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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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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.

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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 107 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 8 7%
Unknown 20 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 41%
Environmental Science 32 28%
Earth and Planetary Sciences 4 3%
Engineering 3 3%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 7 6%
Unknown 20 17%