Evidence map›Paper›PMID 31780703›Full record

ArticleScientific reports2019

Ecological networks: Pursuing the shortest path, however narrow and crooked.

Andrea Costa, Ana M Martín González, Katell Guizien, Andrea M Doglioli, José María Gómez, Anne A Petrenko, Stefano Allesina

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  6. Nine quick tips for analyzing network data.PLoS computational biology · 2019
    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

7 authors.

Andrea Costa1Center for Climate Physics, Institute for Basic Science, Busan, 46241, South Korea. costa.andrea@zoho.com.
Ana M Martín GonzálezCenter for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark. ana.maria.martingonzalez@gmail.com.ORCID http://orcid.org/0000-0001-9429-7180
Katell GuizienLaboratoire d'Ecogéochimie des Environnements Benthique, CNRS, Université Paris VI, UMR 8222, Banyuls-sur-Mer, France.
Andrea M DoglioliAix Marseille Université, CNRS, Université de Toulon, IRD, OSU Pythèas, Mediterranean Institute of Oceanography (MIO), UM 110, 13288, Marseille, France.
José María GómezDepartamento de Ecología Funcional y Evolutiva, Estación Experimental de Zonas Áridas (EEZA-CSIC), Almería, Spain.
Anne A PetrenkoAix Marseille Université, CNRS, Université de Toulon, IRD, OSU Pythèas, Mediterranean Institute of Oceanography (MIO), UM 110, 13288, Marseille, France.
Stefano AllesinaDepartment of Ecology and Evolution, University of Chicago, Chicago, IL, USA.ORCID http://orcid.org/0000-0003-0313-8374

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Representing data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade that use shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point check-list to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies.

Identifiers

PMID31780703
PMCPMC6883044

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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.