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Multivariate Models of Adult Pacific Salmon Returns

Overview of attention for article published in PLOS ONE, January 2013
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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 (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

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1 policy source
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4 X users
reddit
1 Redditor

Citations

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79 Dimensions

Readers on

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114 Mendeley
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Title
Multivariate Models of Adult Pacific Salmon Returns
Published in
PLOS ONE, January 2013
DOI 10.1371/journal.pone.0054134
Pubmed ID
Authors

Brian J. Burke, William T. Peterson, Brian R. Beckman, Cheryl Morgan, Elizabeth A. Daly, Marisa Litz

Abstract

Most modeling and statistical approaches encourage simplicity, yet ecological processes are often complex, as they are influenced by numerous dynamic environmental and biological factors. Pacific salmon abundance has been highly variable over the last few decades and most forecasting models have proven inadequate, primarily because of a lack of understanding of the processes affecting variability in survival. Better methods and data for predicting the abundance of returning adults are therefore required to effectively manage the species. We combined 31 distinct indicators of the marine environment collected over an 11-year period into a multivariate analysis to summarize and predict adult spring Chinook salmon returns to the Columbia River in 2012. In addition to forecasts, this tool quantifies the strength of the relationship between various ecological indicators and salmon returns, allowing interpretation of ecosystem processes. The relative importance of indicators varied, but a few trends emerged. Adult returns of spring Chinook salmon were best described using indicators of bottom-up ecological processes such as composition and abundance of zooplankton and fish prey as well as measures of individual fish, such as growth and condition. Local indicators of temperature or coastal upwelling did not contribute as much as large-scale indicators of temperature variability, matching the spatial scale over which salmon spend the majority of their ocean residence. Results suggest that effective management of Pacific salmon requires multiple types of data and that no single indicator can represent the complex early-ocean ecology of salmon.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Mexico 1 <1%
Denmark 1 <1%
Jersey 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 106 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 28%
Student > Master 26 23%
Student > Ph. D. Student 13 11%
Other 11 10%
Professor > Associate Professor 5 4%
Other 6 5%
Unknown 21 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 41%
Environmental Science 32 28%
Earth and Planetary Sciences 4 4%
Engineering 3 3%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 5 4%
Unknown 21 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 01 October 2017.
All research outputs
#4,990,870
of 24,323,543 outputs
Outputs from PLOS ONE
#76,163
of 209,680 outputs
Outputs of similar age
#51,745
of 290,919 outputs
Outputs of similar age from PLOS ONE
#1,195
of 4,936 outputs
Altmetric has tracked 24,323,543 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 209,680 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.6. This one has gotten more attention than average, scoring higher than 63% 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 290,919 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 4,936 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.