Loading…
Declaration of local chemical eradication of the Argentine ant: Bayesian estimation with a multinomial-mixture model
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 loc...
Saved in:
Published in: | Scientific reports 2017-06, Vol.7 (1), p.3389-8, Article 3389 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c540t-19f07ded21d18ac7eb05b25812df01c6251581b3b485ceeafd7f68f103fd0f0a3 |
---|---|
cites | cdi_FETCH-LOGICAL-c540t-19f07ded21d18ac7eb05b25812df01c6251581b3b485ceeafd7f68f103fd0f0a3 |
container_end_page | 8 |
container_issue | 1 |
container_start_page | 3389 |
container_title | Scientific reports |
container_volume | 7 |
creator | Sakamoto, Yoshiko Kumagai, Naoki H. Goka, Koichi |
description | 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). |
doi_str_mv | 10.1038/s41598-017-03516-z |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_efbc163e8e9142a6a1581829232c24b5</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_efbc163e8e9142a6a1581829232c24b5</doaj_id><sourcerecordid>1909748206</sourcerecordid><originalsourceid>FETCH-LOGICAL-c540t-19f07ded21d18ac7eb05b25812df01c6251581b3b485ceeafd7f68f103fd0f0a3</originalsourceid><addsrcrecordid>eNp1kk9vFSEUxSdGY5vaL-DCTOLGzSgwMMO4MKn1X5MmbnRN7sDlPV6YoQJTbT-9vE7btCay4cL9cYCTU1UvKXlLSSvfJU7FIBtC-4a0gnbN9ZPqkBEuGtYy9vRBfVAdp7QjZQg2cDo8rw6Y7CjlnBxW-RNqDxGyC3MdbO2DBl_rLU5uX2AEU4q7bt5ifRI3OGc3Yw1zfl9_hCtMDuYaU3bTSv52eVtDPS2-cGFy4JvJ_clLxHoKBv2L6pkFn_D4dj6qfn75_OP0W3P-_evZ6cl5owUnuaGDJb1Bw6ihEnSPIxEjE5IyYwnVHRO0LMZ25FJoRLCmt520xR5riCXQHlVnq64JsFMXsbwvXqkATt1shLhRELPTHhXaUdOuRYkD5Qw62EtLNhQDNeOjKFofVq2LZZzQ6OJBBP9I9HFndlu1CZdK8G7o5V7gza1ADL-W4paaXNLoPcwYlqToQIaeS0a6gr7-B92FJc7FqkIJ0XHOelootlI6hpQi2vvHUKL2GVFrRlTJiLrJiLouh149_Mb9kbtEFKBdgVRa8wbjg7v_L_sXcGvJYw</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1955644271</pqid></control><display><type>article</type><title>Declaration of local chemical eradication of the Argentine ant: Bayesian estimation with a multinomial-mixture model</title><source>Open Access: PubMed Central</source><source>Publicly Available Content (ProQuest)</source><source>Free Full-Text Journals in Chemistry</source><source>Springer Nature - nature.com Journals - Fully Open Access</source><creator>Sakamoto, Yoshiko ; Kumagai, Naoki H. ; Goka, Koichi</creator><creatorcontrib>Sakamoto, Yoshiko ; Kumagai, Naoki H. ; Goka, Koichi</creatorcontrib><description>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).</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-017-03516-z</identifier><identifier>PMID: 28611440</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/158/1144 ; 631/158/2178 ; Animals ; Ants - drug effects ; Ants - growth & development ; Bayes Theorem ; Bayesian analysis ; Chemical treatment ; Entomology - methods ; Environmental impact ; Geographical variations ; Humanities and Social Sciences ; Insect Control - methods ; Insecticides - toxicity ; Introduced species ; Introduced Species - statistics & numerical data ; Invasive insects ; Invasive species ; Models, Statistical ; multidisciplinary ; Nonnative species ; Pesticide application ; Pesticides ; Population ; Probability ; Science ; Science (multidisciplinary)</subject><ispartof>Scientific reports, 2017-06, Vol.7 (1), p.3389-8, Article 3389</ispartof><rights>The Author(s) 2017</rights><rights>Copyright Nature Publishing Group Jun 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c540t-19f07ded21d18ac7eb05b25812df01c6251581b3b485ceeafd7f68f103fd0f0a3</citedby><cites>FETCH-LOGICAL-c540t-19f07ded21d18ac7eb05b25812df01c6251581b3b485ceeafd7f68f103fd0f0a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1955644271/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1955644271?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28611440$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sakamoto, Yoshiko</creatorcontrib><creatorcontrib>Kumagai, Naoki H.</creatorcontrib><creatorcontrib>Goka, Koichi</creatorcontrib><title>Declaration of local chemical eradication of the Argentine ant: Bayesian estimation with a multinomial-mixture model</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>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).</description><subject>631/158/1144</subject><subject>631/158/2178</subject><subject>Animals</subject><subject>Ants - drug effects</subject><subject>Ants - growth & development</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Chemical treatment</subject><subject>Entomology - methods</subject><subject>Environmental impact</subject><subject>Geographical variations</subject><subject>Humanities and Social Sciences</subject><subject>Insect Control - methods</subject><subject>Insecticides - toxicity</subject><subject>Introduced species</subject><subject>Introduced Species - statistics & numerical data</subject><subject>Invasive insects</subject><subject>Invasive species</subject><subject>Models, Statistical</subject><subject>multidisciplinary</subject><subject>Nonnative species</subject><subject>Pesticide application</subject><subject>Pesticides</subject><subject>Population</subject><subject>Probability</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp1kk9vFSEUxSdGY5vaL-DCTOLGzSgwMMO4MKn1X5MmbnRN7sDlPV6YoQJTbT-9vE7btCay4cL9cYCTU1UvKXlLSSvfJU7FIBtC-4a0gnbN9ZPqkBEuGtYy9vRBfVAdp7QjZQg2cDo8rw6Y7CjlnBxW-RNqDxGyC3MdbO2DBl_rLU5uX2AEU4q7bt5ifRI3OGc3Yw1zfl9_hCtMDuYaU3bTSv52eVtDPS2-cGFy4JvJ_clLxHoKBv2L6pkFn_D4dj6qfn75_OP0W3P-_evZ6cl5owUnuaGDJb1Bw6ihEnSPIxEjE5IyYwnVHRO0LMZ25FJoRLCmt520xR5riCXQHlVnq64JsFMXsbwvXqkATt1shLhRELPTHhXaUdOuRYkD5Qw62EtLNhQDNeOjKFofVq2LZZzQ6OJBBP9I9HFndlu1CZdK8G7o5V7gza1ADL-W4paaXNLoPcwYlqToQIaeS0a6gr7-B92FJc7FqkIJ0XHOelootlI6hpQi2vvHUKL2GVFrRlTJiLrJiLouh149_Mb9kbtEFKBdgVRa8wbjg7v_L_sXcGvJYw</recordid><startdate>20170613</startdate><enddate>20170613</enddate><creator>Sakamoto, Yoshiko</creator><creator>Kumagai, Naoki H.</creator><creator>Goka, Koichi</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><general>Nature Portfolio</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M7P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20170613</creationdate><title>Declaration of local chemical eradication of the Argentine ant: Bayesian estimation with a multinomial-mixture model</title><author>Sakamoto, Yoshiko ; Kumagai, Naoki H. ; Goka, Koichi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c540t-19f07ded21d18ac7eb05b25812df01c6251581b3b485ceeafd7f68f103fd0f0a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>631/158/1144</topic><topic>631/158/2178</topic><topic>Animals</topic><topic>Ants - drug effects</topic><topic>Ants - growth & development</topic><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Chemical treatment</topic><topic>Entomology - methods</topic><topic>Environmental impact</topic><topic>Geographical variations</topic><topic>Humanities and Social Sciences</topic><topic>Insect Control - methods</topic><topic>Insecticides - toxicity</topic><topic>Introduced species</topic><topic>Introduced Species - statistics & numerical data</topic><topic>Invasive insects</topic><topic>Invasive species</topic><topic>Models, Statistical</topic><topic>multidisciplinary</topic><topic>Nonnative species</topic><topic>Pesticide application</topic><topic>Pesticides</topic><topic>Population</topic><topic>Probability</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sakamoto, Yoshiko</creatorcontrib><creatorcontrib>Kumagai, Naoki H.</creatorcontrib><creatorcontrib>Goka, Koichi</creatorcontrib><collection>Springer_OA刊</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Science Database</collection><collection>ProQuest Biological Science Journals</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sakamoto, Yoshiko</au><au>Kumagai, Naoki H.</au><au>Goka, Koichi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Declaration of local chemical eradication of the Argentine ant: Bayesian estimation with a multinomial-mixture model</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2017-06-13</date><risdate>2017</risdate><volume>7</volume><issue>1</issue><spage>3389</spage><epage>8</epage><pages>3389-8</pages><artnum>3389</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><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).</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>28611440</pmid><doi>10.1038/s41598-017-03516-z</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2045-2322 |
ispartof | Scientific reports, 2017-06, Vol.7 (1), p.3389-8, Article 3389 |
issn | 2045-2322 2045-2322 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_efbc163e8e9142a6a1581829232c24b5 |
source | Open Access: PubMed Central; Publicly Available Content (ProQuest); Free Full-Text Journals in Chemistry; Springer Nature - nature.com Journals - Fully Open Access |
subjects | 631/158/1144 631/158/2178 Animals Ants - drug effects Ants - growth & development Bayes Theorem Bayesian analysis Chemical treatment Entomology - methods Environmental impact Geographical variations Humanities and Social Sciences Insect Control - methods Insecticides - toxicity Introduced species Introduced Species - statistics & numerical data Invasive insects Invasive species Models, Statistical multidisciplinary Nonnative species Pesticide application Pesticides Population Probability Science Science (multidisciplinary) |
title | Declaration of local chemical eradication of the Argentine ant: Bayesian estimation with a multinomial-mixture model |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T04%3A39%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Declaration%20of%20local%20chemical%20eradication%20of%20the%20Argentine%20ant:%20Bayesian%20estimation%20with%20a%20multinomial-mixture%20model&rft.jtitle=Scientific%20reports&rft.au=Sakamoto,%20Yoshiko&rft.date=2017-06-13&rft.volume=7&rft.issue=1&rft.spage=3389&rft.epage=8&rft.pages=3389-8&rft.artnum=3389&rft.issn=2045-2322&rft.eissn=2045-2322&rft_id=info:doi/10.1038/s41598-017-03516-z&rft_dat=%3Cproquest_doaj_%3E1909748206%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c540t-19f07ded21d18ac7eb05b25812df01c6251581b3b485ceeafd7f68f103fd0f0a3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1955644271&rft_id=info:pmid/28611440&rfr_iscdi=true |