Mining activities severely disturb land surfaces and hydrological processes, intensifying hillslope erosion and soil loss. To evaluate the effectiveness of post‐mining restoration measures and identify the factors regulating their performance, we compiled a global dataset of runoff and soil erosion yield from 58 studies spanning multiple mine types, climatic zones, and restoration practices, and conducted a weighted meta‐analysis using random‐effects models. Overall, restoration measures reduced runoff by 49.0% and soil erosion yield by 67.6%, with consistently greater reductions in soil erosion. Combined measures were most effective, whereas soil amendment alone showed the weakest runoff reduction (21.1%). Runoff reduction increased with restoration duration, while soil erosion control was strong initially but showed a transient decline before recovering. Restoration effectiveness also varied substantially among mine types and environmental conditions. Soil erosion reduction was more sensitive than runoff to climatic and topographic factors, with higher rainfall intensity and steeper slopes generally weakening both runoff and soil erosion control. Slopes longer than 15 m sharply reduced soil erosion control (56.9% vs. > 70% on shorter slopes). Vegetation cover further revealed contrasting responses: runoff reduction plateaued at approximately 40% cover, whereas soil erosion reduction continued to increase up to 80%–100% cover. These findings demonstrate that post‐mining restoration effectiveness is jointly regulated by restoration strategy, recovery duration, and site conditions, highlighting the need for context‐specific combinations of restoration measures, vegetation targets, and landform configurations.
{"title":"Post‐Mining Conservation Measures for Erosion Control: A Global Assessment of Their Effectiveness on Runoff and Soil Erosion Reduction","authors":"Liangang Xiao, Wenlong Liu, Rongqin Zhao, Zhixiang Xie","doi":"10.1002/ldr.70948","DOIUrl":"https://doi.org/10.1002/ldr.70948","url":null,"abstract":"Mining activities severely disturb land surfaces and hydrological processes, intensifying hillslope erosion and soil loss. To evaluate the effectiveness of post‐mining restoration measures and identify the factors regulating their performance, we compiled a global dataset of runoff and soil erosion yield from 58 studies spanning multiple mine types, climatic zones, and restoration practices, and conducted a weighted meta‐analysis using random‐effects models. Overall, restoration measures reduced runoff by 49.0% and soil erosion yield by 67.6%, with consistently greater reductions in soil erosion. Combined measures were most effective, whereas soil amendment alone showed the weakest runoff reduction (21.1%). Runoff reduction increased with restoration duration, while soil erosion control was strong initially but showed a transient decline before recovering. Restoration effectiveness also varied substantially among mine types and environmental conditions. Soil erosion reduction was more sensitive than runoff to climatic and topographic factors, with higher rainfall intensity and steeper slopes generally weakening both runoff and soil erosion control. Slopes longer than 15 m sharply reduced soil erosion control (56.9% vs. > 70% on shorter slopes). Vegetation cover further revealed contrasting responses: runoff reduction plateaued at approximately 40% cover, whereas soil erosion reduction continued to increase up to 80%–100% cover. These findings demonstrate that post‐mining restoration effectiveness is jointly regulated by restoration strategy, recovery duration, and site conditions, highlighting the need for context‐specific combinations of restoration measures, vegetation targets, and landform configurations.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"21 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149292566","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}
Shiya Mao, Yuxin Hu, Yihang Jiang, Jun Chen, Xiongqing Zhang
Chinese fir ( Cunninghamia lanceolata ) plantations in southern China are often limited by phosphorus (P) availability, constraining productivity and sustainable management. We hypothesized that multi‐species, multilayered, uneven‐aged configurations would enhance soil P availability by regulating P fractions and microbial P transformation. This study aimed to identify the optimal tree species configuration for alleviating P limitation and improving soil quality. Four configurations were compared: pure Chinese fir (M0), Chinese fir + Phoebe bournei (M1), Chinese fir + P. bournei + Taxus wallichiana var. chinensis (M2), and Chinese fir + P. bournei + T. wallichiana var. chinensis + Schima superba (M3). Soil samples were collected from the 0–20, 20–40 and 40–60 cm layers and analysed for P fractions, acid phosphatase (ACP) activity, soil properties, and bacterial and fungal communities. Multivariate analysis, network analysis, structural equation modelling (SEM), and soil quality index (SQI) analysis were used to identify regulatory pathways. Different tree species configurations significantly altered soil P pool composition and its vertical distribution. Mixed configurations increased organic phosphorus (Po) and available phosphorus (AP), mainly enhanced surface soil organic matter (SOM) and total nitrogen (TN), and reshaped bacterial and fungal communities. M1 was enriched in P‐activating fungi such as Penicillium and Trichoderma , whereas M2 exhibited the highest fungal network complexity and SQI value, as well as higher AP content than the pure plantation. SEM indicated that available Fe (AFe) was an important driver of AP formation, while Al‐bound P (AlP) and occluded P (OP) negatively affected AP. Overall, M2 was the most favorable configuration for improving soil P availability and soil quality.
中国南方杉木（Cunninghamia lanceolata）人工林经常受到磷(P)可用性的限制，制约了生产力和可持续管理。我们假设多物种、多层、不均匀年龄的配置可以通过调节磷组分和微生物磷转化来提高土壤磷有效性。本研究旨在确定缓解磷限制和改善土壤质量的最佳树种配置。比较了纯杉木（M0）、杉木+白僵木（M1）、杉木+白僵木+红豆杉（M2）、杉木+白僵木+木荷（M3） 4种配置。在0-20、20-40和40-60 cm土层采集土壤样品，分析P组分、酸性磷酸酶（ACP）活性、土壤性质和细菌和真菌群落。采用多变量分析、网络分析、结构方程模型（SEM）和土壤质量指数（SQI）分析来确定调控途径。不同树种配置对土壤磷库组成和垂直分布有显著影响。混合配置增加了有机磷（Po）和速效磷（AP），主要增加了表层土壤有机质（SOM）和全氮（TN），重塑了细菌和真菌群落。M1富含P激活真菌，如青霉菌和木霉，而M2表现出最高的真菌网络复杂性和SQI值，并且AP含量高于纯人工林。SEM结果表明，有效态Fe （AFe）是AP形成的重要驱动因子，而Al - bound P （Al -磷）和occluded P （O -磷）则对AP产生负向影响。总体而言，M2是改善土壤P有效性和土壤质量的最有利配置。
{"title":"Tree Species Configuration Shapes Soil Phosphorus Fractions and Microbial Communities in Uneven‐Aged Multilayered Chinese Fir–Broadleaved Mixed Forests","authors":"Shiya Mao, Yuxin Hu, Yihang Jiang, Jun Chen, Xiongqing Zhang","doi":"10.1002/ldr.70933","DOIUrl":"https://doi.org/10.1002/ldr.70933","url":null,"abstract":"Chinese fir ( <jats:styled-content style=\"fixed-case\"> <jats:italic>Cunninghamia lanceolata</jats:italic> </jats:styled-content> ) plantations in southern China are often limited by phosphorus (P) availability, constraining productivity and sustainable management. We hypothesized that multi‐species, multilayered, uneven‐aged configurations would enhance soil P availability by regulating P fractions and microbial P transformation. This study aimed to identify the optimal tree species configuration for alleviating P limitation and improving soil quality. Four configurations were compared: pure Chinese fir (M0), Chinese fir + <jats:italic>Phoebe bournei</jats:italic> (M1), Chinese fir + <jats:italic>P. bournei</jats:italic> + <jats:italic>Taxus wallichiana</jats:italic> var. <jats:italic>chinensis</jats:italic> (M2), and Chinese fir + <jats:italic>P. bournei</jats:italic> + <jats:italic>T. wallichiana</jats:italic> var. <jats:italic>chinensis</jats:italic> + <jats:italic>Schima superba</jats:italic> (M3). Soil samples were collected from the 0–20, 20–40 and 40–60 cm layers and analysed for P fractions, acid phosphatase (ACP) activity, soil properties, and bacterial and fungal communities. Multivariate analysis, network analysis, structural equation modelling (SEM), and soil quality index (SQI) analysis were used to identify regulatory pathways. Different tree species configurations significantly altered soil P pool composition and its vertical distribution. Mixed configurations increased organic phosphorus (Po) and available phosphorus (AP), mainly enhanced surface soil organic matter (SOM) and total nitrogen (TN), and reshaped bacterial and fungal communities. M1 was enriched in P‐activating fungi such as <jats:italic>Penicillium</jats:italic> and <jats:italic>Trichoderma</jats:italic> , whereas M2 exhibited the highest fungal network complexity and SQI value, as well as higher AP content than the pure plantation. SEM indicated that available Fe (AFe) was an important driver of AP formation, while Al‐bound P (AlP) and occluded P (OP) negatively affected AP. Overall, M2 was the most favorable configuration for improving soil P availability and soil quality.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"84 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149292567","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}
Drip irrigation is widely used to conserve water and maintain crop production in water‐limited regions. However, how contrasting drip irrigation systems shape soil water‐salt movement, water and nitrogen (N) use, and maize productivity in semi‐arid environments remains poorly understood. Here, we conducted a two‐year field experiment (2019–2020) with a randomized complete block design to compare shallow buried drip irrigation (SBDI) and mulched drip irrigation (MDI). Relative to MDI, SBDI increased grain yield, dry matter accumulation, and N uptake by 5.86%, 3.11%, and 9.58%, respectively, contributin to greater water and N use efficiency. Soil salinity dynamics were closely coupled with soil water movement, representing a remarkable accumulation in the 0–20 cm soil layer under SBDI compared to MDI, owing to higher evapotranspiration. Although both irrigation systems resulted in soil salt accumulation, SBDI was more conducive for chloride ion elution. Partial least squares path modeling, Random forest, and Mantel tests suggested that water N utilization and salt dynamics were highly related to maize productivity. Our findings enrich the theoretical framework for preventing secondary soil salinization by inhibiting soil resalinization via water regulation or interlayer installation. In the future, the integration of SBDI with desalination measures may be a crucial strategy for enabling sustainable high‐yield maize production in semi‐arid regions.
{"title":"Trade‐Offs Between Maize Productivity Improvement and Topsoil Salinization Risk Under Shallow Burial Drip Irrigation in Semi‐Arid Regions","authors":"Ruifu Zhang, Zhengyu Wang, Xuanliang Ge, Fanhao Meng, Shaokun Li, Hengshan Yang","doi":"10.1002/ldr.70932","DOIUrl":"https://doi.org/10.1002/ldr.70932","url":null,"abstract":"Drip irrigation is widely used to conserve water and maintain crop production in water‐limited regions. However, how contrasting drip irrigation systems shape soil water‐salt movement, water and nitrogen (N) use, and maize productivity in semi‐arid environments remains poorly understood. Here, we conducted a two‐year field experiment (2019–2020) with a randomized complete block design to compare shallow buried drip irrigation (SBDI) and mulched drip irrigation (MDI). Relative to MDI, SBDI increased grain yield, dry matter accumulation, and N uptake by 5.86%, 3.11%, and 9.58%, respectively, contributin to greater water and N use efficiency. Soil salinity dynamics were closely coupled with soil water movement, representing a remarkable accumulation in the 0–20 cm soil layer under SBDI compared to MDI, owing to higher evapotranspiration. Although both irrigation systems resulted in soil salt accumulation, SBDI was more conducive for chloride ion elution. Partial least squares path modeling, Random forest, and Mantel tests suggested that water N utilization and salt dynamics were highly related to maize productivity. Our findings enrich the theoretical framework for preventing secondary soil salinization by inhibiting soil resalinization via water regulation or interlayer installation. In the future, the integration of SBDI with desalination measures may be a crucial strategy for enabling sustainable high‐yield maize production in semi‐arid regions.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"84 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149274696","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}
Soil erosion poses a critical threat to ecological security in mountain watersheds worldwide. Predicting its dynamics and associated soil organic carbon (SOC) loss remains an ongoing challenge during the 21st century due to complex interactions among climate, land use, and topography. This study developed an integrated modeling framework by combining Long Short‐Term Memory (LSTM) neural networks, Cellular Automata‐Markov (CA‐Markov), and the InVEST Sediment Delivery Ratio module to predict soil erosion and SOC loss in the Dayekou Watershed in northwest China's Qilian Mountains. LSTM accurately forecasted 48 months of rainfall (RMSE: 177.9–211.7) using 300 months of historical data (2000–2024), while CA‐Markov simulated land use patterns (2024–2028) with high precision (Kappa = 0.85). Results revealed that severe erosion areas (< 9% of watershed) contribute > 97% of total soil loss, concentrated above 3750 m elevation of the watershed. Land use type dominated erosion spatial distribution ( q = 78.8%), with glacier/snow and bare land exhibiting the highest erosion modulus. Average SOC loss increased from 9.877 to 21.524 t/(km 2 ·a) (2000–2023), with forested areas experiencing disproportionate carbon depletion despite lower erosion rates. The coupled framework demonstrates its robustness in predicting dynamic erosion in complex mountain systems, providing strong evidence‐based conservation support for protected areas in northwest China.
{"title":"Integrated Prediction and Analysis of Soil Erosion and Soil Organic Carbon Loss in the Dayekou Watershed, Qilian Mountains","authors":"Yongde Kang, Shizhe Han, Xiaofeng Ren, Erwen Xu","doi":"10.1002/ldr.70935","DOIUrl":"https://doi.org/10.1002/ldr.70935","url":null,"abstract":"Soil erosion poses a critical threat to ecological security in mountain watersheds worldwide. Predicting its dynamics and associated soil organic carbon (SOC) loss remains an ongoing challenge during the 21st century due to complex interactions among climate, land use, and topography. This study developed an integrated modeling framework by combining Long Short‐Term Memory (LSTM) neural networks, Cellular Automata‐Markov (CA‐Markov), and the InVEST Sediment Delivery Ratio module to predict soil erosion and SOC loss in the Dayekou Watershed in northwest China's Qilian Mountains. LSTM accurately forecasted 48 months of rainfall (RMSE: 177.9–211.7) using 300 months of historical data (2000–2024), while CA‐Markov simulated land use patterns (2024–2028) with high precision (Kappa = 0.85). Results revealed that severe erosion areas (< 9% of watershed) contribute > 97% of total soil loss, concentrated above 3750 m elevation of the watershed. Land use type dominated erosion spatial distribution ( <jats:italic>q</jats:italic> = 78.8%), with glacier/snow and bare land exhibiting the highest erosion modulus. Average SOC loss increased from 9.877 to 21.524 t/(km <jats:sup>2</jats:sup> ·a) (2000–2023), with forested areas experiencing disproportionate carbon depletion despite lower erosion rates. The coupled framework demonstrates its robustness in predicting dynamic erosion in complex mountain systems, providing strong evidence‐based conservation support for protected areas in northwest China.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"20 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149274695","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}
Eve McCallum, Cameron Blackburn, Monte Masarei, Andrew Guzzomi, Sally Thompson
Understanding how rehabilitation measures, such as landform shaping, and surface finishes impact gully erosion risk could assist in designing less erosive rehabilitation. In this study we use high resolution digital elevation models of rehabilitated mine pits to explore risk factors for gully formation. We determine features that pre‐dispose rehabilitated mining pits to gully formation, how topographic features vary across these areas, and generate a binomial regression and a random forest model relating surface features to erosion risk. These models are benchmarked against the ‘topographic threshold’. We found topographic features, like hillslope gradient and curvature, which concentrate and accelerate runoff were overrepresented at gully heads, while at the mine pit level, erosion risk can be predicted by surface area and average pit hillslope gradient, providing a high‐level risk screening tool. The topographic threshold, applied with high resolution accumulation data, outperformed the random forest and logistic regression models in predicting risk from topographic features alone. Despite being based on post‐erosion data, the topographic threshold performs well to predict erosion risk across rehabilitated mining areas. The method balances data requirements with prediction accuracy and is a conservative approach to highlighting risk areas within rehabilitated pits. The random forest and regression approaches underpredicted gully locations, in contrast with the topographic thresholds over prediction, which limits their utility without additional inputs. Operators have opportunities to collect additional data during rehabilitation that could build better predictive models. Informed rehabilitation design offers the opportunity to avoid, where possible, features that occur more commonly in conjunction with erosion.
{"title":"Eroding Confidence in Gully Location Risk Prediction in Mine Pit Rehabilitation","authors":"Eve McCallum, Cameron Blackburn, Monte Masarei, Andrew Guzzomi, Sally Thompson","doi":"10.1002/ldr.70930","DOIUrl":"https://doi.org/10.1002/ldr.70930","url":null,"abstract":"Understanding how rehabilitation measures, such as landform shaping, and surface finishes impact gully erosion risk could assist in designing less erosive rehabilitation. In this study we use high resolution digital elevation models of rehabilitated mine pits to explore risk factors for gully formation. We determine features that pre‐dispose rehabilitated mining pits to gully formation, how topographic features vary across these areas, and generate a binomial regression and a random forest model relating surface features to erosion risk. These models are benchmarked against the ‘topographic threshold’. We found topographic features, like hillslope gradient and curvature, which concentrate and accelerate runoff were overrepresented at gully heads, while at the mine pit level, erosion risk can be predicted by surface area and average pit hillslope gradient, providing a high‐level risk screening tool. The topographic threshold, applied with high resolution accumulation data, outperformed the random forest and logistic regression models in predicting risk from topographic features alone. Despite being based on post‐erosion data, the topographic threshold performs well to predict erosion risk across rehabilitated mining areas. The method balances data requirements with prediction accuracy and is a conservative approach to highlighting risk areas within rehabilitated pits. The random forest and regression approaches underpredicted gully locations, in contrast with the topographic thresholds over prediction, which limits their utility without additional inputs. Operators have opportunities to collect additional data during rehabilitation that could build better predictive models. Informed rehabilitation design offers the opportunity to avoid, where possible, features that occur more commonly in conjunction with erosion.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"11 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149274697","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}
Leila Kashi Zenouzi, Ahmad Asgharzadeh, Federico Rossi, Mohammad Khosroshahi, Seyed Hassan Kaboli
Establishing biocrusts on sandy surfaces in harsh desert environments presents significant challenges due to extreme ecological conditions. To address these challenges, this study examined the effects of two organic superabsorbent cellulosic polymers (OSCPs)—carboxymethyl cellulose (CMC) and guar gum (GUA)—on the establishment of cyanobacterial crusts on aeolian sands, specifically using a consortium of Nostoc sp. and Microcoleus vaginatus . The optimal concentrations of GUA and CMC for maximum cyanobacterial growth were determined through preliminary optimization assays. The resulting suspensions, combining OSCPs and cyanobacteria, were applied to sandy substrates. After 60 days of inoculation, the cyanobacterial crusts were analyzed for exopolysaccharide (EPS) accumulation, chlorophyll a content, physical and chemical properties, shear strength, and compressive strength. Additionally, wind tunnel tests were conducted to measure aeolian mass flux under the different treatments. Results indicated that the cyanobacteria + CMC treatment outperformed all others, increasing chlorophyll a by 114% and EPS production by 108% to 280% depending on the EPS fraction. This treatment also enhanced organic carbon and nitrogen accumulation, crust thickness (~21 mm), shear strength (51.39 kPa), and available water capacity (+110%). Furthermore, it raised the wind erosion threshold velocity from 11.5 to 19.7 m s −1 , reducing aeolian mass flux by over 98% at wind speeds up to 19.7 m s −1 . In contrast, GUA alone resulted in the lowest compressive strength and mass flux rates. These findings suggest that combining cyanobacteria with OSCPs, particularly CMC, is an effective strategy for promoting biocrust formation and mitigating soil erosion in arid environments.
由于极端的生态条件，在恶劣的沙漠环境中，在沙质表面建立生物外壳提出了重大挑战。为了解决这些挑战，本研究考察了两种有机高吸水性纤维素聚合物(oscp) -羧甲基纤维素（CMC）和瓜尔胶(GUA) -对在风沙上建立蓝藻结壳的影响，特别是使用Nostoc sp.和Microcoleus vaginatus。通过初步优化实验，确定了藻蓝菌最大生长的最佳GUA和CMC浓度。所得到的悬浮液，结合oscp和蓝藻，被应用于沙质基质。接种60 d后，对蓝藻结壳进行胞外多糖（EPS）积累、叶绿素a含量、理化性质、抗剪强度和抗压强度分析。此外，还进行了风洞试验，测量了不同处理下的风质量通量。结果表明，蓝藻+ CMC处理的效果优于其他处理，根据EPS组分的不同，叶绿素a提高了114%，EPS产量提高了108%至280%。有机碳氮积累量显著提高，结皮厚度（~21 mm），抗剪强度（51.39 kPa），有效水量（+110%）显著提高。将风蚀阈值速度从11.5 m s−1提高到19.7 m s−1，使风速达到19.7 m s−1时的风沙质量通量减少98%以上。相反，单独使用GUA会导致最低的抗压强度和质量通量率。这些发现表明，在干旱环境中，将蓝藻与oscp（特别是CMC）结合是促进生物结皮和减轻土壤侵蚀的有效策略。
{"title":"Application of Organic Superabsorbent Cellulosic Polymers ( OSCPs ) and Cyanobacteria on Reduction of Aeolian Losses","authors":"Leila Kashi Zenouzi, Ahmad Asgharzadeh, Federico Rossi, Mohammad Khosroshahi, Seyed Hassan Kaboli","doi":"10.1002/ldr.70924","DOIUrl":"https://doi.org/10.1002/ldr.70924","url":null,"abstract":"Establishing biocrusts on sandy surfaces in harsh desert environments presents significant challenges due to extreme ecological conditions. To address these challenges, this study examined the effects of two organic superabsorbent cellulosic polymers (OSCPs)—carboxymethyl cellulose (CMC) and guar gum (GUA)—on the establishment of cyanobacterial crusts on aeolian sands, specifically using a consortium of <jats:italic>Nostoc</jats:italic> sp. and <jats:styled-content style=\"fixed-case\"> <jats:italic>Microcoleus vaginatus</jats:italic> </jats:styled-content> . The optimal concentrations of GUA and CMC for maximum cyanobacterial growth were determined through preliminary optimization assays. The resulting suspensions, combining OSCPs and cyanobacteria, were applied to sandy substrates. After 60 days of inoculation, the cyanobacterial crusts were analyzed for exopolysaccharide (EPS) accumulation, chlorophyll <jats:italic>a</jats:italic> content, physical and chemical properties, shear strength, and compressive strength. Additionally, wind tunnel tests were conducted to measure aeolian mass flux under the different treatments. Results indicated that the cyanobacteria + CMC treatment outperformed all others, increasing chlorophyll <jats:italic>a</jats:italic> by 114% and EPS production by 108% to 280% depending on the EPS fraction. This treatment also enhanced organic carbon and nitrogen accumulation, crust thickness (~21 mm), shear strength (51.39 kPa), and available water capacity (+110%). Furthermore, it raised the wind erosion threshold velocity from 11.5 to 19.7 m s <jats:sup>−1</jats:sup> , reducing aeolian mass flux by over 98% at wind speeds up to 19.7 m s <jats:sup>−1</jats:sup> . In contrast, GUA alone resulted in the lowest compressive strength and mass flux rates. These findings suggest that combining cyanobacteria with OSCPs, particularly CMC, is an effective strategy for promoting biocrust formation and mitigating soil erosion in arid environments.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"5 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149232275","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}
Imbalances between ecosystem service (ES) supply and demand constrain ecological governance and sustainable development. While spatial patterns of these imbalances have been widely studied, less attention has been paid to the land‐use thresholds and regulatory mechanisms needed to maintain ES balance. Using Jiangxi Province as a case study, we developed a threshold‐based spatial regulation framework integrating ESs supply–demand ratio (SDR) analysis, key land‐use type identification, and management zoning. We quantified the spatiotemporal supply and demand of four ESs—carbon sequestration (CS), habitat quality (HQ), water yield (WY), and soil conservation (SC)—from 2003 to 2023. By combining boosted regression tree and segmented regression, we identified key land‐use types affecting ESs balance and their proportional thresholds, and used segmented regression breakpoints for differentiated spatial zoning. The results showed that although the supply of ESs generally exceeded demand, the imbalance intensified over time, particularly for WY and HQ, accompanied by significant spatial heterogeneity. Built‐up land, cropland, and forest land are the dominant land use types affecting the balance of ESs. Built‐up land negatively affected CS and HQ, cropland positively affected WY, HQ, and SC, forest land supported CS and WY, and water area promoted SC. Although land use in Jiangxi remained within the overall balance threshold, some areas approached critical points, with WY showing the smallest balanced area (75.39%). Based on current land‐use structure and ESs thresholds, three ESs management zones and 27 integrated zones were delineated, and differentiated land‐use regulation strategies were proposed, providing a scientific basis for ESs‐oriented spatial governance.
{"title":"Land‐Use Thresholds and Spatial Regulation Oriented Toward Ecosystem Service Supply–Demand Balance: A Case Study of Jiangxi Province","authors":"Yang Yang, Chunyan Li, Zhiyong Liu, Deqi Wang","doi":"10.1002/ldr.70920","DOIUrl":"https://doi.org/10.1002/ldr.70920","url":null,"abstract":"Imbalances between ecosystem service (ES) supply and demand constrain ecological governance and sustainable development. While spatial patterns of these imbalances have been widely studied, less attention has been paid to the land‐use thresholds and regulatory mechanisms needed to maintain ES balance. Using Jiangxi Province as a case study, we developed a threshold‐based spatial regulation framework integrating ESs supply–demand ratio (SDR) analysis, key land‐use type identification, and management zoning. We quantified the spatiotemporal supply and demand of four ESs—carbon sequestration (CS), habitat quality (HQ), water yield (WY), and soil conservation (SC)—from 2003 to 2023. By combining boosted regression tree and segmented regression, we identified key land‐use types affecting ESs balance and their proportional thresholds, and used segmented regression breakpoints for differentiated spatial zoning. The results showed that although the supply of ESs generally exceeded demand, the imbalance intensified over time, particularly for WY and HQ, accompanied by significant spatial heterogeneity. Built‐up land, cropland, and forest land are the dominant land use types affecting the balance of ESs. Built‐up land negatively affected CS and HQ, cropland positively affected WY, HQ, and SC, forest land supported CS and WY, and water area promoted SC. Although land use in Jiangxi remained within the overall balance threshold, some areas approached critical points, with WY showing the smallest balanced area (75.39%). Based on current land‐use structure and ESs thresholds, three ESs management zones and 27 integrated zones were delineated, and differentiated land‐use regulation strategies were proposed, providing a scientific basis for ESs‐oriented spatial governance.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"76 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149232277","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}
Min Wang, Mingjuan Li, Shuyuan Han, Zihao Sheng, Li He, Yang Yang
Understanding how climate and vegetation structural complexity jointly shape fungal communities is essential for effective roadside slope restoration. To address this, we examined restoration effects on fungal diversity, community composition, and ecological networks across three climatically distinct regions: dry‐hot valley, subalpine, and subtropical. In climatically stressful regions (i.e., dry‐hot valley and subalpine), plots with complex vegetation (Herb+Shrub, Herb+Shrub+Tree, and natural sites) harbored higher fungal diversity than herbaceous‐only plots. In contrast, subtropical herbaceous plots supported higher fungal diversity, likely due to disturbance‐induced niche heterogeneity. Fungal community composition differed significantly among climatic regions and vegetation types. Ascomycota was consistently dominant across all sites, whereas Mortierellomycota, Basidiomycota, and Rozellomycota exhibited distinct regional distributions. Network analyses revealed larger and more highly connected fungal networks in the subtropical and subalpine regions than in the dry‐hot valley, with topological keystone taxa identified only in the former two regions. Piecewise structural equation modeling further indicated that climate influenced fungal diversity indirectly via soil nutrients, while vegetation diversity exerted a direct effect. Collectively, these findings demonstrate that the effects of vegetation complexity on fungal communities are climate‐dependent, underscoring the need to integrate climatic context, vegetation management, soil nutrient regulation, and fungal ecological functions into roadside slope restoration.
{"title":"Divergent Responses of Fungal Communities to Vegetation Structural Complexity in Degraded Roadside Slopes Across Climatic Gradients","authors":"Min Wang, Mingjuan Li, Shuyuan Han, Zihao Sheng, Li He, Yang Yang","doi":"10.1002/ldr.70929","DOIUrl":"https://doi.org/10.1002/ldr.70929","url":null,"abstract":"Understanding how climate and vegetation structural complexity jointly shape fungal communities is essential for effective roadside slope restoration. To address this, we examined restoration effects on fungal diversity, community composition, and ecological networks across three climatically distinct regions: dry‐hot valley, subalpine, and subtropical. In climatically stressful regions (i.e., dry‐hot valley and subalpine), plots with complex vegetation (Herb+Shrub, Herb+Shrub+Tree, and natural sites) harbored higher fungal diversity than herbaceous‐only plots. In contrast, subtropical herbaceous plots supported higher fungal diversity, likely due to disturbance‐induced niche heterogeneity. Fungal community composition differed significantly among climatic regions and vegetation types. Ascomycota was consistently dominant across all sites, whereas Mortierellomycota, Basidiomycota, and Rozellomycota exhibited distinct regional distributions. Network analyses revealed larger and more highly connected fungal networks in the subtropical and subalpine regions than in the dry‐hot valley, with topological keystone taxa identified only in the former two regions. Piecewise structural equation modeling further indicated that climate influenced fungal diversity indirectly via soil nutrients, while vegetation diversity exerted a direct effect. Collectively, these findings demonstrate that the effects of vegetation complexity on fungal communities are climate‐dependent, underscoring the need to integrate climatic context, vegetation management, soil nutrient regulation, and fungal ecological functions into roadside slope restoration.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"30 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149221429","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}
Ruochen Jia, Chaoqun Ba, Jinlei Zhu, Wennong Kuang, Lu Zong, Fang Liu, Yuting Liu, Minghu Liu, Zhiming Xin, Zhimin Liu
Soil wind erosion is a major driver of atmospheric dust emissions and land degradation. Many studies have examined dust release from different substrates, but differences in methods and units still limit quantitative understanding of how surface conditions and wind jointly control dust emission and near‐surface transport. A closed‐circuit wind tunnel was used to compare dust emission and vertical transport from dune sand (sand, D50 = 176 μm), farmland soil (sandy loam, D50 = 86 μm), and dry lakebed sediments (sand, D50 = 153 μm). At 14 m s −1 , farmlands transported 6.2–7.2 times more PM 2.5 and 7.1–8.3 times more PM 10 than the other two substrates ( p < 0.001), while dunes and lakebeds transported more total mass. In the emitted material, dunes contributed the lowest fine particle proportion (PM 63 < 6.6%), farmlands maintained high fine fractions (PM 63 up to 55.5%), and lakebeds produced fine‐rich emissions at low wind speed but shifted towards low fine fractions as speed increased. Vertically, fine‐particle proportions increased with height over farmland soil across all wind speeds. Under the strongest wind, dune sand and dry lakebed sediment showed declining transported‐mass profiles and no significant height trends in particle‐size proportions. These results show that the surfaces that dominate total mass are not the same as those that dominate health‐relevant PM. This unified comparative analysis, grounded in controlled wind‐tunnel observations, supports targeted mitigation through modest‐height windbreaks for fine‐dust control on farmland, surface‐roughness enhancement on dunes, and crust stabilization on dry lakebeds.
{"title":"Differences in Dust Emission and Near‐Surface Transport Patterns Among Three Surface Substrate Types","authors":"Ruochen Jia, Chaoqun Ba, Jinlei Zhu, Wennong Kuang, Lu Zong, Fang Liu, Yuting Liu, Minghu Liu, Zhiming Xin, Zhimin Liu","doi":"10.1002/ldr.70925","DOIUrl":"https://doi.org/10.1002/ldr.70925","url":null,"abstract":"Soil wind erosion is a major driver of atmospheric dust emissions and land degradation. Many studies have examined dust release from different substrates, but differences in methods and units still limit quantitative understanding of how surface conditions and wind jointly control dust emission and near‐surface transport. A closed‐circuit wind tunnel was used to compare dust emission and vertical transport from dune sand (sand, <jats:italic>D</jats:italic> <jats:sub>50</jats:sub> = 176 μm), farmland soil (sandy loam, <jats:italic>D</jats:italic> <jats:sub>50</jats:sub> = 86 μm), and dry lakebed sediments (sand, <jats:italic>D</jats:italic> <jats:sub>50</jats:sub> = 153 μm). At 14 m s <jats:sup>−1</jats:sup> , farmlands transported 6.2–7.2 times more PM <jats:sub>2.5</jats:sub> and 7.1–8.3 times more PM <jats:sub>10</jats:sub> than the other two substrates ( <jats:italic>p</jats:italic> < 0.001), while dunes and lakebeds transported more total mass. In the emitted material, dunes contributed the lowest fine particle proportion (PM <jats:sub>63</jats:sub> < 6.6%), farmlands maintained high fine fractions (PM <jats:sub>63</jats:sub> up to 55.5%), and lakebeds produced fine‐rich emissions at low wind speed but shifted towards low fine fractions as speed increased. Vertically, fine‐particle proportions increased with height over farmland soil across all wind speeds. Under the strongest wind, dune sand and dry lakebed sediment showed declining transported‐mass profiles and no significant height trends in particle‐size proportions. These results show that the surfaces that dominate total mass are not the same as those that dominate health‐relevant PM. This unified comparative analysis, grounded in controlled wind‐tunnel observations, supports targeted mitigation through modest‐height windbreaks for fine‐dust control on farmland, surface‐roughness enhancement on dunes, and crust stabilization on dry lakebeds.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"2 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149198904","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}
Kristina E. Young, Nicholas P. Webb, Brandon T. Bestelmeyer, Matthew A. Bowker, Laura M. Burkett, Brandon L. Edwards, Jeffrey E. Herrick, Carrie‐Ann Houdeshell, Sarah E. McCord
Wind erosion and sand and dust storms are a global challenge. While many management practices to mitigate sources of wind erosion and sand and dust storms have been documented, existing guidance largely emphasizes what practices are available, with limited information on where and under what ecological conditions they should be applied. As a result, mitigation efforts can be ineffective or can exacerbate erosion when implemented without regard to local ecological context. Land potential, or the inherent capacity of land to support vegetation, soil stability, and productivity, provides a basis for aligning mitigation practices with a site's resistance and resilience to erosion. Here, we present a land potential‐based framework to improve the selection, implementation, and evaluation of wind erosion and sand and dust storm source mitigation practices across diverse landscapes. The framework uses land potential assessment with agroecological state concepts to guide decision‐making through the following steps: (1) characterize land potential by soils, topography, and climate to identify resistance and resilience to erosion; (2) identify agroecological states that capture vegetation–soil configurations, thresholds, and feedbacks determining erosion dynamics; (3) identify and monitor wind erosion risk and sand and dust storm source areas; (4) define mitigation targets and benchmarks that guide decision‐making; (5) identify and implement practices to avoid, reduce, reverse, or accept wind erosion; and (6) evaluate mitigation outcomes and adapt management. By linking local‐scale land assessments with mitigation practices, this framework increases the likelihood of successful mitigation and provides scalable decision support for advancing Land Degradation Neutrality and sustainable land management.
{"title":"A Land Potential‐Based Framework for Wind Erosion and Sand and Dust Storm Source Mitigation","authors":"Kristina E. Young, Nicholas P. Webb, Brandon T. Bestelmeyer, Matthew A. Bowker, Laura M. Burkett, Brandon L. Edwards, Jeffrey E. Herrick, Carrie‐Ann Houdeshell, Sarah E. McCord","doi":"10.1002/ldr.70913","DOIUrl":"https://doi.org/10.1002/ldr.70913","url":null,"abstract":"Wind erosion and sand and dust storms are a global challenge. While many management practices to mitigate sources of wind erosion and sand and dust storms have been documented, existing guidance largely emphasizes what practices are available, with limited information on where and under what ecological conditions they should be applied. As a result, mitigation efforts can be ineffective or can exacerbate erosion when implemented without regard to local ecological context. Land potential, or the inherent capacity of land to support vegetation, soil stability, and productivity, provides a basis for aligning mitigation practices with a site's resistance and resilience to erosion. Here, we present a land potential‐based framework to improve the selection, implementation, and evaluation of wind erosion and sand and dust storm source mitigation practices across diverse landscapes. The framework uses land potential assessment with agroecological state concepts to guide decision‐making through the following steps: (1) characterize land potential by soils, topography, and climate to identify resistance and resilience to erosion; (2) identify agroecological states that capture vegetation–soil configurations, thresholds, and feedbacks determining erosion dynamics; (3) identify and monitor wind erosion risk and sand and dust storm source areas; (4) define mitigation targets and benchmarks that guide decision‐making; (5) identify and implement practices to avoid, reduce, reverse, or accept wind erosion; and (6) evaluate mitigation outcomes and adapt management. By linking local‐scale land assessments with mitigation practices, this framework increases the likelihood of successful mitigation and provides scalable decision support for advancing Land Degradation Neutrality and sustainable land management.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"167 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149172772","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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