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The utility of bioenergetics modelling in quantifying predation rates of marine apex predators: Ecological and fisheries implications

Overview of attention for article published in Scientific Reports, October 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 (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

blogs
1 blog
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7 X users

Citations

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19 Dimensions

Readers on

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74 Mendeley
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Title
The utility of bioenergetics modelling in quantifying predation rates of marine apex predators: Ecological and fisheries implications
Published in
Scientific Reports, October 2017
DOI 10.1038/s41598-017-13388-y
Pubmed ID
Authors

A. Barnett, M. Braccini, C. L. Dudgeon, N. L. Payne, K. G. Abrantes, M. Sheaves, E. P. Snelling

Abstract

Predators play a crucial role in the structure and function of ecosystems. However, the magnitude of this role is often unclear, particularly for large marine predators, as predation rates are difficult to measure directly. If relevant biotic and abiotic parameters can be obtained, then bioenergetics modelling offers an alternative approach to estimating predation rates, and can provide new insights into ecological processes. We integrate demographic and ecological data for a marine apex predator, the broadnose sevengill shark Notorynchus cepedianus, with energetics data from the literature, to construct a bioenergetics model to quantify predation rates on key fisheries species in Norfolk Bay, Australia. We account for the uncertainty in model parameters by incorporating parameter confidence through Monte Carlo simulations and running alternative variants of the model. Model and parameter variants provide alternative estimates of predation rates. Our simplest model estimates that ca. 1130 ± 137 N. cepedianus individuals consume 11,379 (95% CI: 11,111-11,648) gummy sharks Mustelus antarcticus (~21 tonnes) over a 36-week period in Norfolk Bay, which represents a considerable contribution to total predation mortality on this key fishery species. This study demonstrates how the integration of ecology and fisheries science can provide information for ecosystem and fisheries management.

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X Demographics

The data shown below were collected from the profiles of 7 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 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 74 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 20%
Student > Bachelor 12 16%
Researcher 10 14%
Student > Ph. D. Student 7 9%
Student > Doctoral Student 2 3%
Other 8 11%
Unknown 20 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 33 45%
Environmental Science 8 11%
Unspecified 2 3%
Philosophy 1 1%
Biochemistry, Genetics and Molecular Biology 1 1%
Other 3 4%
Unknown 26 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 November 2017.
All research outputs
#2,631,092
of 23,005,189 outputs
Outputs from Scientific Reports
#22,482
of 124,233 outputs
Outputs of similar age
#52,362
of 324,711 outputs
Outputs of similar age from Scientific Reports
#888
of 5,026 outputs
Altmetric has tracked 23,005,189 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 124,233 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has done well, scoring higher than 81% 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 324,711 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 5,026 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.