The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion

Autores
Vogler, Roberto Eugenio; Beltramino, Ariel Aníbal; Sede, Mariano Miguel; Gutiérrez Gregoric, Diego Eduardo; Núñez, María Verónica; Rumi Macchi Zubiaurre, Alejandra
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The best way to reduce problems related to invasive species is by preventing introductions into potentially susceptible areas. The purpose of this study was to create distribution models for the invasive gastropod Achatina fulica Bowdich, 1822 in South America in order to evaluate its potential geographic distribution and identify areas at potential risk. This mollusc, considered one of the 100 world's worst invasive alien species, is the focus of intense concern due to its impact on agriculture, human health, and native fauna. We tested two commonly used ecological niche modeling methods: Genetic Algorithm for Rule-Set Prediction (GARP) and Maximum Entropy (MaxEnt). Models were run with occurrence points obtained from several sources, including the scientific literature, international databases, governmental reports and newspapers, WorldClim bioclimatic variables, and altitude. Models were evaluated with the threshold-independent Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC). Both models had consistent performances with similar areas predicted as susceptible, including areas already affected and new potentially susceptible areas in both tropical and temperate regions of South America.
Facultad de Ciencias Naturales y Museo
Materia
Ciencias Naturales
Land mollusc
Bioinvasion
Distribution
Garp
Maxent
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/102616

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network_name_str SEDICI (UNLP)
spelling The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasionVogler, Roberto EugenioBeltramino, Ariel AníbalSede, Mariano MiguelGutiérrez Gregoric, Diego EduardoNúñez, María VerónicaRumi Macchi Zubiaurre, AlejandraCiencias NaturalesLand molluscBioinvasionDistributionGarpMaxentThe best way to reduce problems related to invasive species is by preventing introductions into potentially susceptible areas. The purpose of this study was to create distribution models for the invasive gastropod Achatina fulica Bowdich, 1822 in South America in order to evaluate its potential geographic distribution and identify areas at potential risk. This mollusc, considered one of the 100 world's worst invasive alien species, is the focus of intense concern due to its impact on agriculture, human health, and native fauna. We tested two commonly used ecological niche modeling methods: Genetic Algorithm for Rule-Set Prediction (GARP) and Maximum Entropy (MaxEnt). Models were run with occurrence points obtained from several sources, including the scientific literature, international databases, governmental reports and newspapers, WorldClim bioclimatic variables, and altitude. Models were evaluated with the threshold-independent Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC). Both models had consistent performances with similar areas predicted as susceptible, including areas already affected and new potentially susceptible areas in both tropical and temperate regions of South America.Facultad de Ciencias Naturales y Museo2013-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf39-50http://sedici.unlp.edu.ar/handle/10915/102616enginfo:eu-repo/semantics/altIdentifier/url/https://ri.conicet.gov.ar/11336/16743info:eu-repo/semantics/altIdentifier/issn/0740-2783info:eu-repo/semantics/altIdentifier/doi/10.4003/006.031.0115info:eu-repo/semantics/altIdentifier/hdl/11336/16743info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T10:03:40Zoai:sedici.unlp.edu.ar:10915/102616Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 10:03:40.966SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion
title The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion
spellingShingle The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion
Vogler, Roberto Eugenio
Ciencias Naturales
Land mollusc
Bioinvasion
Distribution
Garp
Maxent
title_short The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion
title_full The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion
title_fullStr The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion
title_full_unstemmed The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion
title_sort The giant African snail, <i>Achatina fulica</i> (Gastropoda: Achatinidae): Using bioclimatic models to identify South American areas susceptible to invasion
dc.creator.none.fl_str_mv Vogler, Roberto Eugenio
Beltramino, Ariel Aníbal
Sede, Mariano Miguel
Gutiérrez Gregoric, Diego Eduardo
Núñez, María Verónica
Rumi Macchi Zubiaurre, Alejandra
author Vogler, Roberto Eugenio
author_facet Vogler, Roberto Eugenio
Beltramino, Ariel Aníbal
Sede, Mariano Miguel
Gutiérrez Gregoric, Diego Eduardo
Núñez, María Verónica
Rumi Macchi Zubiaurre, Alejandra
author_role author
author2 Beltramino, Ariel Aníbal
Sede, Mariano Miguel
Gutiérrez Gregoric, Diego Eduardo
Núñez, María Verónica
Rumi Macchi Zubiaurre, Alejandra
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Naturales
Land mollusc
Bioinvasion
Distribution
Garp
Maxent
topic Ciencias Naturales
Land mollusc
Bioinvasion
Distribution
Garp
Maxent
dc.description.none.fl_txt_mv The best way to reduce problems related to invasive species is by preventing introductions into potentially susceptible areas. The purpose of this study was to create distribution models for the invasive gastropod Achatina fulica Bowdich, 1822 in South America in order to evaluate its potential geographic distribution and identify areas at potential risk. This mollusc, considered one of the 100 world's worst invasive alien species, is the focus of intense concern due to its impact on agriculture, human health, and native fauna. We tested two commonly used ecological niche modeling methods: Genetic Algorithm for Rule-Set Prediction (GARP) and Maximum Entropy (MaxEnt). Models were run with occurrence points obtained from several sources, including the scientific literature, international databases, governmental reports and newspapers, WorldClim bioclimatic variables, and altitude. Models were evaluated with the threshold-independent Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC). Both models had consistent performances with similar areas predicted as susceptible, including areas already affected and new potentially susceptible areas in both tropical and temperate regions of South America.
Facultad de Ciencias Naturales y Museo
description The best way to reduce problems related to invasive species is by preventing introductions into potentially susceptible areas. The purpose of this study was to create distribution models for the invasive gastropod Achatina fulica Bowdich, 1822 in South America in order to evaluate its potential geographic distribution and identify areas at potential risk. This mollusc, considered one of the 100 world's worst invasive alien species, is the focus of intense concern due to its impact on agriculture, human health, and native fauna. We tested two commonly used ecological niche modeling methods: Genetic Algorithm for Rule-Set Prediction (GARP) and Maximum Entropy (MaxEnt). Models were run with occurrence points obtained from several sources, including the scientific literature, international databases, governmental reports and newspapers, WorldClim bioclimatic variables, and altitude. Models were evaluated with the threshold-independent Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC). Both models had consistent performances with similar areas predicted as susceptible, including areas already affected and new potentially susceptible areas in both tropical and temperate regions of South America.
publishDate 2013
dc.date.none.fl_str_mv 2013-02
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info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/102616
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dc.language.none.fl_str_mv eng
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info:eu-repo/semantics/altIdentifier/issn/0740-2783
info:eu-repo/semantics/altIdentifier/doi/10.4003/006.031.0115
info:eu-repo/semantics/altIdentifier/hdl/11336/16743
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
39-50
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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