Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models
Johnson, Michelle O., Galbraith, David, Gloor, Manuel, De Deurwaerder, Hannes, Guimberteau, Matthieu, Rammig, Anja, Thonicke, Kirsten, Verbeeck, Hans, von Randow, Celso, Monteagudo, Abel, Phillips, Oliver L., Brienen, Roel J.W., Feldpausch, Ted R., Lopez Gonzalez, Gabriela, Fauset, Sophie, Quesada, Carlos A., Christoffersen, Bradley, Ciais, Philippe, Sampaio, Gilvan, Kruijt, Bart, Meir, Patrick, Moorcroft, Paul, Zhang, Ke, Alvarez-Davila, Esteban, de Oliveira, Atila Alves, Amaral, Ieda, Andrade, Ana, Aragao, Luiz E.O.C., Araujo-Murakami, Alejandro, Arets, Eric J.M.M., Arroyo, Luzmila, Aymard, Gerardo, Baraloto, Christopher, Barroso, Jorcely, Bonal, Damien, Boot, Rene, Camargo, Jose, Chave, Jerome, Cogollo, Alvaro, Cornejo Valverde, Fernando, Lola da Costa, Antonio C., Di Fiore, Anthony, Ferreira, Leandro, Higuchi, Niro, Honorio, Euridice N., Killeen, Tim J., Laurance, Susan G., Laurance, William F., Licona, Juan, Lovejoy, Thomas, Malhi, Yadvinder, Marimon, Bia, Marimon Junior, Ben Hur, Matos, Darley C.L., Mendoza, Casimiro, Neill, David A., Pardo, Guido, Peña-Claros, Marielos, Pitman, Nigel C.A., Poorter, Lourens, Prieto, Adriana, Ramirez-Angulo, Hirma, Roopsind, Anand, Rudas, Agustin, Salomao, Rafael P., Silveira, Marcos, Stropp, Juliana, ter Steege, Hans, Terborgh, John, Thomas, Raqual, Toledo, Marisol, Torres-Lezama, Armando, van der Heijden, Geertje, Vásquez, Rodolfo, Guimarães Vieira, Ima Cèlia, Vilanova, Emilio, Vos, Vincent A., and Baker, Timothy R. (2016) Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models. Global Change Biology, 22 (12). pp. 3996-4013.
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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, basinwide 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.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||allometry, carbon, dynamic global vegetation model, forest plots, productivity, tropical forest|
© 2016 The Authors. Global Change Biology. Published by John Wiley & Sons Ltd.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. https://creativecommons.org/licenses/by/4.0/
|Funders:||European Union (EU), Gordon and Betty Moore Foundation (GBMF), European Research Council (ERC), Natural Environment Research Council (NERC), Tropical Ecology Assessment and Monitoring Network (TEAM), Conservation International (CI), Missouri Botanical Garden (MBG), Smithsonian Institution (SI), Wildlife Conservation Society (WCS), Conselho Nacional de Desenvolvimento Científico e Tecnológico, Brazil (CNPq), Helmholtz Alliance (HA), Dutch Ministry of Economic Affairs (DMEA), United States Department of Energy Biological and Environmental Research (US DOE BER), Royal Society-Wolfson Research Merit Award, Australian Research Council (ARC), Leverhulme Trust (LT)|
|Projects and Grants:||EU Seventh Framework Programme AMAZALERT project 282664, EU Seventh Framework Programme GEOCARBON project 283080, ERC grant Tropical Forests in the Changing Earth System, NERC Urgency Grant AMAZONICA NE/F005806/1, NERC Consortium Grant TROBIT NE/D005590/1, NERC Standard Grant 'Niche Evolution of South American Trees' NE/I028122/1, CNPq project Programa de Pesquisas Ecológicas de Longa Duração PELD-403725/2012-7, HA 'Remote Sensing and Earth System Dynamics', EU FP7 project ROBIN 283093, DMEA KB-14-003-030, US DOE BER NGEE-Tropics Project, ERC Advanced Grant, ARC Grant FT110100457, NERC Grant NE/J011002|
|Date Deposited:||12 Dec 2016 01:39|
|FoR Codes:||05 ENVIRONMENTAL SCIENCES > 0502 Environmental Science and Management > 050202 Conservation and Biodiversity @ 100%|
|SEO Codes:||96 ENVIRONMENT > 9608 Flora, Fauna and Biodiversity > 960899 Flora, Fauna and Biodiversity of Environments not elsewhere classified @ 100%|
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