Evidence map›Paper›PMID 34665974›Full record

ArticleJournal of the Royal Society, Interface2021

Network analysis of intra- and interspecific freshwater fish interactions using year-around tracking.

Sara Vanovac, Dakota Howard, Christopher T Monk, Robert Arlinghaus, Philippe J Giabbanelli

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 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
–field-weighted citation impact
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.

  1. Review
  2. Article
  3. Article
  4. Social networks and the conservation of fish.Communications biology · 2022
    Review
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.

Sara VanovacComputer Science Department, Furman University, Greenville, SC 29613, USA.
Dakota HowardComputer Science Department, Furman University, Greenville, SC 29613, USA.
Christopher T MonkDepartment of Biology and Ecology of Fishes, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 310, 12587 Berlin, Germany.ORCID 0000-0002-1647-4740
Robert ArlinghausDepartment of Biology and Ecology of Fishes, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 310, 12587 Berlin, Germany.ORCID 0000-0003-2861-527X
Philippe J GiabbanelliDepartment of Computer Science and Software Engineering, Miami University, Benton Hall 205 W, 510 E High Street, Oxford, OH 45056, USA.ORCID 0000-0001-6816-355X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A long-term, yet detailed view into the social patterns of aquatic animals has been elusive. With advances in reality mining tracking technologies, a proximity-based social network (PBSN) can capture detailed spatio-temporal underwater interactions. We collected and analysed a large dataset of 108 freshwater fish from four species, tracked every few seconds over 1 year in their natural environment. We calculated the clustering coefficient of minute-by-minute PBSNs to measure social interactions, which can happen among fish sharing resources or habitat preferences (positive/neutral interactions) or in predator and prey during foraging interactions (agonistic interactions). A statistically significant coefficient compared to an equivalent random network suggests interactions, while a significant aggregated clustering across PBSNs indicates prolonged, purposeful social behaviour. Carp (

Indexed as

CarpsPerchesAnimalsEcosystemFresh WaterPredatory Behavioranimal behaviourclusteringdynamic networkpredator–preysocial network analysis

Identifiers

PMID34665974
PMCPMC8526167

What OpenQuestion holds

Textmetadata
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.