Please use this identifier to cite or link to this item: https://repositorio.inpa.gov.br/handle/1/18107
Title: Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment
Authors: Stark, Scott C.
Leitold, Veronika
Wu, Jin
Hunter, Maria O.
Castilho, Carolina Volkmer de
Costa, Flávia Regina Capellotto
McMahon, Sean M.
Parker, Geoffrey G.
Shimabukuro, Mônica Takako
Lefsky, Michael Andrew
Keller, Michael
Alves, Luciana Ferreira
Schietti, Juliana
Shimabukuro, Yosio Edemir
Brandão, Diego Oliveira
Woodcock, Tara K.
Higuchi, Niro
Camargo, Plínio Barbosa de
Oliveira, Raimundo Cosme de
Saleska, Scott Reid
Issue Date: 2012
metadata.dc.publisher.journal: Ecology Letters
metadata.dc.relation.ispartof: Volume 15, Número 12, Pags. 1406-1414
Abstract: Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) - remotely estimated from LiDAR - control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth across tree size classes in forest near Manaus, Brazil. The same statistical model, with no parameterisation change but driven by different observed canopy structure, predicted the higher productivity of a site 500 km east. Gap fraction and a metric of vegetation vertical extent and evenness also predicted biomass gains and losses for one-hectare plots. Despite significant site differences in canopy structure and carbon dynamics, the relation between biomass growth and light fell on a unifying curve. This supported our hypothesis, suggesting that knowledge of canopy structure can explain variation in biomass growth over tropical landscapes and improve understanding of ecosystem function. © 2012 Blackwell Publishing Ltd/CNRS.
metadata.dc.identifier.doi: 10.1111/j.1461-0248.2012.01864.x
Appears in Collections:Artigos

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.