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Vegetation Index Reconstruction and Linkage with Drought for the Source Region of the Yangtze River Based on Tree-ring Data
Variations in vegetation are closely related to climate change, but understanding of their characteristics and causes remains limited. As a typical semi-humid and semi-arid cold plateau region, it is important to understand the knowledge of long term Normalized Difference Vegetation Index (NDVI) var...
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Published in: | Chinese geographical science 2021-08, Vol.31 (4), p.684-695 |
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description | Variations in vegetation are closely related to climate change, but understanding of their characteristics and causes remains limited. As a typical semi-humid and semi-arid cold plateau region, it is important to understand the knowledge of long term Normalized Difference Vegetation Index (NDVI) variations and find the potential causes in the source region of the Yangtze River. Based on four tree-ring width chronologies, the regional mean NDVI for July and August spanning the period 1665–2013 was reconstructed using a regression model, and it explained 43.9% of the total variance during the period 1981–2013. In decadal, the reconstructed NDVI showed eight growth stages (1754–1764, 1766–1783, 1794–1811, 1828–1838, 1843–1855, 1862–1873, 1897–1909, and 1932–1945) and four degradation stages (1679–1698, 1726–1753, 1910–1923, and 1988–2000). And based on wavelet analysis, significant cycles of 2–3 yr and 3–8 yr were identified. In additional, there was a significant positive correlation between the NDVI and the Palmer Drought Severity Index (PDSI) during the past 349 yr, and they were mainly in phase. However, according to the results of correlation analysis between different grades of drought/wet and NDVI, there was significant asymmetry in extreme drought years and extreme wet years. In extreme drought years, NDVI was positively correlated with PDSI, and in extreme wet years they were negatively correlated. |
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As a typical semi-humid and semi-arid cold plateau region, it is important to understand the knowledge of long term Normalized Difference Vegetation Index (NDVI) variations and find the potential causes in the source region of the Yangtze River. Based on four tree-ring width chronologies, the regional mean NDVI for July and August spanning the period 1665–2013 was reconstructed using a regression model, and it explained 43.9% of the total variance during the period 1981–2013. In decadal, the reconstructed NDVI showed eight growth stages (1754–1764, 1766–1783, 1794–1811, 1828–1838, 1843–1855, 1862–1873, 1897–1909, and 1932–1945) and four degradation stages (1679–1698, 1726–1753, 1910–1923, and 1988–2000). And based on wavelet analysis, significant cycles of 2–3 yr and 3–8 yr were identified. In additional, there was a significant positive correlation between the NDVI and the Palmer Drought Severity Index (PDSI) during the past 349 yr, and they were mainly in phase. However, according to the results of correlation analysis between different grades of drought/wet and NDVI, there was significant asymmetry in extreme drought years and extreme wet years. In extreme drought years, NDVI was positively correlated with PDSI, and in extreme wet years they were negatively correlated.</description><identifier>ISSN: 1002-0063</identifier><identifier>EISSN: 1993-064X</identifier><identifier>DOI: 10.1007/s11769-021-1217-5</identifier><language>eng</language><publisher>Heidelberg: Science Press</publisher><subject>Climate change ; Correlation analysis ; Drought ; Earth and Environmental Science ; Extreme drought ; Geography ; Rivers ; Vegetation</subject><ispartof>Chinese geographical science, 2021-08, Vol.31 (4), p.684-695</ispartof><rights>Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2021</rights><rights>Science Press, Northeast Institute of Geography and Agroecology, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2021.</rights><rights>Copyright © Wanfang Data Co. Ltd. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c391t-2dd28e7a3fbf4667bc31019d3b26267e92feaf7bca294dfc701aeefcb7a36c5c3</citedby><cites>FETCH-LOGICAL-c391t-2dd28e7a3fbf4667bc31019d3b26267e92feaf7bca294dfc701aeefcb7a36c5c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://www.wanfangdata.com.cn/images/PeriodicalImages/zgdl-e/zgdl-e.jpg</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Li, Jinjian</creatorcontrib><creatorcontrib>Wang, Shu</creatorcontrib><creatorcontrib>Qin, Ningsheng</creatorcontrib><creatorcontrib>Liu, Xisheng</creatorcontrib><creatorcontrib>Jin, Liya</creatorcontrib><title>Vegetation Index Reconstruction and Linkage with Drought for the Source Region of the Yangtze River Based on Tree-ring Data</title><title>Chinese geographical science</title><addtitle>Chin. Geogr. Sci</addtitle><description>Variations in vegetation are closely related to climate change, but understanding of their characteristics and causes remains limited. As a typical semi-humid and semi-arid cold plateau region, it is important to understand the knowledge of long term Normalized Difference Vegetation Index (NDVI) variations and find the potential causes in the source region of the Yangtze River. Based on four tree-ring width chronologies, the regional mean NDVI for July and August spanning the period 1665–2013 was reconstructed using a regression model, and it explained 43.9% of the total variance during the period 1981–2013. In decadal, the reconstructed NDVI showed eight growth stages (1754–1764, 1766–1783, 1794–1811, 1828–1838, 1843–1855, 1862–1873, 1897–1909, and 1932–1945) and four degradation stages (1679–1698, 1726–1753, 1910–1923, and 1988–2000). And based on wavelet analysis, significant cycles of 2–3 yr and 3–8 yr were identified. 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In extreme drought years, NDVI was positively correlated with PDSI, and in extreme wet years they were negatively correlated.</description><subject>Climate change</subject><subject>Correlation analysis</subject><subject>Drought</subject><subject>Earth and Environmental Science</subject><subject>Extreme drought</subject><subject>Geography</subject><subject>Rivers</subject><subject>Vegetation</subject><issn>1002-0063</issn><issn>1993-064X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp1kUlPBCEQhTtGE9cf4I3Egye0gGlaju6aTGKio9ETYeiip13oERiX8c_L2CaePEFefa-q4BXFNoM9BlDtR8YqqShwRhlnFS2XijWmlKAgB_fL-Q7AKYAUq8V6jI8AQglVrhVfd9hgMqntPLn0NX6Qa7SdjynM7I9ofE2GrX8yDZL3Nk3ISehmzSQR1wWSJkhuulmwmG3NAu_cj_hgfJPmWW3fMJAjE7EmuToKiDS0viEnJpnNYsWZ54hbv-dGcXt2Ojq-oMOr88vjwyG1QrFEeV3zA6yMcGM3kLIaW8GAqVqMueSyQsUdGpdlw9WgdrYCZhCdHWeLtKUVG8Vu3_fdeJcX0495ZZ8n6nlTP2vk-ddgAHCQyZ2enIbudYYx_aG8LIXMAzjLFOspG7oYAzo9De2LCZ-agV6kofs0dO6rF2noMnt474nTxfsx_HX-3_QNUy6N4A</recordid><startdate>20210801</startdate><enddate>20210801</enddate><creator>Li, Jinjian</creator><creator>Wang, Shu</creator><creator>Qin, Ningsheng</creator><creator>Liu, Xisheng</creator><creator>Jin, Liya</creator><general>Science Press</general><general>Springer Nature B.V</general><general>School of Atmospheric Sciences,Plateau Atmosphere and Environment Key Laboratory of Sichuan Province,Chengdu University of Information Technology,Chengdu 610225,China%School of Atmospheric Sciences,Plateau Atmosphere and Environment Key Laboratory of Sichuan Province,Chengdu University of Information Technology,Chengdu 610225,China</general><general>Institute of Plateau Meteorology,China Meteorological Administration,Chengdu/Heavy Rain and Drought-Flood Disasters in Plateau and Basin,Key Laboratory of Sichuan Province,Chengdu 610072,China%Institute of Plateau Meteorology,China Meteorological Administration,Chengdu/Heavy Rain and Drought-Flood Disasters in Plateau and Basin,Key Laboratory of Sichuan Province,Chengdu 610072,China%Hydrology and Water Resources Bureau of Qinghai Province,Xining 810000,China</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7XB</scope><scope>88I</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>M2P</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20210801</creationdate><title>Vegetation Index Reconstruction and Linkage with Drought for the Source Region of the Yangtze River Based on Tree-ring Data</title><author>Li, Jinjian ; Wang, Shu ; Qin, Ningsheng ; Liu, Xisheng ; Jin, Liya</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c391t-2dd28e7a3fbf4667bc31019d3b26267e92feaf7bca294dfc701aeefcb7a36c5c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Climate change</topic><topic>Correlation analysis</topic><topic>Drought</topic><topic>Earth and Environmental Science</topic><topic>Extreme drought</topic><topic>Geography</topic><topic>Rivers</topic><topic>Vegetation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Jinjian</creatorcontrib><creatorcontrib>Wang, Shu</creatorcontrib><creatorcontrib>Qin, Ningsheng</creatorcontrib><creatorcontrib>Liu, Xisheng</creatorcontrib><creatorcontrib>Jin, Liya</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Science Database (ProQuest)</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>Chinese geographical science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Jinjian</au><au>Wang, Shu</au><au>Qin, Ningsheng</au><au>Liu, Xisheng</au><au>Jin, Liya</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Vegetation Index Reconstruction and Linkage with Drought for the Source Region of the Yangtze River Based on Tree-ring Data</atitle><jtitle>Chinese geographical science</jtitle><stitle>Chin. Geogr. Sci</stitle><date>2021-08-01</date><risdate>2021</risdate><volume>31</volume><issue>4</issue><spage>684</spage><epage>695</epage><pages>684-695</pages><issn>1002-0063</issn><eissn>1993-064X</eissn><abstract>Variations in vegetation are closely related to climate change, but understanding of their characteristics and causes remains limited. As a typical semi-humid and semi-arid cold plateau region, it is important to understand the knowledge of long term Normalized Difference Vegetation Index (NDVI) variations and find the potential causes in the source region of the Yangtze River. Based on four tree-ring width chronologies, the regional mean NDVI for July and August spanning the period 1665–2013 was reconstructed using a regression model, and it explained 43.9% of the total variance during the period 1981–2013. In decadal, the reconstructed NDVI showed eight growth stages (1754–1764, 1766–1783, 1794–1811, 1828–1838, 1843–1855, 1862–1873, 1897–1909, and 1932–1945) and four degradation stages (1679–1698, 1726–1753, 1910–1923, and 1988–2000). And based on wavelet analysis, significant cycles of 2–3 yr and 3–8 yr were identified. In additional, there was a significant positive correlation between the NDVI and the Palmer Drought Severity Index (PDSI) during the past 349 yr, and they were mainly in phase. However, according to the results of correlation analysis between different grades of drought/wet and NDVI, there was significant asymmetry in extreme drought years and extreme wet years. In extreme drought years, NDVI was positively correlated with PDSI, and in extreme wet years they were negatively correlated.</abstract><cop>Heidelberg</cop><pub>Science Press</pub><doi>10.1007/s11769-021-1217-5</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Climate change Correlation analysis Drought Earth and Environmental Science Extreme drought Geography Rivers Vegetation |
title | Vegetation Index Reconstruction and Linkage with Drought for the Source Region of the Yangtze River Based on Tree-ring Data |
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