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Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, March 2014
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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 (92nd percentile)

Mentioned by

news
13 news outlets
blogs
5 blogs
twitter
56 X users

Citations

dimensions_citation
794 Dimensions

Readers on

mendeley
712 Mendeley
citeulike
1 CiteULike
Title
Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence
Published in
Proceedings of the National Academy of Sciences of the United States of America, March 2014
DOI 10.1073/pnas.1320008111
Pubmed ID
Authors

Luis Guanter, Yongguang Zhang, Martin Jung, Joanna Joiner, Maximilian Voigt, Joseph A. Berry, Christian Frankenberg, Alfredo R. Huete, Pablo Zarco-Tejada, Jung-Eun Lee, M. Susan Moran, Guillermo Ponce-Campos, Christian Beer, Gustavo Camps-Valls, Nina Buchmann, Damiano Gianelle, Katja Klumpp, Alessandro Cescatti, John M. Baker, Timothy J. Griffis

Abstract

Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50-75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.

X Demographics

X Demographics

The data shown below were collected from the profiles of 56 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 712 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 1%
Mexico 3 <1%
Belgium 2 <1%
Japan 2 <1%
France 2 <1%
Brazil 2 <1%
Australia 2 <1%
New Zealand 2 <1%
South Africa 1 <1%
Other 10 1%
Unknown 676 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 143 20%
Student > Ph. D. Student 134 19%
Student > Master 88 12%
Professor 39 5%
Student > Bachelor 33 5%
Other 121 17%
Unknown 154 22%
Readers by discipline Count As %
Environmental Science 148 21%
Agricultural and Biological Sciences 140 20%
Earth and Planetary Sciences 138 19%
Engineering 21 3%
Unspecified 9 1%
Other 53 7%
Unknown 203 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 163. 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 25 August 2022.
All research outputs
#253,561
of 26,017,215 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#4,703
of 104,451 outputs
Outputs of similar age
#2,038
of 241,840 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#71
of 980 outputs
Altmetric has tracked 26,017,215 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 104,451 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.5. This one has done particularly well, scoring higher than 95% 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 241,840 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 980 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.