Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Detalhes bibliográficos
Autor(a) principal: Johnson, Michelle O.
Data de Publicação: 2016
Outros Autores: 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.
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.
id INPA-2_6a4ae15f7d41a0683bdd450c7e198f75
oai_identifier_str oai:repositorio:1/15382
network_acronym_str INPA-2
network_name_str Repositório Institucional do INPA
repository_id_str
spelling 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
rights_invalid_str_mv 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
dc.source.none.fl_str_mv reponame:Repositório Institucional do INPA
instname:Instituto Nacional de Pesquisas da Amazônia (INPA)
instacron:INPA
instname_str Instituto Nacional de Pesquisas da Amazônia (INPA)
instacron_str INPA
institution INPA
reponame_str Repositório Institucional do INPA
collection Repositório Institucional do INPA
bitstream.url.fl_str_mv https://repositorio.inpa.gov.br/bitstream/1/15382/1/artigo-inpa.pdf
bitstream.checksum.fl_str_mv 31ebfbd1856f4e47c4c4c1d7027abed5
bitstream.checksumAlgorithm.fl_str_mv MD5
repository.name.fl_str_mv Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)
repository.mail.fl_str_mv
_version_ 1809928875394727936