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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; Alves de Oliveira, Atila; Amaral, Ieda; Andrade, Ana; Aragao, Luiz E O C; Araujo-Murakami, Alejandro; Arets, Eric J M M; Arroyo, Luzmila; Aymard, Gerardo A; Baraloto, Christopher; Barroso, Jocely; 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.
Afiliación
  • Johnson MO; School of Geography, University of Leeds, Leeds, LS6 2QT, UK.
  • Galbraith D; School of Geography, University of Leeds, Leeds, LS6 2QT, UK.
  • Gloor M; School of Geography, University of Leeds, Leeds, LS6 2QT, UK.
  • De Deurwaerder H; CAVElab Computational & Applied Vegetation Ecology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000, Gent, Belgium.
  • Guimberteau M; Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France.
  • Rammig A; UMR 7619 METIS, IPSL, Sorbonne Universités, UPMC, CNRS, EPHE, 75252, Paris, France.
  • Thonicke K; TUM School of Life Sciences Weihenstephan, Technical University Munich, Hans-Carl-von-Carlowitz-Platz 2, 85354, Freising, Germany.
  • Verbeeck H; Potsdam Institute for Climate Impact Research (PIK), Telegrafenberg A62, PO Box 60 12 03, D-14412, Potsdam, Germany.
  • von Randow C; Potsdam Institute for Climate Impact Research (PIK), Telegrafenberg A62, PO Box 60 12 03, D-14412, Potsdam, Germany.
  • Monteagudo A; CAVElab Computational & Applied Vegetation Ecology, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, B-9000, Gent, Belgium.
  • Phillips OL; INPE, Av. Dos Astronautas, 1.758, Jd. Granja, CEP: 12227-010, Sao Jose dos Campos, SP, Brazil.
  • Brienen RJ; Jardín Botánico de Missouri, Prolongacion Bolognesi Mz.e, Lote 6, Oxapampa, Pasco, Peru.
  • Feldpausch TR; School of Geography, University of Leeds, Leeds, LS6 2QT, UK.
  • Lopez Gonzalez G; School of Geography, University of Leeds, Leeds, LS6 2QT, UK.
  • Fauset S; Geography, College of Life and Environmental Sciences, University of Exeter, Rennes Drive, Exeter, EX4 4RJ, UK.
  • Quesada CA; School of Geography, University of Leeds, Leeds, LS6 2QT, UK.
  • Christoffersen B; School of Geography, University of Leeds, Leeds, LS6 2QT, UK.
  • Ciais P; INPA, Av. André Araújo, 2.936, CEP 69067-375, Petrópolis, Manaus, AM, Brazil.
  • Sampaio G; School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF, UK.
  • Kruijt B; Earth and Environmental Sciences Division, Los Alamos National Laboratory, PO Box 1663, Los Alamos, NM, 87545, USA.
  • Meir P; Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France.
  • Moorcroft P; INPE, Av. Dos Astronautas, 1.758, Jd. Granja, CEP: 12227-010, Sao Jose dos Campos, SP, Brazil.
  • Zhang K; ALTERRA, Wageningen-UR, PO Box 47, 6700 AA, Wageningen, The Netherlands.
  • Alvarez-Davila E; School of Geosciences, University of Edinburgh, Edinburgh, EH9 3FF, UK.
  • Alves de Oliveira A; Research School of Biology, Australian National University, Canberra, ACT, 0200, Australia.
  • Amaral I; Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge, MA, 02138, USA.
  • Andrade A; Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, National Weather Center, Suite 2100, 120 David L. Boren Blvd, Norman, OK, 73072, USA.
  • Aragao LE; Fundación Con-Vida, Cr68 A 46 A-77 Medellín, Medellín, Colombia.
  • Araujo-Murakami A; INPA, Av. André Araújo, 2.936, CEP 69067-375, Petrópolis, Manaus, AM, Brazil.
  • Arets EJ; INPA, Av. André Araújo, 2.936, CEP 69067-375, Petrópolis, Manaus, AM, Brazil.
  • Arroyo L; INPA, Av. André Araújo, 2.936, CEP 69067-375, Petrópolis, Manaus, AM, Brazil.
  • Aymard GA; Jardín Botánico de Missouri, Prolongacion Bolognesi Mz.e, Lote 6, Oxapampa, Pasco, Peru.
  • Baraloto C; Museo de Historia Natural Noel Kempff Mercado, Universidad Autonoma Gabriel Rene Moreno, Casilla 2489, Av. Irala 565, Santa Cruz, Bolivia.
  • Barroso J; ALTERRA, Wageningen-UR, PO Box 47, 6700 AA, Wageningen, The Netherlands.
  • Bonal D; Museo de Historia Natural Noel Kempff Mercado, Universidad Autonoma Gabriel Rene Moreno, Casilla 2489, Av. Irala 565, Santa Cruz, Bolivia.
  • Boot R; UNELLEZ-Guanare, Programa de Ciencias del Agro y el Mar, Herbario Universitario (PORT), Mesa de Cavacas, Estado Portuguesa, 3350, Venezuela.
  • Camargo J; Department of Biological Sciences, International Center for Tropical Botany (ICTB), Florida International University, 112200 SW 8th Street, OE 167, Miami, FL, 33199, USA.
  • Chave J; Universidade Federal do Acre, Campus de Cruzeiro do Sul, Rio Branco, Brazil.
  • Cogollo A; INRA, UMR 1137 "Ecologie et Ecophysiologie Forestiere", 54280, Champenoux, France.
  • Cornejo Valverde F; Tropenbos International, PO Box 232, 6700 AE, Wageningen, The Netherlands.
  • Lola da Costa AC; INPA, Av. André Araújo, 2.936, CEP 69067-375, Petrópolis, Manaus, AM, Brazil.
  • Di Fiore A; Université Paul Sabatier CNRS, UMR 5174 Evolution et Diversité Biologique, bâtiment 4R1, 31062, Toulouse, France.
  • Ferreira L; Jardín Botánico de Medellín Joaquín Antonio Uribe, Calle 73 # 51 D 14 Medellín, Cartagena, Colombia.
  • Higuchi N; Andes to Amazon Biodiversity Program, Puerto Maldonado, Madre de Dios, Perú.
  • Honorio EN; Centro de Geociencias, Universidade Federal do Para, CEP 66017-970, Belem, Para, Brazil.
  • Killeen TJ; Department of Anthropology, University of Texas at Austin, SAC Room 5.150, 2201 Speedway Stop C3200, Austin, TX, 78712, USA.
  • Laurance SG; Museu Paraense Emilio Goeldi, Av. Magalhães Barata, 376 - São Braz, CEP: 66040-170, Belém, PA, Brazil.
  • Laurance WF; INPA, Av. André Araújo, 2.936, CEP 69067-375, Petrópolis, Manaus, AM, Brazil.
  • Licona J; Instituto de Investigaciones de la Amazonía Peruana, Av. José Quiñones km 2.5, Iquitos, Perú.
  • Lovejoy T; World Wildlife Fund, 1250 24th St NW, Washington, DC, 20037, USA.
Glob Chang Biol ; 22(12): 3996-4013, 2016 12.
Article en En | MEDLINE | ID: mdl-27082541
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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Árboles / Clima Tropical / Bosques / Biomasa / Modelos Teóricos Tipo de estudio: Prognostic_studies País/Región como asunto: America do sul Idioma: En Revista: Glob Chang Biol Año: 2016 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Árboles / Clima Tropical / Bosques / Biomasa / Modelos Teóricos Tipo de estudio: Prognostic_studies País/Región como asunto: America do sul Idioma: En Revista: Glob Chang Biol Año: 2016 Tipo del documento: Article País de afiliación: Reino Unido