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Pushing precipitation to the extremes in distributed experiments: recommendations for simulating wet and dry years

Overview of attention for article published in Global Change Biology, November 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

news
2 news outlets
twitter
9 tweeters
facebook
1 Facebook page

Citations

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94 Dimensions

Readers on

mendeley
217 Mendeley
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Title
Pushing precipitation to the extremes in distributed experiments: recommendations for simulating wet and dry years
Published in
Global Change Biology, November 2016
DOI 10.1111/gcb.13504
Pubmed ID
Authors

Alan K. Knapp, Meghan L. Avolio, Claus Beier, Charles J. W. Carroll, Scott L. Collins, Jeffrey S. Dukes, Lauchlan H. Fraser, Robert J. Griffin-Nolan, David L. Hoover, Anke Jentsch, Michael E. Loik, Richard P. Phillips, Alison K. Post, Osvaldo E. Sala, Ingrid J. Slette, Laura Yahdjian, Melinda D. Smith

Abstract

Intensification of the global hydrological cycle, ranging from larger individual precipitation events to more extreme multi-year droughts, has the potential to cause widespread alterations in ecosystem structure and function. With evidence that the incidence of extreme precipitation years (defined statistically from historical precipitation records) is increasing, there is a clear need to identify ecosystems that are most vulnerable to these changes and understand why some ecosystems are more sensitive to extremes than others. To date, opportunistic studies of naturally occurring extreme precipitation years, combined with results from a relatively small number of experiments, have provided limited mechanistic understanding of differences in ecosystem sensitivity suggesting that new approaches are needed. Coordinated distributed experiments (CDEs) arrayed across multiple ecosystem types and focused on water can enhance our understanding of differential ecosystem sensitivity to precipitation extremes, but there are many design challenges to overcome (e.g., cost, comparability, standardization). Here we evaluate contemporary experimental approaches for manipulating precipitation under field conditions to inform the design of "Drought-Net", a relatively low cost CDE that simulates extreme precipitation years. A common method for imposing both dry and wet years is to alter each ambient precipitation event. We endorse this approach for imposing extreme precipitation years because it simultaneously alters other precipitation characteristics (i.e., event size) consistent with natural precipitation patterns. However, we do not advocate applying identical treatment levels at all sites - a common approach to standardization in CDEs. This is because precipitation variability varies >5-fold globally resulting in a wide range of ecosystem-specific thresholds for defining extreme precipitation years. For CDEs focused on precipitation extremes, treatments should be based on each site's past climatic characteristics. This approach, though not often used by ecologists, allows ecological responses to be directly compared across disparate ecosystems and climates, facilitating process-level understanding of ecosystem sensitivity to precipitation extremes. This article is protected by copyright. All rights reserved.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 217 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 2 <1%
United States 2 <1%
Argentina 1 <1%
Spain 1 <1%
Denmark 1 <1%
Unknown 210 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 54 25%
Researcher 40 18%
Student > Master 23 11%
Student > Doctoral Student 18 8%
Professor > Associate Professor 14 6%
Other 41 19%
Unknown 27 12%
Readers by discipline Count As %
Environmental Science 74 34%
Agricultural and Biological Sciences 69 32%
Earth and Planetary Sciences 15 7%
Biochemistry, Genetics and Molecular Biology 5 2%
Nursing and Health Professions 3 1%
Other 10 5%
Unknown 41 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 September 2017.
All research outputs
#1,039,048
of 17,391,055 outputs
Outputs from Global Change Biology
#1,310
of 4,667 outputs
Outputs of similar age
#19,947
of 227,145 outputs
Outputs of similar age from Global Change Biology
#8
of 44 outputs
Altmetric has tracked 17,391,055 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,667 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.7. This one has gotten more attention than average, scoring higher than 71% 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 227,145 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 91% of its contemporaries.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.