Data from: Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests

  • Jin Wu (Creator)
  • Loren P. Albert (Creator)
  • Aline Pontes Lopes (Creator)
  • N. Restrepo-Coupe (Creator)
  • Matthew Hayek (Creator)
  • Kenia T. Wiedemann (Creator)
  • Kaiyu Guan (Creator)
  • Scott C. Stark (Creator)
  • Bradley O. Christoffersen (Creator)
  • Neill Prohaska (Creator)
  • Julia V. Tavares (Creator)
  • Suelen Marostica (Creator)
  • Hideki Kobayashi (Creator)
  • Mauricio L. Ferreira (Creator)
  • Kleber Silva Campos (Creator)
  • Rodrigo Dda Silva (Contributor)
  • Paulo M. Brando (Creator)
  • Dennis G. Dye (Creator)
  • Travis E. Huxman (Creator)
  • Alfredo R. Huete (Creator)
  • Bruce W. Nelson (Creator)
  • Scott R Saleska (Creator)
  • Scott C. Stark (Creator)
  • Hideki Kobayashi (Creator)
  • Rodrigo da Silva (Creator)

Dataset

Description

In evergreen tropical forests, the extent, magnitude, and controls on photosynthetic seasonality are poorly resolved and inadequately represented in Earth system models. Combining camera observations with ecosystem carbon dioxide fluxes at forests across rainfall gradients in AmazĂ´nia, we show that aggregate canopy phenology, not seasonality of climate drivers, is the primary cause of photosynthetic seasonality in these forests. Specifically, synchronization of new leaf growth with dry season litterfall shifts canopy composition toward younger, more light-use efficient leaves, explaining large seasonal increases (~27%) in ecosystem photosynthesis. Coordinated leaf development and demography thus reconcile seemingly disparate observations at different scales and indicate that accounting for leaf-level phenology is critical for accurately simulating ecosystem-scale responses to climate change.
Date made availableJan 26 2017
PublisherDryad
Geographical coverageAmazon Rainforests

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