↓ Skip to main content

Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests

Overview of attention for article published in Science, February 2016
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

news
8 news outlets
blogs
3 blogs
twitter
46 tweeters
facebook
2 Facebook pages
wikipedia
1 Wikipedia page
googleplus
7 Google+ users

Readers on

mendeley
445 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests
Published in
Science, February 2016
DOI 10.1126/science.aad5068
Pubmed ID
Authors

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

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.

Twitter Demographics

The data shown below were collected from the profiles of 46 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 445 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 5 1%
United States 3 <1%
Spain 2 <1%
Mexico 1 <1%
France 1 <1%
Japan 1 <1%
Austria 1 <1%
Unknown 431 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 100 22%
Researcher 91 20%
Student > Master 55 12%
Student > Doctoral Student 45 10%
Professor > Associate Professor 20 4%
Other 68 15%
Unknown 66 15%
Readers by discipline Count As %
Environmental Science 125 28%
Agricultural and Biological Sciences 103 23%
Earth and Planetary Sciences 78 18%
Engineering 8 2%
Biochemistry, Genetics and Molecular Biology 4 <1%
Other 21 5%
Unknown 106 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 120. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 February 2019.
All research outputs
#288,674
of 22,647,730 outputs
Outputs from Science
#8,045
of 77,780 outputs
Outputs of similar age
#5,745
of 297,631 outputs
Outputs of similar age from Science
#154
of 1,081 outputs
Altmetric has tracked 22,647,730 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 77,780 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 61.9. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 297,631 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 1,081 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.