Analyzing nonlinear variations in terrestrial vegetation in China during 1982–2012
Quantifying the long-term trends of changes in terrestrial vegetation on a large scale is an effective method for detecting the effects of global environmental change. In view of the trend towards overall restoration and local degradation of terrestrial vegetation in China, it is necessary to pay at...
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| Veröffentlicht in: | Environmental monitoring and assessment 2015-11, Vol.187 (11), p.722-722, Article 722 |
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| creator | Liu, Yanxu Liu, Xianfeng Hu, Yi’na Li, Shuangshuang Peng, Jian Wang, Yanglin |
| description | Quantifying the long-term trends of changes in terrestrial vegetation on a large scale is an effective method for detecting the effects of global environmental change. In view of the trend towards overall restoration and local degradation of terrestrial vegetation in China, it is necessary to pay attention to the spatial processes of vegetative restoration or degradation, as well as to clarify the temporal and spatial characteristics of vegetative growth in greater geographical detail. However, traditional linear regression analysis has some drawbacks when describing ecological processes. Combining nonparametric linear regression analysis with high-order nonlinear fitting, the temporal and spatial characteristics of terrestrial vegetative growth in China during 1982–2012 were detected using the third generation of Global Inventory Modeling and Mapping Studies (GIMMS
3g
) dataset. The results showed that high-order curves could be effective. The region joining Ordos City and Shaanxi Gansu Ningxia on the Loess Plateau may have experienced restoration–degradation–restoration processes of vegetative growth. In the Daloushan Mountains, degradation–restoration processes of vegetative growth may have occurred, and the occurrence of several hidden vegetative growth processes was located in different regions of eastern China. Changes in cultivated vegetation were inconsistent with changes in other vegetation types. In southern China and some high-altitude areas, temperature was the primary driver of vegetative growth on an interannual scale, while in the north, the effect of rainfall was more significant. Nevertheless, the influence of climate on vegetation activity in large urban areas was weak. The trend types of degradation–restoration processes in several regions were inconsistent with the implements of regional land development and protection strategy. Thus, the role of human activity cannot be ignored. In future studies, it will be still necessary to quantify the effects of human management on spatial patterns, develop trend-fitting methods, and explore more refined methods of analyzing the driving forces affecting large-scale changes in vegetative growth. |
| doi_str_mv | 10.1007/s10661-015-4922-7 |
| format | Article |
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3g
) dataset. The results showed that high-order curves could be effective. The region joining Ordos City and Shaanxi Gansu Ningxia on the Loess Plateau may have experienced restoration–degradation–restoration processes of vegetative growth. In the Daloushan Mountains, degradation–restoration processes of vegetative growth may have occurred, and the occurrence of several hidden vegetative growth processes was located in different regions of eastern China. Changes in cultivated vegetation were inconsistent with changes in other vegetation types. In southern China and some high-altitude areas, temperature was the primary driver of vegetative growth on an interannual scale, while in the north, the effect of rainfall was more significant. Nevertheless, the influence of climate on vegetation activity in large urban areas was weak. The trend types of degradation–restoration processes in several regions were inconsistent with the implements of regional land development and protection strategy. Thus, the role of human activity cannot be ignored. In future studies, it will be still necessary to quantify the effects of human management on spatial patterns, develop trend-fitting methods, and explore more refined methods of analyzing the driving forces affecting large-scale changes in vegetative growth.</description><identifier>ISSN: 0167-6369</identifier><identifier>EISSN: 1573-2959</identifier><identifier>DOI: 10.1007/s10661-015-4922-7</identifier><identifier>PMID: 26514805</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Atmospheric Protection/Air Quality Control/Air Pollution ; China ; Climate ; Climate change ; Datasets ; Earth and Environmental Science ; Ecology ; Ecotoxicology ; Environment ; Environmental changes ; Environmental degradation ; Environmental Management ; Environmental monitoring ; Environmental Monitoring - methods ; Environmental policy ; Environmental restoration ; Geography ; Humans ; Laboratories ; Land development ; Land use ; Methods ; Monitoring/Environmental Analysis ; Mountains ; Plants - classification ; Predation ; Regions ; Regression analysis ; Remote sensing ; Sensors ; Studies ; Temperature ; Terrestrial ecosystems ; Terrestrial environments ; Trends ; Urban areas ; Vegetation ; Vegetation mapping</subject><ispartof>Environmental monitoring and assessment, 2015-11, Vol.187 (11), p.722-722, Article 722</ispartof><rights>Springer International Publishing Switzerland 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c405t-89e650fcde608d1bc0282a434076d0b478fbaa40ef3eb6fa379e3cbf9efa824b3</citedby><cites>FETCH-LOGICAL-c405t-89e650fcde608d1bc0282a434076d0b478fbaa40ef3eb6fa379e3cbf9efa824b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10661-015-4922-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10661-015-4922-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27929,27930,41493,42562,51324</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26514805$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Yanxu</creatorcontrib><creatorcontrib>Liu, Xianfeng</creatorcontrib><creatorcontrib>Hu, Yi’na</creatorcontrib><creatorcontrib>Li, Shuangshuang</creatorcontrib><creatorcontrib>Peng, Jian</creatorcontrib><creatorcontrib>Wang, Yanglin</creatorcontrib><title>Analyzing nonlinear variations in terrestrial vegetation in China during 1982–2012</title><title>Environmental monitoring and assessment</title><addtitle>Environ Monit Assess</addtitle><addtitle>Environ Monit Assess</addtitle><description>Quantifying the long-term trends of changes in terrestrial vegetation on a large scale is an effective method for detecting the effects of global environmental change. In view of the trend towards overall restoration and local degradation of terrestrial vegetation in China, it is necessary to pay attention to the spatial processes of vegetative restoration or degradation, as well as to clarify the temporal and spatial characteristics of vegetative growth in greater geographical detail. However, traditional linear regression analysis has some drawbacks when describing ecological processes. Combining nonparametric linear regression analysis with high-order nonlinear fitting, the temporal and spatial characteristics of terrestrial vegetative growth in China during 1982–2012 were detected using the third generation of Global Inventory Modeling and Mapping Studies (GIMMS
3g
) dataset. The results showed that high-order curves could be effective. The region joining Ordos City and Shaanxi Gansu Ningxia on the Loess Plateau may have experienced restoration–degradation–restoration processes of vegetative growth. In the Daloushan Mountains, degradation–restoration processes of vegetative growth may have occurred, and the occurrence of several hidden vegetative growth processes was located in different regions of eastern China. Changes in cultivated vegetation were inconsistent with changes in other vegetation types. In southern China and some high-altitude areas, temperature was the primary driver of vegetative growth on an interannual scale, while in the north, the effect of rainfall was more significant. Nevertheless, the influence of climate on vegetation activity in large urban areas was weak. The trend types of degradation–restoration processes in several regions were inconsistent with the implements of regional land development and protection strategy. Thus, the role of human activity cannot be ignored. In future studies, it will be still necessary to quantify the effects of human management on spatial patterns, develop trend-fitting methods, and explore more refined methods of analyzing the driving forces affecting large-scale changes in vegetative growth.</description><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>China</subject><subject>Climate</subject><subject>Climate change</subject><subject>Datasets</subject><subject>Earth and Environmental Science</subject><subject>Ecology</subject><subject>Ecotoxicology</subject><subject>Environment</subject><subject>Environmental changes</subject><subject>Environmental degradation</subject><subject>Environmental Management</subject><subject>Environmental monitoring</subject><subject>Environmental Monitoring - methods</subject><subject>Environmental policy</subject><subject>Environmental restoration</subject><subject>Geography</subject><subject>Humans</subject><subject>Laboratories</subject><subject>Land development</subject><subject>Land use</subject><subject>Methods</subject><subject>Monitoring/Environmental Analysis</subject><subject>Mountains</subject><subject>Plants - classification</subject><subject>Predation</subject><subject>Regions</subject><subject>Regression analysis</subject><subject>Remote sensing</subject><subject>Sensors</subject><subject>Studies</subject><subject>Temperature</subject><subject>Terrestrial ecosystems</subject><subject>Terrestrial environments</subject><subject>Trends</subject><subject>Urban areas</subject><subject>Vegetation</subject><subject>Vegetation mapping</subject><issn>0167-6369</issn><issn>1573-2959</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkclKxEAQhhtRdFwewIsEvHiJVi_p5SiDGwhe9Nx0ksqYIdMZuxNBT76Db-iTmDgqIgieGrq--quoj5B9CscUQJ1EClLSFGiWCsNYqtbIhGaKp8xkZp1MgEqVSi7NFtmOcQ4ARgmzSbaYzKjQkE3I7al3zdNz7WeJb31Te3QheXShdl3d-pjUPukwBIzd8NUkjzjD7qM0Vqb3tXdJ2YexnRrN3l5eGVC2SzYq10Tc-3x3yN352e30Mr2-ubianl6nhYCsS7VBmUFVlChBlzQvgGnmBBegZAm5ULrKnROAFcdcVo4rg7zIK4OV00zkfIccrXKXoX3ohx3too4FNo3z2PbRUmW04kIK9Q-UaamGCWZAD3-h87YPw5lGinMtmKBsoOiKKkIbY8DKLkO9cOHJUrCjHbuyYwc7drRjxyUOPpP7fIHld8eXjgFgKyAux5ti-DH6z9R3qSiZ0w</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Liu, Yanxu</creator><creator>Liu, Xianfeng</creator><creator>Hu, Yi’na</creator><creator>Li, Shuangshuang</creator><creator>Peng, Jian</creator><creator>Wang, Yanglin</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QH</scope><scope>7QL</scope><scope>7SN</scope><scope>7ST</scope><scope>7T7</scope><scope>7TG</scope><scope>7TN</scope><scope>7U7</scope><scope>7UA</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X7</scope><scope>7XB</scope><scope>87Z</scope><scope>88E</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H97</scope><scope>HCIFZ</scope><scope>K60</scope><scope>K6~</scope><scope>K9.</scope><scope>KL.</scope><scope>L.-</scope><scope>L.G</scope><scope>M0C</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7N</scope><scope>P64</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><scope>7X8</scope><scope>7TV</scope><scope>7U6</scope></search><sort><creationdate>20151101</creationdate><title>Analyzing nonlinear variations in terrestrial vegetation in China during 1982–2012</title><author>Liu, Yanxu ; Liu, Xianfeng ; Hu, Yi’na ; Li, Shuangshuang ; Peng, Jian ; Wang, Yanglin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c405t-89e650fcde608d1bc0282a434076d0b478fbaa40ef3eb6fa379e3cbf9efa824b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>China</topic><topic>Climate</topic><topic>Climate change</topic><topic>Datasets</topic><topic>Earth and Environmental Science</topic><topic>Ecology</topic><topic>Ecotoxicology</topic><topic>Environment</topic><topic>Environmental changes</topic><topic>Environmental degradation</topic><topic>Environmental Management</topic><topic>Environmental monitoring</topic><topic>Environmental Monitoring - methods</topic><topic>Environmental policy</topic><topic>Environmental restoration</topic><topic>Geography</topic><topic>Humans</topic><topic>Laboratories</topic><topic>Land development</topic><topic>Land use</topic><topic>Methods</topic><topic>Monitoring/Environmental Analysis</topic><topic>Mountains</topic><topic>Plants - classification</topic><topic>Predation</topic><topic>Regions</topic><topic>Regression analysis</topic><topic>Remote sensing</topic><topic>Sensors</topic><topic>Studies</topic><topic>Temperature</topic><topic>Terrestrial ecosystems</topic><topic>Terrestrial environments</topic><topic>Trends</topic><topic>Urban areas</topic><topic>Vegetation</topic><topic>Vegetation mapping</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Yanxu</creatorcontrib><creatorcontrib>Liu, Xianfeng</creatorcontrib><creatorcontrib>Hu, Yi’na</creatorcontrib><creatorcontrib>Li, Shuangshuang</creatorcontrib><creatorcontrib>Peng, Jian</creatorcontrib><creatorcontrib>Wang, Yanglin</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>Health Research Premium Collection</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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Academic</collection><collection>Pollution Abstracts</collection><collection>Sustainability Science Abstracts</collection><jtitle>Environmental monitoring and assessment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Yanxu</au><au>Liu, Xianfeng</au><au>Hu, Yi’na</au><au>Li, Shuangshuang</au><au>Peng, Jian</au><au>Wang, Yanglin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Analyzing nonlinear variations in terrestrial vegetation in China during 1982–2012</atitle><jtitle>Environmental monitoring and assessment</jtitle><stitle>Environ Monit Assess</stitle><addtitle>Environ Monit Assess</addtitle><date>2015-11-01</date><risdate>2015</risdate><volume>187</volume><issue>11</issue><spage>722</spage><epage>722</epage><pages>722-722</pages><artnum>722</artnum><issn>0167-6369</issn><eissn>1573-2959</eissn><abstract>Quantifying the long-term trends of changes in terrestrial vegetation on a large scale is an effective method for detecting the effects of global environmental change. In view of the trend towards overall restoration and local degradation of terrestrial vegetation in China, it is necessary to pay attention to the spatial processes of vegetative restoration or degradation, as well as to clarify the temporal and spatial characteristics of vegetative growth in greater geographical detail. However, traditional linear regression analysis has some drawbacks when describing ecological processes. Combining nonparametric linear regression analysis with high-order nonlinear fitting, the temporal and spatial characteristics of terrestrial vegetative growth in China during 1982–2012 were detected using the third generation of Global Inventory Modeling and Mapping Studies (GIMMS
3g
) dataset. The results showed that high-order curves could be effective. The region joining Ordos City and Shaanxi Gansu Ningxia on the Loess Plateau may have experienced restoration–degradation–restoration processes of vegetative growth. In the Daloushan Mountains, degradation–restoration processes of vegetative growth may have occurred, and the occurrence of several hidden vegetative growth processes was located in different regions of eastern China. Changes in cultivated vegetation were inconsistent with changes in other vegetation types. In southern China and some high-altitude areas, temperature was the primary driver of vegetative growth on an interannual scale, while in the north, the effect of rainfall was more significant. Nevertheless, the influence of climate on vegetation activity in large urban areas was weak. The trend types of degradation–restoration processes in several regions were inconsistent with the implements of regional land development and protection strategy. Thus, the role of human activity cannot be ignored. In future studies, it will be still necessary to quantify the effects of human management on spatial patterns, develop trend-fitting methods, and explore more refined methods of analyzing the driving forces affecting large-scale changes in vegetative growth.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>26514805</pmid><doi>10.1007/s10661-015-4922-7</doi><tpages>1</tpages></addata></record> |
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| subjects | Atmospheric Protection/Air Quality Control/Air Pollution China Climate Climate change Datasets Earth and Environmental Science Ecology Ecotoxicology Environment Environmental changes Environmental degradation Environmental Management Environmental monitoring Environmental Monitoring - methods Environmental policy Environmental restoration Geography Humans Laboratories Land development Land use Methods Monitoring/Environmental Analysis Mountains Plants - classification Predation Regions Regression analysis Remote sensing Sensors Studies Temperature Terrestrial ecosystems Terrestrial environments Trends Urban areas Vegetation Vegetation mapping |
| title | Analyzing nonlinear variations in terrestrial vegetation in China during 1982–2012 |
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