Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model

Autores
Piacenza, Maria Florencia; Gomez, Maria Daniela; Simone, Ivana; Lamfri, M.; Scavuzzo, Carlos Marcelo; Calderón, G. E.; Polop, J. J.
Año de publicación
2011
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We evaluate several management options for Calomys musculinus populations through the formulation and validation of a cohort structured model. Initially, a basic model was constructed and validated using field population data. Next, the model was altered to allow us to evaluate different management options. In general, basic model results were in agreement with field data, demonstrating that this model would be useful in describing aspects of corn mouse population dynamics. Restricting control measures to when mouse numbers reach high levels would be inadequate, because population numbers tend to increase in size after some years. In contrast, reducing vegetation cover in spring was more effective in reducing field population abundances. Despite some limitations, the model could be useful for evaluating the relationships between population dynamics and some biotic or physical environmental variables, and thus ensure more efficient use of resources in integrated pest management.
Fil: Piacenza, Maria Florencia. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Gomez, Maria Daniela. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Simone, Ivana. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Lamfri, M.. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Fil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Fil: Calderón, G. E.. Dirección Nacional de Instituto de Investigación.Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán"; Argentina
Fil: Polop, J. J.. Universidad Nacional de Río Cuarto; Argentina
Materia
ARGENTINE HEMORRHAGIC FEVER
CALOMYS MUSCULINUS
INTEGRATED PEST MANAGEMENT
REMOTE SENSING
RESOURCE MANAGEMENT
RODENT ECOLOGY
RODENT RESERVOIRS
STRUCTURED MODELS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/195167
Acceder
id CONICETDig_bed138e3b5c304d55876abc321281fa6
oai_identifier_str oai:ri.conicet.gov.ar:11336/195167
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured modelPiacenza, Maria FlorenciaGomez, Maria DanielaSimone, IvanaLamfri, M.Scavuzzo, Carlos MarceloCalderón, G. E.Polop, J. J.ARGENTINE HEMORRHAGIC FEVERCALOMYS MUSCULINUSINTEGRATED PEST MANAGEMENTREMOTE SENSINGRESOURCE MANAGEMENTRODENT ECOLOGYRODENT RESERVOIRSSTRUCTURED MODELShttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1We evaluate several management options for Calomys musculinus populations through the formulation and validation of a cohort structured model. Initially, a basic model was constructed and validated using field population data. Next, the model was altered to allow us to evaluate different management options. In general, basic model results were in agreement with field data, demonstrating that this model would be useful in describing aspects of corn mouse population dynamics. Restricting control measures to when mouse numbers reach high levels would be inadequate, because population numbers tend to increase in size after some years. In contrast, reducing vegetation cover in spring was more effective in reducing field population abundances. Despite some limitations, the model could be useful for evaluating the relationships between population dynamics and some biotic or physical environmental variables, and thus ensure more efficient use of resources in integrated pest management.Fil: Piacenza, Maria Florencia. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Gomez, Maria Daniela. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Simone, Ivana. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Lamfri, M.. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; ArgentinaFil: Calderón, G. E.. Dirección Nacional de Instituto de Investigación.Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán"; ArgentinaFil: Polop, J. J.. Universidad Nacional de Río Cuarto; ArgentinaTaylor & Francis Ltd2011-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/195167Piacenza, Maria Florencia; Gomez, Maria Daniela; Simone, Ivana; Lamfri, M.; Scavuzzo, Carlos Marcelo; et al.; Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model; Taylor & Francis Ltd; International Journal of Pest Management; 57; 4; 12-2011; 255-2650967-0874CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1080/09670874.2011.590240info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:42:09Zoai:ri.conicet.gov.ar:11336/195167instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:42:09.814CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model
title Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model
spellingShingle Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model
Piacenza, Maria Florencia
ARGENTINE HEMORRHAGIC FEVER
CALOMYS MUSCULINUS
INTEGRATED PEST MANAGEMENT
REMOTE SENSING
RESOURCE MANAGEMENT
RODENT ECOLOGY
RODENT RESERVOIRS
STRUCTURED MODELS
title_short Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model
title_full Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model
title_fullStr Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model
title_full_unstemmed Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model
title_sort Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model
dc.creator.none.fl_str_mv Piacenza, Maria Florencia
Gomez, Maria Daniela
Simone, Ivana
Lamfri, M.
Scavuzzo, Carlos Marcelo
Calderón, G. E.
Polop, J. J.
author Piacenza, Maria Florencia
author_facet Piacenza, Maria Florencia
Gomez, Maria Daniela
Simone, Ivana
Lamfri, M.
Scavuzzo, Carlos Marcelo
Calderón, G. E.
Polop, J. J.
author_role author
author2 Gomez, Maria Daniela
Simone, Ivana
Lamfri, M.
Scavuzzo, Carlos Marcelo
Calderón, G. E.
Polop, J. J.
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv ARGENTINE HEMORRHAGIC FEVER
CALOMYS MUSCULINUS
INTEGRATED PEST MANAGEMENT
REMOTE SENSING
RESOURCE MANAGEMENT
RODENT ECOLOGY
RODENT RESERVOIRS
STRUCTURED MODELS
topic ARGENTINE HEMORRHAGIC FEVER
CALOMYS MUSCULINUS
INTEGRATED PEST MANAGEMENT
REMOTE SENSING
RESOURCE MANAGEMENT
RODENT ECOLOGY
RODENT RESERVOIRS
STRUCTURED MODELS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We evaluate several management options for Calomys musculinus populations through the formulation and validation of a cohort structured model. Initially, a basic model was constructed and validated using field population data. Next, the model was altered to allow us to evaluate different management options. In general, basic model results were in agreement with field data, demonstrating that this model would be useful in describing aspects of corn mouse population dynamics. Restricting control measures to when mouse numbers reach high levels would be inadequate, because population numbers tend to increase in size after some years. In contrast, reducing vegetation cover in spring was more effective in reducing field population abundances. Despite some limitations, the model could be useful for evaluating the relationships between population dynamics and some biotic or physical environmental variables, and thus ensure more efficient use of resources in integrated pest management.
Fil: Piacenza, Maria Florencia. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Gomez, Maria Daniela. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Simone, Ivana. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Lamfri, M.. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Fil: Scavuzzo, Carlos Marcelo. Comision Nacional de Actividades Espaciales. Instituto de Altos Estudios Espaciales "Mario Gulich"; Argentina
Fil: Calderón, G. E.. Dirección Nacional de Instituto de Investigación.Administración Nacional de Laboratorios e Institutos de Salud "Dr. Carlos G. Malbrán"; Argentina
Fil: Polop, J. J.. Universidad Nacional de Río Cuarto; Argentina
description We evaluate several management options for Calomys musculinus populations through the formulation and validation of a cohort structured model. Initially, a basic model was constructed and validated using field population data. Next, the model was altered to allow us to evaluate different management options. In general, basic model results were in agreement with field data, demonstrating that this model would be useful in describing aspects of corn mouse population dynamics. Restricting control measures to when mouse numbers reach high levels would be inadequate, because population numbers tend to increase in size after some years. In contrast, reducing vegetation cover in spring was more effective in reducing field population abundances. Despite some limitations, the model could be useful for evaluating the relationships between population dynamics and some biotic or physical environmental variables, and thus ensure more efficient use of resources in integrated pest management.
publishDate 2011
dc.date.none.fl_str_mv 2011-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/195167
Piacenza, Maria Florencia; Gomez, Maria Daniela; Simone, Ivana; Lamfri, M.; Scavuzzo, Carlos Marcelo; et al.; Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model; Taylor & Francis Ltd; International Journal of Pest Management; 57; 4; 12-2011; 255-265
0967-0874
CONICET Digital
CONICET
url http://hdl.handle.net/11336/195167
identifier_str_mv Piacenza, Maria Florencia; Gomez, Maria Daniela; Simone, Ivana; Lamfri, M.; Scavuzzo, Carlos Marcelo; et al.; Providing management options to control corn mouse (Calomys musculinus) reservoir populations using a cohort structured model; Taylor & Francis Ltd; International Journal of Pest Management; 57; 4; 12-2011; 255-265
0967-0874
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1080/09670874.2011.590240
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis Ltd
publisher.none.fl_str_mv Taylor & Francis Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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