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Managing biological invasions in urban environments with the acceptance sampling approach

Detections of invasive species outbreaks are often followed by the removal of susceptible host organisms in order to slow the spread of the invading pest population. We propose the acceptance sampling approach for detection and optional removal of susceptible host trees to manage an outbreak of the...

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Autores principales: Yemshanov, Denys, Haight, Robert G., Chen, Cuicui, Liu, Ning, MacQuarrie, Christian J. K., Koch, Frank H., Venette, Robert, Ryall, Krista
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6707552/
https://www.ncbi.nlm.nih.gov/pubmed/31442239
http://dx.doi.org/10.1371/journal.pone.0220687
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author Yemshanov, Denys
Haight, Robert G.
Chen, Cuicui
Liu, Ning
MacQuarrie, Christian J. K.
Koch, Frank H.
Venette, Robert
Ryall, Krista
author_facet Yemshanov, Denys
Haight, Robert G.
Chen, Cuicui
Liu, Ning
MacQuarrie, Christian J. K.
Koch, Frank H.
Venette, Robert
Ryall, Krista
author_sort Yemshanov, Denys
collection PubMed
description Detections of invasive species outbreaks are often followed by the removal of susceptible host organisms in order to slow the spread of the invading pest population. We propose the acceptance sampling approach for detection and optional removal of susceptible host trees to manage an outbreak of the emerald ash borer (EAB), a highly destructive forest pest, in Winnipeg, Canada. We compare the strategy with two common delimiting survey techniques that do not consider follow-up management actions such as host removal. Our results show that the management objective influences the survey strategy. The survey-only strategies maximized the capacity to detect new infestations and prioritized sites with high likelihood of being invaded. Comparatively, the surveys with subsequent host removal actions allocated most of the budget to sites where complete host removal would minimize the pest’s ability to spread to uninvaded locations. Uncertainty about the pest’s spread causes the host removal measures to cover a larger area in a uniform spatial pattern and extend to farther distances from already infested sites. If a decision maker is ambiguity-averse and strives to avoid the worst-case damages from the invasion, the optimal strategy is to survey more sites with high host densities and remove trees from sites at farther distances, where EAB arrivals may be uncertain, but could cause significant damage if not detected quickly. Accounting for the uncertainty about spread helps develop a more robust pest management strategy. The approach is generalizable and can support management programs for new pest incursions.
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spelling pubmed-67075522019-09-04 Managing biological invasions in urban environments with the acceptance sampling approach Yemshanov, Denys Haight, Robert G. Chen, Cuicui Liu, Ning MacQuarrie, Christian J. K. Koch, Frank H. Venette, Robert Ryall, Krista PLoS One Research Article Detections of invasive species outbreaks are often followed by the removal of susceptible host organisms in order to slow the spread of the invading pest population. We propose the acceptance sampling approach for detection and optional removal of susceptible host trees to manage an outbreak of the emerald ash borer (EAB), a highly destructive forest pest, in Winnipeg, Canada. We compare the strategy with two common delimiting survey techniques that do not consider follow-up management actions such as host removal. Our results show that the management objective influences the survey strategy. The survey-only strategies maximized the capacity to detect new infestations and prioritized sites with high likelihood of being invaded. Comparatively, the surveys with subsequent host removal actions allocated most of the budget to sites where complete host removal would minimize the pest’s ability to spread to uninvaded locations. Uncertainty about the pest’s spread causes the host removal measures to cover a larger area in a uniform spatial pattern and extend to farther distances from already infested sites. If a decision maker is ambiguity-averse and strives to avoid the worst-case damages from the invasion, the optimal strategy is to survey more sites with high host densities and remove trees from sites at farther distances, where EAB arrivals may be uncertain, but could cause significant damage if not detected quickly. Accounting for the uncertainty about spread helps develop a more robust pest management strategy. The approach is generalizable and can support management programs for new pest incursions. Public Library of Science 2019-08-23 /pmc/articles/PMC6707552/ /pubmed/31442239 http://dx.doi.org/10.1371/journal.pone.0220687 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Yemshanov, Denys
Haight, Robert G.
Chen, Cuicui
Liu, Ning
MacQuarrie, Christian J. K.
Koch, Frank H.
Venette, Robert
Ryall, Krista
Managing biological invasions in urban environments with the acceptance sampling approach
title Managing biological invasions in urban environments with the acceptance sampling approach
title_full Managing biological invasions in urban environments with the acceptance sampling approach
title_fullStr Managing biological invasions in urban environments with the acceptance sampling approach
title_full_unstemmed Managing biological invasions in urban environments with the acceptance sampling approach
title_short Managing biological invasions in urban environments with the acceptance sampling approach
title_sort managing biological invasions in urban environments with the acceptance sampling approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6707552/
https://www.ncbi.nlm.nih.gov/pubmed/31442239
http://dx.doi.org/10.1371/journal.pone.0220687
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