The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian Mountains
The Qilian Mountains and Huangshui River Basin (HRB) represent significant ecological functional areas and carbon reservoirs within China. The estimation and prediction of vegetation net primary productivity (NPP) in this area is beneficial for the management of China’s terrestrial ecosystems. Never...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Environmental Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1459669/full |
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| author | Sujing Ding Qiang Sun Yan Guo Xiao Wei |
| author_facet | Sujing Ding Qiang Sun Yan Guo Xiao Wei |
| author_sort | Sujing Ding |
| collection | DOAJ |
| description | The Qilian Mountains and Huangshui River Basin (HRB) represent significant ecological functional areas and carbon reservoirs within China. The estimation and prediction of vegetation net primary productivity (NPP) in this area is beneficial for the management of China’s terrestrial ecosystems. Nevertheless, the existing estimation methods for vegetation NPP at the local scale are characterised by considerable uncertainty and error, and have not accounted for the influence of multi-factor interactions. Accordingly, this study initially sought to quantify the vegetation NPP data within the HRB from 2000 to 2019 through the implementation of an improved Carnegie-Ames-Stanford Approach (CASA) model. Subsequently, it endeavoured to elucidate the spatiotemporal evolution patterns and influencing factors of vegetation NPP within the HRB over the years. Subsequently, the ConvGRU spatiotemporal prediction model was employed to investigate the prospective trajectory of vegetation NPP in the HRB. The findings revealed a notable upward trajectory in the annual variation of vegetation NPP in the HRB between 2000 and 2019. The majority of regions have demonstrated a notable increase in vegetation NPP, although a few areas have exhibited a decline. Furthermore, the correlation between vegetation NPP and PRE, TEMP, SR, and NDVI exhibits regional disparities. Furthermore, the spatial variation characteristics of vegetation NPP in the HRB in the future also demonstrate an overall increasing trend. Additionally, the vegetation NPP in the HRB exhibits significant spatial distribution characteristics, with evident trends of hot spot contraction or cold spot expansion. This study provides pivotal methods and theoretical support for the assessment of carbon sequestration status in the HRB of the Qilian Mountains and analogous regions. |
| format | Article |
| id | doaj-art-bc5f1ec6f85b435c99857720ed57cc25 |
| institution | Kabale University |
| issn | 2296-665X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Environmental Science |
| spelling | doaj-art-bc5f1ec6f85b435c99857720ed57cc252025-01-13T06:11:09ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2025-01-011210.3389/fenvs.2024.14596691459669The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian MountainsSujing Ding0Qiang Sun1Yan Guo2Xiao Wei3Bureau of Natural Resources of Baiyin City, Baiyin, ChinaChina 22MCC Group Co., Ltd., Tangshan, ChinaFaculty of Geomatics, Lanzhou Jiaotong University, Lanzhou, ChinaGansu Provincial Basic Geographic Information Center, Lanzhou, ChinaThe Qilian Mountains and Huangshui River Basin (HRB) represent significant ecological functional areas and carbon reservoirs within China. The estimation and prediction of vegetation net primary productivity (NPP) in this area is beneficial for the management of China’s terrestrial ecosystems. Nevertheless, the existing estimation methods for vegetation NPP at the local scale are characterised by considerable uncertainty and error, and have not accounted for the influence of multi-factor interactions. Accordingly, this study initially sought to quantify the vegetation NPP data within the HRB from 2000 to 2019 through the implementation of an improved Carnegie-Ames-Stanford Approach (CASA) model. Subsequently, it endeavoured to elucidate the spatiotemporal evolution patterns and influencing factors of vegetation NPP within the HRB over the years. Subsequently, the ConvGRU spatiotemporal prediction model was employed to investigate the prospective trajectory of vegetation NPP in the HRB. The findings revealed a notable upward trajectory in the annual variation of vegetation NPP in the HRB between 2000 and 2019. The majority of regions have demonstrated a notable increase in vegetation NPP, although a few areas have exhibited a decline. Furthermore, the correlation between vegetation NPP and PRE, TEMP, SR, and NDVI exhibits regional disparities. Furthermore, the spatial variation characteristics of vegetation NPP in the HRB in the future also demonstrate an overall increasing trend. Additionally, the vegetation NPP in the HRB exhibits significant spatial distribution characteristics, with evident trends of hot spot contraction or cold spot expansion. This study provides pivotal methods and theoretical support for the assessment of carbon sequestration status in the HRB of the Qilian Mountains and analogous regions.https://www.frontiersin.org/articles/10.3389/fenvs.2024.1459669/fullvegetation net primary productivityspatiotemporal evolution patternsfuture predictionHuangshui River Basin in Qilian MountainsConvGRU |
| spellingShingle | Sujing Ding Qiang Sun Yan Guo Xiao Wei The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian Mountains Frontiers in Environmental Science vegetation net primary productivity spatiotemporal evolution patterns future prediction Huangshui River Basin in Qilian Mountains ConvGRU |
| title | The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian Mountains |
| title_full | The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian Mountains |
| title_fullStr | The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian Mountains |
| title_full_unstemmed | The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian Mountains |
| title_short | The spatiotemporal evolution and prediction of vegetation NPP in the Huangshui River Basin of Qilian Mountains |
| title_sort | spatiotemporal evolution and prediction of vegetation npp in the huangshui river basin of qilian mountains |
| topic | vegetation net primary productivity spatiotemporal evolution patterns future prediction Huangshui River Basin in Qilian Mountains ConvGRU |
| url | https://www.frontiersin.org/articles/10.3389/fenvs.2024.1459669/full |
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