Evidence map›Paper›PMID 34673768›Full record

ArticlePLoS computational biology2021

Better tired than lost: Turtle ant trail networks favor coherence over short edges.

Arjun Chandrasekhar, James A R Marshall, Cortnea Austin, Saket Navlakha, Deborah M Gordon

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Distributed algorithms from arboreal ants for the shortest path problem.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 5 institutions in 2 countries.

Arjun ChandrasekharDepartment of Computer Science, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
James A R MarshallDepartment of Computer Science, University of Sheffield, Sheffield, United Kingdom.ORCID 0000-0002-1506-167X
Cortnea AustinCentral Washington University, Ellensburg, Washington, United States of America.ORCID 0000-0002-4232-2417
Saket NavlakhaSimons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.
Deborah M GordonDepartment of Biology, Stanford University, Stanford, California, United States of America.ORCID 0000-0002-1090-9539
Central Washington University · USCold Spring Harbor Laboratory · USStanford University · USUniversity of Pittsburgh · USUniversity of Sheffield · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Creating a routing backbone is a fundamental problem in both biology and engineering. The routing backbone of the trail networks of arboreal turtle ants (Cephalotes goniodontus) connects many nests and food sources using trail pheromone deposited by ants as they walk. Unlike species that forage on the ground, the trail networks of arboreal ants are constrained by the vegetation. We examined what objectives the trail networks meet by comparing the observed ant trail networks with networks of random, hypothetical trail networks in the same surrounding vegetation and with trails optimized for four objectives: minimizing path length, minimizing average edge length, minimizing number of nodes, and minimizing opportunities to get lost. The ants' trails minimized path length by minimizing the number of nodes traversed rather than choosing short edges. In addition, the ants' trails reduced the opportunity for ants to get lost at each node, favoring nodes with 3D configurations most likely to be reinforced by pheromone. Thus, rather than finding the shortest edges, turtle ant trail networks take advantage of natural variation in the environment to favor coherence, keeping the ants together on the trails.

Indexed as

Models, BiologicalAlgorithmsAnimalsAntsBehavior, AnimalComputational BiologyFeeding BehaviorPheromonesWalkingPheromones

Identifiers

PMID34673768
PMCPMC8562808
OpenAlexW3205557991

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.