Soil最新文献

{"title":"Overcoming barriers in long-term, continuous monitoring of soil CO2 flux: a low-cost sensor system","authors":"Thi Thuc Nguyen, Nadav Bekin, Ariel Altman, Martin Maier, Nurit Agam, Elad Levintal","doi":"10.5194/soil-11-639-2025","DOIUrl":"https://doi.org/10.5194/soil-11-639-2025","url":null,"abstract":"Abstract. Soil CO2 flux (Fs) is a carbon cycling metric crucial for assessing ecosystem carbon budgets and global warming. However, global Fs datasets often suffer from low temporal-spatial resolution, as well as from spatial bias. Fs observations are severely deficient in tundra and dryland ecosystems due to financial and logistical constraints of current methods for Fs quantification. In this study, we introduce a novel, low-cost sensor system (LC-SS) for long-term, continuous monitoring of soil CO2 concentration and flux. The LC-SS, built from affordable, open-source hardware and software, offers a cost-effective solution (∼ USD 700 and ∼ 50 h for assembling and troubleshooting), accessible to low-budget users, and opens the scope for research with a large number of sensor system replications. The LC-SS was tested over ∼ 6 months in arid soil conditions, where fluxes are small, and accuracy is critical. CO2 concentration and soil temperature were measured at 10 min intervals at depths of 5 and 10 cm. The LC-SS demonstrated high stability during the tested period. Both diurnal and seasonal soil CO2 concentration variabilities were observed, highlighting the system's capability of continuous, long-term, in-situ monitoring of soil CO2 concentration. In addition, Fs was calculated using the measured CO2 concentration via the gradient method and validated with Fs measured by the flux chamber method using the well-accepted LI-COR gas analyzer system. Gradient method Fs was in good agreement with flux chamber Fs (RMSE = 0.15 µmol m−2 s−1), highlighting the potential for alternative or concurrent use of the LC-SS with current methods for Fs estimation – particularly in environments characterized by consistently low soil water content, such as drylands. Leveraging the accuracy and cost-effectiveness of the LC-SS (below 10 % of automated gas analyzer system cost), strategic implementation of LC-SSs could be a promising means to effectively increase the number of measurements, spatially and temporally, ultimately aiding in bridging the gap between global Fs uncertainties and current measurement limitations.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"17 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133609","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}

{"title":"Combining electromagnetic induction and satellite-based NDVI data for improved determination of management zones for sustainable crop production","authors":"Salar Saeed Dogar, Cosimo Brogi, Dave O'Leary, Ixchel M. Hernández-Ochoa, Marco Donat, Harry Vereecken, Johan Alexander Huisman","doi":"10.5194/soil-11-655-2025","DOIUrl":"https://doi.org/10.5194/soil-11-655-2025","url":null,"abstract":"Abstract. Accurate delineation of management zones is essential for optimizing resource use and improving yield in precision agriculture. Electromagnetic induction (EMI) provides a rapid, non-invasive method to map soil variability, while the Normalized Difference Vegetation Index (NDVI) obtained with remote sensing captures aboveground crop dynamics. Integrating these datasets may enhance management zone delineation but presents challenges in data harmonization and analysis. This study presents a workflow combining unsupervised classification (clustering) and statistical validation to delineate management zones using EMI and NDVI data in a single 70 ha field of the patchCROP experiment in Tempelberg, Germany. Three datasets were investigated: (1) EMI maps, (2) NDVI maps, and (3) a combined EMI–NDVI dataset. Historical yield data and soil samples were used to refine the clusters through statistical analysis. The results demonstrate that four EMI-based zones effectively captured subsurface soil heterogeneity, while three NDVI-based zones better represented yield variability. A combination of EMI and NDVI data resulted in three zones that provided a balanced representation of both subsurface and aboveground variability. The final EMI–NDVI-derived map demonstrates the potential of integrating multi-source datasets for field management. It provides actionable insights for precision agriculture, including optimized fertilization, irrigation, and targeted interventions, while also serving as a valuable resource for environmental modeling and soil surveying.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"40 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145133610","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}

{"title":"Estimating soil organic carbon stocks in Pinus halepensis mill. stands using lidar data and field inventory","authors":"David Moreno-Pérez, María-Belén Turrión, Felipe Bravo, Irene Ruano, Celia Herrero de Aza, Frederico Tupinambá-Simões","doi":"10.5194/egusphere-2025-3669","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3669","url":null,"abstract":"<strong>Abstract.</strong> Accurate estimation of soil organic carbon (SOC) in forest ecosystems is essential for quantifying their contribution as carbon sinks and improving management strategies in the face of climate change. The objective of this study was to model SOC in <em>Pinus halepensis</em> Mill. stands using structural metrics derived from LiDAR data from the National Aerial Orthophotography Plan (PNOA). The study area covered 46.8 hectares located in the municipality of Ampudia, Palencia (Spain). To carry out the work, systematic soil sampling and a forest inventory were conducted. LiDAR technology was also applied and 87 structural metrics were obtained. These metrics were integrated with edaphic variables and above-ground biomass data to build predictive models of carbon stock using multivariate regression techniques. Among the models evaluated, the Random Forest algorithm showed the best performance in cross-validation (R² = 0.81; RMSE = 7.73 Mg/ha), demonstrating adequate predictive capacity compared to other models. The proposed approach made it possible to evaluate the potential of LiDAR data from airborne laser scanning (ALS), acquired within the framework of general mapping programmes, as an effective tool for the spatial estimation of SOC. This procedure, validated on an empirical basis, provides a useful methodological basis for advancing in the estimation of SOC through remote sensing, contributing to improve the quantification of soil-related ecosystem services.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"18 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145127817","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}

{"title":"Crop fertilization as a key determinant of croplands’ soil carbon stocks","authors":"Vincent Chaplot, Pardon Muchaonyerwa","doi":"10.5194/egusphere-2025-4032","DOIUrl":"https://doi.org/10.5194/egusphere-2025-4032","url":null,"abstract":"<strong>Abstract.</strong> Soil organic matter (SOM), which associates organic carbon to key plant nutrients, is a corner stone of soil health, agricultural productivity and ecosystem functioning. While virgin lands (forest or grassland) exhibit the highest SOM stocks, their cultivation leads to their sharp decrease and that of crop yields in the first decade(s), even when zero tillage and cover crops are promoted. The decline in SOM is less acute when crops are fertilized with N, P, K at rates recommended to meet crop needs than when not fertilized, and is often reversed when nutrients are applied above recommendations. This points to the key role of fertilization to manage croplands’ soil carbon that needs to be better understood to mitigate against soil degradation for promoting sustainable agriculture, while minimizing environmental hazards such as water pollution.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"29 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145072264","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}

{"title":"Exploring the link between cation exchange capacity and magnetic susceptibility","authors":"Gaston Matias Mendoza Veirana, Hana Grison, Jeroen Verhegge, Wim Cornelis, Philippe De Smedt","doi":"10.5194/soil-11-629-2025","DOIUrl":"https://doi.org/10.5194/soil-11-629-2025","url":null,"abstract":"Abstract. This study explores the relationship between soil magnetic susceptibility (κ) and cation exchange capacity (CEC) across diverse European soils, aiming to enhance pedotransfer functions (PTFs) for soil CEC using near-surface electromagnetic geophysics. We hypothesize that soil κ, can improve the prediction of CEC by reflecting the soil's mineralogical composition, particularly in sandy soils. We collected data from 49 soil samples in vertical profiles across Belgium, the Netherlands, and Serbia, including κ in situ conditions (κ∗), low and high frequency κ in the laboratory, in-site electrical conductivity (σ), iron content, soil texture, humus content, bulk density, water content, water pH, and CEC. We used these properties as features to develop univariable and multivariable (in pairs) polynomial regressions to predict CEC for sandy and clayey soils. Results indicate that κ∗ significantly improves CEC predictions in sandy soils, independent of clay content, with a combined κ∗-σ model achieving the highest predictive performance (R2 = 0.94). In contrast, laboratory-measured κ was less effective, likely due to sample disturbance. This study presents a novel CEC PTF based on σ and κ∗, offering a rapid, cost-effective method for estimating CEC in field conditions. While our findings underscore the value of integrating geophysical measurements into soil characterization, further research is needed to refine the κ–CEC relationship and develop a more widely applicable model.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"28 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059297","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}

{"title":"Why a mechanistic theory of soils is crucially important: Another line of supportive arguments exists, seldom invoked in soil science","authors":"Philippe C. Baveye","doi":"10.5194/egusphere-2025-4250","DOIUrl":"https://doi.org/10.5194/egusphere-2025-4250","url":null,"abstract":"<strong>Abstract.</strong> In the last few decades, the sizable effort that has been devoted to the mechanistic, quantitative description of soil processes has been justified on the grounds that theories and models help us understand how soils function, and also predict how, e.g., they are likely to adjust in the future to environmental change. The argument, familiar to physicists, that theories uniquely determine what should be measured has rarely if ever been invoked in the soil science literature. On the contrary, to enable the classification and mapping of soil, enormous amounts of “theory-free” data have been and continue to be amassed by soil scientists. In this general context, the key objective of the present Forum article is to argue that the accumulation of more “theory-free” data, in particular to allow the application of artificial intelligence methods, is not sensible at this stage, and that the development of improved theories of soil processes is crucial, to provide guidance about the type of measurements that should be performed. Hopefully, this Forum article will stimulate a debate on this issue, and will lead to a much needed intensification of theoretical research and modelling in soil science.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"7 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145035169","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}

{"title":"Benchmarking soil multifunctionality","authors":"E. R. Jasper Wubs","doi":"10.5194/soil-11-609-2025","DOIUrl":"https://doi.org/10.5194/soil-11-609-2025","url":null,"abstract":"Abstract. Healthy soils provide multiple functions that contribute importantly to human wellbeing, including in primary production, climate and water regulation, and supporting biodiversity. These functions can partially be combined, and some functions also clearly trade off: this motivates soil multifunctionality research. Society needs scientists to help assess which soils are best for which soil functions and to determine appropriate long-term management of any given soil for optimal function delivery. However, for both tasks science lacks coherent tools, and, in this paper, I propose a way forward. Critically, we lack a common measurement framework that pins soil functioning measurements on a common scale. Currently the field is divided with respect to the methods we use to measure and assess soil functioning and indicators thereof. Only three indicator variables (soil organic matter (SOM), acidity, and available P) were commonly measured (> 70 % of schemes) across 65 schemes that aim to measure soil health or quality, and no biological measure is implemented in more than 30 % of the 65 schemes. This status quo prevents us from systematically comparing across and within soils; we lack a soil multifunctionality benchmark. We can address these limitations systematically by setting a common measurement system. To do this, I propose to use latent-variable modelling, based on a common set of functional measurements, to develop a common “IQ test for soils”. I treat soil functions as latent variables; because they are complex processes that cannot be measured directly, we can only detect drivers and consequences of these complex processes. Latent-variable modelling has a long history in social, economic, and psychometric fields, where it is known as factor analysis. Factor analysis aims to derive common descriptors – the factors – of hypothesized constructs by linking measurable response variables together on a common scale. Here, I explain why such a new approach to soil multifunctionality and soil health is needed and how it can be operationalized. The framework developed here is an initial proposal; the issue of soil multifunctionality is too complex and too important to be addressed in one go. It needs to be resolved iteratively by groups of scientist working intensively together. We need to bring our best scientists together, in a collaborative effort, to develop progressively more refined ways of sustainably managing one of humanity's most precious resources: our soils.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"44 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145025307","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}

{"title":"Research at the interface between Indigenous knowledge and soil science; weaving knowledges to understand horticultural land use in Aotearoa / New Zealand","authors":"Julie Gillespie, Matiu Payne, Dione Payne, Sarah Edwards, Dyanna Jolly, Carol Smith, Jo-Anne Cavanagh","doi":"10.5194/soil-11-583-2025","DOIUrl":"https://doi.org/10.5194/soil-11-583-2025","url":null,"abstract":"Abstract. Addressing the complex challenges of soil and food security at international and local scales requires moving beyond the boundaries of individual disciplines and knowledge systems. The value of transdisciplinary research approaches is increasingly recognised, including those that value and incorporate Indigenous knowledge systems and holders. Using a case study at Pōhatu, Aotearoa / New Zealand, this paper demonstrates the value of a transdisciplinary approach to explore past Māori food landscapes and contribute to contemporary Māori soil health and food sovereignty aspirations. Engaging at the interface between soil science and Indigenous knowledge (mātauraka Māori) in an Aotearoa / New Zealand context, we provide an example and guide for weaving knowledges in a transdisciplinary context. Here, mātauraka Māori, including waiata (songs) and ingoa wāhi (place names), provided the map of where to look and why, and soil analysis yielded insight into past cultivation, soil modification, and fertilisation practices. Both knowledges were needed to interpret the findings and support Māori in re-establishing traditional horticultural practices. Furthermore, the paper extends the current literature on the numerous conceptual frameworks developed to support and guide transdisciplinary research by providing an example of how to do this type of research in an on-the-ground application.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"16 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145017703","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}

{"title":"A GLUE-based assessment of WaTEM/SEDEM for simulating soil erosion, transport, and deposition in soil conservation optimised agricultural watersheds","authors":"Kay D. Seufferheld, Pedro V. G. Batista, Hadi Shokati, Thomas Scholten, Peter Fiener","doi":"10.5194/egusphere-2025-3391","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3391","url":null,"abstract":"<strong>Abstract.</strong> Soil erosion models are essential tools for soil conservation planning. Although these models are generally well-tested against plot and field data for in-field soil management, challenges arise when scaling up to the landscape level, where sediment trapping along landscape features becomes increasingly critical. At this scale, a separate analysis of model performance in representing erosion, sediment transport, and deposition processes is both challenging and often lacking. In this study, we assessed the capacity of the spatially distributed erosion and sediment transport model WaTEM/SEDEM to simulate sediment yields in six micro-scale watersheds ranging from 0.8 to 7.8 ha, monitored over eight years from 1994 to 2001. The watersheds were comprised of two groups: four field-dominated watersheds characterised by arable land with minimal landscape structures, and two structure-dominated watersheds featuring a combination of arable land and linear landscape structures (mainly grassed waterways along thalwegs) that minimise sediment connectivity. This setup enabled a separate analysis of model performance for both watershed groups. A Generalised Likelihood Uncertainty Estimation (GLUE) framework was employed to account for measurement and model uncertainties across multiple spatiotemporal scales. Our results show that while WaTEM/SEDEM generally captured the magnitude of the very low measured sediment yields in the monitored watersheds, the model did not meet our pre-defined limits of acceptability when operating on annual timesteps. However, the WaTEM/SEDEM's performance improved substantially when model realisations were aggregated across the eight-year monitoring period and over the two watershed groups, with mean absolute errors of 0.11 t ha⁻¹ yr⁻¹ for field-dominated and 0.18 t ha⁻¹ yr⁻¹ for structure-dominated watersheds. Our findings demonstrate that the model can represent the influence of soil conservation measures on reducing soil erosion and sediment delivery but performs better for long-term conservation planning at larger scales than for precise annual predictions in individual micro-scale watersheds with specific conservation practices.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"13 3 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144995788","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}

{"title":"Soil Health Management Drives Soil Organic Matter More Than Edaphic Properties Across Working Organic Farms","authors":"Kenzo E. Esquivel, Hannah Waterhouse, Jennifer Thompson, Daniel S. Karp, Grace Santos, Yordi Gil-Santos, Patrick Baur, Alastair Iles, Timothy M. Bowles","doi":"10.5194/egusphere-2025-3440","DOIUrl":"https://doi.org/10.5194/egusphere-2025-3440","url":null,"abstract":"<strong>Abstract.</strong> Rebuilding soil organic carbon (SOC) on working lands plays a pivotal role in mitigating climate change and improving soil function, yet its accumulation is constrained by both management decisions and inherent soil properties. Scientists and farm advisors recommend that farmers plant cover crops, reduce tillage, and add organic amendments to increase SOC, yet the effectiveness of practices intended to improve soil health may be limited by underlying edaphic controls such as mineralogy, texture, and pH. Given that SOC consists of two distinct fractions—particulate organic matter (POM) and mineral-associated organic matter (MAOM)—which differ in their stability and response to management, a critical question emerges: How much do inherent soil properties limit the effectiveness of recommended soil health practices in increasing SOC? Despite extensive research in controlled field settings, real-world farming contexts remain less understood, limiting our ability to predict SOC gains across diverse soil conditions. Here, we evaluate how in-season and recent (&lt;5 yr) implementation of soil health management systems on working farms affects SOC fractions and stocks across 28 organic fields growing leafy greens in the Central Coast of California. We find that continuous living cover (e.g., through cover cropping) increases three of our measured carbon pools – free POM, MAOM, and surface soil total carbon stocks – while reduced disturbance (i.e., less tillage) increases two – free POM and MAOM. Crop diversity enhances both free and occluded POM fractions. Surprisingly, organic matter amendments do not show any relationship with any of the measured carbon pools. On average, management variables explain 3.7 times more variance than edaphic variables across carbon fractions, whereas, for carbon stocks, the opposite is true: edaphic variables explain ~2.1 times the variance compared to management. Our findings highlight that soil health practices, and in particular continuous cover, can significantly increase soil carbon levels, including both particulate and mineral-associated organic matter fractions, across diverse soil conditions.","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":"144930254","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}