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Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions

Overview of attention for article published in PLoS Biology, March 2016
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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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
30 news outlets
blogs
6 blogs
twitter
111 tweeters
facebook
3 Facebook pages
googleplus
4 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
78 Dimensions

Readers on

mendeley
270 Mendeley
citeulike
1 CiteULike
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Title
Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions
Published in
PLoS Biology, March 2016
DOI 10.1371/journal.pbio.1002415
Pubmed ID
Authors

Adam M. Wilson, Walter Jetz

Abstract

Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km) monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

Twitter Demographics

The data shown below were collected from the profiles of 111 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 270 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
Colombia 2 <1%
United Kingdom 2 <1%
Germany 2 <1%
South Africa 1 <1%
Australia 1 <1%
Brazil 1 <1%
France 1 <1%
Italy 1 <1%
Other 6 2%
Unknown 248 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 66 24%
Student > Ph. D. Student 63 23%
Student > Master 40 15%
Student > Bachelor 22 8%
Other 18 7%
Other 39 14%
Unknown 22 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 98 36%
Environmental Science 87 32%
Earth and Planetary Sciences 31 11%
Computer Science 5 2%
Biochemistry, Genetics and Molecular Biology 4 1%
Other 11 4%
Unknown 34 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 346. 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 29 June 2019.
All research outputs
#34,205
of 13,925,749 outputs
Outputs from PLoS Biology
#101
of 4,360 outputs
Outputs of similar age
#1,301
of 263,737 outputs
Outputs of similar age from PLoS Biology
#3
of 93 outputs
Altmetric has tracked 13,925,749 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,360 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 49.6. This one has done particularly well, scoring higher than 97% 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 263,737 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 99% of its contemporaries.
We're also able to compare this research output to 93 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 96% of its contemporaries.