↓ Skip to main content

The Regulation of Ant Colony Foraging Activity without Spatial Information

Overview of attention for article published in PLoS Computational Biology, August 2012
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
3 news outlets
blogs
6 blogs
twitter
36 X users
facebook
4 Facebook pages
wikipedia
3 Wikipedia pages
googleplus
9 Google+ users
linkedin
1 LinkedIn user
reddit
1 Redditor
pinterest
1 Pinner
video
1 YouTube creator

Citations

dimensions_citation
68 Dimensions

Readers on

mendeley
266 Mendeley
citeulike
7 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
The Regulation of Ant Colony Foraging Activity without Spatial Information
Published in
PLoS Computational Biology, August 2012
DOI 10.1371/journal.pcbi.1002670
Pubmed ID
Authors

Balaji Prabhakar, Katherine N. Dektar, Deborah M. Gordon

Abstract

Many dynamical networks, such as the ones that produce the collective behavior of social insects, operate without any central control, instead arising from local interactions among individuals. A well-studied example is the formation of recruitment trails in ant colonies, but many ant species do not use pheromone trails. We present a model of the regulation of foraging by harvester ant (Pogonomyrmex barbatus) colonies. This species forages for scattered seeds that one ant can retrieve on its own, so there is no need for spatial information such as pheromone trails that lead ants to specific locations. Previous work shows that colony foraging activity, the rate at which ants go out to search individually for seeds, is regulated in response to current food availability throughout the colony's foraging area. Ants use the rate of brief antennal contacts inside the nest between foragers returning with food and outgoing foragers available to leave the nest on the next foraging trip. Here we present a feedback-based algorithm that captures the main features of data from field experiments in which the rate of returning foragers was manipulated. The algorithm draws on our finding that the distribution of intervals between successive ants returning to the nest is a Poisson process. We fitted the parameter that estimates the effect of each returning forager on the rate at which outgoing foragers leave the nest. We found that correlations between observed rates of returning foragers and simulated rates of outgoing foragers, using our model, were similar to those in the data. Our simple stochastic model shows how the regulation of ant colony foraging can operate without spatial information, describing a process at the level of individual ants that predicts the overall foraging activity of the colony.

X Demographics

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 266 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 5%
France 2 <1%
Germany 2 <1%
Portugal 2 <1%
Brazil 2 <1%
Canada 2 <1%
Netherlands 1 <1%
Italy 1 <1%
United Kingdom 1 <1%
Other 6 2%
Unknown 234 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 69 26%
Researcher 49 18%
Student > Master 31 12%
Student > Bachelor 30 11%
Professor > Associate Professor 16 6%
Other 37 14%
Unknown 34 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 105 39%
Computer Science 34 13%
Physics and Astronomy 15 6%
Engineering 13 5%
Biochemistry, Genetics and Molecular Biology 8 3%
Other 47 18%
Unknown 44 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 117. 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 27 July 2023.
All research outputs
#360,174
of 25,576,801 outputs
Outputs from PLoS Computational Biology
#248
of 9,003 outputs
Outputs of similar age
#1,734
of 186,952 outputs
Outputs of similar age from PLoS Computational Biology
#3
of 103 outputs
Altmetric has tracked 25,576,801 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,003 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done particularly well, scoring higher than 97% 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 186,952 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 99% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.