Low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest China from 1981 to 2019
Karst areas are sensitive to environmental changes due to their fragile ecological environments. It is imperative to explore the temporal and spatial variations in the characteristics of vegetation net primary productivity (NPP) and evaluate the influence of different driving factors on NPP. Taking...
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Elsevier
2023-09-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23006076 |
| _version_ | 1797802869593735168 |
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| author | Wen Zhang Mengzhu Xi Haodong Liu Hui Zheng |
| author_facet | Wen Zhang Mengzhu Xi Haodong Liu Hui Zheng |
| author_sort | Wen Zhang |
| collection | DOAJ |
| description | Karst areas are sensitive to environmental changes due to their fragile ecological environments. It is imperative to explore the temporal and spatial variations in the characteristics of vegetation net primary productivity (NPP) and evaluate the influence of different driving factors on NPP. Taking three karst provinces in southwest China as the study area, where the historical vegetation changes and the mechanisms influencing these changes remain unclear; therefore, the present study used vegetation NPP data from 1981 to 2019 to analyze the temporal and spatial variations in the characteristics of vegetation NPP using slope trend analyses and the sequential Mann-Kendall test. The influence of each driving factor on vegetation NPP and the interaction between each driving factor were investigated using the optimal parameters-based geographic detector (OPGD) model. The results were as follows: (1) The annual variation of the total NPP in the study area from 1981 to 2019 showed a fluctuating growth trend, with a slow growth rate before 2005 followed by a rapid increase. (2) The annual fluctuations in the seasonal NPP in the study area were generally upward, and the total NPP of vegetation in summer was the highest, but the growth rate of NPP in autumn was the fastest, and the area with the largest increase in NPP in autumn was the largest. (3) NPP was related to natural factors, with slope being the primary influencing factor at the annual scale. However, at the seasonal scale, there were differences in the explanatory power of the influencing factors on vegetation NPP. The highest explanatory power was observed for surface soil moisture in spring, air temperature in summer, and precipitation in autumn and winter. (4) The spatiotemporal evolution of NPP characteristics was affected by the interaction among various natural factors. At the annual and seasonal scales, the interaction between each climatic factor and slope greatly enhanced the explanatory power of individual climatic factors. Taken together, the interaction between slope and precipitation contributes the most to NPP. |
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| issn | 1470-160X |
| language | English |
| last_indexed | 2024-03-13T05:13:19Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
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| series | Ecological Indicators |
| spelling | doaj.art-a8652cc6176e4915aea098f2cbfc35de2023-06-16T05:08:54ZengElsevierEcological Indicators1470-160X2023-09-01153110465Low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest China from 1981 to 2019Wen Zhang0Mengzhu Xi1Haodong Liu2Hui Zheng3Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, College of Environment and Planning, Henan University, Kaifeng 475004, China; Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng 475004, China; Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Kaifeng 475004, ChinaKey Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, College of Environment and Planning, Henan University, Kaifeng 475004, China; Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng 475004, China; Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Kaifeng 475004, ChinaKey Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, College of Environment and Planning, Henan University, Kaifeng 475004, China; Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng 475004, China; Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Kaifeng 475004, ChinaKey Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, College of Environment and Planning, Henan University, Kaifeng 475004, China; Henan Key Laboratory of Earth System Observation and Modeling, Henan University, Kaifeng 475004, China; Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security, Kaifeng 475004, China; Corresponding author at: Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, College of Environment and Planning, Henan University, Kaifeng 475004, China.Karst areas are sensitive to environmental changes due to their fragile ecological environments. It is imperative to explore the temporal and spatial variations in the characteristics of vegetation net primary productivity (NPP) and evaluate the influence of different driving factors on NPP. Taking three karst provinces in southwest China as the study area, where the historical vegetation changes and the mechanisms influencing these changes remain unclear; therefore, the present study used vegetation NPP data from 1981 to 2019 to analyze the temporal and spatial variations in the characteristics of vegetation NPP using slope trend analyses and the sequential Mann-Kendall test. The influence of each driving factor on vegetation NPP and the interaction between each driving factor were investigated using the optimal parameters-based geographic detector (OPGD) model. The results were as follows: (1) The annual variation of the total NPP in the study area from 1981 to 2019 showed a fluctuating growth trend, with a slow growth rate before 2005 followed by a rapid increase. (2) The annual fluctuations in the seasonal NPP in the study area were generally upward, and the total NPP of vegetation in summer was the highest, but the growth rate of NPP in autumn was the fastest, and the area with the largest increase in NPP in autumn was the largest. (3) NPP was related to natural factors, with slope being the primary influencing factor at the annual scale. However, at the seasonal scale, there were differences in the explanatory power of the influencing factors on vegetation NPP. The highest explanatory power was observed for surface soil moisture in spring, air temperature in summer, and precipitation in autumn and winter. (4) The spatiotemporal evolution of NPP characteristics was affected by the interaction among various natural factors. At the annual and seasonal scales, the interaction between each climatic factor and slope greatly enhanced the explanatory power of individual climatic factors. Taken together, the interaction between slope and precipitation contributes the most to NPP.http://www.sciencedirect.com/science/article/pii/S1470160X23006076Vegetation NPPSpatiotemporal variabilityOPGDSequential mann-kendall test |
| spellingShingle | Wen Zhang Mengzhu Xi Haodong Liu Hui Zheng Low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest China from 1981 to 2019 Ecological Indicators Vegetation NPP Spatiotemporal variability OPGD Sequential mann-kendall test |
| title | Low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest China from 1981 to 2019 |
| title_full | Low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest China from 1981 to 2019 |
| title_fullStr | Low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest China from 1981 to 2019 |
| title_full_unstemmed | Low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest China from 1981 to 2019 |
| title_short | Low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest China from 1981 to 2019 |
| title_sort | low sensitivity of net primary productivity to climatic factors in three karst provinces in southwest china from 1981 to 2019 |
| topic | Vegetation NPP Spatiotemporal variability OPGD Sequential mann-kendall test |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23006076 |
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