A Decade’s Change in Vegetation Productivity and Its Response to Climate Change over Northeast China
In this study, we simulated vegetation net primary productivity (NPP) using the boreal ecosystem productivity simulator (BEPS) between 2003 and 2012 over Northeast China, a region that is significantly affected by climate change. The NPP was then validated against the measurements that were calculat...
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MDPI AG
2021-04-01
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| Series: | Plants |
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| Online Access: | https://www.mdpi.com/2223-7747/10/5/821 |
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| author | Min Yan Mei Xue Li Zhang Xin Tian Bowei Chen Yuqi Dong |
| author_facet | Min Yan Mei Xue Li Zhang Xin Tian Bowei Chen Yuqi Dong |
| author_sort | Min Yan |
| collection | DOAJ |
| description | In this study, we simulated vegetation net primary productivity (NPP) using the boreal ecosystem productivity simulator (BEPS) between 2003 and 2012 over Northeast China, a region that is significantly affected by climate change. The NPP was then validated against the measurements that were calculated from tree ring data, with a determination coefficient (<i>R</i><sup>2</sup>) = 0.84 and the root mean square error (<i>RMSE</i>) = 42.73 gC/m<sup>2</sup>·a. Overall, the NPP showed an increasing trend over Northeast China, with the average rate being 4.48 gC/m<sup>2</sup>·a. Subsequently, partial correlation and lag analysis were conducted between the NPP and climatic factors. The partial correlation analysis suggested that temperature was the predominant factor that accounted for changes in the forest NPP. Solar radiation was the main factor that affected the forest NPP, and the grass NPP was the most closely associated with precipitation. The relative humidity substantially affected the annual variability of the shrub and crop NPPs. The lag time of the NPP related to precipitation increased with the vegetation growth, and it was found that the lag period of the forest was longer than that of grass and crops, whereas the cumulative lag month of the forest was shorter. This comprehensive analysis of the response of the vegetation NPP to climate change can provide scientific references for the managing departments that oversee relevant resources. |
| first_indexed | 2024-03-10T12:08:42Z |
| format | Article |
| id | doaj.art-82da93da621f4992b73cf7d1c38854d3 |
| institution | Directory Open Access Journal |
| issn | 2223-7747 |
| language | English |
| last_indexed | 2024-03-10T12:08:42Z |
| publishDate | 2021-04-01 |
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| series | Plants |
| spelling | doaj.art-82da93da621f4992b73cf7d1c38854d32023-11-21T16:25:20ZengMDPI AGPlants2223-77472021-04-0110582110.3390/plants10050821A Decade’s Change in Vegetation Productivity and Its Response to Climate Change over Northeast ChinaMin Yan0Mei Xue1Li Zhang2Xin Tian3Bowei Chen4Yuqi Dong5Kay Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaPatent Examination Cooperation (Beijing) Center of the Patent Office, CNIPA, Beijing 100160, ChinaKay Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaInstitute of Forest Resource information Techniques, Chinese Academy of Forestry, Beijing 100091, ChinaKay Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaKay Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaIn this study, we simulated vegetation net primary productivity (NPP) using the boreal ecosystem productivity simulator (BEPS) between 2003 and 2012 over Northeast China, a region that is significantly affected by climate change. The NPP was then validated against the measurements that were calculated from tree ring data, with a determination coefficient (<i>R</i><sup>2</sup>) = 0.84 and the root mean square error (<i>RMSE</i>) = 42.73 gC/m<sup>2</sup>·a. Overall, the NPP showed an increasing trend over Northeast China, with the average rate being 4.48 gC/m<sup>2</sup>·a. Subsequently, partial correlation and lag analysis were conducted between the NPP and climatic factors. The partial correlation analysis suggested that temperature was the predominant factor that accounted for changes in the forest NPP. Solar radiation was the main factor that affected the forest NPP, and the grass NPP was the most closely associated with precipitation. The relative humidity substantially affected the annual variability of the shrub and crop NPPs. The lag time of the NPP related to precipitation increased with the vegetation growth, and it was found that the lag period of the forest was longer than that of grass and crops, whereas the cumulative lag month of the forest was shorter. This comprehensive analysis of the response of the vegetation NPP to climate change can provide scientific references for the managing departments that oversee relevant resources.https://www.mdpi.com/2223-7747/10/5/821vegetation net primary productivityBEPSpartial correlation analysislag analysis |
| spellingShingle | Min Yan Mei Xue Li Zhang Xin Tian Bowei Chen Yuqi Dong A Decade’s Change in Vegetation Productivity and Its Response to Climate Change over Northeast China Plants vegetation net primary productivity BEPS partial correlation analysis lag analysis |
| title | A Decade’s Change in Vegetation Productivity and Its Response to Climate Change over Northeast China |
| title_full | A Decade’s Change in Vegetation Productivity and Its Response to Climate Change over Northeast China |
| title_fullStr | A Decade’s Change in Vegetation Productivity and Its Response to Climate Change over Northeast China |
| title_full_unstemmed | A Decade’s Change in Vegetation Productivity and Its Response to Climate Change over Northeast China |
| title_short | A Decade’s Change in Vegetation Productivity and Its Response to Climate Change over Northeast China |
| title_sort | decade s change in vegetation productivity and its response to climate change over northeast china |
| topic | vegetation net primary productivity BEPS partial correlation analysis lag analysis |
| url | https://www.mdpi.com/2223-7747/10/5/821 |
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