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Ji Z, Xu Y, Sun M, Zhang P, Qi Y, Sun D, Koomen E, Lun F, Liu T. Linking the assessment of ecological engineering construction with zoning management in the typical agro-pastoral area of China: A perspective from quantity, quality and function. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 366:121635. [PMID: 38971067 DOI: 10.1016/j.jenvman.2024.121635] [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: 03/13/2024] [Revised: 05/15/2024] [Accepted: 06/27/2024] [Indexed: 07/08/2024]
Abstract
Combatting land damage has become a global priority, and China has adopted a series of ecological engineering measures, especially in the agro-pastoral area with fragile ecological environment. The effectiveness of ecological engineering construction (EEC), from a comprehensive recognition encompassing its quality, quantity, and function, has remained largely unknown. To this end, Zhangbei County, a typical agro-pastoral ecotone of northern China, was chosen as our focal area. After summarizing the timelines, aims and results of the EEC during various periods in Zhangbei, the linear spectral mixture analysis was employed to process Landsat 5 TM images in 2000 and 2010, as well as Landsat 8 OLI images in 2020. Then, a comprehensive evaluation framework of EEC was established from the perspective of "quantity-quality-function", and the ecological effectiveness of EEC was evaluated from 2000 to 2020 in Zhangbei. Results revealed that EEC played a critical role in enhancing quantity, quality and function, in spite of that, there were still numerous regions showing varying degrees of degradation in terms of these aspects. Then, by extending the three-dimensional cube as the theoretical basis for the zoning management of EEC, we merged four zones according to the space matching relationship among quantity, quality and function of EEC, namely, Ecological conservation area, Ecological improvement area, Ecological restoration area and Ecological remodeling zone. More targeted ecological measures were required for specific matching relationship among quantity, quality and function of EEC. This study is expected to present an empirical case for assessing the ecological effectiveness of EEC in areas or countries with similar restoration demand and support regional management.
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Affiliation(s)
- Zhengxin Ji
- College of Land Science and Technology, China Agricultural University, Beijing, 100193, China; Department of Spatial Economics, Vrije Universiteit Amsterdam, Amsterdam, 1081, HV, the Netherlands
| | - Yueqing Xu
- College of Land Science and Technology, China Agricultural University, Beijing, 100193, China; Key Laboratory for Agricultural Land Quality, The Ministry of Natural Resources, Beijing, 100193, China.
| | - Minxuan Sun
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, 100084, China
| | - Ping Zhang
- National Geomatics Center of China, Beijing, 100830, China
| | - Yuan Qi
- College of Land Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Danfeng Sun
- College of Land Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Eric Koomen
- Department of Spatial Economics, Vrije Universiteit Amsterdam, Amsterdam, 1081, HV, the Netherlands
| | - Fei Lun
- College of Land Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Tianhao Liu
- College of Land Science and Technology, China Agricultural University, Beijing, 100193, China
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Zhang M, He H, Zhang L, Yu G, Ren X, Lv Y, Niu Z, Qin K, Gao Y. Increased ecological land and atmospheric CO 2 dominate the growth of ecosystem carbon sinks under the regulation of environmental conditions in national key ecological function zones in China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 366:121906. [PMID: 39032258 DOI: 10.1016/j.jenvman.2024.121906] [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: 02/06/2024] [Revised: 06/06/2024] [Accepted: 07/14/2024] [Indexed: 07/23/2024]
Abstract
Increased ecological land (IEL) such as forests and grasslands can greatly enhance ecosystem carbon sinks. Understanding the mechanisms for the magnitude of IEL-induced ecosystem carbon sinks is crucial for achieving carbon neutrality. We estimated the impact of IEL, specifically the increase in forests and grasslands, as well as global changes including atmospheric CO2 concentration, nitrogen deposition, and climate change on net ecosystem productivity (NEP) in National Key Ecological Function Zones (NKEFZs) in China using a calibrated ecological process model. The NEP in NKEFZs in China was calculated to be 119.4 Tg C yr-1, showing an increase of 42.6 Tg C yr-1 from 2001 to 2021. Compared to the slight contributions of climate change (-8.0%), nitrogen deposition (11.5%), and reduction in ecological land (-3.5%), the increase in NEP was primarily attributed to CO2 (66.5%) and IEL (33.5%). Moreover, the effect of IEL (14.8 Tg C yr-1) surpassed that of global change (13.1 Tg C yr-1) in the land use change zone. The IEL-induced NEP is significantly associated with CO2 fertilization, regulated by precipitation and nitrogen deposition. The high values of IEL-induced NEP occurred in areas with precipitation exceeding 800 mm and nitrogen deposition exceeding 25 kg N ha-1 yr-1. We recommend prioritizing the expansion of ecological land in areas with sufficient water and nutrients to enhance CO2 fertilization, while avoiding increasing ecological land in regions facing unfavorable climate change conditions. This study serves as a foundation for comprehending the NEP response to ecological restoration and global change.
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Affiliation(s)
- Mengyu Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Honglin He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China.
| | - Li Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Guirui Yu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Xiaoli Ren
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Yan Lv
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhong'en Niu
- School of Resources and Environmental Engineering, Ludong University, Shandong, 264025, China
| | - Keyu Qin
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China
| | - Yanni Gao
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
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Liu Y, Lian J, Chen H. Assessment of the restoration potential for ecological sustainability in the Xijiang River basin, Southwest China: A comparative analysis of karst and non-karst areas. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:168929. [PMID: 38042184 DOI: 10.1016/j.scitotenv.2023.168929] [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: 11/06/2023] [Accepted: 11/25/2023] [Indexed: 12/04/2023]
Abstract
Vegetation restoration is an eco-friendly strategy for countering land degradation and biodiversity loss. Since 2000-2001, large-scale restoration projects have been performed in Southwest China, with the net primary productivity (NPP) increasing over the past two decades. However, negative ecohydrological impacts, including streamflow decline and soil moisture deficit, have been reported following afforestation. Current understanding of the permissible NPP capacity (NPPcap) and NPP potential (NPPpot) under karst and non-karst areas or planted and natural vegetations constrained by environmental factors remains unclear. Here multiple environmental drivers characterizing the heterogeneous landscape in the Xijiang River Basin (Southwest China) were employed to predict the NPPcap using a random forest model. Results showed that 85% of the area exhibited an increasing trend in NPPcap during 2001-2018. Overall, 3.50% of the area has exceeded the NPPcap, implying an excessive plantation and potential water deficit in these areas. Excluding agriculture activities, urban areas, and water bodies, we found there is room for an average extra 22.85% of NPP enhancement. The NPPpot was spatially imbalanced, with high NPPpot located in the northeast, indicating these areas as a target area for future vegetation restoration. Moreover, the NPPpot reduction in karst areas (1.12 g C m-2 a-1) was more pronounced than in non-karst areas (0.26 g C m-2 a-1), highlighting a stronger negative impact on NPPpot in karst areas. Furthermore, significant NPPpot differences were found between planted vegetation and natural vegetation for both karst and non-karst areas. According to the findings, we identified four separate restoration sub-zones and proposed tailored strategies to guide the implementation of future restoration efforts. Our study highlights restoration potential and where land is available for reforestation but also the urgent need for future restoration activities towards ecosystem sustainability.
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Affiliation(s)
- Yeye Liu
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Ecohydrology and Biogeochemistry, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin 12587, Germany
| | - Jinjiao Lian
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, China
| | - Hongsong Chen
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China; Guangxi Key Laboratory of Karst Ecological Processes and Services, Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, China.
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Yang Q, Liu G, Li H, Santagata R, Yang Z. Understanding ecological restoration potential: The role of water resources and slope gradient limits. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169001. [PMID: 38040353 DOI: 10.1016/j.scitotenv.2023.169001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 11/25/2023] [Accepted: 11/28/2023] [Indexed: 12/03/2023]
Abstract
Ecological restoration is one of the most feasible ways to mitigate climate change and conserve ecosystems. However, the scope, intensity, effectiveness, and future potential of ecological restoration are restricted by unfavorable environmental conditions, especially limited water resources and complex topography. This paper proposes an assessment framework of ecological restoration potential under the coupled limits of water resources and slope gradient to quantitatively assess ecological restoration potential (ERP) under these two limiting factors. Results indicate that the current vegetation plantation in 20%, 0.19% and 32% areas of China's 31 provinces are larger, equal, and lower than the vegetation threshold permitted by local water resources respectively, which represents about 0.299 billion ha potential for additional restoration area. The ecological restoration potential under the integrated water resources and slope gradient constraints is 0.4 Pg C, less than half (47%) of the potential under the single limit of water resources (0.856 Pg C). However, this potential and China's existing carbon sink capacity related to terrestrial ecosystems is estimated to offset up to 8% of its current carbon dioxide emissions. Ecological restoration programs in areas with slope >5° will require additional economic investment to support Soil and Water Conservation programs, estimated to average about 212 trillion yuan. Succinctly, it is critical to integrate field investigations, process-based assessments and landscape design for sustainable ecological restoration. This work can provide techniques support for quantitative measurement of ecological restoration potential considering multiple limiting factors and guidance for sustainable implementation of ecological restoration programs.
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Affiliation(s)
- Qing Yang
- Advanced Interdisciplinary Institute of Environment and Ecology, Beijing Normal University, Zhuhai 519087, China
| | - Gengyuan Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Hui Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Remo Santagata
- Department of Engineering, Parthenope University of Napoli, Napoli, Italy
| | - Zhifeng Yang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, China; Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511458, China.
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Li W, Wang Y, Jiang Y, Liu Z, Shen D. Spatial evaluation and zoning strategy of land use elemental conflicts in heavy industrial zones: evidence from central Liaoning Province in Northeast China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:102335-102352. [PMID: 37667119 DOI: 10.1007/s11356-023-29509-2] [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: 04/05/2023] [Accepted: 08/22/2023] [Indexed: 09/06/2023]
Abstract
The matching imbalance of resource factors leads to land use elemental conflicts (LUECs), which has become the bottleneck restricting high-quality social and economic development. The heavy industrial zones (HIZ) have become the focus area of LUECs due to the high-resource consumption. Taking the urban group of central Liaoning Province, the area of industrial revitalization in northeast China as a case study area, the study proposed a wavelet coherence approach to identifying the influencing indicators and indicators weight of LUECs for spatial evaluation. Two-dimensional graph theory is used to cluster the evaluation results of LUECs at the plot scale and controls the main indicators to put forward the zoning strategies of LUECs. The results showed that the main indicators affecting LUECs in the western part of the HIZ are mainly human indicators, while the fierce conflicts in the east mainly come from natural indicators. The zoning strategies of LUECs in the HIZ should prevent excessive energy consumption from increasing carbon emissions in intense conflict zone and moderate conflict zone and strengthen the rural settlement arrangement and soil erosion control in mild conflict zone and structure ecological security early warnings in potential conflict zone. This study provides an important reference for land use conflicts in the global heavy industrial urban agglomeration.
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Affiliation(s)
- Wenying Li
- School of Management, Shenyang Normal University, No. 253 North Street of the Yellow River, Shenyang, 110034, Liaoning Province, China
- School of Public Economics and Administration, Shanghai University of Finance and Economics, Shanghai, 200433, China
| | - Yue Wang
- School of Management, Shenyang Normal University, No. 253 North Street of the Yellow River, Shenyang, 110034, Liaoning Province, China.
| | - Yuting Jiang
- School of Management, Shenyang Normal University, No. 253 North Street of the Yellow River, Shenyang, 110034, Liaoning Province, China
| | - Zhaoyu Liu
- School of Information Engineering, China University of Geosciences, Beijing, 100083, China
| | - Dianshi Shen
- School of Management, Shenyang Normal University, No. 253 North Street of the Yellow River, Shenyang, 110034, Liaoning Province, China
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Zhang M, Zhang L, He H, Ren X, Lv Y, Niu Z, Chang Q, Xu Q, Liu W. Improvement of ecosystem quality in National Key Ecological Function Zones in China during 2000-2015. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 324:116406. [PMID: 36352714 DOI: 10.1016/j.jenvman.2022.116406] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/31/2022] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Improving ecosystem quality is the ultimate goal of ecological restoration projects and sustainable ecosystem management. However, previous results of ecosystem quality lack comparability among different regions when assessing the effectiveness of ecological restoration projects on the regional or national scales, due to the influence of geographical and climatic background conditions. Here we proposed a new index, ecosystem quality ratio (EQR), by integrating the status of landscape structure, ecosystem services, ecosystem stability, and human disturbance relative to their reference conditions, and assessed the EQR changes in China's counties and National Key Ecological Function Zones (NKEFZs) from 1990 to 2015. The results showed that the average ecosystem quality of China's counties deviated from the reference condition by 28%. EQR decreased by 1.2% during 1990-2000 but increased by 3.7% during 2000-2015. Those counties with increasing EQR in 2000-2015 occupy 64.7%, with obviously increasing counties mainly located in the water conservation, biodiversity maintenance, and water and soil conservation types of NKEFZs. The EQR increase in counties within NKEFZs was 3.65 times that outside of NKEFZs. Remarkable improvement of ecosystem quality occurred in the forest region in Changbai Mountain, biodiversity and soil conservation region in Wuling Mountains, and hilly and gully region of Loess Plateau, where EQR increases mainly resulted from the conversion of farmland to forest or grassland and consequent increases in ecosystem services and stability. The magnitude of EQR enhancement showed a positive relationship with the increase in forest and grassland coverage in NKEFZs. Our results highlight the important role of ecological restoration projects in improving ecosystem quality in China, and demonstrate the feasibility of the new index (EQR) for the assessment of ecosystem quality in terms of ecosystem management and restoration.
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Affiliation(s)
- Mengyu Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Li Zhang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China.
| | - Honglin He
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China.
| | - Xiaoli Ren
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100190, China
| | - Yan Lv
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China
| | - Zhong'en Niu
- School of Resources and Environmental Engineering, Ludong University, Shandong, 264025, China
| | - Qingqing Chang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Qian Xu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Weihua Liu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; National Ecosystem Science Data Center, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
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