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Animal Interactions and the Emergence of Territoriality

Overview of attention for article published in PLoS Computational Biology, March 2011
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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)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

Mentioned by

blogs
1 blog
twitter
1 X user

Citations

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105 Dimensions

Readers on

mendeley
340 Mendeley
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5 CiteULike
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Title
Animal Interactions and the Emergence of Territoriality
Published in
PLoS Computational Biology, March 2011
DOI 10.1371/journal.pcbi.1002008
Pubmed ID
Authors

Luca Giuggioli, Jonathan R. Potts, Stephen Harris

Abstract

Inferring the role of interactions in territorial animals relies upon accurate recordings of the behaviour of neighbouring individuals. Such accurate recordings are rarely available from field studies. As a result, quantification of the interaction mechanisms has often relied upon theoretical approaches, which hitherto have been limited to comparisons of macroscopic population-level predictions from un-tested interaction models. Here we present a quantitative framework that possesses a microscopic testable hypothesis on the mechanism of conspecific avoidance mediated by olfactory signals in the form of scent marks. We find that the key parameters controlling territoriality are two: the average territory size, i.e. the inverse of the population density, and the time span during which animal scent marks remain active. Since permanent monitoring of a territorial border is not possible, scent marks need to function in the temporary absence of the resident. As chemical signals carried by the scent only last a finite amount of time, each animal needs to revisit territorial boundaries frequently and refresh its own scent marks in order to deter possible intruders. The size of the territory an animal can maintain is thus proportional to the time necessary for an animal to move between its own territorial boundaries. By using an agent-based model to take into account the possible spatio-temporal movement trajectories of individual animals, we show that the emerging territories are the result of a form of collective animal movement where, different to shoaling, flocking or herding, interactions are highly heterogeneous in space and time. The applicability of our hypothesis has been tested with a prototypical territorial animal, the red fox (Vulpes vulpes).

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 340 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 1%
Brazil 4 1%
United Kingdom 4 1%
Australia 2 <1%
Switzerland 2 <1%
France 2 <1%
New Zealand 2 <1%
Portugal 2 <1%
United Arab Emirates 1 <1%
Other 8 2%
Unknown 308 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 77 23%
Researcher 64 19%
Student > Master 54 16%
Student > Bachelor 30 9%
Professor 16 5%
Other 50 15%
Unknown 49 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 172 51%
Environmental Science 46 14%
Psychology 12 4%
Physics and Astronomy 9 3%
Engineering 7 2%
Other 34 10%
Unknown 60 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 06 January 2018.
All research outputs
#4,210,245
of 25,658,541 outputs
Outputs from PLoS Computational Biology
#3,405
of 9,022 outputs
Outputs of similar age
#20,250
of 120,172 outputs
Outputs of similar age from PLoS Computational Biology
#19
of 59 outputs
Altmetric has tracked 25,658,541 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,022 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.2. This one has gotten more attention than average, scoring higher than 62% 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 120,172 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 59 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.