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Jin A, Li H, Wang X, Wang Z. Spatiotemporal assessment of ecological quality and driving mechanisms in the Beijing metropolitan area. Sci Rep 2025; 15:13136. [PMID: 40240405 PMCID: PMC12003671 DOI: 10.1038/s41598-025-97156-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Accepted: 04/02/2025] [Indexed: 04/18/2025] Open
Abstract
Climate change and human expansion are primary drivers of ecological degradation in metropolitan areas, underscoring the necessity of examining the complex interplay between environmental factors and ecological quality. This study investigates the spatial-temporal evolution of ecological quality within the Beijing Metropolitan Area (BMA) from 2000 to 2020 and proposes a comprehensive assessment framework integrating machine learning techniques and spatial heterogeneity analyses. Ecological quality is quantitatively evaluated using the Remote Sensing Ecological Index (RSEI), leveraging MODIS imagery, climate data, land use patterns, and soil characteristics. Spatial clustering patterns of ecological quality are identified through RSEI calculations and spatial autocorrelation analyses, while future trends are projected utilizing the coefficient of variation, Sen and Mann-Kendall methods, and the Hurst index. The XGBoost algorithm elucidates the multifaceted driving mechanisms, and geographically weighted regression (GWR) quantifies the spatial variability of these drivers. The application of XGBoost reveals nonlinear relationships among ecological drivers, and GWR enhances spatially explicit interpretations of these relationships. Results indicate an overall improvement in ecological quality, with the RSEI rising from 0.428 in 2000 to 0.480 in 2020, corresponding to an annual average increase of approximately 0.55%. Notable spatial variability exists, with ecological quality consistently higher in the Taihang Mountains relative to lower-altitude plains. Current ecological protection policies have effectively mitigated ecological degradation in approximately 32.35% of the study area; however, significant environmental pressures persist in urban-rural transition zones and plain regions. Topography and soil properties emerge as dominant influencing factors, while climate indirectly influences ecological quality by shaping vegetation coverage. Human activities predominantly exert negative impacts within urban expansion zones. This research offers a robust quantitative framework for regional ecological conservation, providing critical insights to inform sustainable development and environmental policy-making.
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Affiliation(s)
- Aibo Jin
- School of Landscape Architecture, Beijing Forestry University, Beijing, 100083, China
| | - Hui Li
- School of Landscape Architecture, Beijing Forestry University, Beijing, 100083, China.
| | - Xiangrong Wang
- School of Landscape Architecture, Beijing Forestry University, Beijing, 100083, China.
| | - Ziyao Wang
- Department of Landscape Architecture, School of Architecture, Tsinghua University, Beijing, 100084, China.
- Ecological Restoration Research Center, School of Architecture, Tsinghua University, Beijing, 100084, China.
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2
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Shi Y, Feng Y, Wang J, Bai Z, Feng X, Chen B. Optimal allocation of technical reclamation and ecological restoration for a cost-effective solution in Pingshuo Opencast Coal Mine area of China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2025; 373:123951. [PMID: 39752959 DOI: 10.1016/j.jenvman.2024.123951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 12/27/2024] [Accepted: 12/27/2024] [Indexed: 01/15/2025]
Abstract
Limiting adverse consequences of mining activities requires ecosystem restoration efforts, whose arrangement around mining areas is poorly designed. It is unclear, however, where best to locate ecological projects to enhance ecosystem services cost-effectively. To answer this question, we conducted an optimized ecological restoration project planning by the Resource Investment Optimization System (RIOS) model to identify the restoration priority areas in the Pingshuo Opencast Coal Mine region in Shanxi Province. This region features notable mining activity, agricultural land use, and urban development. We found that the land use changes were primarily influenced by human activities such as mining and urbanization, as well as ecological interventions from 1986 to 2022, during which the area of industrial and construction land continuously expanded. The RIOS model was configured using input data such as land use, digital elevation models (DEM), and biophysical coefficients. Ecological restoration objectives were selected, including Erosion Control for Drinking Water Quality, Erosion Control for Reservoir Maintenance, Nutrient Retention, and Baseflow. Investment optimization scenario simulations revealed that over 90% of ecological projects in the Pingshuo Opencast Coal Mine are distributed in the low-slope areas (0°-15°). Four types of technical reclamation and ecological restoration projects, i.e., agroforestry, grass strips, riparian management, and terracing, exhibit strong preferences for specific locations. Riparian management and agroforestry tend to be distributed on soil dumps; terracing and grass strips tend to be distributed in the upstream agricultural areas of rivers and junctions of watershed gullies and slopes. The model prioritized areas based on ecological restoration goals and stakeholder interests, optimizing locations that would maximize ecological benefits while addressing the objectives. Moreover, depending on the different goals of ecological restoration in the mining area, investment plans that maximize benefits for stakeholders should range between 3 and 6 million dollars. While the restoration strategies in this study were designed for the Pingshuo region, they hold potential for other mining areas with similar biophysical conditions, surrounding ecosystems, and mining scales. The RIOS model adjusts its recommendations based on specific input data, making it adaptable and broadly applicable to other mining area. The results of this study positively contribute to alleviating the conflict between ecosystem protection and socioeconomic development in mining areas, scientifically regulating ecological restoration activities, and enhancing ecosystem services. Our results provide evidence that ecological restoration interventions contribute measurably to restore the degraded ecosystems in the mining areas.
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Affiliation(s)
- Yuting Shi
- School of Land Science and Technology, China University of Geosciences, 29 Xueyuan Road, Haidian District, 100083, Beijing, People's Republic of China
| | - Yu Feng
- School of Land Science and Technology, China University of Geosciences, 29 Xueyuan Road, Haidian District, 100083, Beijing, People's Republic of China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, 100035, Beijing, People's Republic of China.
| | - Jinman Wang
- School of Land Science and Technology, China University of Geosciences, 29 Xueyuan Road, Haidian District, 100083, Beijing, People's Republic of China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, 100035, Beijing, People's Republic of China
| | - Zhongke Bai
- School of Land Science and Technology, China University of Geosciences, 29 Xueyuan Road, Haidian District, 100083, Beijing, People's Republic of China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, 100035, Beijing, People's Republic of China
| | - Xiaoming Feng
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, People's Republic of China
| | - Bihui Chen
- School of Land Science and Technology, China University of Geosciences, 29 Xueyuan Road, Haidian District, 100083, Beijing, People's Republic of China
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Tian Z, Lu Z, Huo D, Zhang Z, Sun Q, Wu H, Wang J, Kang Y, Xie Y, Tian Y, Yi K, Hou J. Strategic analysis of avian conservation within key areas and key species - A case study of Baiyangdian, China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2025; 373:123821. [PMID: 39731948 DOI: 10.1016/j.jenvman.2024.123821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Revised: 11/11/2024] [Accepted: 12/20/2024] [Indexed: 12/30/2024]
Abstract
Global climate change and extensive human activities are causing rapid transformations in natural ecosystems, leading to the rapid loss of suitable habitats for wildlife, which urgently requires measures to protect global biodiversity. In the past decade, China has invested heavily in ecological restoration, but current projects often do not prioritize biodiversity conservation. Therefore, developing systematic conservation strategies and using quantitative methods to identify conservation key areas and key species within a regional scale is of great importance for current ecological restoration. In this study, we focused on avian species, using an Ensemble Species Distribution Model to identify bird distribution hotspots and accordingly proposed conservation key areas in Baiyangdian. Additionally, the AHP-EWM-TOPSIS method and ENMTools were utilized to select flagship bird species with strong umbrella effects and to determine conservation key species. The results indicate that the Fuhe wetland, southwest of ZaoZaDian, central and northern of ShaoCheDian, northwest of Beitian Village and Datian Village, northern of XiaoBaiYangDian, and the Xiaoyihe wetland should be designated as the birdconservation key areas. The key birds should include Aythya baeri, Ardea alba, Phasianus colchicus, Falco tinnunculus, Upupa epops and Paradoxornis heudei, with higher priority given to A. baeri, A. alba, P. colchicus and F. tinnunculus. This study aims to provide a systematic framework for identifying conservation key areas and key species, facilitating the efficient use of public funding by local governments, and providing scientific guidance for conserving the bird diversity of Baiyangdian.
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Affiliation(s)
- Zengrui Tian
- College of Life Science, Hebei University, Baoding, 071002, China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of MOE, Baoding, 071002, China; Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
| | - Zhenguang Lu
- College of Life Science, Hebei University, Baoding, 071002, China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of MOE, Baoding, 071002, China
| | - Da Huo
- College of Life Science, Hebei University, Baoding, 071002, China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of MOE, Baoding, 071002, China
| | - Zongjun Zhang
- College of Life Science, Hebei University, Baoding, 071002, China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of MOE, Baoding, 071002, China
| | - Qi Sun
- College of Life Science, Hebei University, Baoding, 071002, China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of MOE, Baoding, 071002, China
| | - Heng Wu
- College of Life Science, Hebei University, Baoding, 071002, China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of MOE, Baoding, 071002, China
| | - Jiaojiao Wang
- College of Life Science, Hebei University, Baoding, 071002, China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of MOE, Baoding, 071002, China
| | - Yitong Kang
- Bureau of Natural Resources and Planning of Xiong'an New Area, Xiong'an New Area, 070001, China
| | - Yu Xie
- Planning Research Centre of Xiong'an New Area, Xiong'an New Area, 070001, China
| | - Yongchang Tian
- Bureau of Natural Resources of Anxi County, Xiong'an New Area, 070001, China
| | - Kunpeng Yi
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
| | - Jianhua Hou
- College of Life Science, Hebei University, Baoding, 071002, China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of MOE, Baoding, 071002, China.
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Gou F, Liang W, Liu Y, Fu B, Wang Z, Zhang W, Chen Z, Yan J, Li J, Lv Y. Large-scale ecological infrastructures enhance the productivity of agro-socio-ecological systems by reducing soil erosion in the Loess Plateau. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2025; 373:123751. [PMID: 39705994 DOI: 10.1016/j.jenvman.2024.123751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2024] [Revised: 11/04/2024] [Accepted: 12/13/2024] [Indexed: 12/23/2024]
Abstract
Agro-socio-ecological systems are a crucial link connecting urbanization, agricultural development and environmental evolution. However, there is no effective research on realizing regional collaborative development and environmental governance of the agricultural social-system collaborative governance model, especially spatial differentiation governance. In this study, the region with the most severe soil erosion in the world was selected as the research area. We used socio-economic statistical data and remote sensing data, combined with the Revised Universal Soil Loss Equation, to provide analytical evidence in different sub-regions. Results showed that the soil erosion rate of the Loess Plateau has dropped significantly during the past three decades, with an average decreasing rate of 0.46 t ha-1 yr-2 or 2.33%. Large-scale investments in ecological infrastructure (e.g., check dams) increase agro-socio-ecological productivity by reducing soil erosion. The productivity of social-ecological systems increased significantly, especially after 2000, with the grain production capacity and gross primary productivity rising by 84.28% and 18.06% from 1990 to 2017. The decrease in grain yield caused by the ecological return of upland cropland and the occupation of high-quality cropland will be raised to a better level. Large-scale investment in ecological infrastructure enabled farmers to obtain ecological compensation, and agricultural income resulting from land productivity improvement brought about by infrastructure investment. This study further confirms the dual benefits of ecological infrastructure in controlling erosion and improving land productivity, and provides sustainable support for achieving coordinated economic growth and ecological environmental protection through effective management of agricultural ecosystems.
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Affiliation(s)
- Fen Gou
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China; Shaanxi Observation and Research Station for Ecology and Environment of Desert-Loess Zone at Yulin, Xi'an, 710119, China
| | - Wei Liang
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China; Shaanxi Observation and Research Station for Ecology and Environment of Desert-Loess Zone at Yulin, Xi'an, 710119, China.
| | - Yan Liu
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China; Shaanxi Observation and Research Station for Ecology and Environment of Desert-Loess Zone at Yulin, Xi'an, 710119, China
| | - Bojie Fu
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
| | - Zhenguo Wang
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China; Shaanxi Observation and Research Station for Ecology and Environment of Desert-Loess Zone at Yulin, Xi'an, 710119, China
| | - Weibin Zhang
- College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, 712100, China
| | - Zhigang Chen
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China
| | - Jianwu Yan
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China
| | - Junyi Li
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, 710119, China; Shaanxi Observation and Research Station for Ecology and Environment of Desert-Loess Zone at Yulin, Xi'an, 710119, China
| | - Yihe Lv
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China
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Aili A, Zhang Y, Lin T, Xu H, Waheed A, Zhao W, Kuerban A, Liu K, Dou H. Optimizing Vegetation Restoration: A Comprehensive Index System for Reclaiming Abandoned Mining Areas in Arid Regions of China. BIOLOGY 2024; 14:23. [PMID: 39857254 PMCID: PMC11763323 DOI: 10.3390/biology14010023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2024] [Revised: 12/20/2024] [Accepted: 12/28/2024] [Indexed: 01/27/2025]
Abstract
Mining activities in arid regions of China have led to severe environmental degradation, including soil erosion, vegetation loss, and contamination of soil and water resources. These impacts are particularly pronounced in abandoned mining areas, where the cessation of mining operations has left vast landscapes unrehabilitated. In response, the Chinese government has implemented a series of legal and regulatory frameworks, such as the "Mine Environmental Protection and Restoration Program", aimed at promoting ecological restoration in these areas. However, the unique environmental conditions of arid regions, including water scarcity, extreme temperatures, and poor soil quality, present significant challenges to restoration efforts. This review provides a comprehensive analysis of the ecological restoration of abandoned mining areas in China's arid regions, focusing on the legal framework, restoration techniques, and evaluation systems. The restoration methods, their initiation timelines, monitoring systems, and the cost-benefit aspects of various strategies are critically reviewed alongside case studies from regions such as the Mu Us Desert and Qaidam Basin. Key strategies like phytoremediation, soil rehabilitation, and water resource management are assessed for their effectiveness, while challenges in enforcement, socioeconomic integration, and community engagement are discussed. This review concludes that while significant progress has been made, further improvements in restoration practices and evaluation systems are essential for long-term sustainability. Integration of socioeconomic indicators, community involvement, and advanced monitoring technologies are necessary for successful outcomes.
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Affiliation(s)
- Aishajiang Aili
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; (A.A.); (W.Z.); (A.K.); (K.L.)
| | - Yuguang Zhang
- State Investment and Development Corporation, Hami Energy Development Co., Ltd., Hami 839000, China;
| | - Tao Lin
- Desert-Oasis Ecological Monitoring and Restoration Engineering Innovation Center, Ministry of Natural Resources, Urumqi 830002, China;
| | - Hailiang Xu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; (A.A.); (W.Z.); (A.K.); (K.L.)
| | - Abdul Waheed
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; (A.A.); (W.Z.); (A.K.); (K.L.)
| | - Wanyu Zhao
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; (A.A.); (W.Z.); (A.K.); (K.L.)
| | - Amannisha Kuerban
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; (A.A.); (W.Z.); (A.K.); (K.L.)
| | - Kun Liu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; (A.A.); (W.Z.); (A.K.); (K.L.)
| | - Haitao Dou
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; (A.A.); (W.Z.); (A.K.); (K.L.)
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Xi H, Li T. Unveiling the spatiotemporal dynamics and influencing factors of carbon stocks in the yangtze river basin over the past two decades. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 954:176261. [PMID: 39277012 DOI: 10.1016/j.scitotenv.2024.176261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 09/09/2024] [Accepted: 09/11/2024] [Indexed: 09/17/2024]
Abstract
Terrestrial ecosystems are critical to the global carbon cycle and climate change mitigation. Over the past two decades, the Yangtze River Basin (YRB) has implemented various ecological restoration projects and active management measures, significantly impacting carbon stock patterns. This study employed random forest models to analyze the spatial and temporal patterns of carbon stocks in the YRB from 2001 to 2021. In 2021, carbon density in the YRB ranged from 8.5 to 177.4 MgC/ha, with a total carbon stock of 18.05 PgC. Over 20 years, the YRB sequestered 1.26 billion tons of carbon, accounting for 11.28 % of the region's fossil fuel carbon emissions. Notably, forests exhibited the highest carbon density, averaging 98.01 ± 25.01 MgC/ha (2021) with a carbon stock growth rate of 51.6 TgC/yr. Piecewise structural equation model was used to assess the effects of climate and human activities on carbon density, revealing regional variability, with unique patterns observed in the source region. Human activities primarily influence carbon density indirectly through vegetation alterations., while climate change directly impacts ecosystem biophysical processes. These findings offer critical insights for climate mitigation and adaptation strategies, enhancing the understanding of carbon dynamics for sustainable development and global carbon management.
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Affiliation(s)
- Haojun Xi
- College of Environmental Science and Engineering, Peking University, Beijing 100871, China; State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Beijing 100871, China
| | - Tianhong Li
- College of Environmental Science and Engineering, Peking University, Beijing 100871, China; State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems, Beijing 100871, China.
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Dong YY, Wang P, Hua ZL, Huang SH. Human activities exacerbate river network degrading in the Qinhuai River basin. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 952:176021. [PMID: 39236831 DOI: 10.1016/j.scitotenv.2024.176021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2024] [Revised: 09/02/2024] [Accepted: 09/02/2024] [Indexed: 09/07/2024]
Abstract
Rivers are undergoing significant changes under the pressures of natural processes and human activities. However, characterizing and understanding these changes over the long term and from a spatial perspective have proven challenging. This paper presents a novel framework featuring twelve indicators that combine geometric and spatial structures for evaluating changes in river network patterns. Through global principal component analysis, these indicators were integrated into a comprehensive river network pattern index (RNP). Employing Pearson correlation analysis, geographically weighted regression, geographic detector models, and the Shapley Value, the study quantitatively analyzed various stressors' impacts and relative contributions on river network changes from the 1960s to 2015s. The results showed a clear trend of degradation over time, particularly with frequency and density declining by 57 % and 48 %, respectively. The changes across subbasins varied temporally and spatially, with the 1980s emerging as a significant temporal hotspot and six spatial hotspots identified among twenty subbasins. The analysis showed that agriculture was significantly negatively associated with RNP, while the relationship between urbanization and RNP was inverted N-shaped. To address the negative effects of human activities, a shift from uniform management approaches is crucial. In agricultural areas, adopting more intensive farming practices could help mitigate negative impacts on RNP. For highly urbanized regions, city planning should consider the interactions between urbanization and other factors affecting RNP. Overall, incorporating an understanding of RNP's spatial-temporal dynamics and driving factors into spatial planning is critical for creating effective and sustainable management strategies for human-river interactions.
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Affiliation(s)
- Yue-Yang Dong
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China
| | - Peng Wang
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China.
| | - Zu-Lin Hua
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China
| | - Shan-Heng Huang
- Ministry of Education Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes, Hohai University, Nanjing 210098, China; Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210098, China
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Huang Y, Li X, Liu D, Duan B, Huang X, Chen S. Evaluation of vegetation restoration effectiveness along the Yangtze River shoreline and its response to land use changes. Sci Rep 2024; 14:7611. [PMID: 38556521 PMCID: PMC10982293 DOI: 10.1038/s41598-024-58188-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 03/26/2024] [Indexed: 04/02/2024] Open
Abstract
Assessing the effectiveness of vegetation restoration along the Yangtze River shoreline and exploring its relationship with land use changes are imperative for providing recommendations for sustainable management and environmental protection. However, the impact of vegetation restoration post-implementation of the Yangtze River Conservation Project remains uncertain. In this study, utilizing Sentinel-2 satellite imagery and Dynamic World land use data from pre- (2016) and post- (2022) Yangtze River Conservation Project periods, pixel-based binary models, transition matrices, and geographically weighted regression models were employed to analyze the status and evolution of vegetation coverage along the Yangtze River shoreline. The results indicated that there had been an increase in the area covered by high and high-medium vegetation levels. The proportion of vegetation cover shifting to better was 4201.87 km2 (35.68%). Hotspots of vegetation coverage improvement were predominantly located along the Yangtze River. Moreover, areas witnessing enhanced vegetation coverage experienced notable land use changes, notably the conversion of water to crops (126.93 km2, 22.79%), trees to crops (59.93 km2, 10.76%), and crops to built area (59.93 km2, 10.76%). Notably, the conversion between crops and built area emerged as a significant factor influencing vegetation coverage improvement, with average regression coefficients of 0.68 and 0.50, respectively. These outcomes underscore the significance of this study in guiding ecological environmental protection and sustainable management along the Yangtze River shoreline.
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Affiliation(s)
- Yinlan Huang
- School of Geography and Planning, Chizhou University, Chizhou, 247000, China
| | - Xinyi Li
- School of Geography and Planning, Chizhou University, Chizhou, 247000, China
| | - Dan Liu
- School of Geography and Planning, Chizhou University, Chizhou, 247000, China
| | - Binyan Duan
- School of Geography and Planning, Chizhou University, Chizhou, 247000, China
| | - Xinyu Huang
- School of Geography and Planning, Chizhou University, Chizhou, 247000, China
| | - Shi Chen
- School of Geography and Planning, Chizhou University, Chizhou, 247000, China.
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Sun M, Zhang L, Yang R, Li X, Zhao J, Liu Q. Water resource dynamics and protection strategies for inland lakes: A case study of Hongjiannao Lake. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 355:120462. [PMID: 38422851 DOI: 10.1016/j.jenvman.2024.120462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 01/14/2024] [Accepted: 02/20/2024] [Indexed: 03/02/2024]
Abstract
Globally, lakes are drying up and shrinking and inland lakes, in particular, face severe water shortage problems. Thus, the degradation mechanisms and protection measures for inland lakes urgently need to be explored. Hongjiannao Lake (HL), an inland lake on the border of Shaanxi Province and Inner Mongolia Autonomous Region of China, was selected for the present case study. The evolution of HL was analyzed and the current lake water storage was measured on site. The driving factors of water resource changes in HL were discussed based on meteorological and landcover data. The results showed that (1) from 1929 to 2021, the lake area of HL experienced four stages: formation, stability, shrinkage and recovery. The smallest water area was 31.08 km2 in 2015, half the size of lake in the 1960s. (2) Spatially, the morphological changes of HL mainly occurred where the rivers entered the lake. (3) In 2021, the average depth of HL was 3.77 m, and the water storage capacity was 140.56 million m3. (4) The annual average evaporation was 3.36 times the amount of the annual average precipitation in Hongjiannao Basin (HB), but climate change was not the main driver of changes in the HL area. (5) In the past 20 years, cultivated land and artificial surface increased by 3.11% and 1.04%, respectively, whereas grassland and water body decreased by 3.51% and 0.45%, respectively. The expansion of cultivated land and artificial surface, as well as the construction of reservoirs upstream of the lake, hindered the replenishment of water resources to HL. This study recommends a range of strategies for water resource protection in inland lakes, including implementing ecological restoration projects, carrying out inter-basin water transfer measures, improving the efficiency of regional water resource use, and improving industrial structure and distribution.
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Affiliation(s)
- Meiying Sun
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Le Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Rongjin Yang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Xiuhong Li
- State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
| | - Jian Zhao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Qingqing Liu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
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