Use este identificador para citar ou linkar para este item: https://repositorio.inpa.gov.br/handle/1/15382
Título: Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models
Autor: Johnson, Michelle O.
Galbraith, David R.
Gloor, Manuel E.
Deurwaerder, Hannes de
Guimberteau, Matthieu
Rammig, Anja
Thonicke, Kirsten
Verbeeck, Hans
Randow, Celso Von
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.
Palavras-chave: 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
Data do documento: 2016
Revista: Global Change Biology
É parte de: Volume 22, Número 12, Pags. 3996-4013
Abstract: 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.
DOI: 10.1111/gcb.13315
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