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Progress and Challenges in Coupled Hydrodynamic-Ecological Estuarine Modeling

Overview of attention for article published in Estuaries & Coasts, July 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

twitter
3 tweeters
facebook
1 Facebook page

Citations

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50 Dimensions

Readers on

mendeley
181 Mendeley
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Title
Progress and Challenges in Coupled Hydrodynamic-Ecological Estuarine Modeling
Published in
Estuaries & Coasts, July 2015
DOI 10.1007/s12237-015-0011-y
Pubmed ID
Authors

Neil K. Ganju, Mark J. Brush, Brenda Rashleigh, Alfredo L. Aretxabaleta, Pilar del Barrio, Jason S. Grear, Lora A. Harris, Samuel J. Lake, Grant McCardell, James O’Donnell, David K. Ralston, Richard P. Signell, Jeremy M. Testa, Jamie M. P. Vaudrey

Abstract

Numerical modeling has emerged over the last several decades as a widely accepted tool for investigations in environmental sciences. In estuarine research, hydrodynamic and ecological models have moved along parallel tracks with regard to complexity, refinement, computational power, and incorporation of uncertainty. Coupled hydrodynamic-ecological models have been used to assess ecosystem processes and interactions, simulate future scenarios, and evaluate remedial actions in response to eutrophication, habitat loss, and freshwater diversion. The need to couple hydrodynamic and ecological models to address research and management questions is clear, because dynamic feedbacks between biotic and physical processes are critical interactions within ecosystems. In this review we present historical and modern perspectives on estuarine hydrodynamic and ecological modeling, consider model limitations, and address aspects of model linkage, skill assessment, and complexity. We discuss the balance between spatial and temporal resolution and present examples using different spatiotemporal scales. Finally, we recommend future lines of inquiry, approaches to balance complexity and uncertainty, and model transparency and utility. It is idealistic to think we can pursue a "theory of everything" for estuarine models, but recent advances suggest that models for both scientific investigations and management applications will continue to improve in terms of realism, precision, and accuracy.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 181 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 3%
Mexico 2 1%
United Kingdom 1 <1%
Germany 1 <1%
New Zealand 1 <1%
Unknown 171 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 49 27%
Researcher 40 22%
Student > Master 25 14%
Other 12 7%
Student > Bachelor 11 6%
Other 18 10%
Unknown 26 14%
Readers by discipline Count As %
Environmental Science 48 27%
Earth and Planetary Sciences 37 20%
Agricultural and Biological Sciences 18 10%
Engineering 16 9%
Mathematics 4 2%
Other 16 9%
Unknown 42 23%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 07 March 2016.
All research outputs
#6,605,538
of 12,545,170 outputs
Outputs from Estuaries & Coasts
#221
of 829 outputs
Outputs of similar age
#84,909
of 231,758 outputs
Outputs of similar age from Estuaries & Coasts
#4
of 30 outputs
Altmetric has tracked 12,545,170 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 829 research outputs from this source. They receive a mean Attention Score of 2.7. This one has gotten more attention than average, scoring higher than 73% 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 231,758 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 62% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.