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Author Correction: Declaration of local chemical eradication of the Argentine ant: Bayesian estimation with a multinomial-mixture model
- Source :
- Scientific Reports, Scientific Reports, Vol 8, Iss 1, Pp 1-1 (2018)
- Publication Year :
- 2018
- Publisher :
- Nature Publishing Group UK, 2018.
-
Abstract
- Determining the success of eradication of an invasive species requires a way to decide when its risk of reoccurrence has become acceptably low. In Japan, the area populated by the Argentine ant, Linepithema humile (Mayr), is expanding, and eradication via chemical treatment is ongoing at various locations. One such program in Tokyo was apparently successful, because the ant population decreased to undetectable levels within a short time. However, construction of a population model for management purposes was difficult because the probability of detecting ants decreases rapidly as the population collapses. To predict the time when the ant was eradicated, we developed a multinomial-mixture model for chemical eradication based on monthly trapping data and the history of pesticide applications. We decided when to declare that eradication had been successful by considering both 'eradication' times, which we associated with eradication probabilities of 95% and 99%, and an optimal stopping time based on a 'minimum expected economic cost' that considered the possibility that surveys were stopped too soon. By applying these criteria, we retroactively declared that Argentine ants had been eradicated 38-42 months after the start of treatments (16-17 months after the last sighting).
- Subjects :
- 0106 biological sciences
Insecticides
Computer science
Declaration
lcsh:Medicine
010603 evolutionary biology
01 natural sciences
Insect Control
Argentine ant
Econometrics
Animals
lcsh:Science
Author Correction
Bayes estimator
Multidisciplinary
Models, Statistical
biology
Ants
lcsh:R
Bayes Theorem
biology.organism_classification
Mixture model
010602 entomology
ComputingMethodologies_DOCUMENTANDTEXTPROCESSING
lcsh:Q
Multinomial distribution
Introduced Species
Entomology
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....d966160e2cfa0aa869cd6bb35a9e5b90