Quantifying the Contribution of Extreme Climate Indices to the Dynamics of Net Primary Productivity of Vegetation in the Qinba Mountain Area
［Objective］ To thoroughly investigate the effects of extreme climate events on the net primary productivity (NPP) of vegetation in the Qinba Mountain area. ［Methods］ Using the Qinba Mountain area as an example area, 161 meteorological station observations from 1960 to 2023 and MOD17A3 dataset from 2...
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| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal of Soil and Water Conservation
2025-04-01
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| Series: | Shuitu Baochi Xuebao |
| Subjects: | |
| Online Access: | http://stbcxb.alljournal.com.cn/stbcxben/article/abstract/20250215 |
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| Summary: | ［Objective］ To thoroughly investigate the effects of extreme climate events on the net primary productivity (NPP) of vegetation in the Qinba Mountain area. ［Methods］ Using the Qinba Mountain area as an example area, 161 meteorological station observations from 1960 to 2023 and MOD17A3 dataset from 2001 to 2020 were used, and fitted regression, ridge regression and other analytical methods were applied to study the spatial and temporal evolution of the two and to quantify the contribution of extreme climate indices to the trend of NPP change. ［Results］ 1) the overall development of NPP in the study area was favourable, with an average annual growth rate of 5.02 g/(m2·a) (calculated by C). 2) Extreme warm events significantly increased and extreme cold events significantly decreased in the Qinba Mountain area from 1960 to 2023, whereas the changes in extreme precipitation events were not obvious. 3) Changes in the CSDI, ID, TN10p, CDD, R10, R20 and TR had a positive impact on the NPP trends, with the greatest contribution from the TN10p; changes in the Rx5day negatively affected the NPP trends. ［Conclusion］ The study can provide data or theoretical support for the conservation of terrestrial ecosystems in the Qinba Mountain area under the background of climate warming and for coping with extreme climate events. |
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| ISSN: | 1009-2242 |