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Before-after, control-impact analysis of evidence for the impacts of water level on Walleye, Northern Pike and Yellow Perch in lakes of the Rainy-Namakan complex (MN, USA and ON, CA)

Overview of attention for article published in PLOS ONE, June 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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1 news outlet
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1 X user

Citations

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4 Dimensions

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27 Mendeley
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Title
Before-after, control-impact analysis of evidence for the impacts of water level on Walleye, Northern Pike and Yellow Perch in lakes of the Rainy-Namakan complex (MN, USA and ON, CA)
Published in
PLOS ONE, June 2018
DOI 10.1371/journal.pone.0198612
Pubmed ID
Authors

James H. Larson, Ryan P. Maki, Benjamin A. Vondra, Kevin E. Peterson

Abstract

Water level (WL) fluctuations in lakes influence many aspects of ecosystem processes. Concern about the potential impact of WL fluctuations on fisheries was one of the factors that motivated the decision in 2000 to alter the management of WL in the Rainy-Namakan reservoir complex (on the border between the U.S. state of Minnesota and the Canadian province of Ontario). We used a Before-After, Control-Impact (BACI) framework to identify potential impacts of the change in WL management to Walleye, Northern Pike and Yellow Perch catch per unit effort (CPUE). The CPUE of these species from 1990-1999 and from 2005-2014 were compared in four impact lakes (Lake Kabetogama, Namakan Lake, Rainy Lake and Sand Point Lake) and two control lakes (Lake of the Woods and Lake Vermilion) using a simple Bayesian model. Changes in fish CPUE in the impact lakes were often similar to changes that occurred in at least one control lake. The only change that was not similar to changes in control lakes was an increase of Yellow Perch in Lake Kabetogama. The two control lakes often differed substantially from each other, such that if only one had been available our conclusions about the role of WL management on fisheries would be very different. In general, identifying cause-and-effect relationships in observational field data is very difficult, and the BACI analysis used here does not specify a causative mechanism, so co-occurring environmental and management changes may obscure the effect of WL management.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Other 4 15%
Student > Ph. D. Student 3 11%
Student > Master 2 7%
Student > Bachelor 1 4%
Other 2 7%
Unknown 10 37%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 26%
Environmental Science 6 22%
Unspecified 1 4%
Energy 1 4%
Social Sciences 1 4%
Other 1 4%
Unknown 10 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 19 June 2020.
All research outputs
#3,169,775
of 23,094,276 outputs
Outputs from PLOS ONE
#41,768
of 197,001 outputs
Outputs of similar age
#66,162
of 329,374 outputs
Outputs of similar age from PLOS ONE
#766
of 3,253 outputs
Altmetric has tracked 23,094,276 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 197,001 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.2. This one has done well, scoring higher than 78% 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 329,374 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 79% of its contemporaries.
We're also able to compare this research output to 3,253 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.