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
  • Among the highest-scoring outputs from this source (#40 of 3,145)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

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

Readers on

mendeley
138 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, Wilson, Adam M, Jetz, Walter

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 118 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 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Germany 2 1%
France 2 1%
Brazil 2 1%
Spain 2 1%
Colombia 2 1%
Chile 1 <1%
South Africa 1 <1%
Italy 1 <1%
Other 5 4%
Unknown 115 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 42 30%
Student > Ph. D. Student 31 22%
Student > Bachelor 16 12%
Student > Master 15 11%
Other 12 9%
Other 22 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 59 43%
Environmental Science 52 38%
Earth and Planetary Sciences 17 12%
Computer Science 3 2%
Unspecified 2 1%
Other 5 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 360. 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 27 February 2017.
All research outputs
#12,657
of 7,613,601 outputs
Outputs from PLoS Biology
#40
of 3,145 outputs
Outputs of similar age
#1,192
of 274,617 outputs
Outputs of similar age from PLoS Biology
#2
of 94 outputs
Altmetric has tracked 7,613,601 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 3,145 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.1. This one has done particularly well, scoring higher than 98% 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 274,617 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 94 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 97% of its contemporaries.