Loading…
Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison
To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dat...
Saved in:
Published in: | Global change biology 2016-08, Vol.23 (1) |
---|---|
Main Authors: | , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | |
container_issue | 1 |
container_start_page | |
container_title | Global change biology |
container_volume | 23 |
creator | Restrepo-Coupe, Natalia Levine, Naomi M. Christoffersen, Bradley O. Albert, Loren P. Wu, Jin Costa, Marcos H. Galbraith, David Imbuzeiro, Hewlley Martins, Giordane da Araujo, Alessandro C. Malhi, Yadvinder S. Zeng, Xubin Moorcroft, Paul Saleska, Scott R. |
description | To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments. |
format | article |
fullrecord | <record><control><sourceid>osti</sourceid><recordid>TN_cdi_osti_scitechconnect_1341704</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1341704</sourcerecordid><originalsourceid>FETCH-osti_scitechconnect_13417043</originalsourceid><addsrcrecordid>eNqNzEFqAkEQBdBeGNBE71C4H-i2J7oUMQk5gHup6anRDj1dMlWG6MKzpxEP4OrD_48_MhPn3-vKWefH5lXkx1rrF3Y5MbcPhvaSsY8BDokbTPBLB1LUyBl6bikJBDzpeSDQI4EQCmdMUS_AXZmGpsAunf9IIOa72fR4LWWDEvMaNtCiYnX_KkJpCNyfcIjlZ2peOkxCs0e-mfnX5277XbFo3EuISuEYOGcKune-ditb-6fQP1u7T3k</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Restrepo-Coupe, Natalia ; Levine, Naomi M. ; Christoffersen, Bradley O. ; Albert, Loren P. ; Wu, Jin ; Costa, Marcos H. ; Galbraith, David ; Imbuzeiro, Hewlley ; Martins, Giordane ; da Araujo, Alessandro C. ; Malhi, Yadvinder S. ; Zeng, Xubin ; Moorcroft, Paul ; Saleska, Scott R.</creator><creatorcontrib>Restrepo-Coupe, Natalia ; Levine, Naomi M. ; Christoffersen, Bradley O. ; Albert, Loren P. ; Wu, Jin ; Costa, Marcos H. ; Galbraith, David ; Imbuzeiro, Hewlley ; Martins, Giordane ; da Araujo, Alessandro C. ; Malhi, Yadvinder S. ; Zeng, Xubin ; Moorcroft, Paul ; Saleska, Scott R. ; Brookhaven National Laboratory (BNL), Upton, NY (United States)</creatorcontrib><description>To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.</description><identifier>ISSN: 1354-1013</identifier><language>eng</language><publisher>United States: Wiley</publisher><subject>Amazonia ; carbon dynamics ; dynamic global vegetation models ; ecosystem–climate interactions ; eddy covariance ; ENVIRONMENTAL SCIENCES ; seasonality ; tropical forests phenology</subject><ispartof>Global change biology, 2016-08, Vol.23 (1)</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000000249630535 ; 0000000339211772</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885</link.rule.ids><backlink>$$Uhttps://www.osti.gov/servlets/purl/1341704$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Restrepo-Coupe, Natalia</creatorcontrib><creatorcontrib>Levine, Naomi M.</creatorcontrib><creatorcontrib>Christoffersen, Bradley O.</creatorcontrib><creatorcontrib>Albert, Loren P.</creatorcontrib><creatorcontrib>Wu, Jin</creatorcontrib><creatorcontrib>Costa, Marcos H.</creatorcontrib><creatorcontrib>Galbraith, David</creatorcontrib><creatorcontrib>Imbuzeiro, Hewlley</creatorcontrib><creatorcontrib>Martins, Giordane</creatorcontrib><creatorcontrib>da Araujo, Alessandro C.</creatorcontrib><creatorcontrib>Malhi, Yadvinder S.</creatorcontrib><creatorcontrib>Zeng, Xubin</creatorcontrib><creatorcontrib>Moorcroft, Paul</creatorcontrib><creatorcontrib>Saleska, Scott R.</creatorcontrib><creatorcontrib>Brookhaven National Laboratory (BNL), Upton, NY (United States)</creatorcontrib><title>Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison</title><title>Global change biology</title><description>To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.</description><subject>Amazonia</subject><subject>carbon dynamics</subject><subject>dynamic global vegetation models</subject><subject>ecosystem–climate interactions</subject><subject>eddy covariance</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>seasonality</subject><subject>tropical forests phenology</subject><issn>1354-1013</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqNzEFqAkEQBdBeGNBE71C4H-i2J7oUMQk5gHup6anRDj1dMlWG6MKzpxEP4OrD_48_MhPn3-vKWefH5lXkx1rrF3Y5MbcPhvaSsY8BDokbTPBLB1LUyBl6bikJBDzpeSDQI4EQCmdMUS_AXZmGpsAunf9IIOa72fR4LWWDEvMaNtCiYnX_KkJpCNyfcIjlZ2peOkxCs0e-mfnX5277XbFo3EuISuEYOGcKune-ditb-6fQP1u7T3k</recordid><startdate>20160829</startdate><enddate>20160829</enddate><creator>Restrepo-Coupe, Natalia</creator><creator>Levine, Naomi M.</creator><creator>Christoffersen, Bradley O.</creator><creator>Albert, Loren P.</creator><creator>Wu, Jin</creator><creator>Costa, Marcos H.</creator><creator>Galbraith, David</creator><creator>Imbuzeiro, Hewlley</creator><creator>Martins, Giordane</creator><creator>da Araujo, Alessandro C.</creator><creator>Malhi, Yadvinder S.</creator><creator>Zeng, Xubin</creator><creator>Moorcroft, Paul</creator><creator>Saleska, Scott R.</creator><general>Wiley</general><scope>OIOZB</scope><scope>OTOTI</scope><orcidid>https://orcid.org/0000000249630535</orcidid><orcidid>https://orcid.org/0000000339211772</orcidid></search><sort><creationdate>20160829</creationdate><title>Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison</title><author>Restrepo-Coupe, Natalia ; Levine, Naomi M. ; Christoffersen, Bradley O. ; Albert, Loren P. ; Wu, Jin ; Costa, Marcos H. ; Galbraith, David ; Imbuzeiro, Hewlley ; Martins, Giordane ; da Araujo, Alessandro C. ; Malhi, Yadvinder S. ; Zeng, Xubin ; Moorcroft, Paul ; Saleska, Scott R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-osti_scitechconnect_13417043</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Amazonia</topic><topic>carbon dynamics</topic><topic>dynamic global vegetation models</topic><topic>ecosystem–climate interactions</topic><topic>eddy covariance</topic><topic>ENVIRONMENTAL SCIENCES</topic><topic>seasonality</topic><topic>tropical forests phenology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Restrepo-Coupe, Natalia</creatorcontrib><creatorcontrib>Levine, Naomi M.</creatorcontrib><creatorcontrib>Christoffersen, Bradley O.</creatorcontrib><creatorcontrib>Albert, Loren P.</creatorcontrib><creatorcontrib>Wu, Jin</creatorcontrib><creatorcontrib>Costa, Marcos H.</creatorcontrib><creatorcontrib>Galbraith, David</creatorcontrib><creatorcontrib>Imbuzeiro, Hewlley</creatorcontrib><creatorcontrib>Martins, Giordane</creatorcontrib><creatorcontrib>da Araujo, Alessandro C.</creatorcontrib><creatorcontrib>Malhi, Yadvinder S.</creatorcontrib><creatorcontrib>Zeng, Xubin</creatorcontrib><creatorcontrib>Moorcroft, Paul</creatorcontrib><creatorcontrib>Saleska, Scott R.</creatorcontrib><creatorcontrib>Brookhaven National Laboratory (BNL), Upton, NY (United States)</creatorcontrib><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><jtitle>Global change biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Restrepo-Coupe, Natalia</au><au>Levine, Naomi M.</au><au>Christoffersen, Bradley O.</au><au>Albert, Loren P.</au><au>Wu, Jin</au><au>Costa, Marcos H.</au><au>Galbraith, David</au><au>Imbuzeiro, Hewlley</au><au>Martins, Giordane</au><au>da Araujo, Alessandro C.</au><au>Malhi, Yadvinder S.</au><au>Zeng, Xubin</au><au>Moorcroft, Paul</au><au>Saleska, Scott R.</au><aucorp>Brookhaven National Laboratory (BNL), Upton, NY (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison</atitle><jtitle>Global change biology</jtitle><date>2016-08-29</date><risdate>2016</risdate><volume>23</volume><issue>1</issue><issn>1354-1013</issn><abstract>To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of other fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.</abstract><cop>United States</cop><pub>Wiley</pub><orcidid>https://orcid.org/0000000249630535</orcidid><orcidid>https://orcid.org/0000000339211772</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1354-1013 |
ispartof | Global change biology, 2016-08, Vol.23 (1) |
issn | 1354-1013 |
language | eng |
recordid | cdi_osti_scitechconnect_1341704 |
source | Wiley-Blackwell Read & Publish Collection |
subjects | Amazonia carbon dynamics dynamic global vegetation models ecosystem–climate interactions eddy covariance ENVIRONMENTAL SCIENCES seasonality tropical forests phenology |
title | Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T09%3A35%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-osti&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Do%20dynamic%20global%20vegetation%20models%20capture%20the%20seasonality%20of%20carbon%20fluxes%20in%20the%20Amazon%20basin?%20A%20data-model%20intercomparison&rft.jtitle=Global%20change%20biology&rft.au=Restrepo-Coupe,%20Natalia&rft.aucorp=Brookhaven%20National%20Laboratory%20(BNL),%20Upton,%20NY%20(United%20States)&rft.date=2016-08-29&rft.volume=23&rft.issue=1&rft.issn=1354-1013&rft_id=info:doi/&rft_dat=%3Costi%3E1341704%3C/osti%3E%3Cgrp_id%3Ecdi_FETCH-osti_scitechconnect_13417043%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |