Evidence map›Paper›PMID 34178098›Full record

ReviewEvolutionary applications2021

The evolutionary dynamics of biological invasions: A multi-approach perspective.

Stéphanie Sherpa, Laurence Després

Abstract readReview
In one paragraph

Review in Evolutionary applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Article
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  4. Review
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  10. Local adaptation to climate facilitates a global invasion.bioRxiv : the preprint server for biology · 2025
    Article
  11. Article
  12. Article
  13. Spatially VaryingEvolutionary applications · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
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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.

Stéphanie SherpaCNRS LECA Université Grenoble Alpes Université Savoie Mont Blanc Grenoble France.ORCID https://orcid.org/0000-0001-9958-0073
Laurence DesprésCNRS LECA Université Grenoble Alpes Université Savoie Mont Blanc Grenoble France.ORCID https://orcid.org/0000-0002-0660-6260

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological invasions, the establishment and spread of non-native species in new regions, can have extensive economic and environmental consequences. Increased global connectivity accelerates introduction rates, while climate and land-cover changes may decrease the barriers to invasive populations spread. A detailed knowledge of the invasion history, including assessing source populations, routes of spread, number of independent introductions, and the effects of genetic bottlenecks and admixture on the establishment success, adaptive potential, and further spread, is crucial from an applied perspective to mitigate socioeconomic impacts of invasive species, as well as for addressing fundamental questions on the evolutionary dynamics of the invasion process. Recent advances in genomics together with the development of geographic information systems provide unprecedented large genetic and environmental datasets at global and local scales to link population genomics, landscape ecology, and species distribution modeling into a common framework to study the invasion process. Although the factors underlying population invasiveness have been extensively reviewed, analytical methods currently available to optimally combine molecular and environmental data for inferring invasive population demographic parameters and predicting further spreading are still under development. In this review, we focus on the few recent insect invasion studies that combine different datasets and approaches to show how integrating genetic, observational, ecological, and environmental data pave the way to a more integrative biological invasion science. We provide guidelines to study the evolutionary dynamics of invasions at each step of the invasion process, and conclude on the benefits of including all types of information and up-to-date analytical tools from different research areas into a single framework.

Indexed as

biological invasiondemo‐genomicsdispersalgenetic diversityinsectintegrative approachlocal adaptationoccurrence time seriesspecies distribution modeling

Identifiers

PMID34178098
PMCPMC8210789

What OpenQuestion holds

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Registered trials

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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.