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Predicting the Movement Speeds of Animals in Natural Environments

Overview of attention for article published in Integrative & Comparative Biology, October 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)

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1 news outlet
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Citations

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59 Dimensions

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109 Mendeley
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Title
Predicting the Movement Speeds of Animals in Natural Environments
Published in
Integrative & Comparative Biology, October 2015
DOI 10.1093/icb/icv106
Pubmed ID
Authors

Robbie S. Wilson, Jerry F. Husak, Lewis G. Halsey, Christofer J. Clemente

Abstract

An animal's movement speed affects all behaviors and underlies the intensity of an activity, the time it takes to complete it, and the probability of successfully completing it, but which factors determine how fast or slow an animal chooses to move? Despite the critical importance of an animal's choice of speed (hereafter designated as "speed-choice"), we still lack a framework for understanding and predicting how fast animals should move in nature. In this article, we develop a framework for predicting speed that is applicable to any animal-including humans-performing any behavior where choice of speed occurs. To inspire new research in this area, we (1) detail the main factors likely to affect speed-choice, including organismal constraints (i.e., energetic, physiological, and biomechanical) and environmental constraints (i.e., predation intensity and abiotic factors); (2) discuss the value of optimal foraging theory in developing models of speed-choice; and (3) describe how optimality models might be integrated with the range of potential organismal and environmental constraints to predict speed. We show that by utilizing optimality theory it is possible to provide quantitative predictions of optimal speeds across different ecological contexts. However, the usefulness of any predictive models is still entirely dependent on being able to provide relevant mathematical functions to insert into such models. We still lack basic knowledge about how an animal's speed affects its motor control, maneuverability, observational skills, and vulnerability to predators. Studies exploring these gaps in knowledge will help facilitate the field of optimal performance and allow us to adequately parameterize models predicting the speed-choice of animals, which represents one of the most basic of all behavioral decisions.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 <1%
South Africa 1 <1%
Unknown 107 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 26%
Student > Master 16 15%
Researcher 15 14%
Student > Bachelor 14 13%
Student > Doctoral Student 7 6%
Other 11 10%
Unknown 18 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 46%
Environmental Science 18 17%
Engineering 6 6%
Neuroscience 3 3%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 10 9%
Unknown 20 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 16 December 2021.
All research outputs
#2,707,443
of 25,377,790 outputs
Outputs from Integrative & Comparative Biology
#338
of 2,225 outputs
Outputs of similar age
#36,961
of 294,223 outputs
Outputs of similar age from Integrative & Comparative Biology
#2
of 3 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,225 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done well, scoring higher than 84% 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 294,223 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 87% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.