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Suite of simple metrics reveals common movement syndromes across vertebrate taxa

Overview of attention for article published in Movement Ecology, June 2017
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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 (89th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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36 X users
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301 Mendeley
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Title
Suite of simple metrics reveals common movement syndromes across vertebrate taxa
Published in
Movement Ecology, June 2017
DOI 10.1186/s40462-017-0104-2
Pubmed ID
Authors

Briana Abrahms, Dana P. Seidel, Eric Dougherty, Elliott L. Hazen, Steven J. Bograd, Alan M. Wilson, J. Weldon McNutt, Daniel P. Costa, Stephen Blake, Justin S. Brashares, Wayne M. Getz

Abstract

Because empirical studies of animal movement are most-often site- and species-specific, we lack understanding of the level of consistency in movement patterns across diverse taxa, as well as a framework for quantitatively classifying movement patterns. We aim to address this gap by determining the extent to which statistical signatures of animal movement patterns recur across ecological systems. We assessed a suite of movement metrics derived from GPS trajectories of thirteen marine and terrestrial vertebrate species spanning three taxonomic classes, orders of magnitude in body size, and modes of movement (swimming, flying, walking). Using these metrics, we performed a principal components analysis and cluster analysis to determine if individuals organized into statistically distinct clusters. Finally, to identify and interpret commonalities within clusters, we compared them to computer-simulated idealized movement syndromes representing suites of correlated movement traits observed across taxa (migration, nomadism, territoriality, and central place foraging). Two principal components explained 70% of the variance among the movement metrics we evaluated across the thirteen species, and were used for the cluster analysis. The resulting analysis revealed four statistically distinct clusters. All simulated individuals of each idealized movement syndrome organized into separate clusters, suggesting that the four clusters are explained by common movement syndrome. Our results offer early indication of widespread recurrent patterns in movement ecology that have consistent statistical signatures, regardless of taxon, body size, mode of movement, or environment. We further show that a simple set of metrics can be used to classify broad-scale movement patterns in disparate vertebrate taxa. Our comparative approach provides a general framework for quantifying and classifying animal movements, and facilitates new inquiries into relationships between movement syndromes and other ecological processes.

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X Demographics

The data shown below were collected from the profiles of 36 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 301 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Germany 1 <1%
Canada 1 <1%
Brazil 1 <1%
Unknown 297 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 75 25%
Researcher 54 18%
Student > Master 38 13%
Student > Bachelor 24 8%
Student > Doctoral Student 21 7%
Other 37 12%
Unknown 52 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 139 46%
Environmental Science 60 20%
Earth and Planetary Sciences 10 3%
Biochemistry, Genetics and Molecular Biology 3 <1%
Social Sciences 3 <1%
Other 18 6%
Unknown 68 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 17 May 2022.
All research outputs
#1,745,340
of 25,286,324 outputs
Outputs from Movement Ecology
#74
of 381 outputs
Outputs of similar age
#32,872
of 322,700 outputs
Outputs of similar age from Movement Ecology
#3
of 7 outputs
Altmetric has tracked 25,286,324 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 381 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.2. This one has done well, scoring higher than 80% 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 322,700 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 89% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.