Evidence map›Paper›PMID 37963154›Full record

ArticlePloS one2023

Predicting the spatio-temporal distribution of the invasive alien plant Andropogon virginicus, in the South Korean peninsula considering long-distance dispersal capacities.

Jeong-Soo Park, Hyohyemi Lee

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Antibacterial and Antibiofilm Activities of Bluestem (International journal of microbiology · 2026
    Article
  2. 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.

Jeong-Soo ParkDivision of Climate Change Research, National Institute of Ecology, Seocheon, Korea.ORCID 0000-0001-7311-287X
Hyohyemi LeeDivision of Climate Change Research, National Institute of Ecology, Seocheon, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The spread of invasive alien species is a major threat to biodiversity. Estimating the long-distance dispersal capacity of invasive alien plants is vital for understanding their population dynamics and community composition. We predicted the spatial-temporal distribution of the alien plant Andropogon virginicus, in the Korean peninsula under climate change scenario using Random Forest (RF) and Cellular Automaton (CA) methods. Land use, barriers to dispersal, long-distance dispersal frequency, and maximum long-distance dispersal range were considered in our analysis. Our results showed that, among the five selected environmental variables, annual mean temperature and Human Foot-Printing (HFP) were positively associated with the occurrence probability of A. virginicus. This suggests that A. virginicus is likely to spread to the disturbed northern part of the Korean Peninsula due to climate change and habitat preference. When comparing modeling results for dispersal to field survey data, the modeling raster sets drawn from the long-distance dispersal frequency of 0.05 and maximum long-distance dispersal distance of 30 km y-1 had the most similar spatial expansion among the six long-distance dispersal parameter sets. The dispersal directions were associated with the landscape. Specifically, seeds dispersed by wind (anemochorous seeds) could propagate into open landscapes more easily than in forests. Regarding A. virginicus management, this grass can quickly invade bare ground with their wind-dispersed seeds, therefore habitat destruction, such as excessive logging and weeding, should be restrained.

Indexed as

AndropogonEcosystemHumansIntroduced SpeciesPlantsRepublic of KoreaSeeds

Identifiers

PMID37963154
PMCPMC10645320

What OpenQuestion holds

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LicenceCC BY
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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.