Evidence map›Paper›PMID 25388652›Full record

ArticleScientific reports2014

A computer model of insect traps in a landscape.

Nicholas C Manoukis, Brian Hall, Scott M Geib

Abstract read
In one paragraph

Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Mass TrappingInsects · 2022
    Article
  11. Article
  12. MarkingInsects · 2020
    Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. 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

3 authors.

Nicholas C ManoukisDaniel K. Inouye US Pacific Basin Agricultural Research Center (PBARC), United States Department of Agriculture, Agricultural Research Service, Hilo, Hawaii, USA.
Brian Hall1] Daniel K. Inouye US Pacific Basin Agricultural Research Center (PBARC), United States Department of Agriculture, Agricultural Research Service, Hilo, Hawaii, USA [2] College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa, Hawaii USA.
Scott M GeibDaniel K. Inouye US Pacific Basin Agricultural Research Center (PBARC), United States Department of Agriculture, Agricultural Research Service, Hilo, Hawaii, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Attractant-based trap networks are important elements of invasive insect detection, pest control, and basic research programs. We present a landscape-level, spatially explicit model of trap networks, focused on detection, that incorporates variable attractiveness of traps and a movement model for insect dispersion. We describe the model and validate its behavior using field trap data on networks targeting two species, Ceratitis capitata and Anoplophora glabripennis. Our model will assist efforts to optimize trap networks by 1) introducing an accessible and realistic mathematical characterization of the operation of a single trap that lends itself easily to parametrization via field experiments and 2) allowing direct quantification and comparison of sensitivity between trap networks. Results from the two case studies indicate that the relationship between number of traps and their spatial distribution and capture probability under the model is qualitatively dependent on the attractiveness of the traps, a result with important practical consequences.

Indexed as

Models, StatisticalAnimal DistributionAnimalsCaliforniaCeratopogonidaeColeopteraComputer SimulationFemaleInsect ControlMalePheromonesPopulation DynamicsPheromones

Identifiers

PMID25388652
PMCPMC4228344

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.