Pub Date : 2025-09-17DOI: 10.5194/egusphere-2025-4032
Vincent Chaplot, Pardon Muchaonyerwa
Abstract. 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.
{"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}
Pub Date : 2025-09-15DOI: 10.5194/soil-11-629-2025
Gaston Matias Mendoza Veirana, Hana Grison, Jeroen Verhegge, Wim Cornelis, Philippe De Smedt
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.
{"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}
Pub Date : 2025-09-12DOI: 10.5194/egusphere-2025-4250
Philippe C. Baveye
Abstract. 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.
{"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}
Pub Date : 2025-09-10DOI: 10.5194/soil-11-609-2025
E. R. Jasper Wubs
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.
{"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}
Pub Date : 2025-09-09DOI: 10.5194/soil-11-583-2025
Julie Gillespie, Matiu Payne, Dione Payne, Sarah Edwards, Dyanna Jolly, Carol Smith, Jo-Anne Cavanagh
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.
{"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}
Pub Date : 2025-09-05DOI: 10.5194/egusphere-2025-3391
Kay D. Seufferheld, Pedro V. G. Batista, Hadi Shokati, Thomas Scholten, Peter Fiener
Abstract. 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.
{"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}
Pub Date : 2025-09-03DOI: 10.5194/egusphere-2025-3440
Kenzo E. Esquivel, Hannah Waterhouse, Jennifer Thompson, Daniel S. Karp, Grace Santos, Yordi Gil-Santos, Patrick Baur, Alastair Iles, Timothy M. Bowles
Abstract. 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 (<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.
{"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 (<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}
Pub Date : 2025-09-03DOI: 10.5194/egusphere-2025-4113
Sigrid van Grinsven, Noortje E. M. Janssen, Collin van Rooij, Ruben Peters, Arnaud Temme
Abstract. 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 CO2 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. CO2 flux measurements showed atmospheric CO2 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 <50 yrs, the autotrophic microbial community likely plays an important role in these young systems. Non-saturated locations showed a much larger variation in CO2 fluxes, with both emission and uptake of CO2 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.
{"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 <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}
Pub Date : 2025-08-20DOI: 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
Abstract. 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.
{"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}
Abstract. 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.
{"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}
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