Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
- Autores
- Ceccarelli, Soledad; Balsalobre, Agustin; Susevich, Maria Laura; Echeverria, Maria Gabriela; Gorla, David Eladio; Marti, Gerardo Anibal
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Background: Triatoma virus (TrV) is the only entomopathogenous virus identified in triatomines. We estimated the potential geographic distribution of triatomine species naturally infected by TrV, using remotely sensed and meteorological environmental variables, to predict new potential areas where triatomines infected with TrV may be found. Methods: Detection of TrV infection in samples was performed with RT-PCR. Ecological niche models (ENM) were constructed using the MaxEnt software. We used 42 environmental variables derived from remotely sensed imagery (AVHRR) and 19 bioclimatic variables (Bioclim). The MaxEnt Jackknife procedure was used to minimize the number of environmental variables that showed an influence on final models. The goodness of fit of the model predictions was evaluated by the mean area under the curve (AUC). Results: We obtained 37 samples of 7 species of triatomines naturally infected with TrV. Of the TrV positive samples, 32% were from sylvatic habitat, 46% came from peridomicile habitats and 22% from domicile habitats. Five of the seven infected species were found only in the sylvatic habitat, one species only in the domicile and only Triatoma infestans was found in the three habitats. The MaxEnt model estimated with the Bioclim dataset identified five environmental variables as best predictors: temperature annual range, mean diurnal range, mean temperature of coldest quarter, temperature seasonality and annual mean temperature. The model using the AVHRR dataset identified six environmental variables: minimum Land Surface Temperature (LST), minimum Middle Infrared Radiation (MIR), LST annual amplitude, MIR annual amplitude annual, LST variance and MIR variance. The potential geographic distribution of triatomine species infected by TrV coincides with the Chaco and the Monte ecoregions either modelled by AVHRR or Bioclim environmental datasets. Conclusions: Our results show that the conditions of the Dry Chaco ecoregion in Argentina are favourable for the infection of triatomine species with TrV, and open the possibility of its use as a potential agent for the biological control of peridomestic and/or sylvatic triatomine species. Results identify areas of potential occurrence that should be verified in the field.
Fil: Ceccarelli, Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Balsalobre, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Susevich, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Echeverria, Maria Gabriela. Universidad Nacional de la Plata. Facultad de Ciencias Veterinarias. Departamento de Microbiología. Cátedra de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Gorla, David Eladio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientificas y Transferencia Tecnológica de Anillaco; Argentina
Fil: Marti, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina - Materia
-
Triatoma virus
TriatominaE
Ecological Niche Modelling
MaxEnt
WorldClim
AVHRR imagery - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/10684
Ver los metadatos del registro completo
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Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South AmericaCeccarelli, SoledadBalsalobre, AgustinSusevich, Maria LauraEcheverria, Maria GabrielaGorla, David EladioMarti, Gerardo AnibalTriatoma virusTriatominaEEcological Niche ModellingMaxEntWorldClimAVHRR imageryhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Background: Triatoma virus (TrV) is the only entomopathogenous virus identified in triatomines. We estimated the potential geographic distribution of triatomine species naturally infected by TrV, using remotely sensed and meteorological environmental variables, to predict new potential areas where triatomines infected with TrV may be found. Methods: Detection of TrV infection in samples was performed with RT-PCR. Ecological niche models (ENM) were constructed using the MaxEnt software. We used 42 environmental variables derived from remotely sensed imagery (AVHRR) and 19 bioclimatic variables (Bioclim). The MaxEnt Jackknife procedure was used to minimize the number of environmental variables that showed an influence on final models. The goodness of fit of the model predictions was evaluated by the mean area under the curve (AUC). Results: We obtained 37 samples of 7 species of triatomines naturally infected with TrV. Of the TrV positive samples, 32% were from sylvatic habitat, 46% came from peridomicile habitats and 22% from domicile habitats. Five of the seven infected species were found only in the sylvatic habitat, one species only in the domicile and only Triatoma infestans was found in the three habitats. The MaxEnt model estimated with the Bioclim dataset identified five environmental variables as best predictors: temperature annual range, mean diurnal range, mean temperature of coldest quarter, temperature seasonality and annual mean temperature. The model using the AVHRR dataset identified six environmental variables: minimum Land Surface Temperature (LST), minimum Middle Infrared Radiation (MIR), LST annual amplitude, MIR annual amplitude annual, LST variance and MIR variance. The potential geographic distribution of triatomine species infected by TrV coincides with the Chaco and the Monte ecoregions either modelled by AVHRR or Bioclim environmental datasets. Conclusions: Our results show that the conditions of the Dry Chaco ecoregion in Argentina are favourable for the infection of triatomine species with TrV, and open the possibility of its use as a potential agent for the biological control of peridomestic and/or sylvatic triatomine species. Results identify areas of potential occurrence that should be verified in the field.Fil: Ceccarelli, Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaFil: Balsalobre, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaFil: Susevich, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaFil: Echeverria, Maria Gabriela. Universidad Nacional de la Plata. Facultad de Ciencias Veterinarias. Departamento de Microbiología. Cátedra de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gorla, David Eladio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientificas y Transferencia Tecnológica de Anillaco; ArgentinaFil: Marti, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaBiomed Central2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/10684Ceccarelli, Soledad; Balsalobre, Agustin; Susevich, Maria Laura; Echeverria, Maria Gabriela; Gorla, David Eladio; et al.; Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America; Biomed Central; Parasites And Vectors; 8; 153; 3-20151756-3305enginfo:eu-repo/semantics/altIdentifier/doi/10.1186/s13071-015-0761-1info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pubmed/25881183info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25881183/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:35:41Zoai:ri.conicet.gov.ar:11336/10684instacron: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:34982025-09-29 10:35:41.838CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America |
title |
Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America |
spellingShingle |
Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America Ceccarelli, Soledad Triatoma virus TriatominaE Ecological Niche Modelling MaxEnt WorldClim AVHRR imagery |
title_short |
Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America |
title_full |
Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America |
title_fullStr |
Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America |
title_full_unstemmed |
Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America |
title_sort |
Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America |
dc.creator.none.fl_str_mv |
Ceccarelli, Soledad Balsalobre, Agustin Susevich, Maria Laura Echeverria, Maria Gabriela Gorla, David Eladio Marti, Gerardo Anibal |
author |
Ceccarelli, Soledad |
author_facet |
Ceccarelli, Soledad Balsalobre, Agustin Susevich, Maria Laura Echeverria, Maria Gabriela Gorla, David Eladio Marti, Gerardo Anibal |
author_role |
author |
author2 |
Balsalobre, Agustin Susevich, Maria Laura Echeverria, Maria Gabriela Gorla, David Eladio Marti, Gerardo Anibal |
author2_role |
author author author author author |
dc.subject.none.fl_str_mv |
Triatoma virus TriatominaE Ecological Niche Modelling MaxEnt WorldClim AVHRR imagery |
topic |
Triatoma virus TriatominaE Ecological Niche Modelling MaxEnt WorldClim AVHRR imagery |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Background: Triatoma virus (TrV) is the only entomopathogenous virus identified in triatomines. We estimated the potential geographic distribution of triatomine species naturally infected by TrV, using remotely sensed and meteorological environmental variables, to predict new potential areas where triatomines infected with TrV may be found. Methods: Detection of TrV infection in samples was performed with RT-PCR. Ecological niche models (ENM) were constructed using the MaxEnt software. We used 42 environmental variables derived from remotely sensed imagery (AVHRR) and 19 bioclimatic variables (Bioclim). The MaxEnt Jackknife procedure was used to minimize the number of environmental variables that showed an influence on final models. The goodness of fit of the model predictions was evaluated by the mean area under the curve (AUC). Results: We obtained 37 samples of 7 species of triatomines naturally infected with TrV. Of the TrV positive samples, 32% were from sylvatic habitat, 46% came from peridomicile habitats and 22% from domicile habitats. Five of the seven infected species were found only in the sylvatic habitat, one species only in the domicile and only Triatoma infestans was found in the three habitats. The MaxEnt model estimated with the Bioclim dataset identified five environmental variables as best predictors: temperature annual range, mean diurnal range, mean temperature of coldest quarter, temperature seasonality and annual mean temperature. The model using the AVHRR dataset identified six environmental variables: minimum Land Surface Temperature (LST), minimum Middle Infrared Radiation (MIR), LST annual amplitude, MIR annual amplitude annual, LST variance and MIR variance. The potential geographic distribution of triatomine species infected by TrV coincides with the Chaco and the Monte ecoregions either modelled by AVHRR or Bioclim environmental datasets. Conclusions: Our results show that the conditions of the Dry Chaco ecoregion in Argentina are favourable for the infection of triatomine species with TrV, and open the possibility of its use as a potential agent for the biological control of peridomestic and/or sylvatic triatomine species. Results identify areas of potential occurrence that should be verified in the field. Fil: Ceccarelli, Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina Fil: Balsalobre, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina Fil: Susevich, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina Fil: Echeverria, Maria Gabriela. Universidad Nacional de la Plata. Facultad de Ciencias Veterinarias. Departamento de Microbiología. Cátedra de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Gorla, David Eladio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientificas y Transferencia Tecnológica de Anillaco; Argentina Fil: Marti, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina |
description |
Background: Triatoma virus (TrV) is the only entomopathogenous virus identified in triatomines. We estimated the potential geographic distribution of triatomine species naturally infected by TrV, using remotely sensed and meteorological environmental variables, to predict new potential areas where triatomines infected with TrV may be found. Methods: Detection of TrV infection in samples was performed with RT-PCR. Ecological niche models (ENM) were constructed using the MaxEnt software. We used 42 environmental variables derived from remotely sensed imagery (AVHRR) and 19 bioclimatic variables (Bioclim). The MaxEnt Jackknife procedure was used to minimize the number of environmental variables that showed an influence on final models. The goodness of fit of the model predictions was evaluated by the mean area under the curve (AUC). Results: We obtained 37 samples of 7 species of triatomines naturally infected with TrV. Of the TrV positive samples, 32% were from sylvatic habitat, 46% came from peridomicile habitats and 22% from domicile habitats. Five of the seven infected species were found only in the sylvatic habitat, one species only in the domicile and only Triatoma infestans was found in the three habitats. The MaxEnt model estimated with the Bioclim dataset identified five environmental variables as best predictors: temperature annual range, mean diurnal range, mean temperature of coldest quarter, temperature seasonality and annual mean temperature. The model using the AVHRR dataset identified six environmental variables: minimum Land Surface Temperature (LST), minimum Middle Infrared Radiation (MIR), LST annual amplitude, MIR annual amplitude annual, LST variance and MIR variance. The potential geographic distribution of triatomine species infected by TrV coincides with the Chaco and the Monte ecoregions either modelled by AVHRR or Bioclim environmental datasets. Conclusions: Our results show that the conditions of the Dry Chaco ecoregion in Argentina are favourable for the infection of triatomine species with TrV, and open the possibility of its use as a potential agent for the biological control of peridomestic and/or sylvatic triatomine species. Results identify areas of potential occurrence that should be verified in the field. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-03 |
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/11336/10684 Ceccarelli, Soledad; Balsalobre, Agustin; Susevich, Maria Laura; Echeverria, Maria Gabriela; Gorla, David Eladio; et al.; Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America; Biomed Central; Parasites And Vectors; 8; 153; 3-2015 1756-3305 |
url |
http://hdl.handle.net/11336/10684 |
identifier_str_mv |
Ceccarelli, Soledad; Balsalobre, Agustin; Susevich, Maria Laura; Echeverria, Maria Gabriela; Gorla, David Eladio; et al.; Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America; Biomed Central; Parasites And Vectors; 8; 153; 3-2015 1756-3305 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1186/s13071-015-0761-1 info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pubmed/25881183 info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25881183/ |
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 application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Biomed Central |
publisher.none.fl_str_mv |
Biomed Central |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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13.070432 |