Xiaopeng Wang, Man Zhou, Zechuang Tan, Zumei Wang, Gengen Lin, Yue Zhang, Fangshi Jiang, Yanhe Huang, Jinshi Lin
Although artificial vegetation restoration measures decelerate soil erosion, the impacts on soil microbial communities and soil fertility remain unclear. This impedes our ability to assess the true effects of artificial vegetation restoration measures on degraded soil ecosystems. To address this issue, we used vegetation restoration plots in severely eroded areas in China as research objects and applied high-throughput sequencing technology to determine the composition of the soil bacterial and fungal communities. Compared with eroded sites, artificial vegetation restoration plots not only presented greater microbial diversity and network complexity but also presented increased resistance to environmental stress. Artificial vegetation restoration measures altered the microbial community composition by increasing the content of soil alkali-hydrolyzable nitrogen, reducing the relative abundance of dominant microbes such as Chloroflexi and Ascomycota. Changes in microbial community characteristics were closely associated with variations in a comprehensive index of soil fertility induced by artificial vegetation restoration measures. In summary, these results indicate that artificial vegetation restoration measures have significant positive impacts on the rehabilitation of degraded soil ecosystems.
{"title":"Artificial Vegetation Restoration Enhances Soil Fertility and Microbial Network Complexity in Eroded Areas","authors":"Xiaopeng Wang, Man Zhou, Zechuang Tan, Zumei Wang, Gengen Lin, Yue Zhang, Fangshi Jiang, Yanhe Huang, Jinshi Lin","doi":"10.1002/ldr.5388","DOIUrl":"https://doi.org/10.1002/ldr.5388","url":null,"abstract":"Although artificial vegetation restoration measures decelerate soil erosion, the impacts on soil microbial communities and soil fertility remain unclear. This impedes our ability to assess the true effects of artificial vegetation restoration measures on degraded soil ecosystems. To address this issue, we used vegetation restoration plots in severely eroded areas in China as research objects and applied high-throughput sequencing technology to determine the composition of the soil bacterial and fungal communities. Compared with eroded sites, artificial vegetation restoration plots not only presented greater microbial diversity and network complexity but also presented increased resistance to environmental stress. Artificial vegetation restoration measures altered the microbial community composition by increasing the content of soil alkali-hydrolyzable nitrogen, reducing the relative abundance of dominant microbes such as Chloroflexi and Ascomycota. Changes in microbial community characteristics were closely associated with variations in a comprehensive index of soil fertility induced by artificial vegetation restoration measures. In summary, these results indicate that artificial vegetation restoration measures have significant positive impacts on the rehabilitation of degraded soil ecosystems.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"18 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670417","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}
Feida Sun, Dewei Chen, Linhao Li, Qiaoqiao Zhang, Xin Yuan, Zihong Liao, Chunlian Xiang, Lin Liu, Jiqiong Zhou, Mani Shrestha, Dong Xu, Yanfu Bai, A. Allan Degen
Unmanned aerial vehicles (UAVs) are becoming important tools for modern management and scientific research of grassland resources, especially in the dynamic monitoring of above-ground biomass (AGB). However, current studies rely mostly on vertical images to construct models, with little consideration given to oblique images. Determination of image acquisition height often relies on experience and intuition, but there is limited comparison of models in estimating across different grassland types. To address this gap, this study selected 56 plots on the northern Qinghai–Tibetan Plateau (QTP), comprising 16 alpine meadows (AM), 14 alpine steppes (AS), 13 alpine meadow steppes (AMS), and 13 alpine desert steppes (ADS). We used the DJI Mavic 2 Pro to capture a total of 5040 images at six heights (5, 10, 20, 30, 40, and 50 m) and five angles (30°, 45°, 60°, 90°, and 180° panoramic shots). Based on RGB (red-green-blue) images, seven vegetation indices (normalized difference index (NDI), excess red vegetation index (EXR), modified green red vegetation index (MGRVI), visible atmospherically resistant index (VARI), excess green minus excess (EXG), green leaf index (GLI), and red–green–blue vegetation index (RGBVI)) were employed, displaying a trend in vegetation and biomass changes across different heights and angles, peaking at 20 m and 45°. Linear regression models and machine learning models (random forest, extreme gradient boosting, multilayer perceptron neural network, and stochastic gradient descent) were generated, with NDI, VARI, and MGRVI providing the best estimations. Comparative results on estimations of different grassland types indicated that oblique images helped reduce the models' root mean square error (RMSE), particularly in the machine learning models. All models were best in AMS and ADS, with average R2 of 0.810 and 0.825, with machine learning models (average R2 = 0.746) stronger than linear regression models (average R2 = 0.597), indicating specific requirements for model selection across different grasslands. The findings in this study can provide a reference for the adaptive management of different grassland ecosystems on the QTP and worldwide.
{"title":"Machine Learning Models Based on UAV Oblique Images Improved Above-Ground Biomass Estimation Accuracy Across Diverse Grasslands on the Qinghai–Tibetan Plateau","authors":"Feida Sun, Dewei Chen, Linhao Li, Qiaoqiao Zhang, Xin Yuan, Zihong Liao, Chunlian Xiang, Lin Liu, Jiqiong Zhou, Mani Shrestha, Dong Xu, Yanfu Bai, A. Allan Degen","doi":"10.1002/ldr.5381","DOIUrl":"https://doi.org/10.1002/ldr.5381","url":null,"abstract":"Unmanned aerial vehicles (UAVs) are becoming important tools for modern management and scientific research of grassland resources, especially in the dynamic monitoring of above-ground biomass (AGB). However, current studies rely mostly on vertical images to construct models, with little consideration given to oblique images. Determination of image acquisition height often relies on experience and intuition, but there is limited comparison of models in estimating across different grassland types. To address this gap, this study selected 56 plots on the northern Qinghai–Tibetan Plateau (QTP), comprising 16 alpine meadows (AM), 14 alpine steppes (AS), 13 alpine meadow steppes (AMS), and 13 alpine desert steppes (ADS). We used the DJI Mavic 2 Pro to capture a total of 5040 images at six heights (5, 10, 20, 30, 40, and 50 m) and five angles (30°, 45°, 60°, 90°, and 180° panoramic shots). Based on RGB (red-green-blue) images, seven vegetation indices (normalized difference index (NDI), excess red vegetation index (EXR), modified green red vegetation index (MGRVI), visible atmospherically resistant index (VARI), excess green minus excess (EXG), green leaf index (GLI), and red–green–blue vegetation index (RGBVI)) were employed, displaying a trend in vegetation and biomass changes across different heights and angles, peaking at 20 m and 45°. Linear regression models and machine learning models (random forest, extreme gradient boosting, multilayer perceptron neural network, and stochastic gradient descent) were generated, with NDI, VARI, and MGRVI providing the best estimations. Comparative results on estimations of different grassland types indicated that oblique images helped reduce the models' root mean square error (RMSE), particularly in the machine learning models. All models were best in AMS and ADS, with average <i>R</i><sup>2</sup> of 0.810 and 0.825, with machine learning models (average <i>R</i><sup>2</sup> = 0.746) stronger than linear regression models (average <i>R</i><sup>2</sup> = 0.597), indicating specific requirements for model selection across different grasslands. The findings in this study can provide a reference for the adaptive management of different grassland ecosystems on the QTP and worldwide.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"18 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142670418","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}
Vegetation is a widely used eco‐friendly approach for slope reinforcement and ecological restoration. As a potential planting strategy, mixed planting of plants is often recommended to improve biodiversity, but the effects of mixed planting on soil reinforcement and slope stability are not yet clear. To address this issue, a study on two typical herbaceous slope protection plants, Chrysopogon zizanioides and Cynodon dactylon, were conducted. The biomechanical characteristics of different herbaceous plants were analyzed, and their root distribution and soil reinforcement performance under single and mixed planting were explored. Results show that mixed planting could significantly increase the number and root area ratio of root systems. At 0.1 cm depth after 42 days, the root number under mixed planting increased by 111.42% compared to vetiver grass monoculture and by 19.57% compared to bermuda grass monoculture. Mixed planting can provide stronger soil reinforcement by increasing apparent cohesion, with a maximum increase in apparent cohesion of 47.9%. The results of slope stability analysis showed that vegetation mainly relied on mechanical reinforcement in the root zone and hydrological reinforcement outside the root zone. After 42 days of growth, mixed planting at 0.1 m depth increased slope stability by 11.94% compared to vetiver grass monoculture and by 27.12% compared to bermuda grass monoculture, with both mechanical and hydrological effects of vegetation significantly enhanced. These findings suggest that mixed planting can promote plant development and growth, improve root production, and enhance plant–soil reinforcement and slope stability during the early establishment of vegetation. Therefore, in formulating slope reinforcement and ecological restoration strategies, more consideration can be given to mixed planting of plants, maximizing the utilization of competition characteristics between plants, and reducing the risk of shallow landslides while improving biodiversity.
{"title":"Mixed Grass Species Enhances Root Production and Plant–Soil Reinforcement","authors":"Yuan Wang, Hao Gu, Sheng Liu","doi":"10.1002/ldr.5390","DOIUrl":"https://doi.org/10.1002/ldr.5390","url":null,"abstract":"Vegetation is a widely used eco‐friendly approach for slope reinforcement and ecological restoration. As a potential planting strategy, mixed planting of plants is often recommended to improve biodiversity, but the effects of mixed planting on soil reinforcement and slope stability are not yet clear. To address this issue, a study on two typical herbaceous slope protection plants, <jats:styled-content style=\"fixed-case\"><jats:italic>Chrysopogon zizanioides</jats:italic></jats:styled-content> and <jats:styled-content style=\"fixed-case\"><jats:italic>Cynodon dactylon</jats:italic></jats:styled-content>, were conducted. The biomechanical characteristics of different herbaceous plants were analyzed, and their root distribution and soil reinforcement performance under single and mixed planting were explored. Results show that mixed planting could significantly increase the number and root area ratio of root systems. At 0.1 cm depth after 42 days, the root number under mixed planting increased by 111.42% compared to vetiver grass monoculture and by 19.57% compared to bermuda grass monoculture. Mixed planting can provide stronger soil reinforcement by increasing apparent cohesion, with a maximum increase in apparent cohesion of 47.9%. The results of slope stability analysis showed that vegetation mainly relied on mechanical reinforcement in the root zone and hydrological reinforcement outside the root zone. After 42 days of growth, mixed planting at 0.1 m depth increased slope stability by 11.94% compared to vetiver grass monoculture and by 27.12% compared to bermuda grass monoculture, with both mechanical and hydrological effects of vegetation significantly enhanced. These findings suggest that mixed planting can promote plant development and growth, improve root production, and enhance plant–soil reinforcement and slope stability during the early establishment of vegetation. Therefore, in formulating slope reinforcement and ecological restoration strategies, more consideration can be given to mixed planting of plants, maximizing the utilization of competition characteristics between plants, and reducing the risk of shallow landslides while improving biodiversity.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"5 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642909","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}
Land use conversion critically affects soil structure and associated functions. This study investigated variations in soil structure and hydropedological characteristics across different land use types, that is, uncultivated, cultivated, and abandoned land under an arid condition. Water-stable aggregates in the uncultivated land were 15.4%–37.1% of those in the cultivated and abandoned lands at depths of 0–60 cm. Reclamation of the uncultivated land enhanced soil aggregate stability, while prolonged tillage led to the loss of binding organic matter, breakdown of large aggregates and decrease in aggregate stability. The mean weight diameter of aggregates at 0–40 cm depth in the cultivated land was 39.0% lower than in the abandoned land. The volume fraction of micropores (< 100 μm) in the cultivated soils was 3.7%–39.7% of that in the uncultivated soils, whereas macropores (> 1000 μm) was 1.4–1.8 times greater. Following the abandonment, soil pore diversity recovered and a hierarchical structure developed. In the abandoned land, the volume fraction of micropores (< 100 μm) was 2.4–18.9 times that of the cultivated lands, while macropores (> 1000 μm) constituted 81.4%–93.9% of those in the cultivated lands. The permeability and longitudinal dispersivity of soils in the cultivated land were significantly lower than in the uncultivated and abandoned lands, particularly at deeper soil layers. The increase in large pores in the abandoned land, important for water movement and solute transport, resulted in an order-of-magnitude rise in both permeability and longitudinal dispersivity compared with the cultivated lands. Overall, the abandoned land showed potential for rehabilitation from the perspectives of soil aggregates and pore structure. The findings may provide reference for land reclamation and management in arid regions.
{"title":"Impact of Land Use Conversion on Soil Structure and Hydropedological Functions in an Arid Region","authors":"Jingwen Han, Cunzhen Pan, Yuhang Sun, Zhijun Chen, Yunwu Xiong, Guanhua Huang","doi":"10.1002/ldr.5385","DOIUrl":"https://doi.org/10.1002/ldr.5385","url":null,"abstract":"Land use conversion critically affects soil structure and associated functions. This study investigated variations in soil structure and hydropedological characteristics across different land use types, that is, uncultivated, cultivated, and abandoned land under an arid condition. Water-stable aggregates in the uncultivated land were 15.4%–37.1% of those in the cultivated and abandoned lands at depths of 0–60 cm. Reclamation of the uncultivated land enhanced soil aggregate stability, while prolonged tillage led to the loss of binding organic matter, breakdown of large aggregates and decrease in aggregate stability. The mean weight diameter of aggregates at 0–40 cm depth in the cultivated land was 39.0% lower than in the abandoned land. The volume fraction of micropores (< 100 μm) in the cultivated soils was 3.7%–39.7% of that in the uncultivated soils, whereas macropores (> 1000 μm) was 1.4–1.8 times greater. Following the abandonment, soil pore diversity recovered and a hierarchical structure developed. In the abandoned land, the volume fraction of micropores (< 100 μm) was 2.4–18.9 times that of the cultivated lands, while macropores (> 1000 μm) constituted 81.4%–93.9% of those in the cultivated lands. The permeability and longitudinal dispersivity of soils in the cultivated land were significantly lower than in the uncultivated and abandoned lands, particularly at deeper soil layers. The increase in large pores in the abandoned land, important for water movement and solute transport, resulted in an order-of-magnitude rise in both permeability and longitudinal dispersivity compared with the cultivated lands. Overall, the abandoned land showed potential for rehabilitation from the perspectives of soil aggregates and pore structure. The findings may provide reference for land reclamation and management in arid regions.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"43 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642905","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}
High-quality development in agriculture is crucial for maintaining the harmonious balance between human society and the natural environment, and promoting this development model is one of the key measures to alleviate land degradation issues. This study, grounded in the PRED theory (Population, Resources, Environment, and Development theory) framework, establishes an evaluation system for high-quality agricultural development by selecting 128 cities within the Yangtze River Economic Belt as its samples. It quantifies land carrying capacity, utilizes the Stochastic Frontier Analysis (SFA) model to assess agricultural production efficiency, and applies the Tapio decoupling model to analyze the interplay between these two factors. The results reveal that the land resource carrying index has risen from 1.245 to 1.70, indicating an escalating tension between population and food resources. Furthermore, agricultural production efficiency has seen a 16.56% increase, reflecting positive advancements in agricultural production across the region. Spatial distribution analysis shows that the standard deviation ellipse is concentrated in the mid and lower reaches, centered in Changde, Hunan, and expanding westward, with a broader coverage area and perimeter. Additionally, the decoupling relationship between land carrying capacity and agricultural production efficiency primarily manifests in three forms: strong negative decoupling, weak decoupling, and expansive negative decoupling. This research offers significant insights for effectively mitigating the strain between population growth and resource-environmental carrying capacity.
农业高质量发展是保持人类社会与自然环境和谐平衡的关键,推进这种发展模式是缓解土地退化问题的重要措施之一。本研究以 PRED 理论(人口、资源、环境与发展理论)框架为基础,选取长江经济带 128 个城市为样本,建立了农业高质量发展评价体系。该研究量化了土地承载能力,利用随机前沿分析(SFA)模型评估了农业生产效率,并应用塔皮奥解耦模型分析了这两个因素之间的相互作用。结果显示,土地资源承载指数已从 1.245 上升到 1.70,表明人口与粮食资源之间的紧张关系正在加剧。此外,农业生产效率提高了 16.56%,反映了整个地区农业生产的积极进步。空间分布分析表明,标准差椭圆集中在中下游地区,以湖南常德为中心向西扩展,覆盖面积和周长较广。此外,土地承载力与农业生产效率之间的脱钩关系主要表现为三种形式:强负脱钩、弱脱钩和扩张负脱钩。这项研究为有效缓解人口增长与资源环境承载力之间的矛盾提供了重要启示。
{"title":"Exploring the Path of Balanced Development: The Decoupling Evaluation of Agricultural Production Efficiency and Land Carrying Capacity","authors":"Yihang Hu, Junbiao Zhang, Qiqi Liu","doi":"10.1002/ldr.5382","DOIUrl":"https://doi.org/10.1002/ldr.5382","url":null,"abstract":"High-quality development in agriculture is crucial for maintaining the harmonious balance between human society and the natural environment, and promoting this development model is one of the key measures to alleviate land degradation issues. This study, grounded in the PRED theory (Population, Resources, Environment, and Development theory) framework, establishes an evaluation system for high-quality agricultural development by selecting 128 cities within the Yangtze River Economic Belt as its samples. It quantifies land carrying capacity, utilizes the Stochastic Frontier Analysis (SFA) model to assess agricultural production efficiency, and applies the Tapio decoupling model to analyze the interplay between these two factors. The results reveal that the land resource carrying index has risen from 1.245 to 1.70, indicating an escalating tension between population and food resources. Furthermore, agricultural production efficiency has seen a 16.56% increase, reflecting positive advancements in agricultural production across the region. Spatial distribution analysis shows that the standard deviation ellipse is concentrated in the mid and lower reaches, centered in Changde, Hunan, and expanding westward, with a broader coverage area and perimeter. Additionally, the decoupling relationship between land carrying capacity and agricultural production efficiency primarily manifests in three forms: strong negative decoupling, weak decoupling, and expansive negative decoupling. This research offers significant insights for effectively mitigating the strain between population growth and resource-environmental carrying capacity.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"8 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642906","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}
Łukasz Dylewski, Łukasz Maćkowiak, Marcin K. Dyderski
Linear structures such as woodlots and hedgerows offer many benefits to ecosystems, including enhancing biodiversity, increasing the abundance of plants and animals, and providing a wide range of ecosystem services. However, agriculture expansion has deteriorated and destroyed these elements in the farmland landscape. Human‐made structures like road verges, electricity pylons, or railways may enhance biodiversity in intensive farmland, replacing natural woody elements. We aimed to explore whether abandoned railway lines in agriculture‐dominated landscapes can serve as alternative habitats for plant species. We evaluated the taxonomical, functional, and phylogenetic diversity, along with the community composition of plants, in 25 sites along abandoned railway lines and 25 reference sites in adjacent semi‐natural grasslands. We found no significant difference in species richness and Shannon diversity between grasslands and abandoned railway vegetation, but we observed distinct differences in functional and phylogenetic diversity. Moreover, the vegetation along abandoned railways is not a variant of surrounding semi‐natural grasslands but comprises a novel vegetation type composed of species associated mainly with crops, ruderal, and forest habitats. Abandoned railway lines are characterized by specific abiotic conditions providing a set of opportunities for shaping distinct plant communities in an intensively managed agricultural landscape, fulfilling the concept of a novel ecosystem. Abandoned railways offer a unique opportunity for conservation and can serve as valuable dispersal corridors and habitats for plants, increasing functional and phylogenetic diversity in agricultural landscapes. Combining ecological restoration techniques and sustainable land management practices can help support plant diversity on abandoned railways.
{"title":"Abandoned Railways Support Greater Functional and Phylogenetic Plant Diversity Than Adjacent Grassy Meadows in Agricultural Landscape","authors":"Łukasz Dylewski, Łukasz Maćkowiak, Marcin K. Dyderski","doi":"10.1002/ldr.5383","DOIUrl":"https://doi.org/10.1002/ldr.5383","url":null,"abstract":"Linear structures such as woodlots and hedgerows offer many benefits to ecosystems, including enhancing biodiversity, increasing the abundance of plants and animals, and providing a wide range of ecosystem services. However, agriculture expansion has deteriorated and destroyed these elements in the farmland landscape. Human‐made structures like road verges, electricity pylons, or railways may enhance biodiversity in intensive farmland, replacing natural woody elements. We aimed to explore whether abandoned railway lines in agriculture‐dominated landscapes can serve as alternative habitats for plant species. We evaluated the taxonomical, functional, and phylogenetic diversity, along with the community composition of plants, in 25 sites along abandoned railway lines and 25 reference sites in adjacent semi‐natural grasslands. We found no significant difference in species richness and Shannon diversity between grasslands and abandoned railway vegetation, but we observed distinct differences in functional and phylogenetic diversity. Moreover, the vegetation along abandoned railways is not a variant of surrounding semi‐natural grasslands but comprises a novel vegetation type composed of species associated mainly with crops, ruderal, and forest habitats. Abandoned railway lines are characterized by specific abiotic conditions providing a set of opportunities for shaping distinct plant communities in an intensively managed agricultural landscape, fulfilling the concept of a novel ecosystem. Abandoned railways offer a unique opportunity for conservation and can serve as valuable dispersal corridors and habitats for plants, increasing functional and phylogenetic diversity in agricultural landscapes. Combining ecological restoration techniques and sustainable land management practices can help support plant diversity on abandoned railways.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"23 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637258","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}
M. G. Velásquez Ramírez, J. C. Nazario Rios, A. Gobin, M. Pillaca, E. Thomas, J. A. Guerrero Barrantes, U. Román, E. Becerra Lira, A. Muñoz Ushñahua, P. Nascimento Herbay, L. Rodriguez Achata, J. Garate‐Quispe, S. Malpica, R. Russo, M. Abril, L. F. S. Dionisio, R. Corvera Gomringer, D. del Castillo Torres
Artisanal and Small‐Scale Gold Mining (ASGM) carried out by individual miners or small enterprises with limited capital, significantly contribute to land degradation and loss of biodiversity‐rich forests in the Amazon. Due to limited information on the edaphic conditions crucial for restoring these degraded areas, a soil evaluation method was employed in representative locations of the Peruvian Amazon, including two native communities and one protected natural area. The categorization of ASGM‐degraded areas into cultural landscape units was confirmed and validated. Sentinel‐2 and UAV remote sensing revealed over 122,000 ha of deforestation since the 1980s. Surface and soil profile assessments identified extreme new soil conditions with low chemical and physical fertility, characterized by coarse texture and rock fragments, which hinder revegetation, especially during prolonged dry seasons. These degraded soils were classified as Entisols and Technosols according to Soil Taxonomy and the World Reference Base. Over time, natural regeneration and plantations improved soil formation, aligning with recognized soil classification systems. Under current management practices, restoration planning should prioritize selected shrub and tree species, and consider soil amendments to initiate soil recovery. This approach aligns with self‐sustaining successional stages and contributes to the objectives of Land Degradation Neutrality, Appropriate Mitigation and Adaptation Actions, and Sustainable Development Goals.
{"title":"Degradation, Classification, and Management of Soils From Alluvial‐Gold Mine Spoils in the Southeastern Peruvian Amazon","authors":"M. G. Velásquez Ramírez, J. C. Nazario Rios, A. Gobin, M. Pillaca, E. Thomas, J. A. Guerrero Barrantes, U. Román, E. Becerra Lira, A. Muñoz Ushñahua, P. Nascimento Herbay, L. Rodriguez Achata, J. Garate‐Quispe, S. Malpica, R. Russo, M. Abril, L. F. S. Dionisio, R. Corvera Gomringer, D. del Castillo Torres","doi":"10.1002/ldr.5365","DOIUrl":"https://doi.org/10.1002/ldr.5365","url":null,"abstract":"Artisanal and Small‐Scale Gold Mining (ASGM) carried out by individual miners or small enterprises with limited capital, significantly contribute to land degradation and loss of biodiversity‐rich forests in the Amazon. Due to limited information on the edaphic conditions crucial for restoring these degraded areas, a soil evaluation method was employed in representative locations of the Peruvian Amazon, including two native communities and one protected natural area. The categorization of ASGM‐degraded areas into cultural landscape units was confirmed and validated. Sentinel‐2 and UAV remote sensing revealed over 122,000 ha of deforestation since the 1980s. Surface and soil profile assessments identified extreme new soil conditions with low chemical and physical fertility, characterized by coarse texture and rock fragments, which hinder revegetation, especially during prolonged dry seasons. These degraded soils were classified as Entisols and Technosols according to Soil Taxonomy and the World Reference Base. Over time, natural regeneration and plantations improved soil formation, aligning with recognized soil classification systems. Under current management practices, restoration planning should prioritize selected shrub and tree species, and consider soil amendments to initiate soil recovery. This approach aligns with self‐sustaining successional stages and contributes to the objectives of Land Degradation Neutrality, Appropriate Mitigation and Adaptation Actions, and Sustainable Development Goals.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"246 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637229","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}
In desert ecosystems, afforestation with xerophytic shrubs has the potential to significantly increase soil nutrient levels by mitigating wind and soil erosion. Nevertheless, further investigation is required to elucidate the changes in soil organic carbon (SOC) fractions and stability on different soil depths with afforestation years. We collected soil samples from the 0–20, 20–60, and 60–100 cm depths of three xerophytic shrublands ages (3, 7, and 10 years), with a natural desert as the control, in a hyper‐arid desert region. We investigated the variations of SOC fractions (stable and active C) and stability (stability index and MAOC:POC ratios) after afforestation. The results showed that the rate of increase in SOC fractions and stability did not follow a linear trajectory with afforestation years. Instead, they accelerated around 7 years but then decreased after 10 years. The increase in SOC stability was primarily attributed to the greater increase in stable C within the total SOC pool. Afforestation increased the concentration of ROC from 0.26 to 0.89 g kg−1 and MAOC from 0.11 to 0.78 g kg−1. Afforestation increased SOC stability by 74.36%–231% compared to the CK in the 0–100 cm. SOC stability in the 60–100 cm was higher than that in the 0–20 cm layer, while SOC stability varied insignificantly across soil layers. The strongest direct positive impact on SOC stability was attributed to changes in soil physicochemical properties rather than soil microbial biomass or aggregate stability. These findings contribute to our understanding of the importance of afforestation in increasing SOC stability in desert ecosystems.
{"title":"Afforestation With Xerophytic Shrubs Promoted Soil Organic Carbon Stability in a Hyper‐Arid Environment of Desert","authors":"Guangxing Zhao, Akash Tariq, Zhihao Zhang, Muhammad Nazim, Corina Graciano, Jordi Sardans, Xinping Dong, Yanju Gao, Josep Peñuelas, Fanjiang Zeng","doi":"10.1002/ldr.5387","DOIUrl":"https://doi.org/10.1002/ldr.5387","url":null,"abstract":"In desert ecosystems, afforestation with xerophytic shrubs has the potential to significantly increase soil nutrient levels by mitigating wind and soil erosion. Nevertheless, further investigation is required to elucidate the changes in soil organic carbon (SOC) fractions and stability on different soil depths with afforestation years. We collected soil samples from the 0–20, 20–60, and 60–100 cm depths of three xerophytic shrublands ages (3, 7, and 10 years), with a natural desert as the control, in a hyper‐arid desert region. We investigated the variations of SOC fractions (stable and active C) and stability (stability index and MAOC:POC ratios) after afforestation. The results showed that the rate of increase in SOC fractions and stability did not follow a linear trajectory with afforestation years. Instead, they accelerated around 7 years but then decreased after 10 years. The increase in SOC stability was primarily attributed to the greater increase in stable C within the total SOC pool. Afforestation increased the concentration of ROC from 0.26 to 0.89 g kg<jats:sup>−1</jats:sup> and MAOC from 0.11 to 0.78 g kg<jats:sup>−1</jats:sup>. Afforestation increased SOC stability by 74.36%–231% compared to the CK in the 0–100 cm. SOC stability in the 60–100 cm was higher than that in the 0–20 cm layer, while SOC stability varied insignificantly across soil layers. The strongest direct positive impact on SOC stability was attributed to changes in soil physicochemical properties rather than soil microbial biomass or aggregate stability. These findings contribute to our understanding of the importance of afforestation in increasing SOC stability in desert ecosystems.","PeriodicalId":203,"journal":{"name":"Land Degradation & Development","volume":"11 1","pages":""},"PeriodicalIF":4.7,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637259","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}