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Xuan W, Rao L. Spatiotemporal dynamics of net primary productivity and its influencing factors in the middle reaches of the Yellow River from 2000 to 2020. FRONTIERS IN PLANT SCIENCE 2023; 14:1043807. [PMID: 36778674 PMCID: PMC9911816 DOI: 10.3389/fpls.2023.1043807] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 01/02/2023] [Indexed: 06/18/2023]
Abstract
Introduction Net primary productivity (NPP) is an important indicator used to characterize the productivity of terrestrial ecosystems. The spatial distribution and dynamic change in NPP are closely related to regional climate, vegetation growth and human activities. Studying the spatiotemporal dynamics of NPP and its influencing factors plays a vital role in understanding ecosystem carbon sink capacity. Methods Based on MODIS-NPP data, meteorological data, and land use data from 2000 to 2020, we analyzed the spatiotemporal variation characteristics and influencing factors of NPP in the middle reaches of the Yellow River (MRYR) by using unary linear regression analysis, third-order partial correlation analysis, and Sen+Mann-Kendall trend analysis. Results The results showed that the annual average NPP of the MRYR was 319.24 gCm-2a-1 with a spatially decreasing trend from the southern part to the northern part. From 2000 to 2020, the annual average NPP experienced a fluctuating upward trend at a rate of 2.83 gCm-2a-1, and the area with a significant upward trend accounted for 87.68%. The NPP of different land use types differed greatly, in which forest had the greatest increase in NPP. Temperature had a negative correlation with NPP in most parts of the MRYR. Water vapor pressure promoted the accumulation of NPP in the northwestern MRYR. The areas with a positive correlation between NPP and water vapor pressure accounted for 87.6%, and 20.43% of the MRYR area passed the significance test of P< 0.05. Conclusion The results of the study highlight the impact of climate factors and land-use changes on NPP and provide theoretical guidance for high-quality sustainable development in the MRYR.
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Affiliation(s)
- Wenxi Xuan
- College of Soil and Water Conservation, Beijing Forestry University, Beijing, China
- Key Laboratory of State Forestry and Grassland Administration on Soil and Water Conservation, Beijing, China
| | - Liangyi Rao
- College of Soil and Water Conservation, Beijing Forestry University, Beijing, China
- Key Laboratory of State Forestry and Grassland Administration on Soil and Water Conservation, Beijing, China
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Li Y, Zhang J, Zhu H, Zhou Z, Jiang S, He S, Zhang Y, Huang Y, Li M, Xing G, Li G. Soil Erosion Characteristics and Scenario Analysis in the Yellow River Basin Based on PLUS and RUSLE Models. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:1222. [PMID: 36673979 PMCID: PMC9858744 DOI: 10.3390/ijerph20021222] [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: 12/13/2022] [Revised: 01/03/2023] [Accepted: 01/06/2023] [Indexed: 06/17/2023]
Abstract
Soil erosion is an important global environmental issue that severely affects regional ecological environment and socio-economic development. The Yellow River (YR) is China's second largest river and the fifth largest one worldwide. Its watershed is key to China's economic growth and environmental security. In this study, six impact factors, including rainfall erosivity (R), soil erosivity (K), slope length (L), slope steepness (S), cover management (C), and protective measures (P), were used. Based on the revised universal soil loss equation (RUSLE) model, and combined with a geographic information system (GIS), the temporal and spatial distribution of soil erosion (SE) in the YR from 2000 to 2020 was estimated. The patch-generating land use simulation (PLUS) model was used to simulate the land-use and land-cover change (LUCC) under two scenarios (natural development and ecological protection) in 2040; the RUSLE factor P was found to be associated with LUCC in 2040, and soil erosion in the Yellow River Basin (YRB) in 2040 under the two scenarios were predicted and evaluated. This method has great advantages in land-use simulation, but soil erosion is greatly affected by rainfall and slope, and it only focuses on the link between land-usage alteration and SE. Therefore, this method has certain limitations in assessing soil erosion by simulating and predicting land-use change. We found that there is generally slight soil erosivity in the YRB, with the most serious soil erosion occurring in 2000. Areas with serious SE are predominantly situated in the upper reaches (URs), followed by the middle reaches (MRs), and soil erosion is less severe in the lower reaches. Soil erosion in the YRB decreased 11.92% from 2000 to 2020; thus, soil erosion has gradually reduced in this area over time. Based on the GIS statistics, land-use change strongly influences SE, while an increase in woodland area has an important positive effect in reducing soil erosion. By predicting land-use changes in 2040, compared to the natural development scenario, woodland and grassland under the ecological protection scenario can be increased by 1978 km2 and 2407 km2, respectively. Soil erosion can be decreased by 6.24%, indicating the implementation of woodland and grassland protection will help reduce soil erosion. Policies such as forest protection and grassland restoration should be further developed and implemented on the MRs and URs of the YR. Our research results possess important trend-setting significance for soil erosion control protocols and ecological environmental protection in other large river basins worldwide.
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Affiliation(s)
- Yanyan Li
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Jinbing Zhang
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Hui Zhu
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Zhimin Zhou
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
- Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of Education, Henan University, Kaifeng 475004, China
- Regional Planning and Development Center, Henan University, Kaifeng 475004, China
| | - Shan Jiang
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Shuangyan He
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Ying Zhang
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Yicheng Huang
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Mengfan Li
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Guangrui Xing
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
| | - Guanghui Li
- College of Geography and Environmental Science, Henan University, Kaifeng 475004, China
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