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Climate change and watershed mercury export: a multiple projection and model analysis

Overview of attention for article published in Environmental Toxicology & Chemistry, July 2013
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Title
Climate change and watershed mercury export: a multiple projection and model analysis
Published in
Environmental Toxicology & Chemistry, July 2013
DOI 10.1002/etc.2284
Pubmed ID
Authors

Heather E. Golden, Christopher D. Knightes, Paul A. Conrads, Toby D. Feaster, Gary M. Davis, Stephen T. Benedict, Paul M. Bradley

Abstract

Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

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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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 4%
Canada 1 4%
Unknown 24 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 31%
Professor 5 19%
Student > Ph. D. Student 2 8%
Professor > Associate Professor 2 8%
Student > Master 2 8%
Other 1 4%
Unknown 6 23%
Readers by discipline Count As %
Environmental Science 10 38%
Agricultural and Biological Sciences 7 27%
Immunology and Microbiology 1 4%
Earth and Planetary Sciences 1 4%
Social Sciences 1 4%
Other 2 8%
Unknown 4 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 May 2013.
All research outputs
#22,759,802
of 25,374,647 outputs
Outputs from Environmental Toxicology & Chemistry
#5,118
of 5,612 outputs
Outputs of similar age
#170,625
of 191,893 outputs
Outputs of similar age from Environmental Toxicology & Chemistry
#32
of 76 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,612 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 191,893 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.