Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010
Exploring the spatiotemporal variation in vegetation net primary productivity (NPP) and evaluating the impact of different drivers on NPP are vital for vegetation protection and restoration in Guizhou Province, which is a typical karst area in China. In this study, Cox–Stuart test, linear regression...
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Elsevier
2021
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oai:doaj.org-article:ca984b8bed164f6abd3a93b2cfc229362021-12-01T05:01:51ZSpatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 20101470-160X10.1016/j.ecolind.2021.108280https://doaj.org/article/ca984b8bed164f6abd3a93b2cfc229362021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21009456https://doaj.org/toc/1470-160XExploring the spatiotemporal variation in vegetation net primary productivity (NPP) and evaluating the impact of different drivers on NPP are vital for vegetation protection and restoration in Guizhou Province, which is a typical karst area in China. In this study, Cox–Stuart test, linear regression and spatial statistics were used to analyze the spatiotemporal variation in vegetation NPP in Guizhou. Random Forest combined with local spatial autocorrelation analysis was applied to quantify the effects of eight drivers from climate, topography, human activities and vegetation growth status on the NPP from different clusters in different years based on the NPP product from the Global Production Efficiency Model (GLO-PEM). The following results were obtained. (1) The average annual NPP in Guizhou during 2000–2010 showed no significant increasing or decreasing trend. (2) The annual mean NPP in the west was the lowest in the period, but the NPP per year had a rising tendency in the west and a declining one in the east from 2000 to 2010. (3) The NPP in Guizhou showed a significant clustering trend across each year in the period, whereas the clustering degree reflected a downward trend over time. The statistically significant clusters of high values (HH) and clusters of low values (LL) of NPP were mainly distributed in the east and west, respectively, in 2000, 2005 and 2010. (4) The accuracy of the driver analysis of the three NPP cluster types combined (HH + LL, HL + LH, and HH + HL + LH + LL) was higher than that of the other cluster types in Guizhou in 2000, 2005 and 2010. Vegetation growth and human activities show greater effect on the NPP of the three combined types than climate and topography. These findings are valuable in refining the results of the driver analysis and improving their accuracy. This study provides a deeper insight into the effect of different drivers on the NPP from different spatial clusters in Guizhou. Our results indicate that implementing appropriate silvicultural measures and formulating effective management policies are essential to improve the NPP and reduce the adverse effects of human activities on NPP in Guizhou.Liyi SongMingyang LiHai XuYing GuoZi WangYingchang LiXuejuan WuLuchun FengJun ChenXin LuYanxin XuTao LiElsevierarticleVegetationNet primary productivitySpatiotemporal variationDriverSpatial statisticsGuizhouEcologyQH540-549.5ENEcological Indicators, Vol 132, Iss , Pp 108280- (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Vegetation Net primary productivity Spatiotemporal variation Driver Spatial statistics Guizhou Ecology QH540-549.5 |
| spellingShingle |
Vegetation Net primary productivity Spatiotemporal variation Driver Spatial statistics Guizhou Ecology QH540-549.5 Liyi Song Mingyang Li Hai Xu Ying Guo Zi Wang Yingchang Li Xuejuan Wu Luchun Feng Jun Chen Xin Lu Yanxin Xu Tao Li Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010 |
| description |
Exploring the spatiotemporal variation in vegetation net primary productivity (NPP) and evaluating the impact of different drivers on NPP are vital for vegetation protection and restoration in Guizhou Province, which is a typical karst area in China. In this study, Cox–Stuart test, linear regression and spatial statistics were used to analyze the spatiotemporal variation in vegetation NPP in Guizhou. Random Forest combined with local spatial autocorrelation analysis was applied to quantify the effects of eight drivers from climate, topography, human activities and vegetation growth status on the NPP from different clusters in different years based on the NPP product from the Global Production Efficiency Model (GLO-PEM). The following results were obtained. (1) The average annual NPP in Guizhou during 2000–2010 showed no significant increasing or decreasing trend. (2) The annual mean NPP in the west was the lowest in the period, but the NPP per year had a rising tendency in the west and a declining one in the east from 2000 to 2010. (3) The NPP in Guizhou showed a significant clustering trend across each year in the period, whereas the clustering degree reflected a downward trend over time. The statistically significant clusters of high values (HH) and clusters of low values (LL) of NPP were mainly distributed in the east and west, respectively, in 2000, 2005 and 2010. (4) The accuracy of the driver analysis of the three NPP cluster types combined (HH + LL, HL + LH, and HH + HL + LH + LL) was higher than that of the other cluster types in Guizhou in 2000, 2005 and 2010. Vegetation growth and human activities show greater effect on the NPP of the three combined types than climate and topography. These findings are valuable in refining the results of the driver analysis and improving their accuracy. This study provides a deeper insight into the effect of different drivers on the NPP from different spatial clusters in Guizhou. Our results indicate that implementing appropriate silvicultural measures and formulating effective management policies are essential to improve the NPP and reduce the adverse effects of human activities on NPP in Guizhou. |
| format |
article |
| author |
Liyi Song Mingyang Li Hai Xu Ying Guo Zi Wang Yingchang Li Xuejuan Wu Luchun Feng Jun Chen Xin Lu Yanxin Xu Tao Li |
| author_facet |
Liyi Song Mingyang Li Hai Xu Ying Guo Zi Wang Yingchang Li Xuejuan Wu Luchun Feng Jun Chen Xin Lu Yanxin Xu Tao Li |
| author_sort |
Liyi Song |
| title |
Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010 |
| title_short |
Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010 |
| title_full |
Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010 |
| title_fullStr |
Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010 |
| title_full_unstemmed |
Spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in China from 2000 to 2010 |
| title_sort |
spatiotemporal variation and driving factors of vegetation net primary productivity in a typical karst area in china from 2000 to 2010 |
| publisher |
Elsevier |
| publishDate |
2021 |
| url |
https://doaj.org/article/ca984b8bed164f6abd3a93b2cfc22936 |
| work_keys_str_mv |
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