Xue Chen, Hejun Zuo, Shichao Chen, Haibing Wang, Min Yan
Mine reclamation is essential for promoting soil development and ecological renewal in mining areas. However, changes in the biological stoichiometry of soil microbes, entropy effects and stoichiometric imbalances over increasing reclamation years remain unclear. This study aimed to clarify the responses of soil–microbial carbon (C), nitrogen (N) and phosphorus (P) stoichiometry to reclamation chronosequences, and to evaluate their links with microbial quotient indices, stoichiometric imbalances and microbial entropy ( <jats:italic>q</jats:italic> MB). Accordingly, this study investigated the dynamics of soil–microbial C, N and P within 0–40 cm soil profiles across four reclamation chronosequences (4a, 8a, 12a, 14a) in mining areas. The results showed the following. (1) The reclamation chronosequence had a significant effect on soil–microbial C, N, P and stoichiometric ratios. As the reclamation chronosequence increased, there were overall increasing trends in C <jats:sub>soil</jats:sub> , N <jats:sub>soil</jats:sub> , C <jats:sub>mic</jats:sub> , N <jats:sub>mic</jats:sub> , P <jats:sub>mic</jats:sub> , C <jats:sub>soil</jats:sub> :P <jats:sub>soil</jats:sub> , C <jats:sub>soil</jats:sub> :N <jats:sub>soil</jats:sub> , N <jats:sub>soil</jats:sub> :P <jats:sub>soil</jats:sub> and C <jats:sub>mic</jats:sub> :N <jats:sub>mic</jats:sub> , while P <jats:sub>soil</jats:sub> , N <jats:sub>mic</jats:sub> :P <jats:sub>mic</jats:sub> and C <jats:sub>mic</jats:sub> :P <jats:sub>mic</jats:sub> showed decreasing trends. (2) As the reclamation chronosequence increased, <jats:italic>q</jats:italic> MBP, <jats:italic>q</jats:italic> MBN, C <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> , C <jats:sub>imb</jats:sub> :N <jats:sub>imb</jats:sub> and N <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> generally increased, while <jats:italic>q</jats:italic> MBC showed a decreasing trend. As the soil layer deepened, C <jats:sub>soil</jats:sub> , N <jats:sub>soil</jats:sub> , P <jats:sub>soil</jats:sub> , C <jats:sub>mic</jats:sub> , N <jats:sub>mic</jats:sub> , P <jats:sub>mic</jats:sub> , C <jats:sub>soil</jats:sub> :P <jats:sub>soil</jats:sub> , C <jats:sub>soil</jats:sub> :N <jats:sub>soil</jats:sub> , C <jats:sub>mic</jats:sub> :N <jats:sub>mic</jats:sub> , C <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> , C <jats:sub>imb</jats:sub> :N <jats:sub>imb</jats:sub> and N <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> all tended to decrease, while <jats:italic>q</jats:italic> MBC, <jats:italic>q</jats:italic> MBN and <jats:italic>q</jats:italic> MBP generally increased. (3) Redundancy analysis (RDA) results showed that C <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> , Cimb:N <jats:sub>imb</jats:sub> , N <jats:sub>mic</jats:sub> :P <jats:sub>mic</jats:sub> and C <jats:sub>soil</jats:sub> :N <jats:sub>soil</jats:sub> were the primary factors influencing changes in <jats:italic>q</jats:italic> MB over different years following mine reclamation.
{"title":"Soil–Microbial Biomass Ecological Stoichiometric Characteristics of Coal Mining Reclamation Areas Are Driven by Reclamation Chronosequences","authors":"Xue Chen, Hejun Zuo, Shichao Chen, Haibing Wang, Min Yan","doi":"10.1002/ldr.70512","DOIUrl":"https://doi.org/10.1002/ldr.70512","url":null,"abstract":"Mine reclamation is essential for promoting soil development and ecological renewal in mining areas. However, changes in the biological stoichiometry of soil microbes, entropy effects and stoichiometric imbalances over increasing reclamation years remain unclear. This study aimed to clarify the responses of soil–microbial carbon (C), nitrogen (N) and phosphorus (P) stoichiometry to reclamation chronosequences, and to evaluate their links with microbial quotient indices, stoichiometric imbalances and microbial entropy ( <jats:italic>q</jats:italic> MB). Accordingly, this study investigated the dynamics of soil–microbial C, N and P within 0–40 cm soil profiles across four reclamation chronosequences (4a, 8a, 12a, 14a) in mining areas. The results showed the following. (1) The reclamation chronosequence had a significant effect on soil–microbial C, N, P and stoichiometric ratios. As the reclamation chronosequence increased, there were overall increasing trends in C <jats:sub>soil</jats:sub> , N <jats:sub>soil</jats:sub> , C <jats:sub>mic</jats:sub> , N <jats:sub>mic</jats:sub> , P <jats:sub>mic</jats:sub> , C <jats:sub>soil</jats:sub> :P <jats:sub>soil</jats:sub> , C <jats:sub>soil</jats:sub> :N <jats:sub>soil</jats:sub> , N <jats:sub>soil</jats:sub> :P <jats:sub>soil</jats:sub> and C <jats:sub>mic</jats:sub> :N <jats:sub>mic</jats:sub> , while P <jats:sub>soil</jats:sub> , N <jats:sub>mic</jats:sub> :P <jats:sub>mic</jats:sub> and C <jats:sub>mic</jats:sub> :P <jats:sub>mic</jats:sub> showed decreasing trends. (2) As the reclamation chronosequence increased, <jats:italic>q</jats:italic> MBP, <jats:italic>q</jats:italic> MBN, C <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> , C <jats:sub>imb</jats:sub> :N <jats:sub>imb</jats:sub> and N <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> generally increased, while <jats:italic>q</jats:italic> MBC showed a decreasing trend. As the soil layer deepened, C <jats:sub>soil</jats:sub> , N <jats:sub>soil</jats:sub> , P <jats:sub>soil</jats:sub> , C <jats:sub>mic</jats:sub> , N <jats:sub>mic</jats:sub> , P <jats:sub>mic</jats:sub> , C <jats:sub>soil</jats:sub> :P <jats:sub>soil</jats:sub> , C <jats:sub>soil</jats:sub> :N <jats:sub>soil</jats:sub> , C <jats:sub>mic</jats:sub> :N <jats:sub>mic</jats:sub> , C <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> , C <jats:sub>imb</jats:sub> :N <jats:sub>imb</jats:sub> and N <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> all tended to decrease, while <jats:italic>q</jats:italic> MBC, <jats:italic>q</jats:italic> MBN and <jats:italic>q</jats:italic> MBP generally increased. (3) Redundancy analysis (RDA) results showed that C <jats:sub>imb</jats:sub> :P <jats:sub>imb</jats:sub> , Cimb:N <jats:sub>imb</jats:sub> , N <jats:sub>mic</jats:sub> :P <jats:sub>mic</jats:sub> and C <jats:sub>soil</jats:sub> :N <jats:sub>soil</jats:sub> were the primary factors influencing changes in <jats:italic>q</jats:italic> MB over different years following mine reclamation.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"15 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146215622","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}
Despite increasing attention to low-carbon agriculture, a critical knowledge gap persists in integrating carbon efficiency into spatial land-use restructuring. Most existing approaches prioritize either grain output or economic return, neglecting the synergistic optimization of productivity and emission reduction. This single-dimensional focus impedes the alignment of agricultural production with climate targets and constrains the sector's green transition. Therefore, this study develops a hybrid framework that couples a slacks-based measure (SBM) model with the GeoSOS-FLUS land-use simulator based on county-level agricultural land carbon emission quantitative accounts and thereby generates spatial reconfiguration pathways under alternative scenarios. The findings indicate that: (1) 66.67% of townships operate at low agricultural carbon-utilization efficiency, underscoring the urgent need for land-use restructuring; (2) the food security priority scenario, relying on rural settlement consolidation and optimized garden land allocation, adds 4515 ha of arable land (+14.46%) and delivers a simultaneous reduction in carbon intensity, whereas the intensive development priority scenario—characterized by peri-urban agricultural land contraction, scattered rural growth and northward clustering of protected horticulture—curtails agricultural land by 3558 ha (−11.40%); and (3) four low-carbon optimization strategies—improving agricultural land efficiency, strengthening ecological protection, optimizing green transition models, and promoting sustainable development—are urgently needed to underwrite the green transition of agricultural land and to deliver a theoretical scaffold that secures regional grain security alongside green and sustainable development.
尽管人们越来越关注低碳农业，但在将碳效率纳入空间土地利用结构调整方面，仍然存在一个关键的知识缺口。现有的方法大多只考虑粮食产量或经济效益，而忽视了生产力和减排的协同优化。这种单一维度的关注阻碍了农业生产与气候目标的一致，并限制了该部门的绿色转型。因此，本研究开发了一个混合框架，将基于slack -based测度（SBM）模型与基于县级农业用地碳排放定量核算的GeoSOS-FLUS土地利用模拟器相结合，从而生成不同情景下的空间重构路径。研究结果表明：(1)66.67%的乡镇农业碳利用效率较低，迫切需要进行土地利用结构调整；(2)粮食安全优先情景下，以农村聚落整理和园林用地优化配置为依托，新增耕地4515 ha(+14.46%)，碳强度同步降低，而集约发展优先情景下，以城郊农业用地收缩、农村分散增长和保护性园艺向北集聚为特征，减少农业用地3558 ha (- 11.40%)；(3)提高农用地效率、加强生态保护、优化绿色转型模式、促进可持续发展四项低碳优化战略，迫切需要为农用地绿色转型提供保障，为区域粮食安全与绿色可持续发展提供理论支撑。
{"title":"Integrating Carbon-Efficiency Gains Into Agricultural Land-Use Restructuring: Scenario-Based Simulation for Sustainable Development","authors":"Heyuan You, Hui Liang, Jiahui Tong, Yanjun Guan","doi":"10.1002/ldr.70505","DOIUrl":"https://doi.org/10.1002/ldr.70505","url":null,"abstract":"Despite increasing attention to low-carbon agriculture, a critical knowledge gap persists in integrating carbon efficiency into spatial land-use restructuring. Most existing approaches prioritize either grain output or economic return, neglecting the synergistic optimization of productivity and emission reduction. This single-dimensional focus impedes the alignment of agricultural production with climate targets and constrains the sector's green transition. Therefore, this study develops a hybrid framework that couples a slacks-based measure (SBM) model with the GeoSOS-FLUS land-use simulator based on county-level agricultural land carbon emission quantitative accounts and thereby generates spatial reconfiguration pathways under alternative scenarios. The findings indicate that: (1) 66.67% of townships operate at low agricultural carbon-utilization efficiency, underscoring the urgent need for land-use restructuring; (2) the food security priority scenario, relying on rural settlement consolidation and optimized garden land allocation, adds 4515 ha of arable land (+14.46%) and delivers a simultaneous reduction in carbon intensity, whereas the intensive development priority scenario—characterized by peri-urban agricultural land contraction, scattered rural growth and northward clustering of protected horticulture—curtails agricultural land by 3558 ha (−11.40%); and (3) four low-carbon optimization strategies—improving agricultural land efficiency, strengthening ecological protection, optimizing green transition models, and promoting sustainable development—are urgently needed to underwrite the green transition of agricultural land and to deliver a theoretical scaffold that secures regional grain security alongside green and sustainable development.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"132 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146210325","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}
There are few quantitative prediction studies on farmland soil chromium content in Yunnan. In order to improve the accuracy of the prediction model and increase the generalization ability of the prediction model. In this study, a total of 121 soil visible and near-infrared (Vis–NIR) spectroscopy in upstream and midstream are collected for model training and validation, and 62 soil Vis–NIR samples in downstream are used for testing the generalization ability of the model in new environments. This study systematically compares, for the first time, the performance of five mainstream convolutional neural network (CNN) models with distinct characteristics—traditional LeNet-5, AlexNet-8 with large convolution kernels, VGGNet-7 with small convolution kernels, GoogleNet-7 incorporating the Inception structure, and ResNet with residual connections—in predicting chromium content in plateau soils, as well as their generalization ability on new environmental datasets. The simulation results showed that the prediction performance of the five different CNN models constructed for soil chromium content was excellent, with R2 reaching more than 0.86, RPD reaching more than 2.69 and RMSE reached below 195 mg kg−1 on the validation set. In the experiment for quantitatively predicting soil chromium content, the ResNet-13 model based on residual learning performed the best, with R2 of 0.9194, RMSE of 147.5360 mg kg−1, and RPD of 3.5214 on the validation set. In the model generalization ability experiment, the ResNet-13 model also had the best generalization ability, its R2, RMSE, and RPD were 0.9065, 176.9822 mg kg−1, and 3.2702 respectively. Meanwhile, the DeepExplainer interpreter based on the SHAP library were used to analyze the contribution of the feature bands in the ResNet-13 model, it was found that the peaks near 429, 535, 795, 1003, 1407, 1827, 2197, 2291, and 2483 nm were the main feature bands for predicting soil heavy metal chromium concentrations. This study provides a reliable reference value for quantitative prediction of soil heavy metal chromium concentration and model generalizability research.
{"title":"Prediction of Chromium Content in Farmland Soil Around Plateau Mining Areas Based on Convolutional Neural Networks and Generalization Performance Study","authors":"Chengbiao Fu, Aiping Wang, Anhong Tian","doi":"10.1002/ldr.70473","DOIUrl":"https://doi.org/10.1002/ldr.70473","url":null,"abstract":"There are few quantitative prediction studies on farmland soil chromium content in Yunnan. In order to improve the accuracy of the prediction model and increase the generalization ability of the prediction model. In this study, a total of 121 soil visible and near-infrared (Vis–NIR) spectroscopy in upstream and midstream are collected for model training and validation, and 62 soil Vis–NIR samples in downstream are used for testing the generalization ability of the model in new environments. This study systematically compares, for the first time, the performance of five mainstream convolutional neural network (CNN) models with distinct characteristics—traditional LeNet-5, AlexNet-8 with large convolution kernels, VGGNet-7 with small convolution kernels, GoogleNet-7 incorporating the Inception structure, and ResNet with residual connections—in predicting chromium content in plateau soils, as well as their generalization ability on new environmental datasets. The simulation results showed that the prediction performance of the five different CNN models constructed for soil chromium content was excellent, with <i>R</i><sup>2</sup> reaching more than 0.86, RPD reaching more than 2.69 and RMSE reached below 195 mg kg<sup>−1</sup> on the validation set. In the experiment for quantitatively predicting soil chromium content, the ResNet-13 model based on residual learning performed the best, with <i>R</i><sup>2</sup> of 0.9194, RMSE of 147.5360 mg kg<sup>−1</sup>, and RPD of 3.5214 on the validation set. In the model generalization ability experiment, the ResNet-13 model also had the best generalization ability, its R2, RMSE, and RPD were 0.9065, 176.9822 mg kg<sup>−1</sup>, and 3.2702 respectively. Meanwhile, the DeepExplainer interpreter based on the SHAP library were used to analyze the contribution of the feature bands in the ResNet-13 model, it was found that the peaks near 429, 535, 795, 1003, 1407, 1827, 2197, 2291, and 2483 nm were the main feature bands for predicting soil heavy metal chromium concentrations. This study provides a reliable reference value for quantitative prediction of soil heavy metal chromium concentration and model generalizability research.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"11 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146210484","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}
Marcos Tassano, Mirel Cabrera, Joan Gonzalez, Mario Perez‐Bidegain, Olivier Evrard, Kathrin Grahmann, J. Andrés Quincke
Soil erosion remains a major global concern affecting agricultural productivity and land sustainability. This study investigates the magnitude and variability of soil erosion in a long‐term experiment (LTE) established in 1963 in Colonia, Uruguay, aiming to compare the performance of the 137 Cs tracer technique and the RUSLE model across different crop rotations. We hypothesized that pasture inclusion into rotations reduces soil erosion compared to continuous cropping, regardless of the model. Four contrasting LTE treatments were selected: continuous cropping without fertilization, continuous cropping with fertilization, and two crop‐pasture rotations with 33% or 50% time under pasture. Each plot had a size of 25 × 200 m positioned along a hillslope and was sampled at six sampling points along a transect from the hilltop towards the footslope. Soil erosion was assessed using two methods: (1) the 137 Cs technique, estimating net soil redistribution based on deviations from a reference site, and (2) the RUSLE model, calibrated with national agronomic and climatic data. The 137 Cs method showed erosion rates from −73 to +51 Mg ha −1 year −1 , with accumulation at footslopes and highest losses in eroded gullies under unfertilized continuous cropping. RUSLE predicted losses from −1 to −20 Mg ha −1 year −1 , based on sheet erosion assumptions. The comparison was limited to five sampling points where erosion processes were dominant and compatible with RUSLE assumptions. Nevertheless, results confirmed that crop‐pasture rotations substantially reduced erosion and preserved soil over six decades. We conclude that integrating pastures into rotations is an effective erosion control strategy in sloping agricultural systems and helps maintain long‐term productivity.
{"title":"Assessment of Soil Erosion Over Six Decades in a Long‐Term Experiment Using Fallout 137 Cs and RUSLE : A South American Case Study","authors":"Marcos Tassano, Mirel Cabrera, Joan Gonzalez, Mario Perez‐Bidegain, Olivier Evrard, Kathrin Grahmann, J. Andrés Quincke","doi":"10.1002/ldr.70498","DOIUrl":"https://doi.org/10.1002/ldr.70498","url":null,"abstract":"Soil erosion remains a major global concern affecting agricultural productivity and land sustainability. This study investigates the magnitude and variability of soil erosion in a long‐term experiment (LTE) established in 1963 in Colonia, Uruguay, aiming to compare the performance of the <jats:sup>137</jats:sup> Cs tracer technique and the RUSLE model across different crop rotations. We hypothesized that pasture inclusion into rotations reduces soil erosion compared to continuous cropping, regardless of the model. Four contrasting LTE treatments were selected: continuous cropping without fertilization, continuous cropping with fertilization, and two crop‐pasture rotations with 33% or 50% time under pasture. Each plot had a size of 25 × 200 m positioned along a hillslope and was sampled at six sampling points along a transect from the hilltop towards the footslope. Soil erosion was assessed using two methods: (1) the <jats:sup>137</jats:sup> Cs technique, estimating net soil redistribution based on deviations from a reference site, and (2) the RUSLE model, calibrated with national agronomic and climatic data. The <jats:sup>137</jats:sup> Cs method showed erosion rates from −73 to +51 Mg ha <jats:sup>−1</jats:sup> year <jats:sup>−1</jats:sup> , with accumulation at footslopes and highest losses in eroded gullies under unfertilized continuous cropping. RUSLE predicted losses from −1 to −20 Mg ha <jats:sup>−1</jats:sup> year <jats:sup>−1</jats:sup> , based on sheet erosion assumptions. The comparison was limited to five sampling points where erosion processes were dominant and compatible with RUSLE assumptions. Nevertheless, results confirmed that crop‐pasture rotations substantially reduced erosion and preserved soil over six decades. We conclude that integrating pastures into rotations is an effective erosion control strategy in sloping agricultural systems and helps maintain long‐term productivity.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"43 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146215660","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}
Kaiwen Huang, Jiajun Ou, Wenyi Zhou, Rui Tan, Xin Liu, Ke Huang, Jinling Wang, Jie Lin
Soil carbon stability is critical for global carbon balance and ecosystem sustainability. Coastal saline‐alkali lands have great potential for carbon sequestration, yet the mechanisms by which water‐soluble salt ions regulate soil carbon dynamics remain unclear. To elucidate this relationship, this study systematically evaluated the co‐variations among water‐soluble salt ion distribution, soil chemical properties, and carbon fractions within the 0–100 cm soil profile under different plantation types ( Taxodium hybrid “Zhongshanshan” , Carya cathayensis, and Ulmus parvifolia ) in coastal saline‐alkali land. The objective was to reveal the regulatory mechanisms of salt ions on soil carbon processes. The results showed that afforestation significantly reduced soil pH and electrical conductivity, thereby alleviating soil salinization, particularly within the 40–100 cm layer where the total salt content was markedly lower in C. cathayensis plantations. Afforestation also reshaped the composition of water‐soluble salt ions: Na + and Mg 2+ concentrations decreased in surface soils, while Cl − and SO 42− concentrations increased, reflecting the regulatory role of the rhizosphere microenvironment on ion migration. Regarding carbon accumulation, both T . hybrid and C. cathayensis significantly enhanced total carbon and organic carbon contents in the 0–40 cm soil layer. Redundancy analysis and correlation tests indicated that Na + was the primary driver of soil carbon variation, showing a significant negative correlation with total and organic carbon but a positive correlation with inorganic carbon. Other influential factors included pH, HCO 3− , K + , and SO 42− . This study elucidates how water‐soluble salt ions affect carbon dynamics in coastal saline‐alkali soils, providing theoretical and practical guidance for enhancing carbon sequestration and optimizing plantation selection.
{"title":"Regulation of Water‐Soluble Salt Ions by Plantations to Enhance Carbon Sequestration in Coastal Saline‐Alkali Soils","authors":"Kaiwen Huang, Jiajun Ou, Wenyi Zhou, Rui Tan, Xin Liu, Ke Huang, Jinling Wang, Jie Lin","doi":"10.1002/ldr.70501","DOIUrl":"https://doi.org/10.1002/ldr.70501","url":null,"abstract":"Soil carbon stability is critical for global carbon balance and ecosystem sustainability. Coastal saline‐alkali lands have great potential for carbon sequestration, yet the mechanisms by which water‐soluble salt ions regulate soil carbon dynamics remain unclear. To elucidate this relationship, this study systematically evaluated the co‐variations among water‐soluble salt ion distribution, soil chemical properties, and carbon fractions within the 0–100 cm soil profile under different plantation types ( <jats:italic>Taxodium hybrid “Zhongshanshan”</jats:italic> , <jats:italic>Carya cathayensis,</jats:italic> and <jats:styled-content style=\"fixed-case\"> <jats:italic>Ulmus parvifolia</jats:italic> </jats:styled-content> ) in coastal saline‐alkali land. The objective was to reveal the regulatory mechanisms of salt ions on soil carbon processes. The results showed that afforestation significantly reduced soil pH and electrical conductivity, thereby alleviating soil salinization, particularly within the 40–100 cm layer where the total salt content was markedly lower in <jats:italic>C. cathayensis</jats:italic> plantations. Afforestation also reshaped the composition of water‐soluble salt ions: Na <jats:sup>+</jats:sup> and Mg <jats:sup>2+</jats:sup> concentrations decreased in surface soils, while Cl <jats:sup>−</jats:sup> and SO <jats:sub>4</jats:sub> <jats:sup>2−</jats:sup> concentrations increased, reflecting the regulatory role of the rhizosphere microenvironment on ion migration. Regarding carbon accumulation, both <jats:italic>T</jats:italic> . hybrid and <jats:italic>C. cathayensis</jats:italic> significantly enhanced total carbon and organic carbon contents in the 0–40 cm soil layer. Redundancy analysis and correlation tests indicated that Na <jats:sup>+</jats:sup> was the primary driver of soil carbon variation, showing a significant negative correlation with total and organic carbon but a positive correlation with inorganic carbon. Other influential factors included pH, HCO <jats:sub>3</jats:sub> <jats:sup>−</jats:sup> , K <jats:sup>+</jats:sup> , and SO <jats:sub>4</jats:sub> <jats:sup>2−</jats:sup> . This study elucidates how water‐soluble salt ions affect carbon dynamics in coastal saline‐alkali soils, providing theoretical and practical guidance for enhancing carbon sequestration and optimizing plantation selection.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"17 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146215661","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}
Servet Pehlivan, Ender Makineci, Alper Gün Özturna, Doğanay Tolunay
This study aimed to address the knowledge gap by examining the dynamics of biomass, carbon, and nitrogen pools between foliage and forest floor throughout the development of Pinus pinaster plantations in the restoration site of Durusu coastal dune ecosystem in Istanbul-Türkiye. Live foliage biomass was determined by destructive sampling, while forest floor sampling was carried out separately from litter + fermentation (L + F) and humus (H) layers. Carbon (C) and nitrogen (N) were determined by CN analyzer. The relationship between all calculated variables and the independent variable (D2H), derived to represent stand diameter at breast height (D1.3m) and tree height (H), was revealed by regression analysis. Average foliage mass was determined as 8 t/ha, C as 4 tC/ha, and N as 0.08 tN/ha. The mean biomass, C, and N of forest floor were 40 t/ha, 12 tC/ha, and 0.3 tN/ha, respectively. Foliage C, N, and C/N ratio showed high relationships with D2H as R2adj = 0.779, R2adj = 0.798, and R2adj = 0.943, respectively. However, the differences between the variables of living and non-living components showed a linear regression relationship with stand development. The differences in forest floor − foliage values showed lower R2 values with D2H. C and N were stored primarily in living foliage in young maritime pine stands where forest floor accumulation is just beginning. However, in older stands, where forest floor has begun to accumulate, forest floor stores more C and N than live foliage. The average C/N ratio of 42.47 for the entire forest floor indicating decomposition is slow, and C and N storage role shifts to forest floor as the stand develops.
{"title":"Biomass, Carbon, and Nitrogen Relations Between Tree Foliage and Organic Soil Layers With Stand Development of Pinus pinaster Over Dune Restoration","authors":"Servet Pehlivan, Ender Makineci, Alper Gün Özturna, Doğanay Tolunay","doi":"10.1002/ldr.70507","DOIUrl":"https://doi.org/10.1002/ldr.70507","url":null,"abstract":"This study aimed to address the knowledge gap by examining the dynamics of biomass, carbon, and nitrogen pools between foliage and forest floor throughout the development of <i>Pinus pinaster</i> plantations in the restoration site of Durusu coastal dune ecosystem in Istanbul-Türkiye. Live foliage biomass was determined by destructive sampling, while forest floor sampling was carried out separately from litter + fermentation (L + F) and humus (H) layers. Carbon (C) and nitrogen (N) were determined by CN analyzer. The relationship between all calculated variables and the independent variable (D<sup>2</sup>H), derived to represent stand diameter at breast height (D<sub>1.3m</sub>) and tree height (H), was revealed by regression analysis. Average foliage mass was determined as 8 t/ha, C as 4 tC/ha, and N as 0.08 tN/ha. The mean biomass, C, and N of forest floor were 40 t/ha, 12 tC/ha, and 0.3 tN/ha, respectively. Foliage C, N, and C/N ratio showed high relationships with D<sup>2</sup>H as <i>R</i><sup>2</sup><sub>adj</sub> = 0.779, <i>R</i><sup>2</sup><sub>adj</sub> = 0.798, and <i>R</i><sup>2</sup><sub>adj</sub> = 0.943, respectively. However, the differences between the variables of living and non-living components showed a linear regression relationship with stand development. The differences in forest floor − foliage values showed lower <i>R</i><sup>2</sup> values with D<sup>2</sup>H. C and N were stored primarily in living foliage in young maritime pine stands where forest floor accumulation is just beginning. However, in older stands, where forest floor has begun to accumulate, forest floor stores more C and N than live foliage. The average C/N ratio of 42.47 for the entire forest floor indicating decomposition is slow, and C and N storage role shifts to forest floor as the stand develops.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"107 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146210512","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}
Xiaoying Jin, Wanling Ji, Mingzhen Xing, Xiao Wang, Xiuyan Wang, Shuo Lv, Zhangliu Du
Intensive agriculture may cause substantial soil quality deterioration, leading to decreased crop production, especially under over-use of chemical fertilizers. Despite this, the effects of bio-organic substitutions on soil quality development via soil organic carbon (SOC) chemistry and soil structure remain largely unexplored. Herein, we characterized the changes in soil aggregation and cementing agents involved, image-based pore structure, hydraulic functions, and their connections to soil quality index from a 4-year field trial in North China. Four treatments included: chemical fertilizer alone (CF), 20% bio-organic fertilizer substitution (Bio20), 50% bio-organic fertilizer substitution (Bio50), and 100% bio-organic fertilizer substitution (Bio100). The results showed that Bio20 and Bio100 enhanced soil macroaggregates by 57.0%–61.1% and mean weight diameter by 71.5%–75.4% in comparison to CF. This improvement may likely be attributed to the increased cementing agents (e.g., SOC, extracellular polymeric substances, glomalin-related soil proteins). Bio50 and Bio100 also enhanced fungal necromass C and its contribution to SOC compared to CF. Bio-organic substitutions enhanced the 3D pore structure, showing higher image-identified porosity by 1.0–2.9 times, and pore anisotropy by 48.8%–63.2%. The enhanced soil structure in the bio-organic substituted soils potentially improved water holding capacity by 32.3%–51.6% and saturated hydraulic conductivity by 0.7–1.8 times versus control. Overall, bio-organic substitutions improved S value by 71.3%–144.2%, indicator of soil physical quality, and soil quality index by 25.9%–34.7% relative to control. Collectively, substituting partial chemical fertilizers with bio-organic fertilizers could boost soil quality via augmenting fungal necromass and soil structure, offering effective and economic solutions for revitalizing light saline soil under an intensive cropping system.
{"title":"Bio-Organic Substitutions Reinforce Soil Quality Driven by Fungal Necromass and Soil Structure in a Light Saline Soil","authors":"Xiaoying Jin, Wanling Ji, Mingzhen Xing, Xiao Wang, Xiuyan Wang, Shuo Lv, Zhangliu Du","doi":"10.1002/ldr.70495","DOIUrl":"https://doi.org/10.1002/ldr.70495","url":null,"abstract":"Intensive agriculture may cause substantial soil quality deterioration, leading to decreased crop production, especially under over-use of chemical fertilizers. Despite this, the effects of bio-organic substitutions on soil quality development via soil organic carbon (SOC) chemistry and soil structure remain largely unexplored. Herein, we characterized the changes in soil aggregation and cementing agents involved, image-based pore structure, hydraulic functions, and their connections to soil quality index from a 4-year field trial in North China. Four treatments included: chemical fertilizer alone (CF), 20% bio-organic fertilizer substitution (Bio<sub>20</sub>), 50% bio-organic fertilizer substitution (Bio<sub>50</sub>), and 100% bio-organic fertilizer substitution (Bio<sub>100</sub>). The results showed that Bio<sub>20</sub> and Bio<sub>100</sub> enhanced soil macroaggregates by 57.0%–61.1% and mean weight diameter by 71.5%–75.4% in comparison to CF. This improvement may likely be attributed to the increased cementing agents (e.g., SOC, extracellular polymeric substances, glomalin-related soil proteins). Bio<sub>50</sub> and Bio<sub>100</sub> also enhanced fungal necromass C and its contribution to SOC compared to CF. Bio-organic substitutions enhanced the 3D pore structure, showing higher image-identified porosity by 1.0–2.9 times, and pore anisotropy by 48.8%–63.2%. The enhanced soil structure in the bio-organic substituted soils potentially improved water holding capacity by 32.3%–51.6% and saturated hydraulic conductivity by 0.7–1.8 times versus control. Overall, bio-organic substitutions improved S value by 71.3%–144.2%, indicator of soil physical quality, and soil quality index by 25.9%–34.7% relative to control. Collectively, substituting partial chemical fertilizers with bio-organic fertilizers could boost soil quality via augmenting fungal necromass and soil structure, offering effective and economic solutions for revitalizing light saline soil under an intensive cropping system.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"413 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146210326","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}
Li Junwen, Urszula Mentel, Kamil Gemra, Mohd Ziaur Rehman, Péter Németh
Sustainable forest landscape, digitalization, and green energy are the core pillars of the European Union's policies to achieve sustainable growth; however, their impacts are divergent due to variant regional forest management policies, economic structures, and digital transformation. This study contributes to the literature by uniquely evaluating the asymmetric impacts of forest access, green energy, and digitalization on sustainable growth across the EU countries from 1991 to 2022. It introduces the moderating role of digitalization on forest access, a dimension that has been unexplored previously. This analysis employs the method of moments quantile regression (MMQR) to address the slope heterogeneity and cross‐sectional problems. The outcomes exhibit that green energy and digitalization are the drivers of sustainable growth, while their effects are pronounced at higher and lower growth quantiles, respectively. In contrast, forest access inhibits economic sustainability, with larger impacts realized in high‐growth economies. The interaction term indicates that the applications of digital technologies in the forest landscape significantly support sustainable growth. The robustness analysis confirms the consistency of regression outcomes. These insights offer novel implications for EU climate and digital policy integration under the Green Deal and REPower EU agenda.
{"title":"Leveraging Forest Resources, Green Energy, and Digitalization: Contextual Evidence Apropos Sustainable Growth in the Lens of Climate Resilience Policies","authors":"Li Junwen, Urszula Mentel, Kamil Gemra, Mohd Ziaur Rehman, Péter Németh","doi":"10.1002/ldr.70413","DOIUrl":"https://doi.org/10.1002/ldr.70413","url":null,"abstract":"Sustainable forest landscape, digitalization, and green energy are the core pillars of the European Union's policies to achieve sustainable growth; however, their impacts are divergent due to variant regional forest management policies, economic structures, and digital transformation. This study contributes to the literature by uniquely evaluating the asymmetric impacts of forest access, green energy, and digitalization on sustainable growth across the EU countries from 1991 to 2022. It introduces the moderating role of digitalization on forest access, a dimension that has been unexplored previously. This analysis employs the method of moments quantile regression (MMQR) to address the slope heterogeneity and cross‐sectional problems. The outcomes exhibit that green energy and digitalization are the drivers of sustainable growth, while their effects are pronounced at higher and lower growth quantiles, respectively. In contrast, forest access inhibits economic sustainability, with larger impacts realized in high‐growth economies. The interaction term indicates that the applications of digital technologies in the forest landscape significantly support sustainable growth. The robustness analysis confirms the consistency of regression outcomes. These insights offer novel implications for EU climate and digital policy integration under the Green Deal and REPower EU agenda.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"14 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146184343","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}
The interactive effects of gravel content and slope gradient on soil erosion processes of sloping farmland remain inadequately quantified, limiting predictive capabilities and effective conservation. This study investigated how gravel content, rainfall intensity, and slope gradient collectively influenced the particle size distribution of eroded sediment, thereby advancing the mechanistic understanding of soil erosion processes on sloping farmland containing gravel. Through simulated rainfall experiments, the results demonstrated that sediment yield was more sensitive to rainfall intensity than to other factors, and slopes containing gravel generally yielded more sediment than those without gravel. Fine sand, which accounted for 49%–56%, was the dominant fraction, with a clear coarsening trend observed under higher rainfall intensities. Critically, gravel presence significantly altered sediment structure, reducing the mean weight diameter (MWD) while increasing the fractal dimension ( D ). A key finding was the significant interactive effect ( p < 0.05) between gravel content and slope gradient on particle sorting. The treatment with 20% gravel content and a 15° slope gradient was identified as optimal, promoting the enrichment of clay and silt and suggesting improved aggregate stability and permeability. The findings reveal the complex role of gravel in erosion processes, highlighting its potential to exacerbate sediment yield under certain conditions. The results of this study provide theoretical and data‐based support for the management and conservation of sloping farmland containing gravel in the Three Gorges Reservoir area.
{"title":"Distribution Characteristics of Eroded Sediment Particles on Sloping Farmland Containing Gravel Under Simulated Rainfall Conditions","authors":"Bingqin Zhao, Xingfeng Zhang, Weihao Shi, Wanqing Zhu, Lun Zhang, Zhenyao Xia, Daxiang Liu, Zhongyi Wu, Ruzhang Gao, Wennian Xu","doi":"10.1002/ldr.70485","DOIUrl":"https://doi.org/10.1002/ldr.70485","url":null,"abstract":"The interactive effects of gravel content and slope gradient on soil erosion processes of sloping farmland remain inadequately quantified, limiting predictive capabilities and effective conservation. This study investigated how gravel content, rainfall intensity, and slope gradient collectively influenced the particle size distribution of eroded sediment, thereby advancing the mechanistic understanding of soil erosion processes on sloping farmland containing gravel. Through simulated rainfall experiments, the results demonstrated that sediment yield was more sensitive to rainfall intensity than to other factors, and slopes containing gravel generally yielded more sediment than those without gravel. Fine sand, which accounted for 49%–56%, was the dominant fraction, with a clear coarsening trend observed under higher rainfall intensities. Critically, gravel presence significantly altered sediment structure, reducing the mean weight diameter (MWD) while increasing the fractal dimension ( <jats:italic>D</jats:italic> ). A key finding was the significant interactive effect ( <jats:italic>p</jats:italic> < 0.05) between gravel content and slope gradient on particle sorting. The treatment with 20% gravel content and a 15° slope gradient was identified as optimal, promoting the enrichment of clay and silt and suggesting improved aggregate stability and permeability. The findings reveal the complex role of gravel in erosion processes, highlighting its potential to exacerbate sediment yield under certain conditions. The results of this study provide theoretical and data‐based support for the management and conservation of sloping farmland containing gravel in the Three Gorges Reservoir area.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"34 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146169797","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}
Climate change threatens global food security significantly, especially in agriculture where drought poses a major challenge. This study examines adoption dynamics and economic benefits of drought‐resistant crops among smallholder farmers in China's degraded, highly vulnerable ecosystems. The objective is to analyze adoption determinants and assess impacts on crop yields and agricultural income, while evaluating government policies' role in facilitating adoption. We hypothesize that policy support, education, and farm characteristics positively influence adoption, while adoption improves economic outcomes. The purpose is to inform policy for sustainable agriculture in drought‐prone areas. Using data from China Household Income Project surveys (2002, 2007, 2013) and regional agricultural statistics, we apply econometric models, including probit for adoption determinants and fixed effects for economic benefits. Results indicate adoption rates rose from 20% in 2002 to 76.3% in 2013, driven by policy support, education, farm size, and household income, while age negatively affects adoption. Adoption boosts crop yields by 0.3 tons per hectare and agricultural income by 437 yuan, with larger benefits in degraded ecosystems. These findings underscore targeted policies' importance in promoting climate‐smart agriculture and building resilience in vulnerable regions. The study concludes that government support, including extension services and subsidies, is essential for widespread adoption, advancing sustainable development and food security.
{"title":"Adoption Dynamics and Economic Benefits of Drought‐Resistant Crops Among Smallholder Farmers in Degraded Ecosystems","authors":"Xinyi Huang, Cheng Chen","doi":"10.1002/ldr.70480","DOIUrl":"https://doi.org/10.1002/ldr.70480","url":null,"abstract":"Climate change threatens global food security significantly, especially in agriculture where drought poses a major challenge. This study examines adoption dynamics and economic benefits of drought‐resistant crops among smallholder farmers in China's degraded, highly vulnerable ecosystems. The objective is to analyze adoption determinants and assess impacts on crop yields and agricultural income, while evaluating government policies' role in facilitating adoption. We hypothesize that policy support, education, and farm characteristics positively influence adoption, while adoption improves economic outcomes. The purpose is to inform policy for sustainable agriculture in drought‐prone areas. Using data from China Household Income Project surveys (2002, 2007, 2013) and regional agricultural statistics, we apply econometric models, including probit for adoption determinants and fixed effects for economic benefits. Results indicate adoption rates rose from 20% in 2002 to 76.3% in 2013, driven by policy support, education, farm size, and household income, while age negatively affects adoption. Adoption boosts crop yields by 0.3 tons per hectare and agricultural income by 437 yuan, with larger benefits in degraded ecosystems. These findings underscore targeted policies' importance in promoting climate‐smart agriculture and building resilience in vulnerable regions. The study concludes that government support, including extension services and subsidies, is essential for widespread adoption, advancing sustainable development and food security.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"14 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146169505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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