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Spatio-Temporal Changes and Contribution of Human and Meteorological Factors to Grassland Net Primary Productivity in the Three-Rivers Headwater Region from 2000 to 2019
Since the beginning of the 21st century, the net primary productivity (NPP) of grassland in the Three-Rivers Headwaters (TRH) region has changed significantly. In this study, NPP was assessed by the Carnegie-Ames-Stanford approach (CASA) model in TRH from 2000 to 2019. The abrupt changes of NPP and...
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Published in: | Atmosphere 2023-01, Vol.14 (2), p.278 |
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description | Since the beginning of the 21st century, the net primary productivity (NPP) of grassland in the Three-Rivers Headwaters (TRH) region has changed significantly. In this study, NPP was assessed by the Carnegie-Ames-Stanford approach (CASA) model in TRH from 2000 to 2019. The abrupt changes of NPP and meteorological factors were analyzed by cumulative departure, MK test, and Pettitt test. The contributions of meteorological and human factors to changes in grassland NPP were quantitatively assessed using the scenario simulation method. The obtained results showed that: (1) From 2000 to 2019, the NPP of grasslands increased from 135.72 to 141.16 gC/m−2a−1. However, the overall growth trend was not significant, and the proportion of significant growth was only 31.45%; (2) An abrupt increase in meteorological factors occurred around 2005, while an abrupt increase in NPP occurred around 2008, which showed that 2008 was the year when human factors, such as ecological projects and policies, began to show a significant impact on the growth of NPP; and (3) The contribution of human factors to the abrupt increase in NPP was significantly greater than the contribution of meteorological factors. The contribution of human factors exceeded 70% in 93.68% of the studied area, reaching 98% in general, while the contribution of meteorological factors was less than 2%. Among them, the human contributions to the Yangtze River Source, the Yellow River Source, and the Lancang River Source all exceeded 95%. The negative effects of meteorological factors on the growth of NPP in the abovementioned three regions were as high as 47.35%, 48.66%, and 36.91%, respectively. Human factors have contributed greatly to the increase in NPP in most of the source areas of the Yellow River, the eastern part of Tanggulashan County, the southeastern part of Zhiduo County, and the western part of Zaduo County at the source of the Yangtze River. |
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In this study, NPP was assessed by the Carnegie-Ames-Stanford approach (CASA) model in TRH from 2000 to 2019. The abrupt changes of NPP and meteorological factors were analyzed by cumulative departure, MK test, and Pettitt test. The contributions of meteorological and human factors to changes in grassland NPP were quantitatively assessed using the scenario simulation method. The obtained results showed that: (1) From 2000 to 2019, the NPP of grasslands increased from 135.72 to 141.16 gC/m−2a−1. However, the overall growth trend was not significant, and the proportion of significant growth was only 31.45%; (2) An abrupt increase in meteorological factors occurred around 2005, while an abrupt increase in NPP occurred around 2008, which showed that 2008 was the year when human factors, such as ecological projects and policies, began to show a significant impact on the growth of NPP; and (3) The contribution of human factors to the abrupt increase in NPP was significantly greater than the contribution of meteorological factors. The contribution of human factors exceeded 70% in 93.68% of the studied area, reaching 98% in general, while the contribution of meteorological factors was less than 2%. Among them, the human contributions to the Yangtze River Source, the Yellow River Source, and the Lancang River Source all exceeded 95%. The negative effects of meteorological factors on the growth of NPP in the abovementioned three regions were as high as 47.35%, 48.66%, and 36.91%, respectively. Human factors have contributed greatly to the increase in NPP in most of the source areas of the Yellow River, the eastern part of Tanggulashan County, the southeastern part of Zhiduo County, and the western part of Zaduo County at the source of the Yangtze River.</description><identifier>ISSN: 2073-4433</identifier><identifier>EISSN: 2073-4433</identifier><identifier>DOI: 10.3390/atmos14020278</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>abrupt change ; Analysis ; Climate change ; contribution degree ; Environmental aspects ; Environmental restoration ; grassland NPP ; Grasslands ; Growth ; Headwaters ; Human beings ; Human factors ; Influence on nature ; Meteorological effects ; meteorological factors ; Net Primary Productivity ; Precipitation ; Primary production ; Primary productivity (Biology) ; Radiation ; Remote sensing ; River ecology ; Rivers ; Sustainable development ; Temporal variations ; Three-Rivers Headwater region ; Vegetation</subject><ispartof>Atmosphere, 2023-01, Vol.14 (2), p.278</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c409t-1dd39e8a8094e72e51624ac65371f781d6df98be1098518cdcbc5ee38a6c68c43</citedby><cites>FETCH-LOGICAL-c409t-1dd39e8a8094e72e51624ac65371f781d6df98be1098518cdcbc5ee38a6c68c43</cites><orcidid>0000-0003-1637-9724</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2779435742/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2779435742?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,25731,27901,27902,36989,44566,74869</link.rule.ids></links><search><creatorcontrib>Song, Yang</creatorcontrib><creatorcontrib>Liang, Tian</creatorcontrib><creatorcontrib>Zhang, Linbo</creatorcontrib><creatorcontrib>Hao, Chaozhi</creatorcontrib><creatorcontrib>Wang, Hao</creatorcontrib><title>Spatio-Temporal Changes and Contribution of Human and Meteorological Factors to Grassland Net Primary Productivity in the Three-Rivers Headwater Region from 2000 to 2019</title><title>Atmosphere</title><description>Since the beginning of the 21st century, the net primary productivity (NPP) of grassland in the Three-Rivers Headwaters (TRH) region has changed significantly. In this study, NPP was assessed by the Carnegie-Ames-Stanford approach (CASA) model in TRH from 2000 to 2019. The abrupt changes of NPP and meteorological factors were analyzed by cumulative departure, MK test, and Pettitt test. The contributions of meteorological and human factors to changes in grassland NPP were quantitatively assessed using the scenario simulation method. The obtained results showed that: (1) From 2000 to 2019, the NPP of grasslands increased from 135.72 to 141.16 gC/m−2a−1. However, the overall growth trend was not significant, and the proportion of significant growth was only 31.45%; (2) An abrupt increase in meteorological factors occurred around 2005, while an abrupt increase in NPP occurred around 2008, which showed that 2008 was the year when human factors, such as ecological projects and policies, began to show a significant impact on the growth of NPP; and (3) The contribution of human factors to the abrupt increase in NPP was significantly greater than the contribution of meteorological factors. The contribution of human factors exceeded 70% in 93.68% of the studied area, reaching 98% in general, while the contribution of meteorological factors was less than 2%. Among them, the human contributions to the Yangtze River Source, the Yellow River Source, and the Lancang River Source all exceeded 95%. The negative effects of meteorological factors on the growth of NPP in the abovementioned three regions were as high as 47.35%, 48.66%, and 36.91%, respectively. Human factors have contributed greatly to the increase in NPP in most of the source areas of the Yellow River, the eastern part of Tanggulashan County, the southeastern part of Zhiduo County, and the western part of Zaduo County at the source of the Yangtze River.</description><subject>abrupt change</subject><subject>Analysis</subject><subject>Climate change</subject><subject>contribution degree</subject><subject>Environmental aspects</subject><subject>Environmental restoration</subject><subject>grassland NPP</subject><subject>Grasslands</subject><subject>Growth</subject><subject>Headwaters</subject><subject>Human beings</subject><subject>Human factors</subject><subject>Influence on nature</subject><subject>Meteorological effects</subject><subject>meteorological factors</subject><subject>Net Primary Productivity</subject><subject>Precipitation</subject><subject>Primary production</subject><subject>Primary productivity (Biology)</subject><subject>Radiation</subject><subject>Remote sensing</subject><subject>River ecology</subject><subject>Rivers</subject><subject>Sustainable development</subject><subject>Temporal variations</subject><subject>Three-Rivers Headwater region</subject><subject>Vegetation</subject><issn>2073-4433</issn><issn>2073-4433</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpVkk9v1DAQxSMEElXpkbslzin-l8Q-VivarVSgKss5mtiTrFdJvNjeVv1IfEucBiFqH8Yav_fzszRF8ZHRSyE0_Qxp8pFJyilv1JvijNNGlFIK8fa_8_viIsYDzUtqwYU8K37_OEJyvtzhdPQBRrLZwzxgJDBbsvFzCq47ZcFMfE-2pwnml5uvmNAHP_rBmWy6BpN8iCR5chMgxnHRfMNE7oObIDzn6u3JJPfo0jNxM0l7JLt9QCwf3CNm5xbBPkHCQB5wWJ7rg58Iz0kXKKdMfyje9TBGvPhbz4uf1192m2159_3mdnN1VxpJdSqZtUKjAkW1xIZjxWouwdSVaFjfKGZr22vVIaNaVUwZazpTIQoFtamVkeK8uF251sOhPa4faD249qXhw9BCSM6M2DIt66qzAEwYyUBpS2vKOqmb3oLkJrM-raxj8L9OGFN78Kcw5_gtbxotRdVInlWXq2qADHVz71MAk7fFyRk_Y-9y_ypLtRZULRHL1WCCjzFg_y8mo-0yDe2raRB_AFsaqIg</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Song, Yang</creator><creator>Liang, Tian</creator><creator>Zhang, Linbo</creator><creator>Hao, Chaozhi</creator><creator>Wang, Hao</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>SOI</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-1637-9724</orcidid></search><sort><creationdate>20230101</creationdate><title>Spatio-Temporal Changes and Contribution of Human and Meteorological Factors to Grassland Net Primary Productivity in the Three-Rivers Headwater Region from 2000 to 2019</title><author>Song, Yang ; Liang, Tian ; Zhang, Linbo ; Hao, Chaozhi ; Wang, Hao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c409t-1dd39e8a8094e72e51624ac65371f781d6df98be1098518cdcbc5ee38a6c68c43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>abrupt change</topic><topic>Analysis</topic><topic>Climate change</topic><topic>contribution degree</topic><topic>Environmental aspects</topic><topic>Environmental restoration</topic><topic>grassland NPP</topic><topic>Grasslands</topic><topic>Growth</topic><topic>Headwaters</topic><topic>Human beings</topic><topic>Human factors</topic><topic>Influence on nature</topic><topic>Meteorological effects</topic><topic>meteorological factors</topic><topic>Net Primary Productivity</topic><topic>Precipitation</topic><topic>Primary production</topic><topic>Primary productivity (Biology)</topic><topic>Radiation</topic><topic>Remote sensing</topic><topic>River ecology</topic><topic>Rivers</topic><topic>Sustainable development</topic><topic>Temporal variations</topic><topic>Three-Rivers Headwater region</topic><topic>Vegetation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Song, Yang</creatorcontrib><creatorcontrib>Liang, Tian</creatorcontrib><creatorcontrib>Zhang, Linbo</creatorcontrib><creatorcontrib>Hao, Chaozhi</creatorcontrib><creatorcontrib>Wang, Hao</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content 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>Environment Abstracts</collection><collection>Directory of Open Access Journals</collection><jtitle>Atmosphere</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Song, Yang</au><au>Liang, Tian</au><au>Zhang, Linbo</au><au>Hao, Chaozhi</au><au>Wang, Hao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatio-Temporal Changes and Contribution of Human and Meteorological Factors to Grassland Net Primary Productivity in the Three-Rivers Headwater Region from 2000 to 2019</atitle><jtitle>Atmosphere</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>14</volume><issue>2</issue><spage>278</spage><pages>278-</pages><issn>2073-4433</issn><eissn>2073-4433</eissn><abstract>Since the beginning of the 21st century, the net primary productivity (NPP) of grassland in the Three-Rivers Headwaters (TRH) region has changed significantly. In this study, NPP was assessed by the Carnegie-Ames-Stanford approach (CASA) model in TRH from 2000 to 2019. The abrupt changes of NPP and meteorological factors were analyzed by cumulative departure, MK test, and Pettitt test. The contributions of meteorological and human factors to changes in grassland NPP were quantitatively assessed using the scenario simulation method. The obtained results showed that: (1) From 2000 to 2019, the NPP of grasslands increased from 135.72 to 141.16 gC/m−2a−1. However, the overall growth trend was not significant, and the proportion of significant growth was only 31.45%; (2) An abrupt increase in meteorological factors occurred around 2005, while an abrupt increase in NPP occurred around 2008, which showed that 2008 was the year when human factors, such as ecological projects and policies, began to show a significant impact on the growth of NPP; and (3) The contribution of human factors to the abrupt increase in NPP was significantly greater than the contribution of meteorological factors. The contribution of human factors exceeded 70% in 93.68% of the studied area, reaching 98% in general, while the contribution of meteorological factors was less than 2%. Among them, the human contributions to the Yangtze River Source, the Yellow River Source, and the Lancang River Source all exceeded 95%. The negative effects of meteorological factors on the growth of NPP in the abovementioned three regions were as high as 47.35%, 48.66%, and 36.91%, respectively. Human factors have contributed greatly to the increase in NPP in most of the source areas of the Yellow River, the eastern part of Tanggulashan County, the southeastern part of Zhiduo County, and the western part of Zaduo County at the source of the Yangtze River.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/atmos14020278</doi><orcidid>https://orcid.org/0000-0003-1637-9724</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | abrupt change Analysis Climate change contribution degree Environmental aspects Environmental restoration grassland NPP Grasslands Growth Headwaters Human beings Human factors Influence on nature Meteorological effects meteorological factors Net Primary Productivity Precipitation Primary production Primary productivity (Biology) Radiation Remote sensing River ecology Rivers Sustainable development Temporal variations Three-Rivers Headwater region Vegetation |
title | Spatio-Temporal Changes and Contribution of Human and Meteorological Factors to Grassland Net Primary Productivity in the Three-Rivers Headwater Region from 2000 to 2019 |
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