Evidence map›Paper›PMID 36797315›Full record

ArticleScientific reports2023

Info-gap theory to determine cost-effective eradication of invasive species.

Yang Liu, Melissa L Thomas, Grey T Coupland, Penghao Wang, Dan Zheng, Simon J McKirdy

Abstract read
In one paragraph

Article in Scientific reports, 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

6 authors.

Yang LiuHarry Butler Institute, Murdoch University, Perth, WA, 6150, Australia. Y.Liu@murdoch.edu.au.
Melissa L ThomasHarry Butler Institute, Murdoch University, Perth, WA, 6150, Australia.
Grey T CouplandHarry Butler Institute, Murdoch University, Perth, WA, 6150, Australia.
Penghao WangHarry Butler Institute, Murdoch University, Perth, WA, 6150, Australia.
Dan ZhengQingdao Agricultural University, Shandong, 266109, People's Republic of China.
Simon J McKirdyHarry Butler Institute, Murdoch University, Perth, WA, 6150, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasive species eradication campaigns often fail due to stochastic arrival events, unpredictable detectability and incorrect resource allocation. Severe uncertainty in model parameter estimates may skew the eradication policy results. Using info-gap decision theory, this research aims to provide managers with a method to quantify their confidence in realizing successful eradication of particular invasive species within their specified eradication budgets (i.e. allowed eradication cost) in face of information-gaps. The potential introduction of the Asian house gecko Hemidactylus frenatus to Barrow Island, Australia is used as a case study to illustrate the model. Results of this research demonstrate that, more robustness to uncertainty in the model parameters can be earnt by (1) increasing the allowed eradication cost (2) investment in pre-border quarantine and border inspection (i.e. prevention) or (3) investment in post-border detection surveillance. The combination of a post-border spatial dispersal model and info-gap decision theory demonstrates a novel and spatially efficient method for managers to evaluate the robustness of eradication policies for incursion of invasive species with unexpected behaviour. These methods can be used to provide insight into the success of management goals, in particular the eradication of invasive species on islands or in broader mainland areas. These insights will assist in avoiding eradication failure and wasteful budget allocation and labour investment.

Indexed as

Introduced SpeciesLizardsAnimalsAustraliaCost-Benefit AnalysisPolicyUncertainty

Identifiers

PMID36797315
PMCPMC9935532

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.