Pub Date : 2024-12-20DOI: 10.1016/j.geoderma.2024.117145
Sangyeong Park, Yongjoon Choe, Hangseok Choi, Khanh Pham
Unfrozen water plays a crucial role in thermophysical processes occurring in frozen ground. Measurement difficulties require approximate approaches to describe the relationship between unfrozen water content (θ) and soil temperature, known as soil freezing characteristic curve (SFCC). Despite significant progress, model characteristics, freezing-thawing hysteresis, and phase equilibrium remain challenging. This study developed an alternative approach to estimate θ using a pedotransfer function (PTF) implemented with extreme gradient boosting (XGB). The XGB-PTF model was trained using SFCC data available in the literature, and cooperative game theory was utilized to assess potential impacts on θ predictions. The performance of the XGB-PTF was rigorously evaluated and compared with two high-performance empirical models. Significant reductions in root mean square error and mean absolute error of 42% and 55%, respectively, demonstrated the superiority of the XGB-PTF. The XGB-PTF’s usability was also verified by experimental validation. A notable advantage of the proposed model is its capacity to provide a credible range containing the actual θ with a 95% confidence level. Coupling the XGB-PTF with game theory indicated that the primary factors influencing the SFCC were in order of porosity (n), initial saturation degree (Sr), and clay fraction (Fclay) for fine-grained soils, while for coarse-grained soils, the order is Fclay, n, and Sr. Furthermore, insights derived from game theory aligned with previous experimental studies concerning the phase transition of pore water across various temperature ranges. The proposed XGB-PTF, with its straightforward predictors, efficiency, and transparency, is expected to serve as a versatile tool for advancing SFCC studies.
{"title":"Machine learning-based pseudo-continuous pedotransfer function for predicting soil freezing characteristic curve","authors":"Sangyeong Park, Yongjoon Choe, Hangseok Choi, Khanh Pham","doi":"10.1016/j.geoderma.2024.117145","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117145","url":null,"abstract":"Unfrozen water plays a crucial role in thermophysical processes occurring in frozen ground. Measurement difficulties require approximate approaches to describe the relationship between unfrozen water content (<ce:italic>θ</ce:italic>) and soil temperature, known as soil freezing characteristic curve (SFCC). Despite significant progress, model characteristics, freezing-thawing hysteresis, and phase equilibrium remain challenging. This study developed an alternative approach to estimate <ce:italic>θ</ce:italic> using a pedotransfer function (PTF) implemented with extreme gradient boosting (XGB). The XGB-PTF model was trained using SFCC data available in the literature, and cooperative game theory was utilized to assess potential impacts on <ce:italic>θ</ce:italic> predictions. The performance of the XGB-PTF was rigorously evaluated and compared with two high-performance empirical models. Significant reductions in root mean square error and mean absolute error of 42% and 55%, respectively, demonstrated the superiority of the XGB-PTF. The XGB-PTF’s usability was also verified by experimental validation. A notable advantage of the proposed model is its capacity to provide a credible range containing the actual <ce:italic>θ</ce:italic> with a 95% confidence level. Coupling the XGB-PTF with game theory indicated that the primary factors influencing the SFCC were in order of porosity (<ce:italic>n</ce:italic>), initial saturation degree (<ce:italic>S</ce:italic><ce:inf loc=\"post\">r</ce:inf>), and clay fraction (<ce:italic>F</ce:italic><ce:inf loc=\"post\">clay</ce:inf>) for fine-grained soils, while for coarse-grained soils, the order is <ce:italic>F</ce:italic><ce:inf loc=\"post\">clay</ce:inf>, <ce:italic>n</ce:italic>, and <ce:italic>S</ce:italic><ce:inf loc=\"post\">r</ce:inf>. Furthermore, insights derived from game theory aligned with previous experimental studies concerning the phase transition of pore water across various temperature ranges. The proposed XGB-PTF, with its straightforward predictors, efficiency, and transparency, is expected to serve as a versatile tool for advancing SFCC studies.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"12 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The development of renewable energy technologies is growing rapidly, with solar energy being the most promising source. Agrivoltaics in particular offers the advantage to combine crop and energy production on the same land. While many studies have looked at the impact of ground-mounted solar power panels on uncultivated grassland, very few have focused on agrivoltaic structures, and none on dual axis trackers with bi-dimensional turning mount-holding panels and limited ground anchorage. Our study focused on the relative impact of such trackers (via anchorage constraint to farming practices, and mobile shading) on the physical, chemical and biological soil features in both wheat croplands and meadows relative to farming practices known for impacting these features. Using a PLS-PM analysis, we show that despite altered chemicals conditions near the tracker and the higher specific plant richness brought by the PV structure, thereby changing environmental conditions, there are no significant effects on organisms compared to agricultural practices. Comparing hay meadows and wheat fields suggests varied impacts, prompting the need for further comparative studies across different agricultural contexts.
{"title":"Impacts of punctual solar trackers on soil biodiversity in agricultural lands","authors":"Leroy Valentine, Decocq Guillaume, Noirot-Cosson Paul-Emile, Marrec Ronan","doi":"10.1016/j.geoderma.2024.117147","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117147","url":null,"abstract":"The development of renewable energy technologies is growing rapidly, with solar energy being the most promising source. Agrivoltaics in particular offers the advantage to combine crop and energy production on the same land. While many studies have looked at the impact of ground-mounted solar power panels on uncultivated grassland, very few have focused on agrivoltaic structures, and none on dual axis trackers with bi-dimensional turning mount-holding panels and limited ground anchorage. Our study focused on the relative impact of such trackers (via anchorage constraint to farming practices, and mobile shading) on the physical, chemical and biological soil features in both wheat croplands and meadows relative to farming practices known for impacting these features. Using a PLS-PM analysis, we show that despite altered chemicals conditions near the tracker and the higher specific plant richness brought by the PV structure, thereby changing environmental conditions, there are no significant effects on organisms compared to agricultural practices. Comparing hay meadows and wheat fields suggests varied impacts, prompting the need for further comparative studies across different agricultural contexts.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"8 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-12-19DOI: 10.1016/j.geoderma.2024.117144
Yongliang Qi, Bihang Fan, Yaling Zhang, Yanjia Jiang, Yuanyuan Huang, Elizabeth W. Boyer, Carlos R. Mello, Li Guo, Hongxia Li
Obtaining accurate information regarding root zone soil moisture (RZSM) is a critical element of effective hydrological and agricultural management practices. Previous studies have relied on surface soil moisture (SSM) values, which are more easily measured, to estimate RZSM using the Soil Moisture Analytical Relationship (SMAR) model or regression method. However, the performance of these two types of methods in areas with complex topography still needs more exploration. Here, we assess the accuracy of these two types of methods in a forested mountainous catchment, using daily SSM measurements from 32 monitoring sites. The results show that both methods are capable of accurately estimating RZSM with a high NSE (>0.950) during the validation period. Additionally, they exhibit excellent model transferability at ungauged sites. Spatially, both methods perform better in drier areas than in wetter areas. Temporally, both methods are better in the wet–cold season than in the dry–warm season. Overall, both methods demonstrate comparable performance in the catchment, with NSE values of 0.986 and 0.951 during the validation period, respectively. The regression method is more suited to complex hydropedological environments characterized by long-term soil moisture monitoring and nonlinear hydropedological behaviors. Conversely, the SMAR model is better suited for flat areas and less spatial variability in microtopography. Moreover, the estimation of RZSM by both methods is influenced not only by soil moisture conditions but also by local factors including terrain topography, soil depth, and the degree of subsurface hydrological connectivity. This study adds to our understanding of RZSM estimation from SSM in complex terrain and will act as a reference for selecting appropriate methods of RZSM estimation. The results of this study underscore a discernible relationship between surface and deep soil moisture across varying spatial and temporal scales.
{"title":"Estimating root zone soil moisture using the SMAR model and regression method at a headwater catchment with complex terrain","authors":"Yongliang Qi, Bihang Fan, Yaling Zhang, Yanjia Jiang, Yuanyuan Huang, Elizabeth W. Boyer, Carlos R. Mello, Li Guo, Hongxia Li","doi":"10.1016/j.geoderma.2024.117144","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117144","url":null,"abstract":"Obtaining accurate information regarding root zone soil moisture (RZSM) is a critical element of effective hydrological and agricultural management practices. Previous studies have relied on surface soil moisture (SSM) values, which are more easily measured, to estimate RZSM using the Soil Moisture Analytical Relationship (SMAR) model or regression method. However, the performance of these two types of methods in areas with complex topography still needs more exploration. Here, we assess the accuracy of these two types of methods in a forested mountainous catchment, using daily SSM measurements from 32 monitoring sites. The results show that both methods are capable of accurately estimating RZSM with a high NSE (>0.950) during the validation period. Additionally, they exhibit excellent model transferability at ungauged sites. Spatially, both methods perform better in drier areas than in wetter areas. Temporally, both methods are better in the wet–cold season than in the dry–warm season. Overall, both methods demonstrate comparable performance in the catchment, with NSE values of 0.986 and 0.951 during the validation period, respectively. The regression method is more suited to complex hydropedological environments characterized by long-term soil moisture monitoring and nonlinear hydropedological behaviors. Conversely, the SMAR model is better suited for flat areas and less spatial variability in microtopography. Moreover, the estimation of RZSM by both methods is influenced not only by soil moisture conditions but also by local factors including terrain topography, soil depth, and the degree of subsurface hydrological connectivity. This study adds to our understanding of RZSM estimation from SSM in complex terrain and will act as a reference for selecting appropriate methods of RZSM estimation. The results of this study underscore a discernible relationship between surface and deep soil moisture across varying spatial and temporal scales.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"32 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142884276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The recovery of soil aggregates is crucial for improving soil quality in highly compacted reclaimed farmlands in coal mining subsidence areas. This study aimed to explore the key factors and mechanisms affecting aggregate recovery in reclaimed mine soil (RMS). Surface soil samples (0 ∼ 20 cm) were collected from reclaimed farmlands with varying reclamation durations (0, 2, 6, 12, 16, and 22 years) and adjacent non-subsidence cultivated soil (NCS). A total of 20 soil indicators were analyzed. Complex network theory was then applied to explore their interrelationships and identify critical factors influencing aggregate distribution. The results showed that mechanical compaction during geomorphic reshaping disrupted macroaggregates, reduced aggregate stability, accelerated organic carbon mineralization, and diminished microbial activity. This also resulted in increased complexity and disorder of soil property interactions. After 22 years of reclamation, the proportion of 2 ∼ 0.25 mm aggregates increased by 25.92 %, while 0.25 ∼ 0.053 mm aggregates decreased by 40.93 %. The mean weight diameter and geometric mean diameter increased by 34.48 % and 69.54 %, respectively. Soil organic carbon (SOC) increased by 250.94 %, and microbial biomass by 123.07 %. However, RMS still exhibited differences in aggregate distribution, stability, SOC accumulation, and system functionality compared with the NCS. Soil aggregates, particularly macroaggregates, served as mediators within the RMS system. In the early stages of reclamation, inorganic cementing agents were crucial for maintaining RMS aggregation and SOC sequestration. Over time, particulate organic carbon and microbial activity became dominant in aggregate formation. Iron-aluminum oxides, particularly amorphous forms, facilitated macroaggregate formation and SOC stabilization.
{"title":"Behavior of soil aggregates in reclaimed farmland with different restoration durations: Mediating factors and mechanisms","authors":"Zhaoxinyu Liu, Junying Li, Lina Gao, Xinju Li, Wen Song, Luofan Li, Yulong Zang, Gengdi Zhang","doi":"10.1016/j.geoderma.2024.117140","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117140","url":null,"abstract":"The recovery of soil aggregates is crucial for improving soil quality in highly compacted reclaimed farmlands in coal mining subsidence areas. This study aimed to explore the key factors and mechanisms affecting aggregate recovery in reclaimed mine soil (RMS). Surface soil samples (0 ∼ 20 cm) were collected from reclaimed farmlands with varying reclamation durations (0, 2, 6, 12, 16, and 22 years) and adjacent non-subsidence cultivated soil (NCS). A total of 20 soil indicators were analyzed. Complex network theory was then applied to explore their interrelationships and identify critical factors influencing aggregate distribution. The results showed that mechanical compaction during geomorphic reshaping disrupted macroaggregates, reduced aggregate stability, accelerated organic carbon mineralization, and diminished microbial activity. This also resulted in increased complexity and disorder of soil property interactions. After 22 years of reclamation, the proportion of 2 ∼ 0.25 mm aggregates increased by 25.92 %, while 0.25 ∼ 0.053 mm aggregates decreased by 40.93 %. The mean weight diameter and geometric mean diameter increased by 34.48 % and 69.54 %, respectively. Soil organic carbon (SOC) increased by 250.94 %, and microbial biomass by 123.07 %. However, RMS still exhibited differences in aggregate distribution, stability, SOC accumulation, and system functionality compared with the NCS. Soil aggregates, particularly macroaggregates, served as mediators within the RMS system. In the early stages of reclamation, inorganic cementing agents were crucial for maintaining RMS aggregation and SOC sequestration. Over time, particulate organic carbon and microbial activity became dominant in aggregate formation. Iron-aluminum oxides, particularly amorphous forms, facilitated macroaggregate formation and SOC stabilization.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"420 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-12-16DOI: 10.1016/j.geoderma.2024.117143
Ren-Min Yang, Lai-Ming Huang, Zhifeng Yan, Xin Zhang, Shao-Jun Yan
Alpine grassland ecosystems play a crucial role in the global carbon (C) balance by contributing to the soil organic carbon (SOC) pool; thus, quantifying SOC stocks in these ecosystems is essential for understanding potential gains or losses in soil C under the threat of climate change and anthropogenic activities. Remote sensing plays a vital role in estimating SOC stocks; however, identifying reliable remote sensing proxies to enhance SOC prediction remains a challenge. Information on soil C cycling proxies can reveal how the balance between C inputs and outputs affects SOC. Therefore, these proxies could be effective indicators of SOC variations. In this study, we explored the potential of satellite-derived attributes related to soil C cycling proxies for predicting SOC stocks. We derived remote sensing indices such as gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance and assessed the relationships between these indices and SOC stocks via partial least squares structural equation modeling (PLS-SEM). We evaluated the effectiveness of these indices in predicting SOC stocks, we compared PLS-SEM and quantile regression forest (QRF) models across different variable combinations, including static, intra-annual, and inter-annual information. The PLS-SEM results demonstrated the suitability of the derived remote sensing indices and their interactions in reflecting processes related to soil C balance. The QRF models, using these indices, achieved promising prediction accuracies, with a coefficient of determination (R2) of 0.54 and a root mean square error (RMSE) of 0.79 kg m−2 at the topmost 10 cm of soil. However, the prediction performance generally decreased with increasing soil depth, up to 30 cm. The results also revealed that adding intra- and inter-annual information to remotely sensed proxies did not increase the prediction accuracy. Our study revealed that gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance are effective proxies for representing factors influencing soil C balance and mapping SOC stocks in alpine grasslands.
{"title":"Using satellite-derived attributes as proxies for soil carbon cycling to map carbon stocks in alpine grassland soils","authors":"Ren-Min Yang, Lai-Ming Huang, Zhifeng Yan, Xin Zhang, Shao-Jun Yan","doi":"10.1016/j.geoderma.2024.117143","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117143","url":null,"abstract":"Alpine grassland ecosystems play a crucial role in the global carbon (C) balance by contributing to the soil organic carbon (SOC) pool; thus, quantifying SOC stocks in these ecosystems is essential for understanding potential gains or losses in soil C under the threat of climate change and anthropogenic activities. Remote sensing plays a vital role in estimating SOC stocks; however, identifying reliable remote sensing proxies to enhance SOC prediction remains a challenge. Information on soil C cycling proxies can reveal how the balance between C inputs and outputs affects SOC. Therefore, these proxies could be effective indicators of SOC variations. In this study, we explored the potential of satellite-derived attributes related to soil C cycling proxies for predicting SOC stocks. We derived remote sensing indices such as gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance and assessed the relationships between these indices and SOC stocks via partial least squares structural equation modeling (PLS-SEM). We evaluated the effectiveness of these indices in predicting SOC stocks, we compared PLS-SEM and quantile regression forest (QRF) models across different variable combinations, including static, intra-annual, and inter-annual information. The PLS-SEM results demonstrated the suitability of the derived remote sensing indices and their interactions in reflecting processes related to soil C balance. The QRF models, using these indices, achieved promising prediction accuracies, with a coefficient of determination (<ce:italic>R</ce:italic><ce:sup loc=\"post\">2</ce:sup>) of 0.54 and a root mean square error (RMSE) of 0.79 kg m<ce:sup loc=\"post\">−2</ce:sup> at the topmost 10 cm of soil. However, the prediction performance generally decreased with increasing soil depth, up to 30 cm. The results also revealed that adding intra- and inter-annual information to remotely sensed proxies did not increase the prediction accuracy. Our study revealed that gross primary production, soil respiration, soil moisture, land surface temperature, radiation, and soil disturbance are effective proxies for representing factors influencing soil C balance and mapping SOC stocks in alpine grasslands.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"65 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-12-16DOI: 10.1016/j.geoderma.2024.117133
S. Carolina Córdova, Alexandra N. Kravchenko, Jessica R. Miesel, G. Philip Robertson
Changes in soil organic carbon (SOC) and nitrogen (SON) are strongly affected by land management but few long-term comparative studies have surveyed changes throughout the whole soil profile. We quantified 25-year SOC and SON changes to 1 m in 10 replicate ecosystems at an Upper Midwest, USA site. We compared four annual cropping systems in maize (Zea mays)-soybean (Glycine max)-winter wheat (Triticum aestivum) rotations, each managed differently (Conventional, No-till, Reduced input, and Biologically based); in three managed perennial systems (hybrid Poplar (Populus × euramericana), Alfalfa (Medicago sativa), and Conifer (Pinus spp.); and in three successional systems (Early, Mid- and Late succession undergoing a gradual change in species composition and structure over time). Both Reduced input and Biologically based systems included winter cover crops. Neither SOC nor SON changed significantly in the Conventional or Late successional systems over 25 years. All other systems gained SOC and SON to different degrees. SOC accrual was fastest in the Early successional system (0.8 ± 0.1 Mg C ha−1 y−1) followed by Alfalfa and Conifer (avg. 0.7 ± 0.1 Mg C ha−1 y−1), Poplar, Reduced input, and Biologically based systems (avg. 0.4 ± 0.1 Mg C ha−1 y−1), and Mid-successional and No-till systems (0.3 and 0.2 Mg C ha−1 y−1, respectively). Over the most recent 12 years, rates of SOC accrual slowed in all systems except Reduced input and Mid-successional. There was no evidence of SOC loss at depth in any system, including No-till. Rates of SON accrual ranged from 64.7 to 0.8 kg N ha−1 y−1 in the order Alfalfa ≥ Early successional > Reduced input and Biologically based ≥ Poplar > No-till and Conifer > Mid-successional systems. Pyrogenic C levels in the Conventional, Early, and Late successional systems were similar despite 17 years of annual burning in the Early successional system (∼ 15 % of SOC to 50 cm, on average, and ∼40 % of SOC from 50 to 100 cm). Results underscore the importance of cover crops, perennial crops, and no-till options for sequestering whole profile C in intensively managed croplands.
{"title":"Soil carbon change in intensive agriculture after 25 years of conservation management","authors":"S. Carolina Córdova, Alexandra N. Kravchenko, Jessica R. Miesel, G. Philip Robertson","doi":"10.1016/j.geoderma.2024.117133","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117133","url":null,"abstract":"Changes in soil organic carbon (SOC) and nitrogen (SON) are strongly affected by land management but few long-term comparative studies have surveyed changes throughout the whole soil profile. We quantified 25-year SOC and SON changes to 1 m in 10 replicate ecosystems at an Upper Midwest, USA site. We compared four annual cropping systems in maize (<ce:italic>Zea mays</ce:italic>)-soybean (<ce:italic>Glycine</ce:italic> max)-winter wheat (<ce:italic>Triticum aestivum</ce:italic>) rotations, each managed differently (Conventional, No-till, Reduced input, and Biologically based); in three managed perennial systems (hybrid Poplar (<ce:italic>Populus</ce:italic> × <ce:italic>euramericana</ce:italic>), Alfalfa (<ce:italic>Medicago sativa</ce:italic>), and Conifer (<ce:italic>Pinus</ce:italic> spp.); and in three successional systems (Early, Mid- and Late succession undergoing a gradual change in species composition and structure over time). Both Reduced input and Biologically based systems included winter cover crops. Neither SOC nor SON changed significantly in the Conventional or Late successional systems over 25 years. All other systems gained SOC and SON to different degrees. SOC accrual was fastest in the Early successional system (0.8 ± 0.1 Mg C ha<ce:sup loc=\"post\">−1</ce:sup> y<ce:sup loc=\"post\">−1</ce:sup>) followed by Alfalfa and Conifer (avg. 0.7 ± 0.1 Mg C ha<ce:sup loc=\"post\">−1</ce:sup> y<ce:sup loc=\"post\">−1</ce:sup>), Poplar, Reduced input, and Biologically based systems (avg. 0.4 ± 0.1 Mg C ha<ce:sup loc=\"post\">−1</ce:sup> y<ce:sup loc=\"post\">−1</ce:sup>), and Mid-successional and No-till systems (0.3 and 0.2 Mg C ha<ce:sup loc=\"post\">−1</ce:sup> y<ce:sup loc=\"post\">−1</ce:sup>, respectively). Over the most recent 12 years, rates of SOC accrual slowed in all systems except Reduced input and Mid-successional. There was no evidence of SOC loss at depth in any system, including No-till. Rates of SON accrual ranged from 64.7 to 0.8 kg N ha<ce:sup loc=\"post\">−1</ce:sup> y<ce:sup loc=\"post\">−1</ce:sup> in the order Alfalfa ≥ Early successional > Reduced input and Biologically based ≥ Poplar > No-till and Conifer > Mid-successional systems. Pyrogenic C levels in the Conventional, Early, and Late successional systems were similar despite 17 years of annual burning in the Early successional system (∼ 15 % of SOC to 50 cm, on average, and ∼40 % of SOC from 50 to 100 cm). Results underscore the importance of cover crops, perennial crops, and no-till options for sequestering whole profile C in intensively managed croplands.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"32 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Atmospheric nitrogen (N) deposition and anthropogenic phosphorus (P) input simultaneously affect soil respiration (RS), a crucial process that mediates soil carbon (C) cycling. However, the interaction of N deposition and anthropogenic P input on RS, as well as its components—autotrophic respiration (RA) and heterotrophic respiration (RH)—remain largely unexplored. Herein, we conducted an 8-year field experiment with N and P additions in a tropical secondary forest, integrating the vegetation traits, soil physicochemical properties, organic C fractions, and microbial properties, to explore the effects of nutrient inputs and their interactions on RS, RA, and RH. Over eight years, along P input significantly increased RS by 19.2% and RH by 42.1%. These increases were partially mitigated (by 33.2% annually for RS and 58.3% annually for RH) with the addition of N. In contrast, the co-addition of N and P enhanced RA compared to alone N or P addition, suggesting that N deposition mitigated the stimulative effect of P input on RS by reducing RH rather than RA. The structural equation model further revealed that N deposition reduced RH primarily by increasing soil N:P ratio and decreasing both the labile C fraction and fungi biomass. Our findings suggest that prevalent N deposition across low latitudes could have substantially mitigate C emissions from forest soils under anthropogenic P input.
大气氮（N）沉积和人为磷（P）输入同时影响土壤呼吸（RS），而土壤呼吸是介导土壤碳（C）循环的一个关键过程。然而，氮沉降和人为磷输入对土壤呼吸作用及其组成部分--自养呼吸作用（RA）和异养呼吸作用（RH）--的相互作用在很大程度上仍未得到研究。在此，我们在热带次生林中进行了为期 8 年的氮磷添加田间试验，综合考虑了植被性状、土壤理化性质、有机碳组分和微生物特性，探讨了养分输入及其相互作用对 RS、RA 和 RH 的影响。在八年时间里，随着 P 的输入，RS 显著增加了 19.2%，RH 增加了 42.1%。相反，与单独添加氮或磷相比，氮和磷的共同添加增强了 RA，这表明氮的沉积通过降低 RH 而不是 RA 来减轻了磷对 RS 的刺激作用。结构方程模型进一步表明，氮沉积主要通过提高土壤氮磷比、降低可溶性碳组分和真菌生物量来降低相对湿度。我们的研究结果表明，低纬度地区普遍的氮沉积可能会大大缓解人为磷输入下森林土壤的碳排放。
{"title":"Nitrogen deposition mitigates long-term phosphorus input-induced stimulative effects on soil respiration in a tropical forest","authors":"Xingyun Huang, Yingwen Li, Shiqin Yu, Yongxing Cui, Fangyuan Guan, Yongxing Li, Jingtao Wu, Yang Hu, Zhian Li, Ping Zhuang, Bi Zou, Guoming Qin, Jingfan Zhang, Jinge Zhou, Ruyi Ding, Faming Wang","doi":"10.1016/j.geoderma.2024.117142","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117142","url":null,"abstract":"Atmospheric nitrogen (N) deposition and anthropogenic phosphorus (P) input simultaneously affect soil respiration (R<ce:inf loc=\"post\">S</ce:inf>), a crucial process that mediates soil carbon (C) cycling. However, the interaction of N deposition and anthropogenic P input on R<ce:inf loc=\"post\">S</ce:inf>, as well as its components—autotrophic respiration (R<ce:inf loc=\"post\">A</ce:inf>) and heterotrophic respiration (R<ce:inf loc=\"post\">H</ce:inf>)—remain largely unexplored. Herein, we conducted an 8-year field experiment with N and P additions in a tropical secondary forest, integrating the vegetation traits, soil physicochemical properties, organic C fractions, and microbial properties, to explore the effects of nutrient inputs and their interactions on R<ce:inf loc=\"post\">S</ce:inf>, R<ce:inf loc=\"post\">A</ce:inf>, and R<ce:inf loc=\"post\">H</ce:inf>. Over eight years, along P input significantly increased R<ce:inf loc=\"post\">S</ce:inf> by 19.2% and R<ce:inf loc=\"post\">H</ce:inf> by 42.1%. These increases were partially mitigated (by 33.2% annually for R<ce:inf loc=\"post\">S</ce:inf> and 58.3% annually for R<ce:inf loc=\"post\">H</ce:inf>) with the addition of N. In contrast, the co-addition of N and P enhanced R<ce:inf loc=\"post\">A</ce:inf> compared to alone N or P addition, suggesting that N deposition mitigated the stimulative effect of P input on R<ce:inf loc=\"post\">S</ce:inf> by reducing R<ce:inf loc=\"post\">H</ce:inf> rather than R<ce:inf loc=\"post\">A</ce:inf>. The structural equation model further revealed that N deposition reduced R<ce:inf loc=\"post\">H</ce:inf> primarily by increasing soil N:P ratio and decreasing both the labile C fraction and fungi biomass. Our findings suggest that prevalent N deposition across low latitudes could have substantially mitigate C emissions from forest soils under anthropogenic P input.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"24 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-12-14DOI: 10.1016/j.geoderma.2024.117141
Xianglong Li, Xue Yang, Ze Zhang, Jinbang Zhai, Xiangxi Meng
The annual frequency of ground surface freeze–thaw (AFGSFT) on the Qinghai-Xizang Plateau (QXP) is one of the most prominent features of the high plateau ground surface processes. Seasonal freezing and thawing of the ground surface led to changes, and sometimes anomalies, in the energy balance between the ground surface and the atmosphere, thereby impacting the ecological environment. However, the relationship between AFGSFT and normalized difference vegetation index (NDVI), as major influencing factors of near-ground surface hydrothermal processes, has not been well elucidated. Based on meteorological observation data from 1982 to 2020, National Oceanic and Atmospheric Administration Climate Data Record (NOAA CDR) NDVI data, and some auxiliary data, this study employs trend analysis, GeoDetector, and correlation analysis to explore the impact of NDVI on AFGSFT. The findings indicate that AFGSFT on the QXP has gradually decreased, while NDVI has generally shown an upward trend. NDVI exerts a strong controlling effect on AFGSFT changes. Specifically, as AFGSFT decreases, NDVI tends to increase, but the increasing NDVI gradually inhibits the downward trend of AFGSFT. Thus, the relationship between NDVI and AFGSFT trend is not merely one of amplification or inhibition but rather exhibits a more complex nonlinear relationship. Moreover, the changes in AFGSFT and NDVI in grassland areas are greater than those in other land cover types. This may suggest that grassland regions are experiencing a more rapid climate response and ground surface processes. These findings contribute to a better understanding of the ground surface characteristics of the high plateau and provide data support for formulating scientific ecological protection and climate adaptation strategies.
{"title":"Evaluating of ground surface freeze–thaw and the interrelationship with vegetation cover on the Qinghai-Xizang Plateau","authors":"Xianglong Li, Xue Yang, Ze Zhang, Jinbang Zhai, Xiangxi Meng","doi":"10.1016/j.geoderma.2024.117141","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117141","url":null,"abstract":"The annual frequency of ground surface freeze–thaw (AFGSFT) on the Qinghai-Xizang Plateau (QXP) is one of the most prominent features of the high plateau ground surface processes. Seasonal freezing and thawing of the ground surface led to changes, and sometimes anomalies, in the energy balance between the ground surface and the atmosphere, thereby impacting the ecological environment. However, the relationship between AFGSFT and normalized difference vegetation index (NDVI), as major influencing factors of near-ground surface hydrothermal processes, has not been well elucidated. Based on meteorological observation data from 1982 to 2020, National Oceanic and Atmospheric Administration Climate Data Record (NOAA CDR) NDVI data, and some auxiliary data, this study employs trend analysis, GeoDetector, and correlation analysis to explore the impact of NDVI on AFGSFT. The findings indicate that AFGSFT on the QXP has gradually decreased, while NDVI has generally shown an upward trend. NDVI exerts a strong controlling effect on AFGSFT changes. Specifically, as AFGSFT decreases, NDVI tends to increase, but the increasing NDVI gradually inhibits the downward trend of AFGSFT. Thus, the relationship between NDVI and AFGSFT trend is not merely one of amplification or inhibition but rather exhibits a more complex nonlinear relationship. Moreover, the changes in AFGSFT and NDVI in grassland areas are greater than those in other land cover types. This may suggest that grassland regions are experiencing a more rapid climate response and ground surface processes. These findings contribute to a better understanding of the ground surface characteristics of the high plateau and provide data support for formulating scientific ecological protection and climate adaptation strategies.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"258 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2024-12-14DOI: 10.1016/j.geoderma.2024.117139
Justin Louis Kafana Coulibaly, Xin Gong, Yuanhu Shao, Huayuan Shangguan, Alexis Kayiranga, Ismail Koné, Yanjiang Cai, Xin Sun
Urbanization converts natural lands into anthropogenic-disturbed soils, which can dramatically influence soil biota. However, how urbanization influences patterns of soil biodiversity and the effects on habitat sensible groups, generalist and specialist species, are poorly understood. Here, we examined the responses of diversity and community composition of soil nematodes, the most abundant metazoans on Earth, to several urban land use types (i.e., forests, farmlands, green belts, hospitals, industrials, urban parks, and residential areas) related to urbanization. We found moderate effects of land use and its associated variables on patterns of species richness, but more dramatic changes in the abundance of habitat specialists versus generalists. Specifically, while specialists tended to be reduced, primarily due to an increase in soil pH, generalists were robust to land use changes, buffering the overall effect on the overall nematode diversity. Furthermore, our results showed that human density, as a proxy of urbanization intensity, was linked to changes in soil pH between land use types. Our results suggest that urbanization could influence the community composition of soil nematodes by favoring generalists over specialists. Together, these findings highlight the importance of understanding and considering the ecological consequences of urbanization on soil microfauna specialization in light of the urban land use management.
{"title":"Urban greenspaces reduce the community specialization of soil nematodes","authors":"Justin Louis Kafana Coulibaly, Xin Gong, Yuanhu Shao, Huayuan Shangguan, Alexis Kayiranga, Ismail Koné, Yanjiang Cai, Xin Sun","doi":"10.1016/j.geoderma.2024.117139","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117139","url":null,"abstract":"Urbanization converts natural lands into anthropogenic-disturbed soils, which can dramatically influence soil biota. However, how urbanization influences patterns of soil biodiversity and the effects on habitat sensible groups, generalist and specialist species, are poorly understood. Here, we examined the responses of diversity and community composition of soil nematodes, the most abundant metazoans on Earth, to several urban land use types (i.e., forests, farmlands, green belts, hospitals, industrials, urban parks, and residential areas) related to urbanization. We found moderate effects of land use and its associated variables on patterns of species richness, but more dramatic changes in the abundance of habitat specialists versus generalists. Specifically, while specialists tended to be reduced, primarily due to an increase in soil pH, generalists were robust to land use changes, buffering the overall effect on the overall nematode diversity. Furthermore, our results showed that human density, as a proxy of urbanization intensity, was linked to changes in soil pH between land use types. Our results suggest that urbanization could influence the community composition of soil nematodes by favoring generalists over specialists. Together, these findings highlight the importance of understanding and considering the ecological consequences of urbanization on soil microfauna specialization in light of the urban land use management.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"48 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elevational gradients are often used to reveal how soil microorganisms will respond to climate change. However, inconsistent microbial distribution patterns across different elevational transects have raised doubts about their practical applicability. We hypothesized that variations in bedrock, which influence soil physical and chemical properties, would explain these inconsistencies. We therefore investigated soil microbial communities (bacterial and fungal) along two adjacent elevational transects with different bedrocks (granite vs. slate) in a subtropical forest. Our findings reveal that soil microbial communities are shaped by complex interactions between bedrock type and environmental factors along elevational gradients. Bacterial biomass was higher on slate, whereas fungal biomass was higher on granite. On granite, both bacterial and fungal biomass increased with elevation, whereas divergent patterns were observed on slate, likely due to the distinct soil properties or combinations of properties influencing microbial biomass on each bedrock. Bedrock and elevation strongly influenced microbial beta-diversity, with beta-diversity on granite driven primarily by soil total phosphorus and moisture, and on slate by soil organic carbon and pH. In contrast, alpha-diversity was impacted less by bedrock and elevation, but its relationship with environmental factors varied markedly between bedrock types. Overall, our results highlight the critical influence of bedrock in determining soil microbial community structure along elevational gradients and their potential responses to climate change.
{"title":"Bedrock modulates the elevational patterns of soil microbial communities","authors":"Xianjin He, Ruiqi Wang, Daniel S. Goll, Laurent Augusto, Naoise Nunan, M.D. Farnon Ellwood, Quanzhou Gao, Junlong Huang, Shenhua Qian, Yonghua Zhang, Zufei Shu, Buhang Li, Chengjin Chu","doi":"10.1016/j.geoderma.2024.117136","DOIUrl":"https://doi.org/10.1016/j.geoderma.2024.117136","url":null,"abstract":"Elevational gradients are often used to reveal how soil microorganisms will respond to climate change. However, inconsistent microbial distribution patterns across different elevational transects have raised doubts about their practical applicability. We hypothesized that variations in bedrock, which influence soil physical and chemical properties, would explain these inconsistencies. We therefore investigated soil microbial communities (bacterial and fungal) along two adjacent elevational transects with different bedrocks (granite vs. slate) in a subtropical forest. Our findings reveal that soil microbial communities are shaped by complex interactions between bedrock type and environmental factors along elevational gradients. Bacterial biomass was higher on slate, whereas fungal biomass was higher on granite. On granite, both bacterial and fungal biomass increased with elevation, whereas divergent patterns were observed on slate, likely due to the distinct soil properties or combinations of properties influencing microbial biomass on each bedrock. Bedrock and elevation strongly influenced microbial beta-diversity, with beta-diversity on granite driven primarily by soil total phosphorus and moisture, and on slate by soil organic carbon and pH. In contrast, alpha-diversity was impacted less by bedrock and elevation, but its relationship with environmental factors varied markedly between bedrock types. Overall, our results highlight the critical influence of bedrock in determining soil microbial community structure along elevational gradients and their potential responses to climate change.","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":"1 1","pages":""},"PeriodicalIF":6.1,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142841522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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