Spatiotemporal variation and driving mechanisms of vegetation net primary productivity in Hunan Province from 2001 to 2023
Understanding the spatiotemporal variation in vegetation net primary productivity (NPP) and its response to natural and anthropogenic factors is essential for advancing regional ecological conservation and restoration. Therefore, this study employed the Mann–Kendall test, Sen's slope estimator,...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Science of Remote Sensing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666017225000756 |
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| Summary: | Understanding the spatiotemporal variation in vegetation net primary productivity (NPP) and its response to natural and anthropogenic factors is essential for advancing regional ecological conservation and restoration. Therefore, this study employed the Mann–Kendall test, Sen's slope estimator, and partial correlation analysis to identify the trends and relationships between NPP and climatic factors across Hunan Province, China. Additionally, Random Forest and Geodetector models were used to evaluate the explanatory power of natural and anthropogenic factors on NPP. The following results were obtained: (1) During the study period from 2001 to 2023, the average annual NPP showed an increasing trend, with a growth rate of 2.66 gC/m2/a; (2) in high-altitude areas and the Dongting Lake Plain, average NPP was lower during 2019–2023 than that during 2001–2005, but higher in other regions. (3) in Hunan Province, NPP was more sensitive to temperature than to precipitation. Considering the lag effect of climatic factors, the temperature from the previous year showed a significant positive impact on NPP; (4) elevation had the strongest explanatory power for NPP and exhibited notable bivariate enhancement when interacting with other factors. Thus, our study provides a systematic analysis of the temporal and spatial variations in NPP, offering a scientific basis for the sustainable management of regional ecosystems. |
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| ISSN: | 2666-0172 |