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Incorporating food web dynamics into ecological restoration: a modeling approach for river ecosystems

Overview of attention for article published in Ecological Applications, March 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
28 X users

Citations

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44 Dimensions

Readers on

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126 Mendeley
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Title
Incorporating food web dynamics into ecological restoration: a modeling approach for river ecosystems
Published in
Ecological Applications, March 2017
DOI 10.1002/eap.1486
Pubmed ID
Authors

J. Ryan Bellmore, Joseph R. Benjamin, Michael Newsom, Jennifer A. Bountry, Daniel Dombroski

Abstract

Restoration is frequently aimed at the recovery of target species, but also influences the larger food web in which these species participate. Effects of restoration on this broader network of organisms can influence target species both directly and indirectly via changes in energy flow through food webs. To help incorporate these complexities into river restoration planning we constructed a model that links river food web dynamics to in-stream physical habitat and riparian vegetation conditions. We present an application of the model to the Methow River, Washington (USA), a location of on-going restoration aimed at recovering salmon. Three restoration strategies were simulated: riparian vegetation restoration, nutrient augmentation via salmon carcass addition, and side-channel reconnection. We also added populations of nonnative aquatic snails and fish to the modeled food web to explore how changes in food web structure mediate responses to restoration. Simulations suggest that side-channel reconnection may be a better strategy than carcass addition and vegetation planting for improving conditions for salmon in this river segment. However, modeled responses were strongly sensitive to changes in the structure of the food web. The addition of nonnative snails and fish modified pathways of energy through the food web, which negated restoration improvements. This finding illustrates that forecasting responses to restoration may require accounting for the structure of food webs, and that changes in this structure-as might be expected with the spread of invasive species-could compromise restoration outcomes. Unlike habitat-based approaches to restoration assessment that focus on the direct effects of physical habitat conditions on single species of interest, our approach dynamically links the success of target organisms to the success of competitors, predators, and prey. By elucidating the direct and indirect pathways by which restoration affects target species, dynamic food web models can improve restoration planning by fostering a deeper understanding of system connectedness and dynamics. This article is protected by copyright. All rights reserved.

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X Demographics

The data shown below were collected from the profiles of 28 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 126 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 126 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 20%
Student > Master 24 19%
Student > Ph. D. Student 23 18%
Student > Bachelor 12 10%
Other 8 6%
Other 13 10%
Unknown 21 17%
Readers by discipline Count As %
Environmental Science 47 37%
Agricultural and Biological Sciences 37 29%
Engineering 4 3%
Earth and Planetary Sciences 3 2%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 5 4%
Unknown 28 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 November 2019.
All research outputs
#1,357,174
of 25,074,338 outputs
Outputs from Ecological Applications
#362
of 3,351 outputs
Outputs of similar age
#26,670
of 313,579 outputs
Outputs of similar age from Ecological Applications
#12
of 68 outputs
Altmetric has tracked 25,074,338 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,351 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.0. This one has done well, scoring higher than 89% 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 313,579 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 68 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.