Research on Vegetation Dynamics and Driving Mechanisms in Karst Desertified Areas Integrating Remote Sensing and Multi-Source Data
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| Publicat a: | Agriculture vol. 15, no. 23 (2025), p. 2464-2484 |
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| Autor principal: | |
| Altres autors: | , , , , , |
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MDPI AG
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| Accés en línia: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3280927171 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2077-0472 | ||
| 024 | 7 | |a 10.3390/agriculture15232464 |2 doi | |
| 035 | |a 3280927171 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231331 |2 nlm | ||
| 100 | 1 | |a Tang, Jimin |u College of Soil and Water Conservation, Southwest Forestry University, Kunming 650244, China | |
| 245 | 1 | |a Research on Vegetation Dynamics and Driving Mechanisms in Karst Desertified Areas Integrating Remote Sensing and Multi-Source Data | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Rocky desertification severely restricts socio-economic development in the karst regions. However, assessments linking karst rocky desertification and NPP changes over the long term and at high resolution are limited. This study aims to reveal the spatiotemporal patterns and driving mechanisms of NPP changes in Wenshan Prefecture, addressing the scientific gap in quantitative process research and mechanism identification in karst desertification areas. We estimated vegetation NPP from 2000 to 2020 using remote sensing data and the CASA model. The Theil–Sen trend analysis and Mann–Kendall test were applied to assess temporal variation, while a Geographical Detector identified the dominant natural and human factors and their interactions shaping NPP spatial patterns. Our results showed that NPP increased overall by 4.07 gC m−2 a−1, alongside a general decline in rocky desertification. The most significant improvement occurred between 2010 and 2015, when rocky desertification shrank by 2224 km2 and the dynamic rate reached 1.42%. Mean NPP reached 1057 gC m−2 a−1, with a “northwest high–southeast low” spatial pattern, and 77% of the region showed significant increases. Rocky desertification was most severe at elevations between 1000 and 2000 m. In the karst region, NPP is mainly controlled by natural factors, with soil depth and slope being the strongest influences. Human activity had the largest negative impact, and most factors interacted synergistically, where hydrothermal gradients and human disturbances more strongly suppressed NPP on steep, thin slopes than individually expected. These findings provide robust scientific evidence and practical decision-making support for ecological restoration, rocky desertification control and long-term sustainable development in Wenshan and other karst regions, highlighting the importance of continuous monitoring and adaptive management strategies to consolidate restoration achievements and guide future land-use planning and regional ecological policy. | |
| 651 | 4 | |a China | |
| 651 | 4 | |a East Asia | |
| 653 | |a Desertification | ||
| 653 | |a Vegetation | ||
| 653 | |a Karst | ||
| 653 | |a Datasets | ||
| 653 | |a Trend analysis | ||
| 653 | |a Soil erosion | ||
| 653 | |a Productivity | ||
| 653 | |a Remote sensing | ||
| 653 | |a Environmental restoration | ||
| 653 | |a Lithology | ||
| 653 | |a Land use | ||
| 653 | |a Human influences | ||
| 653 | |a Human impact | ||
| 653 | |a Human factors | ||
| 653 | |a Soil depth | ||
| 653 | |a Geology | ||
| 653 | |a Computer centers | ||
| 653 | |a Carbon sequestration | ||
| 653 | |a Land use management | ||
| 653 | |a Economic development | ||
| 653 | |a Regions | ||
| 653 | |a Sustainable development | ||
| 653 | |a Regional planning | ||
| 653 | |a Temporal variations | ||
| 653 | |a Adaptive management | ||
| 653 | |a Spatial data | ||
| 653 | |a Decision making | ||
| 653 | |a Land use planning | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Liu, Yifei |u College of Forestry, Southwest Forestry University, Kunming 650224, China | |
| 700 | 1 | |a Wang, Yan |u College of Soil and Water Conservation, Southwest Forestry University, Kunming 650244, China | |
| 700 | 1 | |a Ye Jiangxia |u College of Forestry, Southwest Forestry University, Kunming 650224, China | |
| 700 | 1 | |a Yin Xiaojie |u College of Forestry, Southwest Forestry University, Kunming 650224, China | |
| 700 | 1 | |a Yu Zhexiu |u College of Soil and Water Conservation, Southwest Forestry University, Kunming 650244, China | |
| 700 | 1 | |a Zhang, Chao |u College of Forestry, Southwest Forestry University, Kunming 650224, China | |
| 773 | 0 | |t Agriculture |g vol. 15, no. 23 (2025), p. 2464-2484 | |
| 786 | 0 | |d ProQuest |t Agriculture Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3280927171/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3280927171/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3280927171/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |