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Zheng Y, Du S, Sun W, Feng C, Su Q. Spatiotemporal patterns of net regional productivity and its causes throughout Ordos, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:22038-22054. [PMID: 38400969 DOI: 10.1007/s11356-024-32368-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/03/2024] [Indexed: 02/26/2024]
Abstract
A comprehensive understanding of the terrestrial carbon sink is essential for proficient regional carbon management. However, previous studies predominantly relied on net ecosystem productivity (NEP) as an indicator of regional carbon sink, overlooking the impacts of carbon emissions from physical processes and carbon leakage associated with anthropogenic activities. In this study, net region productivity (NRP), a vital metric representing carbon sink dynamics in regional multi-landscape ecosystems, was employed to systematically analyze the patterns, trends, and causes of carbon sink in Ordos. The results revealed that spatially averaged NRP in Ordos was 70.334 g·m-2·a-1, indicating a carbon sink effect. The coefficient of variation of NRP was 68.035%, with a higher NRP in the southern region. Normalized difference vegetation index (NDVI) predominantly controlled the spatial heterogeneity of NRP in Ordos, while precipitation emerged as the primary climatic factor influencing spatial differences in NRP. Regional variations in the impact of environmental factors on NRP were evident. In most areas, NRP showed a notable increasing trend influenced by various factors. Specifically, the simultaneous rise in NDVI and improvements in hydrothermal conditions contributed to the gradual elevation of NRP, each with varying degrees of influence across Ordos and its sub-regions.
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Affiliation(s)
- Yurong Zheng
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Shouhang Du
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China.
| | - Wenbin Sun
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Cui Feng
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
| | - Qing Su
- College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China
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Wen Y, Cai H, Han D. Driving factors analysis of spatial-temporal evolution of vegetation ecosystem in rocky desertification restoration area of Guizhou Province, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:13122-13140. [PMID: 38240979 DOI: 10.1007/s11356-024-31934-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 01/04/2024] [Indexed: 02/23/2024]
Abstract
The investigation of the temporal-spatial characteristics and driving factors of vegetation ecosystem (VE) alterations held significant practical implications for the evaluation of the efficacy of rocky desertification management initiatives and safeguarding the ecological environment in the rocky desertification restoration region of Guizhou. We computed the comprehensive ecological quality index (Q) of vegetation based on the normalized difference vegetation index (NDVI) and net primary productivity (NPP). Combined with temperature, precipitation, sunshine duration, rocky desertification grade, land use, and the time series of various regions being included in national ecological functional zones, we analyzed the spatial-temporal distribution characteristics of VE changes and their response to climate change (CC) and ecological engineering (EE) by using partial derivative analysis method and scenario setting method in rocky desertification restoration areas in Guizhou. Results demonstrated that (1) the average values of NDVI, NPP, and Q all showed a fluctuating upward trend since 2000. Although the VE status of rocky desertification area was obviously worse than that of no rocky desertification area, it has a higher growth rate, especially the growth rates of NDVI, NPP, and Q in severe rocky desertification area were as high as 0.0050 year-1, 9.0733 g C m-2 year-1, and 0.7829 year-1, and the area with high recovery degree accounted for 93.19%, followed by the middle rocky desertification area. (2) CC was the main driving factor for NDVI and Q recovery, and EE was the main driving factor for NPP recovery. The contribution of EE to NPP and Q recovery increased with the increase of rocky desertification, as high as 82.13% and 30.31% in severe rocky desertification area. (3) The more serious the rocky desertification was, the more dependent the vegetation restoration was on ecological engineering, and the more difficult the restoration was. It was urgent to solve the ecological environmental problems. (4) EE played a greater role in the restoration of VE in the early stage of implementation. Its role gradually decreased in the later stages of implementation, while the role of CC increased. We provide a scientific basis for the follow-up treatment of rocky desertification, ecological environment restoration, and ecological protection effectiveness evaluation in Guizhou.
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Affiliation(s)
- Yiting Wen
- College of Mining, Guizhou University, Guiyang, 550025, China
| | - Hong Cai
- College of Mining, Guizhou University, Guiyang, 550025, China.
| | - Duo Han
- College of Mining, Guizhou University, Guiyang, 550025, China
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Yang C, Zhai G, Fu M, Sun C. Spatiotemporal characteristics and influencing factors of net primary production from 2000 to 2021 in China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:91084-91094. [PMID: 37466838 DOI: 10.1007/s11356-023-28666-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 07/03/2023] [Indexed: 07/20/2023]
Abstract
With the rapid development of remote sensing, variously high temporal and spatial resolution products of different sensors were gradually applied aspects of researches, which could achieve rapid and low-cost monitors of terrestrial environment. It was meaningful to analyze the latest and long-term changes of net primary production (NPP), which could reflect the human-induced effects on ecological environment. In our study, we used Sen's slope and Mann-Kendall test to analyze the spatiotemporal changes of NPP. Then, we used fluctuation model and Moran model to reveal the stability and clusters of NPP, respectively. Next, we quantitatively analyzed NPP changes in the perspectives of land use types and provinces. Finally, we used geographically weighted regression (GWR) model to analyze effects of different factors on NPP. The result showed that NPP presented significant increase in most areas of China from 2000 to 2021. Especially, Loess Plateau showed obvious NPP increase. Meanwhile, "high-high" cluster of NPP difference were mainly distributed in the ecological policies-influenced areas. The slope in 5-15° has the highest growth trend, and the slope > 25° has the slowest growth trend. Cropland, forests, and shrub revealed an obvious improvement of NPP, which indicated afforestation and intensive farmed played a key role. Temperature, precipitation, population density, and elevation had significant effects on NPP (p < 0.05) in 2000, 2011, and 2021. The degree of effects of human activities was gradually increase in GWR model. In this scenario, related ecological policies had vita influencing on NPP improvement. Our study could provide a help for monitor of ecological environment and government policies.
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Affiliation(s)
- Chen Yang
- School of Land Science and Technology, China University of Geosciences (Beijing), Haidian District, 29 Xueyuan Road, Beijing, 100083, China
- Real Estate Registration Center, Ministry of Natural Resources, Beijing, 100034, China
| | - Guohui Zhai
- Real Estate Registration Center, Ministry of Natural Resources, Beijing, 100034, China
| | - Meichen Fu
- School of Land Science and Technology, China University of Geosciences (Beijing), Haidian District, 29 Xueyuan Road, Beijing, 100083, China.
| | - Chang Sun
- School of Modern Science & Technology, Hebei Agricultural University, Hebei, 071001, China
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Liu Y, Gui D, Yin C, Zhang L, Xue D, Liu Y, Ahmed Z, Zeng F. Effects of Human Activities on Evapotranspiration and Its Components in Arid Areas. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:2795. [PMID: 36833495 PMCID: PMC9956289 DOI: 10.3390/ijerph20042795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/16/2023] [Accepted: 01/26/2023] [Indexed: 06/18/2023]
Abstract
With the increasing impact of human activities on the environment, evapotranspiration (ET) has changed in arid areas, which further affects the water resources availability in the region. Therefore, understanding the impact of human activities on ET and its components is helpful to the management of water resources in arid areas. This study verified the accuracy of Fisher's model (PT-JPL model) for ET estimation in southern Xinjiang, China by using the evaporation complementarity theory dataset (AET dataset). The ET and the evapotranspiration components (T:E) of six land-use types were estimated in southern Xinjiang from 1982 to 2015, and the impact of human activities on ET was analyzed. In addition, the impact of four environmental factors (temperature (Temp), net radiation (Rn), relative humidity (RH), and NDVI) on ET were evaluated. The results showed that the calculated ET values of the PT-JPL model were close to the ET values of the AET dataset. The correlation coefficient (R2) was more than 0.8, and the NSE was close to 1. In grassland, water area, urban industrial and mining land, forest land, and cultivated land, the ET values were high, and in unused land types, the ET values were the lowest. The T:E values varied greatly in urban industrial and mining land, forest land, and cultivated land, which was due to the intensification of human activities, and the values were close to 1 in summer in recent years. Among the four environmental factors, temperature largely influenced the monthly ET. These findings suggest that human activities have significantly reduced soil evaporation and improved water use efficiency. The impact of human activities on environmental factors has caused changes in ET and its components, and appropriate oasis expansion is more conducive to regional sustainable development.
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Affiliation(s)
- Yunfei Liu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele 848300, China
- College of Resources and Environment, University of Chinese Academy of Sciences, College of Resources and Environment, Beijing 100049, China
| | - Dongwei Gui
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele 848300, China
| | - Changjun Yin
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele 848300, China
- College of Resources and Environment, University of Chinese Academy of Sciences, College of Resources and Environment, Beijing 100049, China
| | - Lei Zhang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele 848300, China
- College of Resources and Environment, University of Chinese Academy of Sciences, College of Resources and Environment, Beijing 100049, China
| | - Dongping Xue
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele 848300, China
- College of Resources and Environment, University of Chinese Academy of Sciences, College of Resources and Environment, Beijing 100049, China
| | - Yi Liu
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele 848300, China
| | - Zeeshan Ahmed
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele 848300, China
| | - Fanjiang Zeng
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
- Cele National Station of Observation and Research for Desert-Grassland Ecosystems, Cele 848300, China
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Shi X, Shi M, Zhang N, Wu M, Ding H, Li Y, Chen F. Effects of climate change and human activities on gross primary productivity in the Heihe River Basin, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:4230-4244. [PMID: 35965299 DOI: 10.1007/s11356-022-22505-y] [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: 03/01/2022] [Accepted: 08/08/2022] [Indexed: 06/15/2023]
Abstract
As the primary source of carbon dioxide fixation, vegetation is critical to the carbon sink process. In this paper, the Net Primary Productivity (NPP) and the Gross Primary Productivity (GPP) were simulated using the Carnegie-Ames-Stanford Approach (CASA) model and the Vegetation Photosynthesis Model (VPM), respectively, and then the Potential Gross Primary Productivity (PGPP) and the GPP affected by human activities (AGPP) were simulated by combining Potential Net Primary Productivity (PNPP), and then the impact of climate change and human activities on GPP was assessed in the Heihe River Basin (HRB). The results showed that the GPP of grassland and Bare or Sparse Vegetation (BSV) exhibited a fluctuation rise, with increases of 0.709 gCm-2 a-1 and 0.115 gCm-2 a-1, respectively, whereas the GPP of cropland showed a fluctuation reduction, with a decline rate of -0.465 gCm-2 a-1. Climate change and human activity are both positive for vegetation growth, and human activity being the primary factor influencing GPP change. Human-dominated vegetation restoration accounted for 56.1% of the overall restoration area, with grassland GPP being the most visible response to human activities. The GPP changes in crop and grassland had a positive correlation with precipitation but a negative correlation with temperature among climate change factors, whereas the GPP changes in BSV had a negative correlation with both precipitation and temperature. Quantitative analyses of climate change and human activities' dynamic contributions to vegetation can give scientific and theoretical insight for dealing with global climate change.
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Affiliation(s)
- Xiaoliang Shi
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China
| | - Mengqi Shi
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China.
| | - Na Zhang
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China
- Aerial Photogrammetry and Remote Sensing Group Co., Ltd., Xi'an, 710100, China
| | - Mengyue Wu
- Aerial Photogrammetry and Remote Sensing Group Co., Ltd., Xi'an, 710100, China
| | - Hao Ding
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China
| | - Yi Li
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China
| | - Fei Chen
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China
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