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Proglacial wetlands: an overlooked CO2 sink within recently deglaciated landscapes 前冰期湿地:在最近冰川消融的景观中被忽视的二氧化碳汇
IF 6.8 2区 农林科学
Soil Pub Date : 2025-09-03 DOI: 10.5194/egusphere-2025-4113
Sigrid van Grinsven, Noortje E. M. Janssen, Collin van Rooij, Ruben Peters, Arnaud Temme
{"title":"Proglacial wetlands: an overlooked CO2 sink within recently deglaciated landscapes","authors":"Sigrid van Grinsven, Noortje E. M. Janssen, Collin van Rooij, Ruben Peters, Arnaud Temme","doi":"10.5194/egusphere-2025-4113","DOIUrl":"https://doi.org/10.5194/egusphere-2025-4113","url":null,"abstract":"<strong>Abstract.</strong> Glacial retreat has uncovered vast landmasses in the European Alps over the last 150 yrs. Soil formation in these areas is considered to be slow due to low temperatures, lack of moisture, and short growing seasons. Previous studies have however focused solely on dry soils, omitting any water saturated locations. Our research shows that these water saturated locations are key locations of CO<sub>2</sub> uptake and have a significant role in carbon storage in the proglacial valley, despite their small surface area. Loss-on-ignition analyses showed certain wetland soils contained up to 85 % carbon, suggesting these wetlands can become peatlands over time, storing large amounts of carbon. CO<sub>2</sub> flux measurements showed atmospheric CO<sub>2</sub> uptake in wetlands of all measured ages, even as young as 5 years after deglaciation. As little moss or plant cover was generally observed at locations &lt;50 yrs, the autotrophic microbial community likely plays an important role in these young systems. Non-saturated locations showed a much larger variation in CO<sub>2</sub> fluxes, with both emission and uptake of CO<sub>2</sub> being observed across ages. Overall, our research shows that wetlands are hotspots of biological activity and pedogenic processes in proglacial areas and should therefore receive more attention in proglacial research.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"32 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144930260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Soil degradation assessment across tropical grassland of Western Kenya 肯尼亚西部热带草原土壤退化评价
IF 6.8 2区 农林科学
Soil Pub Date : 2025-08-20 DOI: 10.5194/egusphere-2025-3722
John N. Quinton, Gabriel Yesuf, German Baldi, Mengyi Gong, Kelvin Kinuthia, Ellen L. Fry, Yuda Odongo, Barthelemew Nyakundi, Joseph Hitimana, Patricia de Britto Costa, Alice A. Onyango, Sonja M. Leitner, Richard D. Bardgett, Mariana C. Rufino
{"title":"Soil degradation assessment across tropical grassland of Western Kenya","authors":"John N. Quinton, Gabriel Yesuf, German Baldi, Mengyi Gong, Kelvin Kinuthia, Ellen L. Fry, Yuda Odongo, Barthelemew Nyakundi, Joseph Hitimana, Patricia de Britto Costa, Alice A. Onyango, Sonja M. Leitner, Richard D. Bardgett, Mariana C. Rufino","doi":"10.5194/egusphere-2025-3722","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3722","url":null,"abstract":"<strong>Abstract.</strong> Soils across sub-Saharan Africa are exposed to extensive degradation, reducing their ability to produce crops and support livestock. While there has been a significant research effort focussing on soil degradation in sub-Saharan croplands, less research effort had been directed towards grasslands. Here, we tested the effectiveness of remote sensing to classify the soil degradation status of smallholder grazing lands. Focussing on grasslands used by smallholders in the districts of Nyando and Kuresoi in Western Kenya, we first used remote sensing (RS) to classify grasslands as either equilibrium, transition or degraded, and then tested how this classification related to measured soil parameters indicative of soil degradation. We then used this classification, which was based on a temporal analysis of Normalised Differential Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Normalised Differential Water Index (NDWI) between 2013 and 2018, to identify 90 field sites across the two districts, which we then sampled and analysed for a range of physical, chemical and biological soil properties. Only soil microbial biomass carbon (C) showed consistent alignment with the RS classification, although there was some overlap with other soil parameters at one or other of the sites. To group the sites using the soil parameters, which we split by district and into stable and transient soil variables, K-means clustering was undertaken. Two clusters were produced. One of the clusters included sites with higher levels of C, nitrogen (N), phosphorus (P) and pH, that aligned well with the RS classification at Kuresoi, with seven out of ten equilibrium sites being assigned to this cluster. The other cluster, in Nyando, had high soil C and P, but low pH and relatively low soil bulk density, and corresponded to 12 out of the 16 equilibrium sites. Overall, our results suggest that while the use of RS methods for classifying degraded grasslands and the soils supporting them does have significant advantages in terms of time and costs over field survey, supplementing these methods with a limited set of soil parameters related to nutrient cycling, such as microbial biomass C, soil P, percent C and N, and soil pH, could enhance our ability to to identify degraded soils and target restoration efforts.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"21 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Forest conversion reduces soil water retention in tropical rainforest by altering soil properties 森林转化通过改变土壤性质减少了热带雨林的土壤保水
IF 6.8 2区 农林科学
Soil Pub Date : 2025-08-18 DOI: 10.5194/egusphere-2025-3772
Qiaoyan Chen, Siyuan Cheng, Shuting Yu, Xiaowei Guo, Zhongyi Sun, Zhongmin Hu, Licong Dai
{"title":"Forest conversion reduces soil water retention in tropical rainforest by altering soil properties","authors":"Qiaoyan Chen, Siyuan Cheng, Shuting Yu, Xiaowei Guo, Zhongyi Sun, Zhongmin Hu, Licong Dai","doi":"10.5194/egusphere-2025-3772","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3772","url":null,"abstract":"<strong>Abstract.</strong> Extensive primary forests are being converted to secondary forests and plantation owing to human activities in recent decades, which has substantial effects on soil hydrological processes. However, the potential impact of forest conversion on soil water retention remains poorly understood. In this study, tropical primary forests (PF), secondary forests (SF) and rubber monocultures (RM) converted from tropical primary forests were selected on Hainan Island, to examine the variation in soil water retention across three forest types and their controlling factors. We found that the primary forests exhibited significantly greater water retention capacity than secondary forests and rubber monocultures. However, secondary forests showed higher water retention than rubber monocultures in shallow soils but lower in deep soils. Similarly, primary forests demonstrated significantly greater soil water storage capacity than secondary forests and rubber monocultures, but secondary forests and rubber monocultures had obvious seasonal variations, which showed that secondary forests had a higher water storage capacity than rubber monocultures in the rainy season, and display opposite pattern in the dry season. The saturated hydraulic conductivity in primary forests was higher than that in secondary forests and rubber monoculture. Furthermore, forest types influenced soil properties, with secondary forests and rubber monoculture showing higher bulk density but lower soil capillary porosity compared with primary forests. Among all factors, soil porosity emerged as the dominant controller of water retention, where total porosity and capillary porosity accounted for 31.49 % and 30.61 % of variation respectively, while soil bulk density contributed relatively less (12.46 %). These findings indicate that the conversion of tropical primary forests to secondary forests and rubber monocultures is detrimental to soil water retention and storage. Our results can provide scientific insights for forest development and management in the tropical rainforest.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"146 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Soil erosion in Mediterranean olive groves: a review 地中海橄榄园土壤侵蚀研究进展
IF 6.8 2区 农林科学
Soil Pub Date : 2025-08-18 DOI: 10.5194/egusphere-2025-3542
Andres Peñuela, Filippo Milazzo, Emilio Jesús González-Sánchez
{"title":"Soil erosion in Mediterranean olive groves: a review","authors":"Andres Peñuela, Filippo Milazzo, Emilio Jesús González-Sánchez","doi":"10.5194/egusphere-2025-3542","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3542","url":null,"abstract":"<strong>Abstract.</strong> Olive groves are a defining feature of the Mediterranean landscape, economy, and culture. However, this keystone agroecosystem is under severe threat from soil erosion, a problem exacerbated by the region's unique topographic, climatic conditions and agricultural practices. Although soil erosion in olive groves has been extensively studied, significant uncertainties remain due to the high variability of scales and measurement methods. Knowledge gaps persist regarding the average soil loss rates and runoff coefficients as well as the effects of different management approaches and the influence of triggering factors on soil erosion rates. So far, an effort to quantify this effect on Mediterranean olive cultivation has not been made comprehensively. Therefore, the aim of this literature review is to discern clearer patterns and trends that are often obscured by the overall heterogeneity of the available data. By systematically analysing the data according to measurement methodology, this review provides clear answers to these knowledge gaps and reveals a consistent narrative about the primary drivers of soil loss. While natural factors like topography, rainfall intensity and soil properties establish a baseline risk, this review shows that agricultural management, particularly the presence of groundcovers, is the pivotal factor controlling soil degradation. The long-standing debate on erosion severity is largely reconciled by the finding that reported rates are highly dependent on the measurement methodology, and hence on the spatial and temporal scale. Conservation practices consistently reduce soil loss by more than half, an effect far more pronounced for sediment control than for runoff reduction. Ultimately, the path to sustainability requires a shift away from conventional tillage and bare-soil management towards the widespread adoption of vegetation/groundcover, driven by effective policies and a commitment to multi-scale and multi-proxy research to improve predictive models.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"25 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144898638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Portable X-ray fluorescence as a tool for urban soil contamination analysis: accuracy, precision, and practicality 便携式x射线荧光作为城市土壤污染分析的工具:准确性、精密度和实用性
IF 6.8 2区 农林科学
Soil Pub Date : 2025-08-13 DOI: 10.5194/soil-11-565-2025
Eriell M. Jenkins, John Galbraith, Anna A. Paltseva
{"title":"Portable X-ray fluorescence as a tool for urban soil contamination analysis: accuracy, precision, and practicality","authors":"Eriell M. Jenkins, John Galbraith, Anna A. Paltseva","doi":"10.5194/soil-11-565-2025","DOIUrl":"https://doi.org/10.5194/soil-11-565-2025","url":null,"abstract":"Abstract. Urban agriculture has become an essential component of urban sustainability, but it often faces the challenge of soil contamination with heavy metal(loid)s like lead (Pb), arsenic (As), chromium (Cr), copper (Cu), manganese (Mn), nickel (Ni), and zinc (Zn). Traditional laboratory methods for detecting these contaminants, such as atomic absorption spectroscopy and other inductively coupled plasma techniques, are accurate but can be costly and time-consuming and require extensive sample preparation. Portable X-ray fluorescence (PXRF) presents a promising alternative, offering rapid, in situ analysis with minimal sample preparation. The study reviews literature on PXRF analyzers to determine their accuracy and precision in analyzing heavy metal(loid)s in urban soils, with the goal of optimizing sampling, reducing laboratory costs and time, and identifying priority metal contamination hotspots. A literature review was conducted using Web of Science and Google Scholar, focusing on studies that validated PXRF measurements with alternate laboratory methods or certified reference materials (CRMs). This study reviews 84 publications to evaluate the accuracy and precision of PXRF in analyzing heavy metal(loid)s in urban soils. The review covers instrument types, action methods, testing conditions, and sample preparation techniques. Results show that, when properly calibrated, particularly with CRMs, PXRF can achieve reliable accuracy. Ex situ measurements tend to be more precise due to controlled conditions, although in situ measurements offer practical advantages in urban settings. Portable XRF emerges as a viable method for assessing urban soil contamination by balancing accuracy and practicality. Future research should focus on optimizing sample preparation and calibration to further enhance PXRF reliability in urban environments, ultimately strengthening PXRF methodologies and supporting extension efforts through improved, accessible soil-testing tools, facilitating healthier urban soils, safer urban food production, and enhanced community well-being.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"8 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144825295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Effect of trachyte and basalt rock powders on maize (Zea mays L.) growth and yield on Fluvisols in Cameroon’s Sudano-Sahelian zone (Central Africa) 粗粗纤维和玄武岩粉末对喀麦隆苏丹-萨赫勒地区玉米生长和Fluvisols产量的影响
IF 6.8 2区 农林科学
Soil Pub Date : 2025-08-08 DOI: 10.5194/egusphere-2025-3474
Bienvenu Sidsi, Claudine Vounba, Simon Djakba Basga, Aubin Nzeugang Nzeukou, Merlin Gountié Dedzo, Désiré Tsozué
{"title":"Effect of trachyte and basalt rock powders on maize (Zea mays L.) growth and yield on Fluvisols in Cameroon’s Sudano-Sahelian zone (Central Africa)","authors":"Bienvenu Sidsi, Claudine Vounba, Simon Djakba Basga, Aubin Nzeugang Nzeukou, Merlin Gountié Dedzo, Désiré Tsozué","doi":"10.5194/egusphere-2025-3474","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3474","url":null,"abstract":"<strong>Abstract.</strong> The Sudano-Sahelian zone of Cameroon, characterized by a low annual rainfall, faces challenges in soil fertility preservation due to agricultural intensification and unsustainable practices. This study aims to evaluate the effect of trachyte and basalt powders inputs on soil and maize yield in Guiring experimental farm. Fieldwork involved collecting and describing samples of trachyte, basalt, and soil and setting up the experimental design. In the laboratory, the ground rock samples underwent geochemical analysis, and the soil samples were analysed for their mineralogical and physicochemical properties. The experiment followed a completely randomized block design with six treatments (T<sub>0</sub>, T<sub>1</sub>, T<sub>2</sub>, T<sub>3</sub>, T<sub>4</sub>, and T<sub>5</sub>) and four replications. Growth and yield parameters of maize, include germination rate, plant height, number of leaves per plant, stem diameter, ear length, ear diameter, ear weight, 100-grain weight, and grain yield (kg ha<sup>-1</sup>). The soil consists of kaolinite, smectite, sepiolite, and quartz. Its texture is dominated by sand fraction, with a neutral pH (7.0). The organic matter (2.6±0.67 %) and total nitrogen contents (0.1±0.0 %) are relatively low. The concentrations of potassium, magnesium, sodium, and calcium are 0.2±0.1 cmol<sub>c</sub> kg<sup>-1</sup>, 2.5±1.6 cmol<sub>c</sub> kg<sup>-1</sup>, 0.3±0.2 cmol<sub>c</sub> kg<sup>-1</sup>, and 3.9±1.5 cmol<sub>c</sub> kg<sup>-1</sup>, respectively. The cation exchange capacity is moderate to high (22.1±2.5 cmol<sub>c</sub> kg<sup>-1</sup>), while the available phosphorus content is high (19±7.0 mg kg<sup>-1</sup>). This soil is classified as Ochric Dystric Fluvisols according to the WRB. These soil characteristics are moderately suitable for maize cultivation. Fertilization trials showed a significant improvement in maize growth and yield, within plots treated with basalt powder yielding higher (2558.6 kg ha<sup>-1</sup> and 2931.2 kg ha<sup>-1</sup>) than those treated with trachyte powder (2362.9 kg ha<sup>-1</sup> and 2763.9 kg ha<sup>-1</sup>) and the control plots (645.8 kg ha<sup>-1</sup>). Plots treated with NPK fertilizer recorded the highest yield (3164.5 kg ha<sup>-1</sup>). Although the treatment with conventional fertiliser resulted in a relative higher yield, the advantage of using rock powders lies in their environmental benefits, long-term effectiveness, and more affordable cost.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"160 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144796725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Assessing the potential of complex artificial neural networks for modelling small-scale soil erosion by water 评估复杂人工神经网络模拟小规模水土流失的潜力
IF 6.8 2区 农林科学
Soil Pub Date : 2025-08-08 DOI: 10.5194/egusphere-2025-3583
Nils Barthel, Simone Ott, Benjamin Burkhard, Bastian Steinhoff-Knopp
{"title":"Assessing the potential of complex artificial neural networks for modelling small-scale soil erosion by water","authors":"Nils Barthel, Simone Ott, Benjamin Burkhard, Bastian Steinhoff-Knopp","doi":"10.5194/egusphere-2025-3583","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3583","url":null,"abstract":"<strong>Abstract.</strong> Accurately modelling soil erosion by water is essential for developing effective mitigation strategies and preventing on- and off-site damages in agricultural areas. So far, complex artificial neural networks have rarely been applied in small-scale soil erosion modelling, and their potential still remains unclear. This study compares the performance of different neural network architectures for modelling soil erosion by water at a small spatial scale in agricultural cropland. The analysis is based on erosion rate data at a 5 m × 5 m resolution, derived from a 20-year monitoring programme, and covers 458 hectares of cropland across six investigation areas in northern Germany. Nineteen predictor variables related to topography, climate, management and soil properties were selected as inputs to assess their interrelationships with observed erosion patterns and to predict continuous soil erosion rates. A single-layer neural network (SNN), a deep neural network (DNN), and a convolutional neural network (CNN) were applied and evaluated against a random forest (RF) model used as a benchmark. All machine learning models have successfully captured spatial patterns of soil erosion, with the CNN consistently outperforming the others across all evaluation metrics. The CNN achieves the lowest root mean squared error (RMSE: 1.05) and mean absolute error (MAE: 0.41), outperforming the RF (RMSE: 1.31, MAE: 0.58) and the SNN (RMSE: 1.48, MAE: 0.63), while the DNN performs similarly to the CNN with a slightly higher RMSE (1.1) and MAE (0.45). The CNN notably outperforms the other three approaches when evaluating their capability to accurately predict soil erosion within given classes, achieving a weighted mean F1 score of 0.7. A permutation importance analysis identified the digital elevation model as the most influential predictor variable across all models, contributing between 15 % and 18.3 %, while USLE C and R factors also had significant importance. Overall, these findings highlight the potential of complex neural networks for predicting spatially explicit rates of soil erosion by water.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"17 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144802708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Soil stoichiometric characteristics and influencing factors in karst forests under micro-topography and microhabitat scales 微地形和微生境尺度下喀斯特森林土壤化学计量特征及其影响因素
IF 6.8 2区 农林科学
Soil Pub Date : 2025-07-29 DOI: 10.5194/egusphere-2025-3510
Yi Dang, Hua Zhou, Wenjun Zhao, Yingchun Cui, Chengjiang Tan, Fangjun Ding, Yukun Wang, Run Liu, Peng Wu
{"title":"Soil stoichiometric characteristics and influencing factors in karst forests under micro-topography and microhabitat scales","authors":"Yi Dang, Hua Zhou, Wenjun Zhao, Yingchun Cui, Chengjiang Tan, Fangjun Ding, Yukun Wang, Run Liu, Peng Wu","doi":"10.5194/egusphere-2025-3510","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3510","url":null,"abstract":"<strong>Abstract.</strong> To quantitatively evaluate the stoichiometric characteristics of karst forest soils and their response mechanisms to complex microenvironments, the study systematically investigated soil stoichiometric traits and influencing factors across micro-topography and microhabitat scales in the Maolan karst forest. Key findings include: (1) Soil nutrients (organic carbon, total nitrogen, hydrolyzable nitrogen, available phosphorus, available potassium, total calcium, exchangeable calcium, and exchangeable magnesium) exhibited strong variability with significant spatial heterogeneity; (2) Microhabitat factors significantly influenced nutrient accumulation, though different elements showed distinct response patterns to microhabitat variations; (3) Micro-topographic parameters (slope gradient, aspect, and position) exerted indirect effects through gravity, light exposure, and erosion, driving the formation of gradient patterns in soil stoichiometry; (4) Differential response mechanisms of nutrients to abiotic factors, combined with the differential nutrient regulation and absorption strategies of various plant life forms, collectively shaped the complex stoichiometric characteristics. Synergistic interactions were observed among microhabitat-micro-topography-plant life form factors, with geomorphological abiotic factors playing predominant roles at this scale. Although biotic factors like plant life forms showed relatively weaker direct influences, their regulatory effects were closely interrelated with microhabitat-topographic factors. This multi-dimensional feedback mechanism between biotic and abiotic factors reflects the complexity of nutrient cycling in karst ecosystems.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"27 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144719707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Mineral-bound organic carbon exposed by hillslope thermokarst terrain: case study in Cape Bounty, Canadian High Arctic 由山坡热岩溶地形暴露的矿物结合有机碳:加拿大高北极邦蒂角的案例研究
IF 6.8 2区 农林科学
Soil Pub Date : 2025-07-22 DOI: 10.5194/egusphere-2025-3428
Maxime Thomas, Julien Fouché, Hugues Titeux, Charlotte Morelle, Nathan Bemelmans, Melissa J. Lafrenière, Joanne K. Heslop, Sophie Opfergelt
{"title":"Mineral-bound organic carbon exposed by hillslope thermokarst terrain: case study in Cape Bounty, Canadian High Arctic","authors":"Maxime Thomas, Julien Fouché, Hugues Titeux, Charlotte Morelle, Nathan Bemelmans, Melissa J. Lafrenière, Joanne K. Heslop, Sophie Opfergelt","doi":"10.5194/egusphere-2025-3428","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3428","url":null,"abstract":"<strong>Abstract.</strong> Arctic landscapes could add 55–230 Pg of carbon (in CO<sub>2</sub> equivalent) to the atmosphere, through CO<sub>2</sub> and CH<sub>4</sub> emissions, by the end of this century. These estimates could be quantified more accurately by constraining the contribution of rapid thawing processes such as thermokarst landscapes to permafrost carbon loss, and by investigating the exposed organic carbon (OC) interacting with mineral surfaces or metallic cations, i.e., the nature of these interactions and what controls their relative abundance. Here, we investigate two contrasted types of hillslope thermokarst landscapes: an Active Layer Detachment (ALD) which is a one-time event, and a Retrogressive Thaw Slump (RTS) which repeats annually during summer months in the Cape Bounty Arctic Watershed Observatory (Melville Island, Canada). We analyzed mineralogy, total and soluble element concentrations, total OC and mineral-OC interactions within the headwalls of both disturbances, and within corresponding undisturbed profiles. Our results show that OC stabilized by chemical bonds account for 13 ± 5 % of total OC in the form of organo-metallic complexes and up to 6 ± 2 % associated with poorly crystalline iron oxides. If we add the mechanisms of physical protection of particulate organic matter in aggregates and larger molecules stabilized by chemical bonds, we reach 64 ± 10 % of the total OC being stabilized. Importantly, we observe a decrease in the proportion of mineral-bound OC in the deeper layers exposed by the retrogressive thaw slump: the proportion of organo-metallic complexes drops from ~18 % in surface samples to ~1 % in the deepest samples. These results therefore suggest that the OC exposed by thermokarst disturbances at Cape Bounty is protected by interactions with minerals to a certain extent, but that deep thaw features could expose OC more readily accessible to degradation.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"51 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Using Monte Carlo conformal prediction to evaluate the uncertainty of deep-learning soil spectral models 用蒙特卡罗保形预测方法评价深度学习土壤光谱模型的不确定性
IF 6.8 2区 农林科学
Soil Pub Date : 2025-07-22 DOI: 10.5194/soil-11-553-2025
Yin-Chung Huang, José Padarian, Budiman Minasny, Alex B. McBratney
{"title":"Using Monte Carlo conformal prediction to evaluate the uncertainty of deep-learning soil spectral models","authors":"Yin-Chung Huang, José Padarian, Budiman Minasny, Alex B. McBratney","doi":"10.5194/soil-11-553-2025","DOIUrl":"https://doi.org/10.5194/soil-11-553-2025","url":null,"abstract":"Abstract. Uncertainty quantification is a crucial step in the practical application of soil spectral models, particularly in supporting real-world decision making and risk assessment. While machine learning has made remarkable strides in predicting various physiochemical properties of soils using spectroscopy, its practical utility in decision making remains limited without quantified uncertainty. Despite its importance, uncertainty quantification is rarely incorporated into soil spectral models, with existing methods facing significant limitations. Existing methods are either computationally demanding, fail to achieve the desired coverage of observed data, or struggle to handle out-of-domain uncertainty. This study introduces an innovative application of Monte Carlo conformal prediction (MC-CP) to quantify uncertainty in deep-learning models for predicting clay content from mid-infrared spectroscopy. We compared MC-CP with two established methods: (1) Monte Carlo dropout and (2) conformal prediction. Monte Carlo dropout generates prediction intervals for each sample and can address larger uncertainties associated with out-of-domain data. Conformal prediction, on the other hand, guarantees ideal coverage of true values but generates unnecessarily wide prediction intervals, making it overly conservative for many practical applications. Using 39 177 samples from the mid-infrared spectral library of the Kellogg Soil Survey Laboratory to build convolutional neural networks, we found that Monte Carlo dropout itself falls short in achieving the desired coverage – its 90 % prediction intervals only covered the observed values in 74 % of the cases, well below the expected 90 % coverage. In contrast, MC-CP successfully combines the strengths of both methods. It achieved a prediction interval coverage probability of 91 %, closely matching the expected 90 % coverage and far surpassing the performance of the Monte Carlo dropout. Additionally, the mean prediction interval width for MC-CP was 9.05 %, narrower than the conformal prediction's 11.11 %. The success of MC-CP enhances the real-world applicability of soil spectral models, paving the way for their integration into large-scale machine learning models, such as soil inference systems, and further transforming decision making and risk assessment in soil science.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"282 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144677499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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