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Reconstructing vapor pressure deficit from leaf wax lipid molecular distributions

Overview of attention for article published in Scientific Reports, March 2018
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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 (97th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
10 news outlets
blogs
1 blog
twitter
13 tweeters
facebook
1 Facebook page
video
1 video uploader

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
75 Mendeley
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Title
Reconstructing vapor pressure deficit from leaf wax lipid molecular distributions
Published in
Scientific Reports, March 2018
DOI 10.1038/s41598-018-21959-w
Pubmed ID
Authors

Yvette L. Eley, Michael T. Hren

Abstract

Estimates of atmospheric moisture are critical for understanding the links and feedbacks between atmospheric CO2and global climate. At present, there are few quantitative moisture proxies that are applicable to deep time. We present a new proxy for atmospheric moisture derived from modern climate and leaf biomarker data from North and Central America. Plants have a direct genetic pathway to regulate the production of lipids in response to osmotic stress, which is manifested in a change in the distribution of simple aliphatic lipids such as n-alkanes. The Average Chain Length (ACL) of these lipids is therefore statistically related to mean annual vapor pressure deficit (VPDav), enabling quantitative reconstruction of VPD from sedimentary n-alkanes. We apply this transfer function to the Armantes section of the Calatayud-Daroca Basin in Central Spain, that spans the Middle Miocene Climatic Optimum (MMCO) and the Middle Miocene Climate Transition (MMCT). Reconstructed VPDavrises from 0.13 to 0.92 kPa between 16.5 and 12.4 Ma, indicating a substantial drying through the MMCT. These data are consistent with fossil assemblages and mammalian stable isotope data, highlighting the utility of this new organic molecular tool for quantifying hydrologic variability over geologic timescales.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 21%
Student > Master 10 13%
Researcher 10 13%
Student > Doctoral Student 7 9%
Student > Bachelor 6 8%
Other 12 16%
Unknown 14 19%
Readers by discipline Count As %
Earth and Planetary Sciences 25 33%
Environmental Science 9 12%
Agricultural and Biological Sciences 5 7%
Nursing and Health Professions 2 3%
Biochemistry, Genetics and Molecular Biology 2 3%
Other 10 13%
Unknown 22 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 94. 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 11 May 2020.
All research outputs
#248,377
of 16,651,312 outputs
Outputs from Scientific Reports
#2,925
of 89,187 outputs
Outputs of similar age
#8,400
of 281,138 outputs
Outputs of similar age from Scientific Reports
#1
of 5 outputs
Altmetric has tracked 16,651,312 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 89,187 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.3. This one has done particularly well, scoring higher than 96% 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 281,138 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 97% of its contemporaries.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them