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Dryad

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

Cite this dataset

Wu, Jin et al. (2017). Data from: Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests [Dataset]. Dryad. https://doi.org/10.5061/dryad.8fb47

Abstract

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 Amazônia, 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.

Usage notes

Location

Amazon Rainforests