↓ Skip to main content

Can mercury in fish be reduced by water level management? Evaluating the effects of water level fluctuation on mercury accumulation in yellow perch (Perca flavescens)

Overview of attention for article published in Ecotoxicology, August 2014
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
42 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Can mercury in fish be reduced by water level management? Evaluating the effects of water level fluctuation on mercury accumulation in yellow perch (Perca flavescens)
Published in
Ecotoxicology, August 2014
DOI 10.1007/s10646-014-1296-5
Pubmed ID
Authors

James H. Larson, Ryan P. Maki, Brent C. Knights, Brian R. Gray

Abstract

Mercury (Hg) contamination of fisheries is a major concern for resource managers of many temperate lakes. Anthropogenic Hg contamination is largely derived from atmospheric deposition within a lake's watershed, but its incorporation into the food web is facilitated by bacterial activity in sediments. Temporal variation in Hg content of fish (young-of-year yellow perch) in the regulated lakes of the Rainy-Namakan complex (on the border of the United States and Canada) has been linked to water level (WL) fluctuations, presumably through variation in sediment inundation. As a result, Hg contamination of fish has been linked to international regulations of WL fluctuation. Here we assess the relationship between WL fluctuations and fish Hg content using a 10-year dataset covering six lakes. Within-year WL rise did not appear in strongly supported models of fish Hg, but year-to-year variation in maximum water levels (∆maxWL) was positively associated with fish Hg content. This WL effect varied in magnitude among lakes: In Crane Lake, a 1 m increase in ∆maxWL from the previous year was associated with a 108 ng increase in fish Hg content (per gram wet weight), while the same WL change in Kabetogama was associated with only a 5 ng increase in fish Hg content. In half the lakes sampled here, effect sizes could not be distinguished from zero. Given the persistent and wide-ranging extent of Hg contamination and the large number of regulated waterways, future research is needed to identify the conditions in which WL fluctuations influence fish Hg content.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 17%
Researcher 6 14%
Student > Ph. D. Student 6 14%
Professor 5 12%
Other 4 10%
Other 5 12%
Unknown 9 21%
Readers by discipline Count As %
Environmental Science 11 26%
Earth and Planetary Sciences 5 12%
Agricultural and Biological Sciences 4 10%
Chemistry 3 7%
Nursing and Health Professions 3 7%
Other 7 17%
Unknown 9 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 2014.
All research outputs
#14,138,089
of 22,763,032 outputs
Outputs from Ecotoxicology
#525
of 1,472 outputs
Outputs of similar age
#120,493
of 235,517 outputs
Outputs of similar age from Ecotoxicology
#15
of 69 outputs
Altmetric has tracked 22,763,032 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,472 research outputs from this source. They receive a mean Attention Score of 3.5. 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 235,517 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.