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Designing ecological climate change impact assessments to reflect key climatic drivers

Overview of attention for article published in Global Change Biology, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)

Mentioned by

twitter
10 tweeters
facebook
2 Facebook pages

Citations

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9 Dimensions

Readers on

mendeley
88 Mendeley
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Title
Designing ecological climate change impact assessments to reflect key climatic drivers
Published in
Global Change Biology, March 2017
DOI 10.1111/gcb.13653
Pubmed ID
Authors

Helen R. Sofaer, Joseph J. Barsugli, Catherine S. Jarnevich, John T. Abatzoglou, Marian K. Talbert, Brian W. Miller, Jeffrey T. Morisette

Abstract

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profiles of 10 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 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 1%
United States 1 1%
Norway 1 1%
Canada 1 1%
Unknown 84 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 27%
Researcher 20 23%
Student > Master 10 11%
Unspecified 7 8%
Professor 6 7%
Other 21 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 42%
Environmental Science 28 32%
Unspecified 13 15%
Earth and Planetary Sciences 4 5%
Social Sciences 3 3%
Other 3 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 03 June 2017.
All research outputs
#2,978,327
of 12,353,915 outputs
Outputs from Global Change Biology
#2,077
of 3,359 outputs
Outputs of similar age
#94,964
of 334,369 outputs
Outputs of similar age from Global Change Biology
#122
of 163 outputs
Altmetric has tracked 12,353,915 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,359 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.2. This one is in the 37th percentile – i.e., 37% of its peers scored the same or lower than it.
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 334,369 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 163 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.