Pub Date : 2024-01-29DOI: 10.5194/egusphere-2024-170
Daniel Rasche, Theresa Blume, Andreas Güntner
Abstract. Soil moisture measurements at the field scale are highly beneficial for different hydrological applications including the validation of space-borne soil moisture products, landscape water budgeting or multi-criteria calibration of rainfall-runoff models from field to catchment scale. Many of these applications require information on soil water dynamics in deeper soil layers. Cosmic-ray neutron sensing (CRNS) allows for non-invasive monitoring of field-scale soil moisture across several hectares around the instrument but only for the first few tens of centimeters of the soil. Simple depth-extrapolation approaches often used in remote sensing applications may be used to estimate soil moisture in deeper layers based on the near-surface soil moisture information. However, most approaches require a site-specific calibration using depth-profiles of in-situ soil moisture data, which are often not available. The physically-based soil moisture analytical relationship SMAR is usually also calibrated to sensor data, but could be applied without calibration if all its parameters were known. However, in particular its water loss parameter is difficult to estimate. In this paper, we introduce and test a simple modification of the SMAR model to estimate the water loss in the second layer based on soil physical parameters and the surface soil moisture time series. We apply the model at a forest site with sandy soils with and without calibration. Comparing the model results against in-situ reference measurements down to depths of 450 cm shows that the SMAR models both with and without modification do not capture the observed soil moisture dynamics well. The performance of the SMAR models nevertheless meets a previously used benchmark RMSE of ≤ 0.06 cm3 cm−3 in both, calibrated and uncalibrated scenarios. Only with effective parameters in a non-physical range, a better model performance could be achieved. Different transfer functions to derive surface soil moisture from CRNS do not translate into markedly different results of the depth-extrapolated soil moisture time series simulated with SMAR. However, a more accurate estimation of the sensitive measurement depth of the CRNS improved the soil moisture estimates in the second layer. Despite the fact that the soil moisture dynamics are not well represented at our study site using physically reasonable parameters, the modified SMAR model may provide valuable first estimates of soil moisture in a deeper soil layer derived from surface measurements based on stationary and roving CRNS as well as remote sensing products where in-situ data for calibration are not available.
{"title":"Depth-extrapolation of field-scale soil moisture time series derived with cosmic-ray neutron sensing using the SMAR model","authors":"Daniel Rasche, Theresa Blume, Andreas Güntner","doi":"10.5194/egusphere-2024-170","DOIUrl":"https://doi.org/10.5194/egusphere-2024-170","url":null,"abstract":"<strong>Abstract.</strong> Soil moisture measurements at the field scale are highly beneficial for different hydrological applications including the validation of space-borne soil moisture products, landscape water budgeting or multi-criteria calibration of rainfall-runoff models from field to catchment scale. Many of these applications require information on soil water dynamics in deeper soil layers. Cosmic-ray neutron sensing (CRNS) allows for non-invasive monitoring of field-scale soil moisture across several hectares around the instrument but only for the first few tens of centimeters of the soil. Simple depth-extrapolation approaches often used in remote sensing applications may be used to estimate soil moisture in deeper layers based on the near-surface soil moisture information. However, most approaches require a site-specific calibration using depth-profiles of in-situ soil moisture data, which are often not available. The physically-based soil moisture analytical relationship SMAR is usually also calibrated to sensor data, but could be applied without calibration if all its parameters were known. However, in particular its water loss parameter is difficult to estimate. In this paper, we introduce and test a simple modification of the SMAR model to estimate the water loss in the second layer based on soil physical parameters and the surface soil moisture time series. We apply the model at a forest site with sandy soils with and without calibration. Comparing the model results against in-situ reference measurements down to depths of 450 cm shows that the SMAR models both with and without modification do not capture the observed soil moisture dynamics well. The performance of the SMAR models nevertheless meets a previously used benchmark RMSE of ≤ 0.06 cm<sup>3</sup> cm<sup>−3</sup> in both, calibrated and uncalibrated scenarios. Only with effective parameters in a non-physical range, a better model performance could be achieved. Different transfer functions to derive surface soil moisture from CRNS do not translate into markedly different results of the depth-extrapolated soil moisture time series simulated with SMAR. However, a more accurate estimation of the sensitive measurement depth of the CRNS improved the soil moisture estimates in the second layer. Despite the fact that the soil moisture dynamics are not well represented at our study site using physically reasonable parameters, the modified SMAR model may provide valuable first estimates of soil moisture in a deeper soil layer derived from surface measurements based on stationary and roving CRNS as well as remote sensing products where in-situ data for calibration are not available.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"165 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139573978","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 : 2024-01-22DOI: 10.5194/egusphere-2023-3016
Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, Raphael Viscarra Rossel
Abstract. Spatially explicit prediction of soil organic carbon (SOC) serves as a crucial foundation for effective land management strategies aimed at mitigating soil degradation and assessing carbon sequestration potential. Here, using more than 1000 in-situ observations, we trained two machine learning models (random forest, and K-means coupled with multiple linear regression), and one process-based model (the vertically resolved MIcrobial-MIneral Carbon Stabilization (MIMICS)) to predict SOC content of the top 30 cm of soil in Australia. Parameters of MIMICS were optimized for different site groupings, using two distinct approaches, plant functional types (MIMICS-PFT), and the most influential environmental factors (MIMICS-ENV). We found that at the continental scale, soil bulk density and mean annual temperature are the dominant controls of SOC variation, and that dominant controls vary for different vegetation types. All models showed good performance in SOC predictions with R2 greater than 0.8 during out-of-sample validation with random forest being the most accurate, and SOC in forests is more predictable than that in non-forest soils. Parameter optimization approaches made a notable difference in the performance of MIMICS SOC prediction with MIMICS-ENV performing better than MIMICS-PFT especially in non-forest soils. Digital maps of terrestrial SOC stocks generated using all the models showed similar spatial distribution with higher values in southeast and southwest Australia, but the magnitude of estimated SOC stocks varied. The mean ensemble estimate of SOC stocks was 30.08 t/ha with K-means coupled with multiple linear regression generating the highest estimate (mean SOC stocks at 38.15 t/ha) and MIMICS-PFT generating the lowest estimate (mean SOC stocks at 24.29 t/ha). We suggest that enhancing process-based models to incorporate newly identified drivers that significantly influence SOC variations in different environments could be key to reducing the discrepancies in these estimates. Our findings underscore the considerable uncertainty in SOC estimates derived from different modelling approaches and emphasize the importance of rigorous out-of-sample validation before applying any one approach in Australia.
{"title":"An ensemble estimate of Australian soil organic carbon using machine learning and process-based modelling","authors":"Lingfei Wang, Gab Abramowitz, Ying-Ping Wang, Andy Pitman, Raphael Viscarra Rossel","doi":"10.5194/egusphere-2023-3016","DOIUrl":"https://doi.org/10.5194/egusphere-2023-3016","url":null,"abstract":"<strong>Abstract.</strong> Spatially explicit prediction of soil organic carbon (SOC) serves as a crucial foundation for effective land management strategies aimed at mitigating soil degradation and assessing carbon sequestration potential. Here, using more than 1000 in-situ observations, we trained two machine learning models (random forest, and K-means coupled with multiple linear regression), and one process-based model (the vertically resolved MIcrobial-MIneral Carbon Stabilization (MIMICS)) to predict SOC content of the top 30 cm of soil in Australia. Parameters of MIMICS were optimized for different site groupings, using two distinct approaches, plant functional types (MIMICS-PFT), and the most influential environmental factors (MIMICS-ENV). We found that at the continental scale, soil bulk density and mean annual temperature are the dominant controls of SOC variation, and that dominant controls vary for different vegetation types. All models showed good performance in SOC predictions with R<sup>2</sup> greater than 0.8 during out-of-sample validation with random forest being the most accurate, and SOC in forests is more predictable than that in non-forest soils. Parameter optimization approaches made a notable difference in the performance of MIMICS SOC prediction with MIMICS-ENV performing better than MIMICS-PFT especially in non-forest soils. Digital maps of terrestrial SOC stocks generated using all the models showed similar spatial distribution with higher values in southeast and southwest Australia, but the magnitude of estimated SOC stocks varied. The mean ensemble estimate of SOC stocks was 30.08 t/ha with K-means coupled with multiple linear regression generating the highest estimate (mean SOC stocks at 38.15 t/ha) and MIMICS-PFT generating the lowest estimate (mean SOC stocks at 24.29 t/ha). We suggest that enhancing process-based models to incorporate newly identified drivers that significantly influence SOC variations in different environments could be key to reducing the discrepancies in these estimates. Our findings underscore the considerable uncertainty in SOC estimates derived from different modelling approaches and emphasize the importance of rigorous out-of-sample validation before applying any one approach in Australia.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"11 8 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139510841","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. Soil erosion, considered a major environmental and social problem, leads to the loss of soil nutrients and the degradation of soil structure and impacts plant growth. However, data on the effects of land use changes caused by vegetation restoration on soil nutrients and erodibility for different slope aspects are limited. This study was conducted to detect the response of soil nutrients and erodibility to slope aspect in a typical watershed in the northern agro-pastoral ecotone in China. The following indexes were used to determine the improvement in soil nutrients and erodibility through a weighted summation method: the comprehensive soil nutrient index and the comprehensive soil erodibility index. The results showed that the vegetation types with the highest comprehensive soil quality index (CSQI) values on western, northern, southern, and eastern slopes were Pinus sylvestris and Astragalus melilotoides (1.45), Caragana korshinskii and Capillipedium parviflorum (2.35), Astragalus melilotoides (4.78), and Caragana korshinskii and Lespedeza bicolor (5.00), respectively. Slope aspect had a significant effect on understory vegetation characteristics, soil nutrients, and soil erodibility. Understory vegetation and soil characteristics explained 50.86 %–74.56 % of the total variance in soil nutrients and the erodibility. Mean weight diameter and total phosphorus were the main factors that affected the CSQI for different slope aspects. Our study suggests that the combinations of species, such as C. korshinskii and L. bicolor, were the optimal selection to improve soil nutrients and soil erodibility for any slope aspect.
摘要水土流失被认为是一个重大的环境和社会问题，它会导致土壤养分流失、土壤结构退化并影响植物生长。然而，关于植被恢复引起的土地利用变化对不同坡度土壤养分和侵蚀性影响的数据却很有限。本研究以中国北方农牧生态区典型流域为研究对象，探讨土壤养分和侵蚀性对坡度的响应。通过加权求和法确定了土壤养分和侵蚀性的改善指数：土壤养分综合指数和土壤侵蚀性综合指数。结果表明，西坡、北坡、南坡和东坡上土壤综合质量指数（CSQI）值最高的植被类型分别是欧洲赤松和黄芪（1.45）、高山乌骨鸡和毛蕊花（2.35）、黄芪（4.78）和高山乌骨鸡和双色芒（5.00）。坡度对林下植被特征、土壤养分和土壤侵蚀性有显著影响。林下植被和土壤特性解释了土壤养分和侵蚀性总方差的 50.86 %-74.56 %。平均重量直径和总磷是影响不同坡向 CSQI 的主要因素。我们的研究表明，对于任何坡度，树种组合（如 C. korshinskii 和 L. bicolor）都是改善土壤养分和土壤侵蚀性的最佳选择。
{"title":"Response of soil nutrients and erodibility to slope aspect in the northern agro-pastoral ecotone, China","authors":"Yuxin Wu, Guodong Jia, Xinxiao Yu, Honghong Rao, Xiuwen Peng, Yusong Wang, Yushi Wang, Xu Wang","doi":"10.5194/soil-10-61-2024","DOIUrl":"https://doi.org/10.5194/soil-10-61-2024","url":null,"abstract":"Abstract. Soil erosion, considered a major environmental and social problem, leads to the loss of soil nutrients and the degradation of soil structure and impacts plant growth. However, data on the effects of land use changes caused by vegetation restoration on soil nutrients and erodibility for different slope aspects are limited. This study was conducted to detect the response of soil nutrients and erodibility to slope aspect in a typical watershed in the northern agro-pastoral ecotone in China. The following indexes were used to determine the improvement in soil nutrients and erodibility through a weighted summation method: the comprehensive soil nutrient index and the comprehensive soil erodibility index. The results showed that the vegetation types with the highest comprehensive soil quality index (CSQI) values on western, northern, southern, and eastern slopes were Pinus sylvestris and Astragalus melilotoides (1.45), Caragana korshinskii and Capillipedium parviflorum (2.35), Astragalus melilotoides (4.78), and Caragana korshinskii and Lespedeza bicolor (5.00), respectively. Slope aspect had a significant effect on understory vegetation characteristics, soil nutrients, and soil erodibility. Understory vegetation and soil characteristics explained 50.86 %–74.56 % of the total variance in soil nutrients and the erodibility. Mean weight diameter and total phosphorus were the main factors that affected the CSQI for different slope aspects. Our study suggests that the combinations of species, such as C. korshinskii and L. bicolor, were the optimal selection to improve soil nutrients and soil erodibility for any slope aspect.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"25 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139480686","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. Long-term excessive application of mineral fertilizer leads to phosphorus (P) accumulation, increasing the risk of P migration and loss from the soil profile. The colloids in the soil profile are important carriers for P migration due to their high P adsorption and transport capacity. It is not clearly understood how colloidal P (CP) is distributed in subsoils (<1.2 m) of a Vertisol, contributing to subsurface P loss. Understanding the depth sequence distribution and speciation of colloidal P in the soil profile is critical for a comprehensive assessment of P loss. In this study, water-extractable colloids (WECs) with the size of 0.35–2 µm were obtained from a 0–120 cm soil profile by a sedimentation and centrifugation scheme. The dissolved reactive P (DRP) and dissolved total P (DTP) in soil supernatant with particle sizes <0.35 µm were measured by molybdate blue colorimetry. Solution 31P nuclear magnetic resonance (NMR) and P K-edge XANES (X-ray absorption near-edge structure) were used to characterize the species and distribution of CP in the soil profile of fertilized farmland. Total and available P in bulk soil and colloids decreased with soil depth. The organic P (OP) contained 97–344 mg kg−1 per bulk soil and 110–630 mg kg−1 per WEC. The OP in soil profile consists of orthophosphate mono-esters and diesters primarily according to NMR results. It suggested that OP in WECs from subsoils might be affected by the translocation of CP from surface soils, probably due to soil acidification and preferential flow caused by swelling–shrinkage clays, including montmorillonite and nontronite detected by X-ray powder diffractometer (XRD) results. Additionally, the more negative zeta potential of surface soil colloids suggests the high mobility of colloidal P towards the subsoils. The CP concentration for <2 µm was about 38–93 mg P kg−1 per bulk soil, which is 6–37 times that of DRP, suggesting that CP plays a dominant role in P transport within the soil profile. The relatively small fraction of orthophosphate diesters suggests limited P assimilation by microorganisms for the accumulation of WECs containing organically bound P in subsoils. The P K-edge XANES results indicated that the proportions of Al-P, Fe-P, and inositol hexakisphosphate (IHP) of WECs decreased, but hydroxyapatite (HAP) increased with soil depth. This study showed that inorganic and organic P migrated from the surface to deeper layers along the soil profile, with soil colloids having a significant effect on P migration from both surface and subsurface layers. The findings have an important significance for soil P migration evaluation and agricultural non-point source pollution control in Vertisols.
摘要。长期过量施用矿物肥料会导致磷（P）积累，增加土壤剖面中磷迁移和流失的风险。土壤剖面中的胶体具有很强的磷吸附和迁移能力，是磷迁移的重要载体。目前尚不清楚胶体磷（CP）如何在惰性土壤的底土（<1.2 米）中分布，从而导致地表下的钾流失。了解土壤剖面中胶体磷的深度顺序分布和种类对于全面评估钾流失至关重要。本研究采用沉淀和离心方法，从 0-120 厘米的土壤剖面中获得了粒径为 0.35-2 微米的水提取胶体（WECs）。通过钼酸蓝比色法测量了粒径小于 0.35 µm 的土壤上清液中的溶解活性 P（DRP）和溶解总 P（DTP）。利用溶液 31P 核磁共振 (NMR) 和 P K 边 XANES（X 射线吸收近边结构）来表征施肥农田土壤剖面中 CP 的种类和分布。块状土壤和胶体中的总磷和可利用磷随土壤深度的增加而减少。有机钾（OP）含量为每块土壤 97-344 毫克/千克-1，每块 WEC 110-630 毫克/千克-1。核磁共振结果表明，土壤剖面中的有机磷主要由正磷酸盐单酯和二酯组成。X 射线粉末衍射仪（XRD）结果表明，底层土壤 WEC 中的 OP 可能受到表层土壤中 CP 迁移的影响，这可能是由于土壤酸化和膨胀收缩粘土（包括蒙脱石和褐铁矿）造成的优先流动。此外，表层土壤胶体的 zeta 电位较负，表明胶体 P 对底土的流动性较高。小于 2 µm 的 CP 浓度约为 38-93 mg P kg-1，是 DRP 浓度的 6-37 倍，这表明 CP 在土壤剖面内的钾迁移中起着主导作用。正磷酸盐二酯的比例相对较小，这表明微生物对含有机结合态 P 的 WECs 在底土中的积累所进行的 P 同化作用有限。P K-edge XANES 结果表明，随着土壤深度的增加，WECs 中 Al-P、Fe-P 和肌醇六磷酸（IHP）的比例降低，但羟基磷灰石（HAP）的比例增加。该研究表明，无机钾和有机钾沿着土壤剖面从表层向深层迁移，土壤胶体对钾从表层和地下层的迁移有显著影响。该研究结果对于沃土中土壤钾迁移评估和农业非点源污染控制具有重要意义。
{"title":"Intensive agricultural management-induced subsurface accumulation of water-extractable colloidal P in a Vertisol","authors":"Shouhao Li, Shuiqing Chen, Shanshan Bai, Jinfang Tan, Xiaoqian Jiang","doi":"10.5194/soil-10-49-2024","DOIUrl":"https://doi.org/10.5194/soil-10-49-2024","url":null,"abstract":"Abstract. Long-term excessive application of mineral fertilizer leads to phosphorus (P) accumulation, increasing the risk of P migration and loss from the soil profile. The colloids in the soil profile are important carriers for P migration due to their high P adsorption and transport capacity. It is not clearly understood how colloidal P (CP) is distributed in subsoils (<1.2 m) of a Vertisol, contributing to subsurface P loss. Understanding the depth sequence distribution and speciation of colloidal P in the soil profile is critical for a comprehensive assessment of P loss. In this study, water-extractable colloids (WECs) with the size of 0.35–2 µm were obtained from a 0–120 cm soil profile by a sedimentation and centrifugation scheme. The dissolved reactive P (DRP) and dissolved total P (DTP) in soil supernatant with particle sizes <0.35 µm were measured by molybdate blue colorimetry. Solution 31P nuclear magnetic resonance (NMR) and P K-edge XANES (X-ray absorption near-edge structure) were used to characterize the species and distribution of CP in the soil profile of fertilized farmland. Total and available P in bulk soil and colloids decreased with soil depth. The organic P (OP) contained 97–344 mg kg−1 per bulk soil and 110–630 mg kg−1 per WEC. The OP in soil profile consists of orthophosphate mono-esters and diesters primarily according to NMR results. It suggested that OP in WECs from subsoils might be affected by the translocation of CP from surface soils, probably due to soil acidification and preferential flow caused by swelling–shrinkage clays, including montmorillonite and nontronite detected by X-ray powder diffractometer (XRD) results. Additionally, the more negative zeta potential of surface soil colloids suggests the high mobility of colloidal P towards the subsoils. The CP concentration for <2 µm was about 38–93 mg P kg−1 per bulk soil, which is 6–37 times that of DRP, suggesting that CP plays a dominant role in P transport within the soil profile. The relatively small fraction of orthophosphate diesters suggests limited P assimilation by microorganisms for the accumulation of WECs containing organically bound P in subsoils. The P K-edge XANES results indicated that the proportions of Al-P, Fe-P, and inositol hexakisphosphate (IHP) of WECs decreased, but hydroxyapatite (HAP) increased with soil depth. This study showed that inorganic and organic P migrated from the surface to deeper layers along the soil profile, with soil colloids having a significant effect on P migration from both surface and subsurface layers. The findings have an important significance for soil P migration evaluation and agricultural non-point source pollution control in Vertisols.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"56 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139474275","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}
Gina Garland, John Koestel, Alice Johannes, Olivier Heller, Sebastian Doetterl, Dani Or, Thomas Keller
Abstract. Soil aggregation is an important process in nearly all soils across the globe. Aggregates develop over time through a series of abiotic and biotic processes and interactions, including plant growth and decay, microbial activity, plant and microbial exudation, bioturbation, and physicochemical stabilization processes, and are greatly influenced by soil management practices. Together, and through feedback with organic matter and primary soil particles, these processes form dynamic soil aggregates and pore spaces, which jointly constitute a soil's structure and contribute to overall soil functioning. Nevertheless, the concept of soil aggregates is hotly debated, leading to confusion about their function or relevancy to soil processes. We argue here that the opposition to the concept of soil aggregation likely stems from the fact that the methods for the characterization of soil aggregates have largely been developed in the context of arable soils, where tillage promotes the formation of distinct soil aggregates that are easily visible in the topsoil. We propose that the widespread use of conceptual figures showing detached and isolated aggregates can be misleading and has contributed to the skepticism towards soil aggregates. However, the fact that we do not always see discrete aggregates within soils in situ does not mean that aggregates do not exist or are not relevant to the study of soil processes. Given that, by definition, soil aggregates consist of any group of soil particles that cohere more strongly to each other than neighboring particles, aggregates may, but do not necessarily need to be, bordered by pore space. Here, we illustrate how aggregates can form and dissipate within the context of undisturbed, intact soils, highlighting the point that aggregates do not necessarily need to have a discrete physical boundary and can exist seamlessly embedded in the soil. We hope that our contribution helps the debate on soil aggregates and supports the foundation of a shared understanding on the characterization and function of soil structure.
{"title":"Perspectives on the misconception of levitating soil aggregates","authors":"Gina Garland, John Koestel, Alice Johannes, Olivier Heller, Sebastian Doetterl, Dani Or, Thomas Keller","doi":"10.5194/soil-10-23-2024","DOIUrl":"https://doi.org/10.5194/soil-10-23-2024","url":null,"abstract":"Abstract. Soil aggregation is an important process in nearly all soils across the globe. Aggregates develop over time through a series of abiotic and biotic processes and interactions, including plant growth and decay, microbial activity, plant and microbial exudation, bioturbation, and physicochemical stabilization processes, and are greatly influenced by soil management practices. Together, and through feedback with organic matter and primary soil particles, these processes form dynamic soil aggregates and pore spaces, which jointly constitute a soil's structure and contribute to overall soil functioning. Nevertheless, the concept of soil aggregates is hotly debated, leading to confusion about their function or relevancy to soil processes. We argue here that the opposition to the concept of soil aggregation likely stems from the fact that the methods for the characterization of soil aggregates have largely been developed in the context of arable soils, where tillage promotes the formation of distinct soil aggregates that are easily visible in the topsoil. We propose that the widespread use of conceptual figures showing detached and isolated aggregates can be misleading and has contributed to the skepticism towards soil aggregates. However, the fact that we do not always see discrete aggregates within soils in situ does not mean that aggregates do not exist or are not relevant to the study of soil processes. Given that, by definition, soil aggregates consist of any group of soil particles that cohere more strongly to each other than neighboring particles, aggregates may, but do not necessarily need to be, bordered by pore space. Here, we illustrate how aggregates can form and dissipate within the context of undisturbed, intact soils, highlighting the point that aggregates do not necessarily need to have a discrete physical boundary and can exist seamlessly embedded in the soil. We hope that our contribution helps the debate on soil aggregates and supports the foundation of a shared understanding on the characterization and function of soil structure.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"43 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139474194","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. Ameliorating soil acidity using a combination of lime and organic amendments (OAs) can be an alternative to lime alone, but determining the appropriate OA rates can be difficult. We developed a new method for calculating the combined application rate of lime and OAs (wheat straw, faba bean straw, blended poultry litter, biochar, and compost) that is based on the titratable alkalinity of OAs and the equilibrium lime buffer capacity (LBCeq) of acidic soils. The effect of calculated soil amendment rates on soil pH was validated at soil water contents of 60 %, 100 %, and 150 % of field capacity (FC). The soil used to develop and validate the method was a sandy loam with a soil pH in deionised water (pHW) of 4.84 and a soil pH in 0.01 M CaCl2 solution (pHCa) of 4.21. The LBCeq of the soil was 1657 mg CaCO3 kg−1 pH−1 (where “CaCO3 kg−1 pH−1” denotes the amount of lime required to raise the pH of 1 kg of soil by one unit). The titratable alkalinity of the OAs ranged from 11.7 cmol Heq+ kg−1 for wheat straw to 357 cmol Heq+ kg−1 for compost. At 60 % FC, faba bean and wheat straw amendment increased the soil pHW to 6.48 and 6.42, respectively, but lower pH values were reached in soil amended with less biodegradable or resistant OAs (ROAs) (i.e. blended poultry litter, biochar, and compost). At 150 % FC, the two straws increased the soil pHW to only 5.93 and 5.75, respectively, possibly due to slower decomposition under submerged conditions, resulting in limited alkalinity production, whereas amendment with ROAs produced pHW values close to 6.5. With an increasing lime-equivalent value (LEV) of the OA, from 5.8 g CaCO3 kg−1 (wheat straw) to 179 g CaCO3 kg−1 (compost), the lime requirement to reach pHW 6.5 in lime–OA combinations decreased from 2.72 to 0.09 g CaCO3 kg−1. The developed method was shown to be effective in determining the appropriate rates of OAs (with or without additional lime) for the management of acidic sandy loam soils in this study and highlights the importance of the soil water content with respect to its acid-neutralising effect.
摘要。使用石灰和有机改良剂（OA）的组合来改善土壤酸度可以替代单独使用石灰，但确定适当的 OA 施用量可能比较困难。我们开发了一种新方法来计算石灰和有机添加剂（小麦秸秆、蚕豆秸秆、混合家禽粪便、生物炭和堆肥）的综合施用率，该方法基于有机添加剂的可滴定碱度和酸性土壤的平衡石灰缓冲能力（LBCeq）。在土壤含水量为田间容量（FC）的 60%、100% 和 150% 时，验证了计算出的土壤改良率对土壤 pH 值的影响。用于开发和验证该方法的土壤为砂壤土，去离子水中的土壤 pH 值（pHW）为 4.84，0.01 M CaCl2 溶液中的土壤 pH 值（pHCa）为 4.21。土壤的 LBCeq 为 1657 mg CaCO3 kg-1 pH-1（其中 "CaCO3 kg-1 pH-1 "表示将 1 kg 土壤的 pH 值提高一个单位所需的石灰量）。OA 的可滴定碱度从小麦秸秆的 11.7 cmol Heq+ kg-1 到堆肥的 357 cmol Heq+ kg-1 不等。在 60% FC 条件下，蚕豆和小麦秸秆改良剂分别将土壤 pHW 提高到 6.48 和 6.42，但生物降解性或抗性较低的 OA（即混合家禽粪便、生物炭和堆肥）改良土壤的 pH 值较低。在 FC 值为 150% 时，两种秸秆分别只将土壤 pHW 值提高到 5.93 和 5.75，这可能是由于在浸没条件下分解较慢，导致碱度产生有限，而使用 ROAs 改良土壤时，pHW 值接近 6.5。随着 OA 石灰当量（LEV）的增加，从 5.8 g CaCO3 kg-1（小麦秸秆）到 179 g CaCO3 kg-1（堆肥），石灰-OA 组合达到 pHW 6.5 所需的石灰从 2.72 g CaCO3 kg-1 降至 0.09 g CaCO3 kg-1。在这项研究中，所开发的方法被证明能有效确定治理酸性砂质壤土所需的适当的 OA（添加或不添加石灰）用量，并强调了土壤含水量对其酸性中和效果的重要性。
{"title":"Combining lime and organic amendments based on titratable alkalinity for efficient amelioration of acidic soils","authors":"Birhanu Iticha, Luke M. Mosley, Petra Marschner","doi":"10.5194/soil-10-33-2024","DOIUrl":"https://doi.org/10.5194/soil-10-33-2024","url":null,"abstract":"Abstract. Ameliorating soil acidity using a combination of lime and organic amendments (OAs) can be an alternative to lime alone, but determining the appropriate OA rates can be difficult. We developed a new method for calculating the combined application rate of lime and OAs (wheat straw, faba bean straw, blended poultry litter, biochar, and compost) that is based on the titratable alkalinity of OAs and the equilibrium lime buffer capacity (LBCeq) of acidic soils. The effect of calculated soil amendment rates on soil pH was validated at soil water contents of 60 %, 100 %, and 150 % of field capacity (FC). The soil used to develop and validate the method was a sandy loam with a soil pH in deionised water (pHW) of 4.84 and a soil pH in 0.01 M CaCl2 solution (pHCa) of 4.21. The LBCeq of the soil was 1657 mg CaCO3 kg−1 pH−1 (where “CaCO3 kg−1 pH−1” denotes the amount of lime required to raise the pH of 1 kg of soil by one unit). The titratable alkalinity of the OAs ranged from 11.7 cmol Heq+ kg−1 for wheat straw to 357 cmol Heq+ kg−1 for compost. At 60 % FC, faba bean and wheat straw amendment increased the soil pHW to 6.48 and 6.42, respectively, but lower pH values were reached in soil amended with less biodegradable or resistant OAs (ROAs) (i.e. blended poultry litter, biochar, and compost). At 150 % FC, the two straws increased the soil pHW to only 5.93 and 5.75, respectively, possibly due to slower decomposition under submerged conditions, resulting in limited alkalinity production, whereas amendment with ROAs produced pHW values close to 6.5. With an increasing lime-equivalent value (LEV) of the OA, from 5.8 g CaCO3 kg−1 (wheat straw) to 179 g CaCO3 kg−1 (compost), the lime requirement to reach pHW 6.5 in lime–OA combinations decreased from 2.72 to 0.09 g CaCO3 kg−1. The developed method was shown to be effective in determining the appropriate rates of OAs (with or without additional lime) for the management of acidic sandy loam soils in this study and highlights the importance of the soil water content with respect to its acid-neutralising effect.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"238 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139468565","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 : 2024-01-12DOI: 10.5194/egusphere-2023-3104
Brigitta Szabó, Piroska Kassai, Svajunas Plunge, Attila Nemes, Péter Braun, Michael Strauch, Felix Witing, János Mészáros, Natalja Čerkasova
Abstract. To effectively guide agricultural management planning strategies and policy, it is important to simulate water quantity and quality patterns and quantify the impact of land use and climate change on underlying processes. Environmental models that depict alterations in surface and groundwater quality and quantity at a catchment scale require substantial input, particularly concerning movement and retention in the unsaturated zone. Over the past few decades, numerous soil information sources, containing structured data on diverse basic and advanced soil parameters, alongside innovative solutions to estimate missing soil data, have become increasingly available. This study aims to: i) catalogue open-source soil datasets and pedotransfer functions (PTFs) applicable in simulation studies across European catchments, ii) evaluate the performance of selected PTFs and iii) present compiled R scripts proposing estimation solutions to address soil physical, hydraulic, and chemical soil data needs and gaps in catchment-scale environmental modelling in Europe. Our focus encompassed basic soil properties, bulk density, porosity, albedo, soil erodibility factor, field capacity, wilting point, available water capacity, saturated hydraulic conductivity, and phosphorus content. We aim to recommend widely supported data sources and pioneering prediction methods that maintain physical consistency, and present them through streamlined workflows.
摘要为有效指导农业管理规划战略和政策，必须模拟水量和水质模式，并量化土地利用和气候变化对基本过程的影响。在集水区范围内描述地表水和地下水水质和水量变化的环境模型需要大量输入，特别是有关非饱和带的移动和滞留的输入。在过去的几十年里，包含各种基本和高级土壤参数结构化数据的众多土壤信息源，以及估算缺失土壤数据的创新解决方案，已经越来越多。本研究旨在：i) 对适用于欧洲流域模拟研究的开源土壤数据集和土壤转移函数 (PTF) 进行编目；ii) 评估所选 PTF 的性能；iii) 提出 R 脚本汇编，提出估算解决方案，以解决欧洲流域尺度环境建模中的土壤物理、水力和化学数据需求和缺口。我们的重点包括基本土壤特性、容重、孔隙度、反照率、土壤侵蚀系数、田间容重、萎蔫点、可用水容量、饱和导水率和磷含量。我们的目标是推荐得到广泛支持的数据源和保持物理一致性的开创性预测方法，并通过简化的工作流程将其呈现出来。
{"title":"Addressing soil data needs and data-gaps in catchment scale environmental modelling: the European perspective","authors":"Brigitta Szabó, Piroska Kassai, Svajunas Plunge, Attila Nemes, Péter Braun, Michael Strauch, Felix Witing, János Mészáros, Natalja Čerkasova","doi":"10.5194/egusphere-2023-3104","DOIUrl":"https://doi.org/10.5194/egusphere-2023-3104","url":null,"abstract":"<strong>Abstract.</strong> To effectively guide agricultural management planning strategies and policy, it is important to simulate water quantity and quality patterns and quantify the impact of land use and climate change on underlying processes. Environmental models that depict alterations in surface and groundwater quality and quantity at a catchment scale require substantial input, particularly concerning movement and retention in the unsaturated zone. Over the past few decades, numerous soil information sources, containing structured data on diverse basic and advanced soil parameters, alongside innovative solutions to estimate missing soil data, have become increasingly available. This study aims to: i) catalogue open-source soil datasets and pedotransfer functions (PTFs) applicable in simulation studies across European catchments, ii) evaluate the performance of selected PTFs and iii) present compiled R scripts proposing estimation solutions to address soil physical, hydraulic, and chemical soil data needs and gaps in catchment-scale environmental modelling in Europe. Our focus encompassed basic soil properties, bulk density, porosity, albedo, soil erodibility factor, field capacity, wilting point, available water capacity, saturated hydraulic conductivity, and phosphorus content. We aim to recommend widely supported data sources and pioneering prediction methods that maintain physical consistency, and present them through streamlined workflows.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"17 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139431259","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. Silicon (Si) is a beneficial plant element that has been shown to mitigate the effects of potentially toxic elements (PTEs) on crops. Biochar is a soil amendment that sequesters soil carbon, and that can immobilize PTEs and enhance crop growth in soils. Considering these beneficial properties, it remains to be investigated how the simultaneous utilization of Si and biochars affects PTEs immobilization in soils. Therefore, the aim of this study was to examine the interaction effects of Si levels and biochars, to alleviate soil Ni bioavailability and its corresponding uptake in corn(Zea Mays) in a calcareous soil. A 90-day factorial greenhouse study with corn was conducted. Si application levels were applied at 0 (S0), 250 (S1) and 500 (S2) mg Si kg-1 soil and biochar treatments (3 % wt.) included rice husk (RH) and sheep manure (SM) biochars produced at 300 °C and 500 °C (SM300, SM500, RH300 and RH500). At harvest, corn shoot Ni-concentrations, soil chemical Ni fractions and DPTA-release kinetics were determined. Simultaneous utilization of Si and SM biochars led to a synergistic reduction (15–36 %) of soluble and exchangeable soil Ni fractions compared to application of Si (5–9 %) and SM (5–7 %) biochars separately. The application of the Si and biochars also decreased DPTA-extractable Ni and corn Ni shoot concentration (by up to 57 %), with the combined application of SM500+S2 being the most effective. These effects were attributed to the transformation of Ni from more bioavailable fractions to more stable iron oxide bound fractions, related to soil pH increase. The SM500 was likely the most effective biochar due to its higher alkalinity and lower acidic functional group content which enhanced Ni sorption reactions with Si. The study demonstrates the synergistic potential Si and sheep manure biochar at immobilizing Ni in contaminated calcareous soils.
摘要。硅（Si）是一种有益的植物元素，已被证明可以减轻潜在有毒元素（PTEs）对作物的影响。生物炭是一种土壤改良剂，可固化土壤中的碳，并能固定 PTEs，促进土壤中作物的生长。考虑到这些有益特性，同时利用硅和生物炭如何影响土壤中 PTEs 的固定化仍有待研究。因此，本研究旨在考察硅含量和生物沥青的交互作用，以减轻石灰性土壤中玉米（Zea Mays）对土壤中镍的生物利用率及其相应的吸收。对玉米进行了为期 90 天的因子温室研究。施硅水平为 0（S0）、250（S1）和 500（S2）毫克 Si kg-1 土壤，生物炭处理（3 % wt.）包括在 300 °C 和 500 °C 下生产的稻壳（RH）和羊粪（SM）生物炭（SM300、SM500、RH300 和 RH500）。收获时，测定了玉米芽中的镍浓度、土壤化学镍组分和 DPTA 释放动力学。与分别施用 Si（5-9%）和 SM（5-7%）生物酵素相比，同时施用 Si 和 SM 生物酵素可协同减少（15-36%）可溶性和可交换性土壤镍组分。施用硅和生物炭还能降低 DPTA 可萃取镍和玉米镍芽浓度（降幅高达 57%），其中 SM500+S2 的联合施用效果最好。这些效果归因于镍从生物可利用部分转化为更稳定的氧化铁结合部分，这与土壤 pH 值升高有关。SM500 可能是最有效的生物炭，因为其碱度较高，酸性官能团含量较低，从而增强了镍与硅的吸附反应。这项研究证明了硅和羊粪生物炭在固定受污染钙质土壤中的镍方面的协同潜力。
{"title":"Investigating the synergistic potential Si and biochar to immobilize soil Ni in a contaminated calcareous soil after Zea mays L. cultivation","authors":"Hamid Reza Boostani, Ailsa G. Hardie, Mahdi Najafi-Ghiri, Ehsan Bijanzadeh, Dariush Khalili, Esmaeil Farrokhnejad","doi":"10.5194/egusphere-2023-2687","DOIUrl":"https://doi.org/10.5194/egusphere-2023-2687","url":null,"abstract":"<strong>Abstract.</strong> Silicon (Si) is a beneficial plant element that has been shown to mitigate the effects of potentially toxic elements (PTEs) on crops. Biochar is a soil amendment that sequesters soil carbon, and that can immobilize PTEs and enhance crop growth in soils. Considering these beneficial properties, it remains to be investigated how the simultaneous utilization of Si and biochars affects PTEs immobilization in soils. Therefore, the aim of this study was to examine the interaction effects of Si levels and biochars, to alleviate soil Ni bioavailability and its corresponding uptake in corn<em> </em>(<em>Zea Mays</em>) in a calcareous soil. A 90-day factorial greenhouse study with corn was conducted. Si application levels were applied at 0 (S<sub>0</sub>), 250 (S<sub>1)</sub> and 500 (S<sub>2</sub>) mg Si kg<sup>-1</sup> soil and biochar treatments (3 % wt.) included rice husk (RH) and sheep manure (SM) biochars produced at 300 °C and 500 <strong>°</strong>C (SM300, SM500, RH300 and RH500). At harvest, corn shoot Ni-concentrations, soil chemical Ni fractions and DPTA-release kinetics were determined. Simultaneous utilization of Si and SM biochars led to a synergistic reduction (15–36 %) of soluble and exchangeable soil Ni fractions compared to application of Si (5–9 %) and SM (5–7 %) biochars separately. The application of the Si and biochars also decreased DPTA-extractable Ni and corn Ni shoot concentration (by up to 57 %), with the combined application of SM500+S<sub>2</sub> being the most effective. These effects were attributed to the transformation of Ni from more bioavailable fractions to more stable iron oxide bound fractions, related to soil pH increase. The SM500 was likely the most effective biochar due to its higher alkalinity and lower acidic functional group content which enhanced Ni sorption reactions with Si. The study demonstrates the synergistic potential Si and sheep manure biochar at immobilizing Ni in contaminated calcareous soils.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"8 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139431163","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}
Félix García-Pereira, Jesús Fidel González-Rouco, Thomas Schmid, Camilo Melo-Aguilar, Cristina Vegas-Cañas, Norman Julius Steinert, Pedro José Roldán-Gómez, Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, Philipp de Vrese
Abstract. An assessment of the soil and bedrock thermal structure of the Sierra de Guadarrama, in central Spain, is provided using subsurface and ground surface temperature data coming from four deep (20 m) monitoring profiles belonging to the Guadarrama Monitoring Network (GuMNet) and two shallow profiles (1 m) from the Spanish Meteorology Service (Agencia Estatal de Meteorología, AEMET) covering the time spans of 2015–2021 and 1989–2018, respectively. An evaluation of air and ground surface temperature coupling showed that soil insulation due to snow cover is the main source of seasonal decoupling, being especially relevant in winter at high-altitude sites. Temperature propagation in the subsurface was characterized by assuming a heat conductive regime by considering apparent thermal diffusivity values derived from the amplitude attenuation and phase shift of the annual cycle with depth. This methodology was further extended to consider the attenuation of all harmonics in the spectral domain, which allowed for analysis of thermal diffusivity from high-frequency changes in the soil near the surface at short timescales. For the deep profiles, the apparent thermal diffusivity ranges from 1 to 1.3×10-6 m2 s−1, which is consistent with values for gneiss and granite, the major bedrock components in the Sierra de Guadarrama. However, thermal diffusivity is lower and more heterogeneous in the soil layers close to the surface (0.4–0.8×10-6 m2 s−1). An increase in diffusivity with depth was observed that was generally larger in the soil–bedrock transition at 4–8 m depth. The outcomes are relevant for the understanding of soil thermodynamics in relation to other soil properties. Results with the spectral method suggest that changes in near-surface thermal diffusivity are related to changes in soil moisture content, which makes it a potential tool to gain information about soil drought and water resource availability from soil temperature data.
{"title":"Thermodynamic and hydrological drivers of the soil and bedrock thermal regimes in central Spain","authors":"Félix García-Pereira, Jesús Fidel González-Rouco, Thomas Schmid, Camilo Melo-Aguilar, Cristina Vegas-Cañas, Norman Julius Steinert, Pedro José Roldán-Gómez, Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, Philipp de Vrese","doi":"10.5194/soil-10-1-2024","DOIUrl":"https://doi.org/10.5194/soil-10-1-2024","url":null,"abstract":"Abstract. An assessment of the soil and bedrock thermal structure of the Sierra de Guadarrama, in central Spain, is provided using subsurface and ground surface temperature data coming from four deep (20 m) monitoring profiles belonging to the Guadarrama Monitoring Network (GuMNet) and two shallow profiles (1 m) from the Spanish Meteorology Service (Agencia Estatal de Meteorología, AEMET) covering the time spans of 2015–2021 and 1989–2018, respectively. An evaluation of air and ground surface temperature coupling showed that soil insulation due to snow cover is the main source of seasonal decoupling, being especially relevant in winter at high-altitude sites. Temperature propagation in the subsurface was characterized by assuming a heat conductive regime by considering apparent thermal diffusivity values derived from the amplitude attenuation and phase shift of the annual cycle with depth. This methodology was further extended to consider the attenuation of all harmonics in the spectral domain, which allowed for analysis of thermal diffusivity from high-frequency changes in the soil near the surface at short timescales. For the deep profiles, the apparent thermal diffusivity ranges from 1 to 1.3×10-6 m2 s−1, which is consistent with values for gneiss and granite, the major bedrock components in the Sierra de Guadarrama. However, thermal diffusivity is lower and more heterogeneous in the soil layers close to the surface (0.4–0.8×10-6 m2 s−1). An increase in diffusivity with depth was observed that was generally larger in the soil–bedrock transition at 4–8 m depth. The outcomes are relevant for the understanding of soil thermodynamics in relation to other soil properties. Results with the spectral method suggest that changes in near-surface thermal diffusivity are related to changes in soil moisture content, which makes it a potential tool to gain information about soil drought and water resource availability from soil temperature data.","PeriodicalId":48610,"journal":{"name":"Soil","volume":"24 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139407784","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 : 2024-01-08DOI: 10.5194/egusphere-2023-3031
Esko Karvinen, Leif Backman, Leena Järvi, Liisa Kulmala
Abstract. As an increasing share of the human population is being clustered in cities, urban areas have swiftly become the epicentres of anthropogenic carbon (C) emissions. Understanding different parts of the biogenic C cycle in urban ecosystems is needed in order to assess the potential of enhancing their C stocks as a cost-efficient means to balance the C emissions and mitigate climate change. Here, we conducted a field measurement campaign over three consecutive growing seasons to examine soil respiration carbon dioxide (CO2) fluxes and soil organic carbon (SOC) stocks at four measurement sites in Helsinki representing different types of tree-covered urban green space commonly found in northern European cities. We expected to find variation in the main drivers of soil respiration – soil temperature, soil moisture, and SOC – as a result of the heterogeneity of urban landscape, and that this variation would be reflected in the measured soil respiration rates. In the end, we could see fairly constant statistically significant differences between the sites in terms of soil temperature but only sporadic and seemingly momentary differences in soil moisture and soil respiration. There were also statistically significant differences in SOC stocks: the highest SOC stock was found in inactively managed deciduous urban forest and the lowest under managed streetside lawn with common linden trees. We studied the impacts of the urban heat island (UHI) effect and irrigation on heterotrophic soil respiration with process-based model simulations, and found that the variation created by the UHI is relatively minor compared to the increase associated with active irrigation, especially during dry summers. We conclude that, within our study area, the observed variation in soil temperature alone was not enough to cause variation in soil respiration rates between the studied green space types, perhaps because the soil moisture conditions were uniform. Thus, irrigation could potentially be a key factor in altering the soil respiration dynamics in urban green space both within the urban area and in comparison to non-urban ecosystems.
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