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Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity

Overview of attention for article published in Environmental Pollution, April 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

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6 tweeters

Citations

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1 Dimensions

Readers on

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21 Mendeley
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Title
Disentangling the effects of low pH and metal mixture toxicity on macroinvertebrate diversity
Published in
Environmental Pollution, April 2018
DOI 10.1016/j.envpol.2017.12.097
Pubmed ID
Authors

Riccardo Fornaroli, Alessio Ippolito, Mari J. Tolkkinen, Heikki Mykrä, Timo Muotka, Laurie S. Balistrieri, Travis S. Schmidt

Abstract

One of the primary goals of biological assessment of streams is to identify which of a suite of chemical stressors is limiting their ecological potential. Elevated metal concentrations in streams are often associated with low pH, yet the effects of these two potentially limiting factors of freshwater biodiversity are rarely considered to interact beyond the effects of pH on metal speciation. Using a dataset from two continents, a biogeochemical model of the toxicity of metal mixtures (Al, Cd, Cu, Pb, Zn) and quantile regression, we addressed the relative importance of both pH and metals as limiting factors for macroinvertebrate communities. Current environmental quality standards for metals proved to be protective of stream macroinvertebrate communities and were used as a starting point to assess metal mixture toxicity. A model of metal mixture toxicity accounting for metal interactions was a better predictor of macroinvertebrate responses than a model considering individual metal toxicity. We showed that the direct limiting effect of pH on richness was of the same magnitude as that of chronic metal toxicity, independent of its influence on the availability and toxicity of metals. By accounting for the direct effect of pH on macroinvertebrate communities, we were able to determine that acidic streams supported less diverse communities than neutral streams even when metals were below no-effect thresholds. Through a multivariate quantile model, we untangled the limiting effect of both pH and metals and predicted the maximum diversity that could be expected at other sites as a function of these variables. This model can be used to identify which of the two stressors is more limiting to the ecological potential of running waters.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 19%
Professor 3 14%
Student > Master 3 14%
Student > Bachelor 3 14%
Student > Ph. D. Student 3 14%
Other 5 24%
Readers by discipline Count As %
Environmental Science 9 43%
Agricultural and Biological Sciences 7 33%
Unspecified 4 19%
Earth and Planetary Sciences 1 5%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 26 May 2018.
All research outputs
#3,187,321
of 12,199,526 outputs
Outputs from Environmental Pollution
#828
of 3,836 outputs
Outputs of similar age
#91,913
of 272,769 outputs
Outputs of similar age from Environmental Pollution
#43
of 197 outputs
Altmetric has tracked 12,199,526 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 3,836 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. 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 272,769 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 197 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.