content for Merguellil. The method accurately mapped SOC content in 70 % of the Naizin area and STC content in more than 90 % of the Merguellil area. Future research could assess effects of using different methods for kriging, the potential of using hyper-spectral images for calculating spectral indices which would avoid effects of kriging on the spatial patterns in the maps of soil properties produced and the transferability of the models across different pedoclimatic regions.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117513"},"PeriodicalIF":6.6,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of land-use change on morphological, physicochemical, and mineralogical properties of volcanic soils in southern Chile","authors":"Belén Caurapan ,&nbsp;Franz Zehetner ,&nbsp;Franz Ottner ,&nbsp;Felipe Zúñiga ,&nbsp;Susana Valle","doi":"10.1016/j.geoderma.2025.117510","DOIUrl":"10.1016/j.geoderma.2025.117510","url":null,"abstract":"<div><div>Chilean volcanic soils, such as Andisols and Ultisols, cover much of the country’s arable land and are valued for their unique mineralogical characteristics. This study investigated the effects of land-use change from native forest to silvoagricultural systems on pedogenesis across four volcanic soil types: Acrudoxic Duraquand, Duric Hapludand, Typic Paleudult, and Typic Hapludult. Morphological analyses revealed that soils under agricultural uses have undergone changes in soil structure in addition to a loss in organic horizons. Significant differences were noted in physical and chemical properties, including bulk density, soil organic carbon (SOC), pH, and extractable aluminum. Andisols under croplands displayed higher bulk densities, lower SOC, and decreased extractable aluminum contents compared to those under native forests. Principal component analyses (PCA) revealed a distinct separation between land uses based on andic properties, suggesting, in some cases, a partial loss of these distinctive characteristics. Mineralogical analyses detected allophane, gibbsite, kaolinite, and hydroxy-interlayered minerals; however, no direct evidence was found for crystalline clay mineralogical transformations due to land-use change. Furthermore, while future studies would benefit from a finer-scale soil classification to account for the geomorphological variability of southern Chile, the present findings already highlight clear impacts of land-use change on pedogenesis in volcanic soils. Keywords: Volcanic soils, Land-use change, Pedogenesis, Andic properties, Soil mineralogy.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117510"},"PeriodicalIF":6.6,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High contributions of anaerobic decomposition to greenhouse gas emissions of agriculturally used peatlands","authors":"Jim Boonman ,&nbsp;Duygu Tolunay ,&nbsp;Joost Keuskamp ,&nbsp;Liam Heffernan ,&nbsp;Alexander J.V. Buzacott ,&nbsp;Sarah Faye Harpenslager ,&nbsp;Gijs van Dijk ,&nbsp;Mariet Hefting ,&nbsp;Ype van der Velde","doi":"10.1016/j.geoderma.2025.117521","DOIUrl":"10.1016/j.geoderma.2025.117521","url":null,"abstract":"<div><div>Globally, peatlands store one third of global soil carbon. Peatlands accumulate carbon under waterlogged anoxic conditions, but current drainage increases oxygen availability enhancing degradation of these carbon reserves. Therefore, drainage is responsible for ∼ 2 % of anthropogenic greenhouse gas (GHG) emissions. GHG emission estimates from drained peatlands are often based on hydrological proxies, but these methods are known to result in consistent inaccuracies. In this research, we propose to improve these estimates by using the redox potential that controls peat degradation more directly as compared to hydrological proxies. We aimed to quantify in-situ (net) soil production rates of CO₂ and CH₄ by combining in-situ redox potential measurements with corresponding laboratory basal respiration rates scaled to in-situ soil temperature. Using this approach, we estimated soil CO₂ and net CH₄ production rates at 12 field sites over multiple years and validated these estimates by comparing them to aboveground Net Ecosystem Carbon Balance (NECB) measurements using continuously operating chambers (for CO₂) and eddy covariance measurements (for CH₄) over the same sites and timeframes. We hypothesized that (1) laboratory incubation measurements can serve as a basis to estimate field-scale CO₂ and CH₄ emissions, (2) compared to water table depth, the redox potential is a more reliable parameter for estimating soil CO₂ production, and (3) anaerobic respiration processes contribute substantially to peat decomposition and soil CO₂ production. Averaged soil production estimates over multipole years for all sites of CO₂ showed strong agreement with measured NECBs (concordance correlation coefficient, CCC = 0.80) and net soil production estimates of CH₄ showed moderately strong agreement (CCC = 0.65) with CH₄ emissions. Using water table depth instead of soil redox condition to calculate soil CO₂ production rates resulted in a very low agreement with measured NECBs (CCC = 0.08) due to overestimation of the prevalence of oxic conditions. Shorter term comparisons generally resulted in lower CCC values, likely due to (bio)chemical legacy effects that balanced out over longer timescales. Anaerobic respiration processes accounted for 68 % of total soil CO₂ production over all sites, with 61 % originating from soil layers that were exposed to oxygen within the past 1.5 years, also likely influenced by biological and chemical legacy effects. By bridging the gap between laboratory and field-scale, our approach provides a valuable tool for assessing GHG emissions from drained peatlands and enhances our understanding of aerobic and anaerobic peat decomposition processes.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117521"},"PeriodicalIF":6.6,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatio-temporal stability of micro-dams as mitigation measures and disconnective elements to water erosion in potato farming","authors":"Matthias Konzett,&nbsp;Thomas Brunner,&nbsp;Peter Strauss,&nbsp;Elmar M. Schmaltz","doi":"10.1016/j.geoderma.2025.117519","DOIUrl":"10.1016/j.geoderma.2025.117519","url":null,"abstract":"<div><div>Micro-dams in potato fields help reduce surface runoff and soil loss. This study evaluated their stability by examining the effects of topography, rainfall intensity, and cover crops on failure mechanisms. Micro-dams were categorized as either without cover crops (MD) or with cover crops (MD + CC), which acted as potential stabilizing factors. Field observations and UAV imagery were taken from five potato fields in Northeast Austria to create a spatio-temporal inventory of failed micro-dams. The UAV imagery enabled the construction of Digital Elevation Models (DEM) for all observations, with failure detected through an automatic routine and compared to in-field mapping. Various topographic factors, such as slope steepness and the Topographic Wetness Index (TWI), were used to classify micro-dams into stable, damaged, or broken states. Rainfall intensities were calculated to compare triggering events, and a Generalized Additive Model (GAM) assessed the resilience of micro-dams across Austria’s main potato production areas. Results indicated that MD + CC were 20 % less likely to break (OR = 0.31, 95 % CI: 0.24 – 0.41, p &lt; 0.001), showcasing a higher proportion of stable micro-dams. These differences were significant among all state classes. MD + CC exhibited both damaged and stable micro-dams in topographic areas where standard MD had failed. The GAM results also pointed to a more sustainable performance for MD + CC. While an exact rainfall intensity threshold for failure was not established, specific conditions (53 mm total rainfall and 27.7 mm h⁻¹ intensity) were identified as indicative until future research is undertaken.</div></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"462 ","pages":"Article 117519"},"PeriodicalIF":6.6,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156190","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}