Evidence map›Paper›PMID 37312603›Full record

ArticleJournal of economic entomology2023

Simulation to investigate site-based monitoring of pest insect species for trade.

Rieks D van Klinken, Daniel W Gladish, Nicholas C Manoukis, Peter Caley, Matthew P Hill

Open access · hybridAbstract read
In one paragraph

Article in Journal of economic entomology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

5 authors at 3 institutions in 2 countries.

Rieks D van KlinkenCSIRO Health and Biosecurity, GPO Box 2583, Brisbane, QLD 4001, Australia.ORCID 0000-0002-7578-8977
Daniel W GladishCSIRO Data61, GPO Box 2583, Brisbane, QLD 4001, Australia.ORCID 0000-0001-6297-890X
Nicholas C ManoukisTropical Crop and Commodity Protection Research Unit, Daniel K. Inouye U.S. Pacific Basin Agricultural Research Centre, Hilo, HI, USA.ORCID 0000-0001-5062-7256
Peter CaleyCSIRO Data61, GPO Box 1700 Canberra, ACT 2601, Australia.
Matthew P HillCSIRO Health and Biosecurity, GPO Box 1700, Black Mountain, ACT 2601, Australia.ORCID 0000-0002-7762-5258
Commonwealth Scientific and Industrial Research Organisation · AUCSIRO Health and Biosecurity · AUDaniel K. Inouye U.S. Pacific Basin Agricultural Research Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pest insect surveillance using lures is widely used to support market access requirements for traded articles that are hosts or carriers of quarantine pests. Modeling has been used extensively to guide the design of surveillance to support pest free area claims but is less commonly applied to provide confidence in pest freedom or low pest prevalence within sites registered for trade. Site-based surveillance typically needs to detect pests that are already present in the site or that may be entering the site from surrounding areas. We assessed the ability of site-based surveillance strategies to detect pests originating from within or outside the registered site using a probabilistic trapping network simulation model with random-walk insect movement and biologically realistic parameters. For a given release size, time-dependent detection probability was primarily determined by trap density and lure attractiveness, whereas mean step size (daily dispersal) had limited effect. Results were robust to site shape and size. For pests already within the site, detection was most sensitive using regularly spaced traps. Perimeter traps performed best for detecting pests moving into the site, although the importance of trap arrangement decreased with time from release, and random trap placement performed relatively well compared to regularly spaced traps. High detection probabilities were achievable within 7 days using realistic values for lure attractiveness and trap density. These findings, together with the modeling approach, can guide the development of internationally agreed principles for designing site-based surveillance of lure-attractant pests that is calibrated against the risk of non-detection.

Indexed as

Insect ControlMothsAnimalsModels, StatisticalPheromonesPheromonesmarket accessquarantine pestsurvey and detectiontrapping

Identifiers

PMID37312603
PMCPMC10413999
OpenAlexW4380576274

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.