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Tree‐ring analysis and modeling approaches yield contrary response of circumboreal forest productivity to climate change
Circumboreal forest ecosystems are exposed to a larger magnitude of warming in comparison with the global average, as a result of warming‐induced environmental changes. However, it is not clear how tree growth in these ecosystems responds to these changes. In this study, we investigated the sensitiv...
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Published in: | Global change biology 2017-12, Vol.23 (12), p.5179-5188 |
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creator | Tei, Shunsuke Sugimoto, Atsuko Yonenobu, Hitoshi Matsuura, Yojiro Osawa, Akira Sato, Hisashi Fujinuma, Junichi Maximov, Trofim |
description | Circumboreal forest ecosystems are exposed to a larger magnitude of warming in comparison with the global average, as a result of warming‐induced environmental changes. However, it is not clear how tree growth in these ecosystems responds to these changes. In this study, we investigated the sensitivity of forest productivity to climate change using ring width indices (RWI) from a tree‐ring width dataset accessed from the International Tree‐Ring Data Bank and gridded climate datasets from the Climate Research Unit. A negative relationship of RWI with summer temperature and recent reductions in RWI were typically observed in continental dry regions, such as inner Alaska and Canada, southern Europe, and the southern part of eastern Siberia. We then developed a multiple regression model with regional meteorological parameters to predict RWI, and then applied to these models to predict how tree growth will respond to twenty‐first‐century climate change (RCP8.5 scenario). The projections showed a spatial variation and future continuous reduction in tree growth in those continental dry regions. The spatial variation, however, could not be reproduced by a dynamic global vegetation model (DGVM). The DGVM projected a generally positive trend in future tree growth all over the circumboreal region. These results indicate that DGVMs may overestimate future wood net primary productivity (NPP) in continental dry regions such as these; this seems to be common feature of current DGVMs. DGVMs should be able to express the negative effect of warming on tree growth, so that they simulate the observed recent reduction in tree growth in continental dry regions.
The negative response of RWI to summer temperature is a widespread phenomenon over circumboreal forest, and the current CO2 fertilization effect for tree growth seems to be unable to overcome this negative effect. The negative response, however, could not be reproduced by a DGVM. DGVMs should be able to express the negative effect of warming on tree growth. Otherwise, future projections of tree NPP by DGVMs may be overestimated under the conditions of the expected future increase in global precipitation. |
doi_str_mv | 10.1111/gcb.13780 |
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The negative response of RWI to summer temperature is a widespread phenomenon over circumboreal forest, and the current CO2 fertilization effect for tree growth seems to be unable to overcome this negative effect. The negative response, however, could not be reproduced by a DGVM. DGVMs should be able to express the negative effect of warming on tree growth. Otherwise, future projections of tree NPP by DGVMs may be overestimated under the conditions of the expected future increase in global precipitation.</description><identifier>ISSN: 1354-1013</identifier><identifier>EISSN: 1365-2486</identifier><identifier>DOI: 10.1111/gcb.13780</identifier><identifier>PMID: 28585765</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>Alaska ; Atmospheric models ; boreal forest ; Canada ; Climate ; Climate Change ; Climate models ; climate sensitivity ; Computer simulation ; Dendrochronology ; DGVM ; Ecosystems ; Environmental changes ; Europe ; Forest ecosystems ; Forest productivity ; Forests ; Growth ; ITRDB ; Meteorological parameters ; Modelling ; Multiple regression models ; Net Primary Productivity ; Primary production ; Productivity ; Reduction ; Regional development ; Regions ; Regression analysis ; Seasons ; Siberia ; Spatial variations ; Temperature ; Terrestrial ecosystems ; tree ring ; Trees - growth & development ; Width ; Wood ; Yields</subject><ispartof>Global change biology, 2017-12, Vol.23 (12), p.5179-5188</ispartof><rights>2017 John Wiley & Sons Ltd</rights><rights>2017 John Wiley & Sons Ltd.</rights><rights>Copyright © 2017 John Wiley & Sons Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4190-5c05a73f900e415776cebc62351413dab11a2870be152ffe6cd3ad805bf1a6ba3</citedby><cites>FETCH-LOGICAL-c4190-5c05a73f900e415776cebc62351413dab11a2870be152ffe6cd3ad805bf1a6ba3</cites><orcidid>0000-0003-3213-6829</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28585765$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Tei, Shunsuke</creatorcontrib><creatorcontrib>Sugimoto, Atsuko</creatorcontrib><creatorcontrib>Yonenobu, Hitoshi</creatorcontrib><creatorcontrib>Matsuura, Yojiro</creatorcontrib><creatorcontrib>Osawa, Akira</creatorcontrib><creatorcontrib>Sato, Hisashi</creatorcontrib><creatorcontrib>Fujinuma, Junichi</creatorcontrib><creatorcontrib>Maximov, Trofim</creatorcontrib><title>Tree‐ring analysis and modeling approaches yield contrary response of circumboreal forest productivity to climate change</title><title>Global change biology</title><addtitle>Glob Chang Biol</addtitle><description>Circumboreal forest ecosystems are exposed to a larger magnitude of warming in comparison with the global average, as a result of warming‐induced environmental changes. However, it is not clear how tree growth in these ecosystems responds to these changes. In this study, we investigated the sensitivity of forest productivity to climate change using ring width indices (RWI) from a tree‐ring width dataset accessed from the International Tree‐Ring Data Bank and gridded climate datasets from the Climate Research Unit. A negative relationship of RWI with summer temperature and recent reductions in RWI were typically observed in continental dry regions, such as inner Alaska and Canada, southern Europe, and the southern part of eastern Siberia. We then developed a multiple regression model with regional meteorological parameters to predict RWI, and then applied to these models to predict how tree growth will respond to twenty‐first‐century climate change (RCP8.5 scenario). The projections showed a spatial variation and future continuous reduction in tree growth in those continental dry regions. The spatial variation, however, could not be reproduced by a dynamic global vegetation model (DGVM). The DGVM projected a generally positive trend in future tree growth all over the circumboreal region. These results indicate that DGVMs may overestimate future wood net primary productivity (NPP) in continental dry regions such as these; this seems to be common feature of current DGVMs. DGVMs should be able to express the negative effect of warming on tree growth, so that they simulate the observed recent reduction in tree growth in continental dry regions.
The negative response of RWI to summer temperature is a widespread phenomenon over circumboreal forest, and the current CO2 fertilization effect for tree growth seems to be unable to overcome this negative effect. The negative response, however, could not be reproduced by a DGVM. DGVMs should be able to express the negative effect of warming on tree growth. Otherwise, future projections of tree NPP by DGVMs may be overestimated under the conditions of the expected future increase in global precipitation.</description><subject>Alaska</subject><subject>Atmospheric models</subject><subject>boreal forest</subject><subject>Canada</subject><subject>Climate</subject><subject>Climate Change</subject><subject>Climate models</subject><subject>climate sensitivity</subject><subject>Computer simulation</subject><subject>Dendrochronology</subject><subject>DGVM</subject><subject>Ecosystems</subject><subject>Environmental changes</subject><subject>Europe</subject><subject>Forest ecosystems</subject><subject>Forest productivity</subject><subject>Forests</subject><subject>Growth</subject><subject>ITRDB</subject><subject>Meteorological parameters</subject><subject>Modelling</subject><subject>Multiple regression models</subject><subject>Net Primary Productivity</subject><subject>Primary production</subject><subject>Productivity</subject><subject>Reduction</subject><subject>Regional development</subject><subject>Regions</subject><subject>Regression analysis</subject><subject>Seasons</subject><subject>Siberia</subject><subject>Spatial variations</subject><subject>Temperature</subject><subject>Terrestrial ecosystems</subject><subject>tree ring</subject><subject>Trees - growth & development</subject><subject>Width</subject><subject>Wood</subject><subject>Yields</subject><issn>1354-1013</issn><issn>1365-2486</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1kc1OxCAUhYnR-DO68AUMiRtdVKEU2lnqxL_ExM24bii9ncHQUqHV1JWP4DP6JDJ2dGEim3tz83HugYPQISVnNJzzhSrOKEszsoF2KRM8ipNMbK56nkSUULaD9rx_IoSwmIhttBNnPOOp4Lvobe4APt8_nG4WWDbSDF770JS4tiWY72nbOivVEjweNJgSK9t0TroBO_CtbTxgW2GlnerrwjqQBleh-A6He2WvOv2iuwF3Fiuja9kBVkvZLGAfbVXSeDhY1wl6vL6az26j-4ebu9nFfaQSOiURV4TLlFVTQiChPE2FgkKJmHGaUFbKglIZZykpgPK4qkCokskyI7yoqBSFZBN0MuoGO8998JXX2iswRjZge5-HJSIRPE2ygB7_QZ9s78KvrCjBCCfxlAfqdKSUs947qPLWhYe5IackXwWSh0Dy70ACe7RW7Isayl_yJ4EAnI_AqzYw_K-U38wuR8kvOgWXbA</recordid><startdate>201712</startdate><enddate>201712</enddate><creator>Tei, Shunsuke</creator><creator>Sugimoto, Atsuko</creator><creator>Yonenobu, Hitoshi</creator><creator>Matsuura, Yojiro</creator><creator>Osawa, Akira</creator><creator>Sato, Hisashi</creator><creator>Fujinuma, Junichi</creator><creator>Maximov, Trofim</creator><general>Blackwell Publishing Ltd</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>7SN</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H97</scope><scope>L.G</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-3213-6829</orcidid></search><sort><creationdate>201712</creationdate><title>Tree‐ring analysis and modeling approaches yield contrary response of circumboreal forest productivity to climate change</title><author>Tei, Shunsuke ; 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However, it is not clear how tree growth in these ecosystems responds to these changes. In this study, we investigated the sensitivity of forest productivity to climate change using ring width indices (RWI) from a tree‐ring width dataset accessed from the International Tree‐Ring Data Bank and gridded climate datasets from the Climate Research Unit. A negative relationship of RWI with summer temperature and recent reductions in RWI were typically observed in continental dry regions, such as inner Alaska and Canada, southern Europe, and the southern part of eastern Siberia. We then developed a multiple regression model with regional meteorological parameters to predict RWI, and then applied to these models to predict how tree growth will respond to twenty‐first‐century climate change (RCP8.5 scenario). The projections showed a spatial variation and future continuous reduction in tree growth in those continental dry regions. The spatial variation, however, could not be reproduced by a dynamic global vegetation model (DGVM). The DGVM projected a generally positive trend in future tree growth all over the circumboreal region. These results indicate that DGVMs may overestimate future wood net primary productivity (NPP) in continental dry regions such as these; this seems to be common feature of current DGVMs. DGVMs should be able to express the negative effect of warming on tree growth, so that they simulate the observed recent reduction in tree growth in continental dry regions.
The negative response of RWI to summer temperature is a widespread phenomenon over circumboreal forest, and the current CO2 fertilization effect for tree growth seems to be unable to overcome this negative effect. The negative response, however, could not be reproduced by a DGVM. DGVMs should be able to express the negative effect of warming on tree growth. Otherwise, future projections of tree NPP by DGVMs may be overestimated under the conditions of the expected future increase in global precipitation.</abstract><cop>England</cop><pub>Blackwell Publishing Ltd</pub><pmid>28585765</pmid><doi>10.1111/gcb.13780</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-3213-6829</orcidid></addata></record> |
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subjects | Alaska Atmospheric models boreal forest Canada Climate Climate Change Climate models climate sensitivity Computer simulation Dendrochronology DGVM Ecosystems Environmental changes Europe Forest ecosystems Forest productivity Forests Growth ITRDB Meteorological parameters Modelling Multiple regression models Net Primary Productivity Primary production Productivity Reduction Regional development Regions Regression analysis Seasons Siberia Spatial variations Temperature Terrestrial ecosystems tree ring Trees - growth & development Width Wood Yields |
title | Tree‐ring analysis and modeling approaches yield contrary response of circumboreal forest productivity to climate change |
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