Pub Date : 2024-03-27DOI: 10.3389/fsoil.2024.1371777
J. Antonangelo, Steven Culman, Hailin Zhang
Enhancing soil cation exchange capacity (CEC) is of paramount importance for sustainable agriculture and ecosystem health. This study investigated the pivotal role of biochar in altering soil CEC and challenges conventional assumptions about universal effects of biochar application.Contrasting biochar types, one with a low ash content of 4.4% (switchgrass-derived biochar, SGB) and the other with a high ash content of 45.9% (poultry litter-derived biochar, PLB) were used. Two experiments treated with increasing biochar application rates were conducted: one without plants and the other grown with ryegrass. Effective CEC (summation method) was determined by two extraction methods: Mehlich-3 (M3) and ammonium acetate (AA).The SGB decreased CEC by 27% on average (from both experiments) from the lowest to the highest rate of biochar application, while the PLB significantly increased CEC by 91%. This highlights the critical role of biochar properties in influencing CEC dynamics. In the second experiment, ryegrass cultivation revealed the greater importance of the calcium and magnesium/potassium ratio ([Ca+Mg]/K) in the soil CEC than CEC only for plant growth in biochar-amended soils. The ratios for optimum ryegrass production ranged from 82‒86 (M3) and 69‒74 (AA), which was translated to 88:11:1 Ca:Mg:K percent base saturation ratios. Moreover, predictive models for estimation of soil CEC after biochar application were successfully developed based on initial soil and biochar CEC. However, M3 was more reliable than AA for such predictions mainly because it was more successful in predicting nutrient availability from biochar. These models offer a promising tool for informed soil management decisions.This research emphasizes the importance of biochar feedstock, elucidates nutrient ratio effects on plant growth, and provides a practical means to anticipate soil CEC changes post-biochar application.
{"title":"Comparative analysis and prediction of cation exchange capacity via summation: influence of biochar type and nutrient ratios","authors":"J. Antonangelo, Steven Culman, Hailin Zhang","doi":"10.3389/fsoil.2024.1371777","DOIUrl":"https://doi.org/10.3389/fsoil.2024.1371777","url":null,"abstract":"Enhancing soil cation exchange capacity (CEC) is of paramount importance for sustainable agriculture and ecosystem health. This study investigated the pivotal role of biochar in altering soil CEC and challenges conventional assumptions about universal effects of biochar application.Contrasting biochar types, one with a low ash content of 4.4% (switchgrass-derived biochar, SGB) and the other with a high ash content of 45.9% (poultry litter-derived biochar, PLB) were used. Two experiments treated with increasing biochar application rates were conducted: one without plants and the other grown with ryegrass. Effective CEC (summation method) was determined by two extraction methods: Mehlich-3 (M3) and ammonium acetate (AA).The SGB decreased CEC by 27% on average (from both experiments) from the lowest to the highest rate of biochar application, while the PLB significantly increased CEC by 91%. This highlights the critical role of biochar properties in influencing CEC dynamics. In the second experiment, ryegrass cultivation revealed the greater importance of the calcium and magnesium/potassium ratio ([Ca+Mg]/K) in the soil CEC than CEC only for plant growth in biochar-amended soils. The ratios for optimum ryegrass production ranged from 82‒86 (M3) and 69‒74 (AA), which was translated to 88:11:1 Ca:Mg:K percent base saturation ratios. Moreover, predictive models for estimation of soil CEC after biochar application were successfully developed based on initial soil and biochar CEC. However, M3 was more reliable than AA for such predictions mainly because it was more successful in predicting nutrient availability from biochar. These models offer a promising tool for informed soil management decisions.This research emphasizes the importance of biochar feedstock, elucidates nutrient ratio effects on plant growth, and provides a practical means to anticipate soil CEC changes post-biochar application.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140376103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-15DOI: 10.3389/fsoil.2024.1239497
G. Blanchy, Paul McLachlan, Benjamin Mary, Matteo Censini, J. Boaga, Giorgio Cassiani
Characterization of the shallow subsurface in mountain catchments is important for understanding hydrological processes and soil formation. The depth to the soil/bedrock interface (e.g., the upper ~5 m) is of particular interest. Frequency domain electromagnetic induction (FDEM) methods are well suited for high productivity characterization for this target as they have short acquisition times and do not require direct coupling with the ground. Although traditionally used for revealing lateral electrical conductivity (EC) patterns, e.g., to produce maps of salinity or water content, FDEM inversion is increasingly used to produce depth-specific models of EC. These quantitative models can be used to inform several depth-specific properties relevant to hydrological modeling (e.g. depths to interfaces and soil water content).There are a number of commercial FDEM instruments available; this work compares a multi-coil device (i.e., a single-frequency device with multiple receiver coils) and a multi-frequency device (i.e., a single receiver device with multiple frequencies) using the open-source software EMagPy. Firstly, the performance of both devices is assessed using synthetic modeling. Secondly, the analysis is applied to field data from an alpine catchment.Both instruments retrieved a similar EC model in the synthetic and field cases. However, the multi-frequency instrument displayed shallower sensitivity patterns when operated above electrically conductive grounds (i.e., 150 mS/m) and therefore had a lower depth of investigation. From synthetic modeling, it also appears that the model convergence for the multi-frequency instrument is more sensitive to noise than the multi-coil instrument.Despite these limitations, the multi-frequency instrument is smaller and more portable; consequently, it is easier to deploy in mountainous catchments.
{"title":"Comparison of multi-coil and multi-frequency frequency domain electromagnetic induction instruments","authors":"G. Blanchy, Paul McLachlan, Benjamin Mary, Matteo Censini, J. Boaga, Giorgio Cassiani","doi":"10.3389/fsoil.2024.1239497","DOIUrl":"https://doi.org/10.3389/fsoil.2024.1239497","url":null,"abstract":"Characterization of the shallow subsurface in mountain catchments is important for understanding hydrological processes and soil formation. The depth to the soil/bedrock interface (e.g., the upper ~5 m) is of particular interest. Frequency domain electromagnetic induction (FDEM) methods are well suited for high productivity characterization for this target as they have short acquisition times and do not require direct coupling with the ground. Although traditionally used for revealing lateral electrical conductivity (EC) patterns, e.g., to produce maps of salinity or water content, FDEM inversion is increasingly used to produce depth-specific models of EC. These quantitative models can be used to inform several depth-specific properties relevant to hydrological modeling (e.g. depths to interfaces and soil water content).There are a number of commercial FDEM instruments available; this work compares a multi-coil device (i.e., a single-frequency device with multiple receiver coils) and a multi-frequency device (i.e., a single receiver device with multiple frequencies) using the open-source software EMagPy. Firstly, the performance of both devices is assessed using synthetic modeling. Secondly, the analysis is applied to field data from an alpine catchment.Both instruments retrieved a similar EC model in the synthetic and field cases. However, the multi-frequency instrument displayed shallower sensitivity patterns when operated above electrically conductive grounds (i.e., 150 mS/m) and therefore had a lower depth of investigation. From synthetic modeling, it also appears that the model convergence for the multi-frequency instrument is more sensitive to noise than the multi-coil instrument.Despite these limitations, the multi-frequency instrument is smaller and more portable; consequently, it is easier to deploy in mountainous catchments.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140240590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-05DOI: 10.3389/fsoil.2024.1345073
H. Rupp, Nadine Tauchnitz, Ralph Meissner
Despite various efforts to reduce nitrogen leaching from agricultural land, the permissible nitrate concentrations in groundwater have often been exceeded in the past. Intensive farming is often seen as the cause of the deterioration in water quality. Therefore, the present lysimeter study aimed to quantify nitrogen (N) leaching at different N fertilization levels for the agricultural land use systems of arable land and grassland to derive suitable management measures for improving groundwater quality.The effects of three different of mineral fertilization treatments (50%, 100%, and 150%) in arable land and grassland use on four distinct soil types (loamy sand, sand, loam, loess) concerning seepage formation, nitrogen concentrations, nitrogen loads, dry matter yields and nitrogen balances were tested. The study was conducted at the lysimeter facility of the Helmholtz Centre of Environmental Research – UFZ at Falkenberg (northeast Germany). Twenty-four non-weighable lysimeters with a surface area of 1 m² and a depth of 1.25 m were managed as grassland and arable land with three different fertilization treatments since 1985.For arable land use, N leaching differed between the studied soil types, with the highest N loads from the sand (36.6 kg ha–1 yr–1 ) and loamy sand (30.7 kg ha–1 yr–1 ) and the lowest N loads from loess (12.1 kg ha–1 yr–1) and loam soil (13.1 kg ha–1 yr–1). In contrast to grassland use, a reduction of N fertilization level by 50 % did not result in reduced N leaching for arable land, whereas a maximal 29% reduced dry matter yields was observed. An increase of N fertilization by 50 % did not cause significant enhanced N leaching at arable land use. Soil-and management-related factors (soil type, texture, soil tillage, crop rotation, and others) mask the effect of increased N fertilization rates in arable land using lysimeters. For arable land use, a reduction of N fertilizer levels as the only measure was insufficient to reduce NO3– leaching, and other strategies besides N fertilization levels are required to improve groundwater quality. Measures should be targeted to reduce N losses by mineralization processes.
{"title":"The influence of increasing mineral fertilizer application on nitrogen leaching of arable land and grassland—results of a long-term lysimeter study","authors":"H. Rupp, Nadine Tauchnitz, Ralph Meissner","doi":"10.3389/fsoil.2024.1345073","DOIUrl":"https://doi.org/10.3389/fsoil.2024.1345073","url":null,"abstract":"Despite various efforts to reduce nitrogen leaching from agricultural land, the permissible nitrate concentrations in groundwater have often been exceeded in the past. Intensive farming is often seen as the cause of the deterioration in water quality. Therefore, the present lysimeter study aimed to quantify nitrogen (N) leaching at different N fertilization levels for the agricultural land use systems of arable land and grassland to derive suitable management measures for improving groundwater quality.The effects of three different of mineral fertilization treatments (50%, 100%, and 150%) in arable land and grassland use on four distinct soil types (loamy sand, sand, loam, loess) concerning seepage formation, nitrogen concentrations, nitrogen loads, dry matter yields and nitrogen balances were tested. The study was conducted at the lysimeter facility of the Helmholtz Centre of Environmental Research – UFZ at Falkenberg (northeast Germany). Twenty-four non-weighable lysimeters with a surface area of 1 m² and a depth of 1.25 m were managed as grassland and arable land with three different fertilization treatments since 1985.For arable land use, N leaching differed between the studied soil types, with the highest N loads from the sand (36.6 kg ha–1 yr–1 ) and loamy sand (30.7 kg ha–1 yr–1 ) and the lowest N loads from loess (12.1 kg ha–1 yr–1) and loam soil (13.1 kg ha–1 yr–1). In contrast to grassland use, a reduction of N fertilization level by 50 % did not result in reduced N leaching for arable land, whereas a maximal 29% reduced dry matter yields was observed. An increase of N fertilization by 50 % did not cause significant enhanced N leaching at arable land use. Soil-and management-related factors (soil type, texture, soil tillage, crop rotation, and others) mask the effect of increased N fertilization rates in arable land using lysimeters. For arable land use, a reduction of N fertilizer levels as the only measure was insufficient to reduce NO3– leaching, and other strategies besides N fertilization levels are required to improve groundwater quality. Measures should be targeted to reduce N losses by mineralization processes.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140264756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.3389/fsoil.2024.1259907
M. K. Samuel, Stephanie L. Evers
Compaction is recognized as an effective method for mitigating the risk of fires by enhancing soil moisture levels. This technique involves restricting peat pore spaces through compaction, facilitating improved capillary action for water retention and rehydration. The compaction of tropical peatlands, while beneficial for fire prevention, has the potential to influence biogeochemical processes and subsequent carbon emissions. The magnitude of compaction and groundwater level are strongly coupled in such environments, making it difficult to distinguish the control of physicochemical properties. Therefore, this study seeks to understand how peat compaction affects its properties, carbon emissions, and their relationship, with a focus on geophysical processes. Intact peat samples were collected from a secondary peat swamp forest and an oil palm plantation in Selangor, Peninsular Malaysia. Compaction treatments were applied to achieve three levels of volume reduction. CO2 and CH4 emissions were measured using an automated gas analyzer, and the physicochemical properties of the peat were determined. The results revealed that mechanical compaction significantly altered the physicochemical properties of the secondary forest peat, displaying an opposite pattern to the oil palm plantation, particularly regarding total nitrogen and sulfur. Moreover, the average reduction percentage ratio of CO2 emissions (from 275.4 to 182.0 mg m-2 hr-1; 33.9%) to CH4 uptakes (from -17.8 to -5.2 µg m-2 hr-1; 70.1%) (~1:2) indicated distinct stages of decomposition and translocation of less decomposed peat to deeper layers due to compaction, predominantly in secondary peat swamp forest samples. The oil palm plantation samples were unaffected by compaction in terms of physicochemical properties and carbon emissions, indicating the ineffectiveness of this approach for reducing fire risk in already drained systems. This study underscores the necessity of understanding the effects of compaction in the absence of groundwater to accurately evaluate the widespread application of this technique.
{"title":"Translocation of tropical peat surface to deeper soil horizons under compaction controls carbon emissions in the absence of groundwater","authors":"M. K. Samuel, Stephanie L. Evers","doi":"10.3389/fsoil.2024.1259907","DOIUrl":"https://doi.org/10.3389/fsoil.2024.1259907","url":null,"abstract":"Compaction is recognized as an effective method for mitigating the risk of fires by enhancing soil moisture levels. This technique involves restricting peat pore spaces through compaction, facilitating improved capillary action for water retention and rehydration. The compaction of tropical peatlands, while beneficial for fire prevention, has the potential to influence biogeochemical processes and subsequent carbon emissions. The magnitude of compaction and groundwater level are strongly coupled in such environments, making it difficult to distinguish the control of physicochemical properties. Therefore, this study seeks to understand how peat compaction affects its properties, carbon emissions, and their relationship, with a focus on geophysical processes. Intact peat samples were collected from a secondary peat swamp forest and an oil palm plantation in Selangor, Peninsular Malaysia. Compaction treatments were applied to achieve three levels of volume reduction. CO2 and CH4 emissions were measured using an automated gas analyzer, and the physicochemical properties of the peat were determined. The results revealed that mechanical compaction significantly altered the physicochemical properties of the secondary forest peat, displaying an opposite pattern to the oil palm plantation, particularly regarding total nitrogen and sulfur. Moreover, the average reduction percentage ratio of CO2 emissions (from 275.4 to 182.0 mg m-2 hr-1; 33.9%) to CH4 uptakes (from -17.8 to -5.2 µg m-2 hr-1; 70.1%) (~1:2) indicated distinct stages of decomposition and translocation of less decomposed peat to deeper layers due to compaction, predominantly in secondary peat swamp forest samples. The oil palm plantation samples were unaffected by compaction in terms of physicochemical properties and carbon emissions, indicating the ineffectiveness of this approach for reducing fire risk in already drained systems. This study underscores the necessity of understanding the effects of compaction in the absence of groundwater to accurately evaluate the widespread application of this technique.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139782224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-12DOI: 10.3389/fsoil.2024.1259907
M. K. Samuel, Stephanie L. Evers
Compaction is recognized as an effective method for mitigating the risk of fires by enhancing soil moisture levels. This technique involves restricting peat pore spaces through compaction, facilitating improved capillary action for water retention and rehydration. The compaction of tropical peatlands, while beneficial for fire prevention, has the potential to influence biogeochemical processes and subsequent carbon emissions. The magnitude of compaction and groundwater level are strongly coupled in such environments, making it difficult to distinguish the control of physicochemical properties. Therefore, this study seeks to understand how peat compaction affects its properties, carbon emissions, and their relationship, with a focus on geophysical processes. Intact peat samples were collected from a secondary peat swamp forest and an oil palm plantation in Selangor, Peninsular Malaysia. Compaction treatments were applied to achieve three levels of volume reduction. CO2 and CH4 emissions were measured using an automated gas analyzer, and the physicochemical properties of the peat were determined. The results revealed that mechanical compaction significantly altered the physicochemical properties of the secondary forest peat, displaying an opposite pattern to the oil palm plantation, particularly regarding total nitrogen and sulfur. Moreover, the average reduction percentage ratio of CO2 emissions (from 275.4 to 182.0 mg m-2 hr-1; 33.9%) to CH4 uptakes (from -17.8 to -5.2 µg m-2 hr-1; 70.1%) (~1:2) indicated distinct stages of decomposition and translocation of less decomposed peat to deeper layers due to compaction, predominantly in secondary peat swamp forest samples. The oil palm plantation samples were unaffected by compaction in terms of physicochemical properties and carbon emissions, indicating the ineffectiveness of this approach for reducing fire risk in already drained systems. This study underscores the necessity of understanding the effects of compaction in the absence of groundwater to accurately evaluate the widespread application of this technique.
{"title":"Translocation of tropical peat surface to deeper soil horizons under compaction controls carbon emissions in the absence of groundwater","authors":"M. K. Samuel, Stephanie L. Evers","doi":"10.3389/fsoil.2024.1259907","DOIUrl":"https://doi.org/10.3389/fsoil.2024.1259907","url":null,"abstract":"Compaction is recognized as an effective method for mitigating the risk of fires by enhancing soil moisture levels. This technique involves restricting peat pore spaces through compaction, facilitating improved capillary action for water retention and rehydration. The compaction of tropical peatlands, while beneficial for fire prevention, has the potential to influence biogeochemical processes and subsequent carbon emissions. The magnitude of compaction and groundwater level are strongly coupled in such environments, making it difficult to distinguish the control of physicochemical properties. Therefore, this study seeks to understand how peat compaction affects its properties, carbon emissions, and their relationship, with a focus on geophysical processes. Intact peat samples were collected from a secondary peat swamp forest and an oil palm plantation in Selangor, Peninsular Malaysia. Compaction treatments were applied to achieve three levels of volume reduction. CO2 and CH4 emissions were measured using an automated gas analyzer, and the physicochemical properties of the peat were determined. The results revealed that mechanical compaction significantly altered the physicochemical properties of the secondary forest peat, displaying an opposite pattern to the oil palm plantation, particularly regarding total nitrogen and sulfur. Moreover, the average reduction percentage ratio of CO2 emissions (from 275.4 to 182.0 mg m-2 hr-1; 33.9%) to CH4 uptakes (from -17.8 to -5.2 µg m-2 hr-1; 70.1%) (~1:2) indicated distinct stages of decomposition and translocation of less decomposed peat to deeper layers due to compaction, predominantly in secondary peat swamp forest samples. The oil palm plantation samples were unaffected by compaction in terms of physicochemical properties and carbon emissions, indicating the ineffectiveness of this approach for reducing fire risk in already drained systems. This study underscores the necessity of understanding the effects of compaction in the absence of groundwater to accurately evaluate the widespread application of this technique.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139842143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-01DOI: 10.3389/fsoil.2024.1342986
Shaima Khalifah, M. Foltz
Nitrous oxide (N2O) is a potent greenhouse gas that contributes to stratospheric ozone depletion and global climate change. Soil denitrification has two potential end-products, N2O and dinitrogen (N2), and the ratio of these end-products (N2O:(N2O+N2) or the N2O ratio) is controlled by various factors. This study aims to quantify the influence of soil pH on the ratio of denitrification end-products in Oklahoma soils with different soil textures. Six natural grassland soils encompassing three distinct soil textures were incubated in the laboratory under natural and modified pH with an overall tested pH ranging from 2 to 10. Denitrification end-products were measured in the laboratory using the acetylene inhibition technique and further estimated using a process-based biogeochemical model. Both the laboratory and model results showed that soil pH and texture influenced the ratio of the denitrification end-products. Generally, as soil pH increased the N2O ratio decreased, although both lab and model results indicated that this relationship was not linear. Soil texture may have an indirect effect on the N2O ratio, as two soils of the same texture could have different N2O ratios. However, clay percentage of the soil did show a linear positive correlation with the N2O ratio, suggesting components of soil texture may be more influential than others. Overall, soil pH was a controlling factor in the ratio of denitrification end-products and the newly observed nonlinear relationship warrants further study, particularly when considering its effects in different soil textures.
{"title":"The ratio of denitrification end-products were influenced by soil pH and clay content across different texture classes in Oklahoma soils","authors":"Shaima Khalifah, M. Foltz","doi":"10.3389/fsoil.2024.1342986","DOIUrl":"https://doi.org/10.3389/fsoil.2024.1342986","url":null,"abstract":"Nitrous oxide (N2O) is a potent greenhouse gas that contributes to stratospheric ozone depletion and global climate change. Soil denitrification has two potential end-products, N2O and dinitrogen (N2), and the ratio of these end-products (N2O:(N2O+N2) or the N2O ratio) is controlled by various factors. This study aims to quantify the influence of soil pH on the ratio of denitrification end-products in Oklahoma soils with different soil textures. Six natural grassland soils encompassing three distinct soil textures were incubated in the laboratory under natural and modified pH with an overall tested pH ranging from 2 to 10. Denitrification end-products were measured in the laboratory using the acetylene inhibition technique and further estimated using a process-based biogeochemical model. Both the laboratory and model results showed that soil pH and texture influenced the ratio of the denitrification end-products. Generally, as soil pH increased the N2O ratio decreased, although both lab and model results indicated that this relationship was not linear. Soil texture may have an indirect effect on the N2O ratio, as two soils of the same texture could have different N2O ratios. However, clay percentage of the soil did show a linear positive correlation with the N2O ratio, suggesting components of soil texture may be more influential than others. Overall, soil pH was a controlling factor in the ratio of denitrification end-products and the newly observed nonlinear relationship warrants further study, particularly when considering its effects in different soil textures.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139687173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-23DOI: 10.3389/fsoil.2023.1242647
D. Babos, Wesley Nascimento Guedes, V. Freitas, Fernanda Pavani Silva, Marcelo Larsen de Lima Tozo, P. Villas-Boas, L. Martin-Neto, D. Milori
The demand for efficient, accurate, and cost-effective methods of measuring soil carbon (C) in agriculture is growing. Traditional approaches are time consuming and expensive, highlighting the need for alternatives. This study tackles the challenge of utilizing laser-induced breakdown spectroscopy (LIBS) as a more economical method while managing its potential accuracy issues due to physical–chemical matrix effects. A set of 1,019 soil samples from 11 Brazilian farms was analyzed using various univariate and multivariate calibration strategies. The artificial neural network (ANN) demonstrated the best performance with the lowest root mean square error of prediction (RMSEP) of 0.48 wt% C, a 28% reduction compared to the following best calibration method (matrix-matching calibration – MMC inverse regression and multiple linear regression – MLR at 0.67 wt% C). Furthermore, the study revealed a strong correlation between total C determined by LIBS and the elemental CHNS analyzer for soils samples in nine farms (R² ≥ 0.73). The proposed method offers a reliable, rapid, and cost-efficient means of measuring total soil C content, showing that LIBS and ANN modeling can significantly reduce errors compared to other calibration methods. This research fills the knowledge gap in utilizing LIBS for soil C measurement in agriculture, potentially benefiting producers and the soil C credit market. Specific recommendations include further exploration of ANN modeling for broader applications, ensuring that agricultural soil management becomes more accessible and efficient.
{"title":"Laser-induced breakdown spectroscopy as an analytical tool for total carbon quantification in tropical and subtropical soils: evaluation of calibration algorithms","authors":"D. Babos, Wesley Nascimento Guedes, V. Freitas, Fernanda Pavani Silva, Marcelo Larsen de Lima Tozo, P. Villas-Boas, L. Martin-Neto, D. Milori","doi":"10.3389/fsoil.2023.1242647","DOIUrl":"https://doi.org/10.3389/fsoil.2023.1242647","url":null,"abstract":"The demand for efficient, accurate, and cost-effective methods of measuring soil carbon (C) in agriculture is growing. Traditional approaches are time consuming and expensive, highlighting the need for alternatives. This study tackles the challenge of utilizing laser-induced breakdown spectroscopy (LIBS) as a more economical method while managing its potential accuracy issues due to physical–chemical matrix effects. A set of 1,019 soil samples from 11 Brazilian farms was analyzed using various univariate and multivariate calibration strategies. The artificial neural network (ANN) demonstrated the best performance with the lowest root mean square error of prediction (RMSEP) of 0.48 wt% C, a 28% reduction compared to the following best calibration method (matrix-matching calibration – MMC inverse regression and multiple linear regression – MLR at 0.67 wt% C). Furthermore, the study revealed a strong correlation between total C determined by LIBS and the elemental CHNS analyzer for soils samples in nine farms (R² ≥ 0.73). The proposed method offers a reliable, rapid, and cost-efficient means of measuring total soil C content, showing that LIBS and ANN modeling can significantly reduce errors compared to other calibration methods. This research fills the knowledge gap in utilizing LIBS for soil C measurement in agriculture, potentially benefiting producers and the soil C credit market. Specific recommendations include further exploration of ANN modeling for broader applications, ensuring that agricultural soil management becomes more accessible and efficient.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139605415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-17DOI: 10.3389/fsoil.2023.1290591
Lorenzo De Carlo, A. C. Turturro, M. C. Caputo
In agriculture, accurate hydrological information is crucial to infer water requirements for hydrological modeling, as well as for appropriate water management.To achieve this purpose, geophysical frequency domain electromagnetic induction (FDEM) measurements are increasingly used for integration with traditional point-scale measurements to provide effective soil moisture estimations over large areas. The conversion of electromagnetic properties to soil moisture requires specific tools that must take into account the spatial variability of the two measurements and the data and model uncertainties. In a vineyard of about 4.5 ha located in Southern Italy, we tested an innovative assessment approach that uses a freeware code licensed from USGS, MoisturEC, to integrate electromagnetic data, collected with a CMD Mini-Explorer electromagnetic sensor, and point-scale soil moisture data.About 30,000 data measurements of apparent electrical conductivity (sa) allowed us to build a 3D inverted electromagnetic model obtained via an inversion process. Soil properties at different depths were inferred from the FDEM model and confirmed through the ground truth sampling.The data analysis tool allowed a more accurate estimation of the moisture distribution of the investigated area by combining the accuracy of the point-scale soil moisture measurements and the spatial coverage of the electrical conductivity (EC) data. The results confirmed the capability of the electromagnetic data to accurately map the moisture content of agricultural soils and, at the same time, the need to employ integrated analysis tools able to update such quantitative estimations in order to optimize soil and water management.
{"title":"Assessing soil moisture variability in a vineyard via frequency domain electromagnetic induction data","authors":"Lorenzo De Carlo, A. C. Turturro, M. C. Caputo","doi":"10.3389/fsoil.2023.1290591","DOIUrl":"https://doi.org/10.3389/fsoil.2023.1290591","url":null,"abstract":"In agriculture, accurate hydrological information is crucial to infer water requirements for hydrological modeling, as well as for appropriate water management.To achieve this purpose, geophysical frequency domain electromagnetic induction (FDEM) measurements are increasingly used for integration with traditional point-scale measurements to provide effective soil moisture estimations over large areas. The conversion of electromagnetic properties to soil moisture requires specific tools that must take into account the spatial variability of the two measurements and the data and model uncertainties. In a vineyard of about 4.5 ha located in Southern Italy, we tested an innovative assessment approach that uses a freeware code licensed from USGS, MoisturEC, to integrate electromagnetic data, collected with a CMD Mini-Explorer electromagnetic sensor, and point-scale soil moisture data.About 30,000 data measurements of apparent electrical conductivity (sa) allowed us to build a 3D inverted electromagnetic model obtained via an inversion process. Soil properties at different depths were inferred from the FDEM model and confirmed through the ground truth sampling.The data analysis tool allowed a more accurate estimation of the moisture distribution of the investigated area by combining the accuracy of the point-scale soil moisture measurements and the spatial coverage of the electrical conductivity (EC) data. The results confirmed the capability of the electromagnetic data to accurately map the moisture content of agricultural soils and, at the same time, the need to employ integrated analysis tools able to update such quantitative estimations in order to optimize soil and water management.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139617286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-18DOI: 10.3389/fsoil.2023.1268037
Eloise Mason, Antonio Bispo, Mireille Matt, Katharina Helming, Elena Rodriguez, Rocio Lansac, Violeta Carrasco, Mohammad Rafiul Hashar, Loes Verdonk, Gundula Prokop, David Wall, Nancy Francis, Peter Laszlo, Michael Löbmann
Healthy soil is vital for our wellbeing and wealth. However, increasing demand for food and biomass may lead to unsustainable soil and land management practices that threaten soils. Other degradation processes such as soil sealing also endanger soil resources. Identifying and accessing the best available knowledge is crucial to address related sustainability issues and promote the needed transition towards sustainable soil and land management practices. Such knowledge has to cover all knowledge domains, system knowledge, target knowledge, and transformation knowledge. However, a comprehensive overview of existing research addressing societal needs related to soil is still missing, which hinders the identification of knowledge gaps. This study provides a detailed analysis of scientific literature to identify ongoing research activities and trends. A quantitative and qualitative analysis of scientific literature related to sustainable soil and land management was conducted. A systems-oriented analytical framework was used that combines soil and land related societal challenges with related knowledge domains. Our analysis revealed a significant increase in scientific publications and related interest in soil and land use-related research, above the average increase of publications within all scientific fields. Different forms of reduction and remediation of soil degradation processes (e.g. erosion, contamination) have been studied most extensively. Other topic areas like land take mitigation, soil biodiversity increase, increase of ecosystem services provision and climate change mitigation and adaption seem to be rather recent concerns, less investigated. We could highlight the importance of context-specific research, as different regions require different practices. For instance, boreal, tropical, karst and peatland regions were less studied. Furthermore, we found that diversifying soil management practices such as agroforestry or including livestock into arable systems are valuable options for increasing biomass, mitigating/adapting to climate change, and improving soil related ecosystem services. A recent trend towards the latter research topic indicates the transition from a soil conservation-oriented perspective to a soil service-oriented perspective, which may be better suited to integrate the social and economic dimensions of soil health improvement alongside the ecological dimension.
{"title":"Sustainable soil and land management: a systems-oriented overview of scientific literature","authors":"Eloise Mason, Antonio Bispo, Mireille Matt, Katharina Helming, Elena Rodriguez, Rocio Lansac, Violeta Carrasco, Mohammad Rafiul Hashar, Loes Verdonk, Gundula Prokop, David Wall, Nancy Francis, Peter Laszlo, Michael Löbmann","doi":"10.3389/fsoil.2023.1268037","DOIUrl":"https://doi.org/10.3389/fsoil.2023.1268037","url":null,"abstract":"Healthy soil is vital for our wellbeing and wealth. However, increasing demand for food and biomass may lead to unsustainable soil and land management practices that threaten soils. Other degradation processes such as soil sealing also endanger soil resources. Identifying and accessing the best available knowledge is crucial to address related sustainability issues and promote the needed transition towards sustainable soil and land management practices. Such knowledge has to cover all knowledge domains, system knowledge, target knowledge, and transformation knowledge. However, a comprehensive overview of existing research addressing societal needs related to soil is still missing, which hinders the identification of knowledge gaps. This study provides a detailed analysis of scientific literature to identify ongoing research activities and trends. A quantitative and qualitative analysis of scientific literature related to sustainable soil and land management was conducted. A systems-oriented analytical framework was used that combines soil and land related societal challenges with related knowledge domains. Our analysis revealed a significant increase in scientific publications and related interest in soil and land use-related research, above the average increase of publications within all scientific fields. Different forms of reduction and remediation of soil degradation processes (e.g. erosion, contamination) have been studied most extensively. Other topic areas like land take mitigation, soil biodiversity increase, increase of ecosystem services provision and climate change mitigation and adaption seem to be rather recent concerns, less investigated. We could highlight the importance of context-specific research, as different regions require different practices. For instance, boreal, tropical, karst and peatland regions were less studied. Furthermore, we found that diversifying soil management practices such as agroforestry or including livestock into arable systems are valuable options for increasing biomass, mitigating/adapting to climate change, and improving soil related ecosystem services. A recent trend towards the latter research topic indicates the transition from a soil conservation-oriented perspective to a soil service-oriented perspective, which may be better suited to integrate the social and economic dimensions of soil health improvement alongside the ecological dimension.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139175416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.3389/fsoil.2023.1305105
Raphaël Deragon, Brandon Heung, Nicholas Lefebvre, Kingsley John, A. Cambouris, Jean Caron
The increased adoption of proximal sensors has helped to generate peat mapping products: they gather data quickly and can detect the peat-mineral later boundary. A third layer, made of sedimentary peat (limnic layers, gyttja), can sometimes be found in between them. This material is highly variable spatially and is associated with degraded soil properties when located near the surface.This study aimed to assess the potential of direct current resistivity measurements to predict the maximum peat thickness (MPT), defined as the non-limnic peat thickness, to facilitate soil conservation and management practices at the field-scale. The results were also compared to a regional map of the MPT from a previous study used and also tested as a covariate. This study was conducted in a shallow (MPT = 8-138 cm) cultivated organic soil from Québec, Canada. The MPT was mapped using the apparent electrical conductivity (ECa) from a Veris Q2800, and a digital elevation model, with and without a regional MPT map (RM) as a covariate to downscale it. Three machine-learning algorithms (Cubist, Random Forest, and Support Vector Regression) were compared to ordinary kriging (OK), multiple linear regression, and multiple linear regression kriging (MLRK) models.The best predictive performance was achieved with OK (Lin’s CCC = 0.89, RMSE = 13.75 cm), followed by MLRK-RM (CCC = 0.85, RMSE = 15.7 cm). All models were more accurate than the RM (CCC = 0.65, RMSE = 29.85 cm), although they underpredicted MPT > 100 cm. Moreover, the addition of the RM as a covariate led to a lower prediction error and higher accuracy for all models. Overall, a field-scale approach could better support precision soil conservation interventions by generating more accurate management zones. Future studies should test multi-sensor fusion and other geophysical sensors to further improve the model performance and detect deeper boundaries.
{"title":"Improving a regional peat thickness map using soil apparent electrical conductivity measurements at the field-scale","authors":"Raphaël Deragon, Brandon Heung, Nicholas Lefebvre, Kingsley John, A. Cambouris, Jean Caron","doi":"10.3389/fsoil.2023.1305105","DOIUrl":"https://doi.org/10.3389/fsoil.2023.1305105","url":null,"abstract":"The increased adoption of proximal sensors has helped to generate peat mapping products: they gather data quickly and can detect the peat-mineral later boundary. A third layer, made of sedimentary peat (limnic layers, gyttja), can sometimes be found in between them. This material is highly variable spatially and is associated with degraded soil properties when located near the surface.This study aimed to assess the potential of direct current resistivity measurements to predict the maximum peat thickness (MPT), defined as the non-limnic peat thickness, to facilitate soil conservation and management practices at the field-scale. The results were also compared to a regional map of the MPT from a previous study used and also tested as a covariate. This study was conducted in a shallow (MPT = 8-138 cm) cultivated organic soil from Québec, Canada. The MPT was mapped using the apparent electrical conductivity (ECa) from a Veris Q2800, and a digital elevation model, with and without a regional MPT map (RM) as a covariate to downscale it. Three machine-learning algorithms (Cubist, Random Forest, and Support Vector Regression) were compared to ordinary kriging (OK), multiple linear regression, and multiple linear regression kriging (MLRK) models.The best predictive performance was achieved with OK (Lin’s CCC = 0.89, RMSE = 13.75 cm), followed by MLRK-RM (CCC = 0.85, RMSE = 15.7 cm). All models were more accurate than the RM (CCC = 0.65, RMSE = 29.85 cm), although they underpredicted MPT > 100 cm. Moreover, the addition of the RM as a covariate led to a lower prediction error and higher accuracy for all models. Overall, a field-scale approach could better support precision soil conservation interventions by generating more accurate management zones. Future studies should test multi-sensor fusion and other geophysical sensors to further improve the model performance and detect deeper boundaries.","PeriodicalId":73107,"journal":{"name":"Frontiers in soil science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138625268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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