Evidence map›Paper›PMID 38077691›Full record

ArticlePNAS nexus2023

Temporal origin of nestedness in interaction networks.

Phillip P A Staniczenko, Debabrata Panja

Abstract read
In one paragraph

Article in PNAS nexus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Phillip P A StaniczenkoDepartment of Biology, Brooklyn College, City University of New York, Brooklyn, NY 11210, USA.ORCID https://orcid.org/0000-0001-5091-8416
Debabrata PanjaDepartment of Information and Computing Sciences, Utrecht University, Utrecht 3584 CC, The Netherlands.ORCID https://orcid.org/0000-0003-2141-9735

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nestedness is a common property of communication, finance, trade, and ecological networks. In networks with high levels of nestedness, the link positions of low-degree nodes (those with few links) form nested subsets of the link positions of high-degree nodes (those with many links), leading to matrix representations with characteristic upper triangular or staircase patterns. Recent theoretical work has connected nestedness to the functionality of complex systems and has suggested that it is a structural by-product of the skewed degree distributions often seen in empirical data. However, mechanisms for generating nestedness remain poorly understood, limiting the connections that can be made between system processes and observed network structures. Here, we show that a simple probabilistic model based on phenology-the timing of copresences among interaction partners-can produce nested structures and correctly predict around two-thirds of interactions in two fish market networks and around one-third of interactions in 22 plant-pollinator networks. Notably, the links most readily explained by frequent actor copresences appear to form a backbone of nested interactions, with the remaining interactions attributable to opportunistic interactions or preferences for particular interaction partners that are not routinely available.

Indexed as

complex systemsinteraction networksnestedness

Identifiers

PMID38077691
PMCPMC10708905

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.