Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional do INPA |
Texto Completo: | https://repositorio.inpa.gov.br/handle/1/15382 |
Resumo: | Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. |
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Johnson, Michelle O.Galbraith, David R.Gloor, Manuel E.Deurwaerder, Hannes deGuimberteau, MatthieuRammig, AnjaThonicke, KirstenVerbeeck, HansVon Randow, CelsoMonteagudo, Abel LorenzoPhillips, Oliver L.Brienen, Roel J.W.Feldpausch, Ted R.Lopez-Gonzalez, GabrielaFauset, SophieQuesada, Carlos AlbertoChristoffersen, Bradley O.Ciais, PhilippeSampaio, Gilvan de OliveiraKruijt, Bart J.Meir, Patrick W.Moorcroft, Paul R.Zhang, KeAlvarez, EstebanAlves de Oliveira, AtilaAmaral, Iêda Leão doAndrade, Ana C.S.Aragao, L. E.O.C.Araujo-Murakami, AlejandroArets, Eric J.M.M.Arroyo, Luzmila P.Aymard, Gerardo Antonio C.Baraloto, ChristopherBarroso, JorcelyBonal, DamienBoot, René G.A.Camargo, José Luís CampanaChave, JérômeCogollo, ÁlvaroCornejo-Valverde, FernandoCosta, Antônio Carlos Lôla daDi Fiore, AnthonyFerreira, Leandro ValleHiguchi, NiroHonorio Coronado, Euridice N.Killeen, Timothy J.Laurance, Susan G.W.Laurance, William F.Licona, Juan CarlosLovejoy, Thomas E.Malhi, Yadvinder SinghMarimon, Ben HurMarimon, Beatriz SchwantesMatos, Darley Calderado LealMendoza, CasimiroNeill, David A.Pardo, GuidoPena-Claros, MarielosPitman, Nigel C.A.Poorter, L.Prieto, AdrianaRamírez-Angulo, HirmaRoopsind, AnandRudas, AgustínSalomão, Rafael PaivaSilveira, MarcosStropp, Julianater Steege, H.Terborgh, John W.Thomas, Raquel S.Toledo, MarisolTorres-Lezama, ArmandoVan Der Heijden, Geertje M.F.Vásquez, Rodolfo V.Guimarães Vieira, Ima CèliaVilanova, EmilioVos, Vincent A.Baker, Timothy R.2020-05-08T20:36:29Z2020-05-08T20:36:29Z2016https://repositorio.inpa.gov.br/handle/1/1538210.1111/gcb.13315Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.Volume 22, Número 12, Pags. 3996-4013Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessAboveground BiomassAllometryCarbon CycleForest EcosystemMortalityNet Primary ProductionStemTropical ForestVegetationAmazoniaBiomassForestGrowth, Development And AgingSouth AmericaTheoretical ModelTreeTropic ClimateBiomassForestsModels, TheoreticalSouth AmericaTreesTropical ClimateVariation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation modelsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleGlobal Change Biologyengreponame:Repositório Institucional do INPAinstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPAORIGINALartigo-inpa.pdfartigo-inpa.pdfapplication/pdf1064353https://repositorio.inpa.gov.br/bitstream/1/15382/1/artigo-inpa.pdf31ebfbd1856f4e47c4c4c1d7027abed5MD511/153822020-07-14 11:05:33.246oai:repositorio:1/15382Repositório de PublicaçõesPUBhttps://repositorio.inpa.gov.br/oai/requestopendoar:2020-07-14T15:05:33Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)false |
dc.title.en.fl_str_mv |
Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models |
title |
Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models |
spellingShingle |
Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models Johnson, Michelle O. Aboveground Biomass Allometry Carbon Cycle Forest Ecosystem Mortality Net Primary Production Stem Tropical Forest Vegetation Amazonia Biomass Forest Growth, Development And Aging South America Theoretical Model Tree Tropic Climate Biomass Forests Models, Theoretical South America Trees Tropical Climate |
title_short |
Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models |
title_full |
Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models |
title_fullStr |
Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models |
title_full_unstemmed |
Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models |
title_sort |
Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models |
author |
Johnson, Michelle O. |
author_facet |
Johnson, Michelle O. Galbraith, David R. Gloor, Manuel E. Deurwaerder, Hannes de Guimberteau, Matthieu Rammig, Anja Thonicke, Kirsten Verbeeck, Hans Von Randow, Celso Monteagudo, Abel Lorenzo Phillips, Oliver L. Brienen, Roel J.W. Feldpausch, Ted R. Lopez-Gonzalez, Gabriela Fauset, Sophie Quesada, Carlos Alberto Christoffersen, Bradley O. Ciais, Philippe Sampaio, Gilvan de Oliveira Kruijt, Bart J. Meir, Patrick W. Moorcroft, Paul R. Zhang, Ke Alvarez, Esteban Alves de Oliveira, Atila Amaral, Iêda Leão do Andrade, Ana C.S. Aragao, L. E.O.C. Araujo-Murakami, Alejandro Arets, Eric J.M.M. Arroyo, Luzmila P. Aymard, Gerardo Antonio C. Baraloto, Christopher Barroso, Jorcely Bonal, Damien Boot, René G.A. Camargo, José Luís Campana Chave, Jérôme Cogollo, Álvaro Cornejo-Valverde, Fernando Costa, Antônio Carlos Lôla da Di Fiore, Anthony Ferreira, Leandro Valle Higuchi, Niro Honorio Coronado, Euridice N. Killeen, Timothy J. Laurance, Susan G.W. Laurance, William F. Licona, Juan Carlos Lovejoy, Thomas E. Malhi, Yadvinder Singh Marimon, Ben Hur Marimon, Beatriz Schwantes Matos, Darley Calderado Leal Mendoza, Casimiro Neill, David A. Pardo, Guido Pena-Claros, Marielos Pitman, Nigel C.A. Poorter, L. Prieto, Adriana Ramírez-Angulo, Hirma Roopsind, Anand Rudas, Agustín Salomão, Rafael Paiva Silveira, Marcos Stropp, Juliana ter Steege, H. Terborgh, John W. Thomas, Raquel S. Toledo, Marisol Torres-Lezama, Armando Van Der Heijden, Geertje M.F. Vásquez, Rodolfo V. Guimarães Vieira, Ima Cèlia Vilanova, Emilio Vos, Vincent A. Baker, Timothy R. |
author_role |
author |
author2 |
Galbraith, David R. Gloor, Manuel E. Deurwaerder, Hannes de Guimberteau, Matthieu Rammig, Anja Thonicke, Kirsten Verbeeck, Hans Von Randow, Celso Monteagudo, Abel Lorenzo Phillips, Oliver L. Brienen, Roel J.W. Feldpausch, Ted R. Lopez-Gonzalez, Gabriela Fauset, Sophie Quesada, Carlos Alberto Christoffersen, Bradley O. Ciais, Philippe Sampaio, Gilvan de Oliveira Kruijt, Bart J. Meir, Patrick W. Moorcroft, Paul R. Zhang, Ke Alvarez, Esteban Alves de Oliveira, Atila Amaral, Iêda Leão do Andrade, Ana C.S. Aragao, L. E.O.C. Araujo-Murakami, Alejandro Arets, Eric J.M.M. Arroyo, Luzmila P. Aymard, Gerardo Antonio C. Baraloto, Christopher Barroso, Jorcely Bonal, Damien Boot, René G.A. Camargo, José Luís Campana Chave, Jérôme Cogollo, Álvaro Cornejo-Valverde, Fernando Costa, Antônio Carlos Lôla da Di Fiore, Anthony Ferreira, Leandro Valle Higuchi, Niro Honorio Coronado, Euridice N. Killeen, Timothy J. Laurance, Susan G.W. Laurance, William F. Licona, Juan Carlos Lovejoy, Thomas E. Malhi, Yadvinder Singh Marimon, Ben Hur Marimon, Beatriz Schwantes Matos, Darley Calderado Leal Mendoza, Casimiro Neill, David A. Pardo, Guido Pena-Claros, Marielos Pitman, Nigel C.A. Poorter, L. Prieto, Adriana Ramírez-Angulo, Hirma Roopsind, Anand Rudas, Agustín Salomão, Rafael Paiva Silveira, Marcos Stropp, Juliana ter Steege, H. Terborgh, John W. Thomas, Raquel S. Toledo, Marisol Torres-Lezama, Armando Van Der Heijden, Geertje M.F. Vásquez, Rodolfo V. Guimarães Vieira, Ima Cèlia Vilanova, Emilio Vos, Vincent A. Baker, Timothy R. |
author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Johnson, Michelle O. Galbraith, David R. Gloor, Manuel E. Deurwaerder, Hannes de Guimberteau, Matthieu Rammig, Anja Thonicke, Kirsten Verbeeck, Hans Von Randow, Celso Monteagudo, Abel Lorenzo Phillips, Oliver L. Brienen, Roel J.W. Feldpausch, Ted R. Lopez-Gonzalez, Gabriela Fauset, Sophie Quesada, Carlos Alberto Christoffersen, Bradley O. Ciais, Philippe Sampaio, Gilvan de Oliveira Kruijt, Bart J. Meir, Patrick W. Moorcroft, Paul R. Zhang, Ke Alvarez, Esteban Alves de Oliveira, Atila Amaral, Iêda Leão do Andrade, Ana C.S. Aragao, L. E.O.C. Araujo-Murakami, Alejandro Arets, Eric J.M.M. Arroyo, Luzmila P. Aymard, Gerardo Antonio C. Baraloto, Christopher Barroso, Jorcely Bonal, Damien Boot, René G.A. Camargo, José Luís Campana Chave, Jérôme Cogollo, Álvaro Cornejo-Valverde, Fernando Costa, Antônio Carlos Lôla da Di Fiore, Anthony Ferreira, Leandro Valle Higuchi, Niro Honorio Coronado, Euridice N. Killeen, Timothy J. Laurance, Susan G.W. Laurance, William F. Licona, Juan Carlos Lovejoy, Thomas E. Malhi, Yadvinder Singh Marimon, Ben Hur Marimon, Beatriz Schwantes Matos, Darley Calderado Leal Mendoza, Casimiro Neill, David A. Pardo, Guido Pena-Claros, Marielos Pitman, Nigel C.A. Poorter, L. Prieto, Adriana Ramírez-Angulo, Hirma Roopsind, Anand Rudas, Agustín Salomão, Rafael Paiva Silveira, Marcos Stropp, Juliana ter Steege, H. Terborgh, John W. Thomas, Raquel S. Toledo, Marisol Torres-Lezama, Armando Van Der Heijden, Geertje M.F. Vásquez, Rodolfo V. Guimarães Vieira, Ima Cèlia Vilanova, Emilio Vos, Vincent A. Baker, Timothy R. |
dc.subject.eng.fl_str_mv |
Aboveground Biomass Allometry Carbon Cycle Forest Ecosystem Mortality Net Primary Production Stem Tropical Forest Vegetation Amazonia Biomass Forest Growth, Development And Aging South America Theoretical Model Tree Tropic Climate Biomass Forests Models, Theoretical South America Trees Tropical Climate |
topic |
Aboveground Biomass Allometry Carbon Cycle Forest Ecosystem Mortality Net Primary Production Stem Tropical Forest Vegetation Amazonia Biomass Forest Growth, Development And Aging South America Theoretical Model Tree Tropic Climate Biomass Forests Models, Theoretical South America Trees Tropical Climate |
description |
Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. |
publishDate |
2016 |
dc.date.issued.fl_str_mv |
2016 |
dc.date.accessioned.fl_str_mv |
2020-05-08T20:36:29Z |
dc.date.available.fl_str_mv |
2020-05-08T20:36:29Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://repositorio.inpa.gov.br/handle/1/15382 |
dc.identifier.doi.none.fl_str_mv |
10.1111/gcb.13315 |
url |
https://repositorio.inpa.gov.br/handle/1/15382 |
identifier_str_mv |
10.1111/gcb.13315 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Volume 22, Número 12, Pags. 3996-4013 |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ info:eu-repo/semantics/openAccess |
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Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Global Change Biology |
publisher.none.fl_str_mv |
Global Change Biology |
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