Evidence map›Paper›PMID 39713560›Full record

ReviewBioscience2024

A conceptual classification scheme of invasion science.

Camille L Musseau, Maud Bernard-Verdier, Tina Heger, Leonidas H Skopeteas, David Strasiewsky, Daniel Mietchen, Jonathan M Jeschke

Abstract readReview
In one paragraph

Review in Bioscience, 2024. 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. 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

7 authors.

Camille L MusseauDepartment of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB).ORCID https://orcid.org/0000-0002-5633-2384
Maud Bernard-VerdierDepartment of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB).ORCID https://orcid.org/0000-0003-4240-9560
Tina HegerDepartment of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB).ORCID https://orcid.org/0000-0002-5522-5632
Leonidas H SkopeteasDepartment of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB).
David StrasiewskyDepartment of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB).
Daniel MietchenDepartment of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB).ORCID https://orcid.org/0000-0001-9488-1870
Jonathan M JeschkeDepartment of Evolutionary and Integrative Ecology, Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB).ORCID https://orcid.org/0000-0003-3328-4217

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of big data and global biodiversity decline, there is a pressing need to transform data and information into findable and actionable knowledge. We propose a conceptual classification scheme for invasion science that goes beyond hypothesis networks and allows to organize publications and data sets, guide research directions, and identify knowledge gaps. Combining expert knowledge with literature analysis, we identified five major research themes in this field: introduction pathways, invasion success and invasibility, impacts of invasion, managing biological invasions, and meta-invasion science. We divided these themes into 10 broader research questions and linked them to 39 major hypotheses forming the theoretical foundation of invasion science. As artificial intelligence advances, such classification schemes will become important references for organizing scientific information. Our approach can be extended to other research fields, fostering cross-disciplinary connections to leverage the scientific knowledge needed to address Anthropocene challenges.

Indexed as

biological invasionshierarchy-of-hypotheses (HoH) approachknowledge mappingmeta-invasion scienceresearch themes

Identifiers

PMID39713560
PMCPMC11660931

What OpenQuestion holds

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LicenceCC BY
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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.