Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America

Autores
Ceccarelli, Soledad; Balsalobre, Agustín; Susevich, María Laura; Echeverría, María Gabriela; Gorla, David Eladio; Martí, Gerardo Aníbal
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.
Facultad de Ciencias Veterinarias
Centro de Estudios Parasitológicos y de Vectores
Materia
Ciencias Naturales
Ciencias Veterinarias
AVHRR imagery
Ecological Niche Modelling
MaxEnt
Triatoma virus
Triatominae
WorldClim
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/85862

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oai_identifier_str oai:sedici.unlp.edu.ar:10915/85862
network_acronym_str SEDICI
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network_name_str SEDICI (UNLP)
spelling Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South AmericaCeccarelli, SoledadBalsalobre, AgustínSusevich, María LauraEcheverría, María GabrielaGorla, David EladioMartí, Gerardo AníbalCiencias NaturalesCiencias VeterinariasAVHRR imageryEcological Niche ModellingMaxEntTriatoma virusTriatominaeWorldClimBackground: <i>Triatoma virus</i> (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 <i>Triatoma infestans</i> 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.Facultad de Ciencias VeterinariasCentro de Estudios Parasitológicos y de Vectores2015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/85862enginfo:eu-repo/semantics/altIdentifier/issn/1756-3305info:eu-repo/semantics/altIdentifier/doi/10.1186/s13071-015-0761-1info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:16:55Zoai:sedici.unlp.edu.ar:10915/85862Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:16:55.563SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America
title Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America
spellingShingle Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America
Ceccarelli, Soledad
Ciencias Naturales
Ciencias Veterinarias
AVHRR imagery
Ecological Niche Modelling
MaxEnt
Triatoma virus
Triatominae
WorldClim
title_short Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America
title_full Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America
title_fullStr Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America
title_full_unstemmed Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America
title_sort Modelling the potential geographic distribution of triatomines infected by <i>Triatoma virus</i> in the southern cone of South America
dc.creator.none.fl_str_mv Ceccarelli, Soledad
Balsalobre, Agustín
Susevich, María Laura
Echeverría, María Gabriela
Gorla, David Eladio
Martí, Gerardo Aníbal
author Ceccarelli, Soledad
author_facet Ceccarelli, Soledad
Balsalobre, Agustín
Susevich, María Laura
Echeverría, María Gabriela
Gorla, David Eladio
Martí, Gerardo Aníbal
author_role author
author2 Balsalobre, Agustín
Susevich, María Laura
Echeverría, María Gabriela
Gorla, David Eladio
Martí, Gerardo Aníbal
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Naturales
Ciencias Veterinarias
AVHRR imagery
Ecological Niche Modelling
MaxEnt
Triatoma virus
Triatominae
WorldClim
topic Ciencias Naturales
Ciencias Veterinarias
AVHRR imagery
Ecological Niche Modelling
MaxEnt
Triatoma virus
Triatominae
WorldClim
dc.description.none.fl_txt_mv Background: <i>Triatoma virus</i> (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 <i>Triatoma infestans</i> 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.
Facultad de Ciencias Veterinarias
Centro de Estudios Parasitológicos y de Vectores
description Background: <i>Triatoma virus</i> (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 <i>Triatoma infestans</i> 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
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1756-3305
info:eu-repo/semantics/altIdentifier/doi/10.1186/s13071-015-0761-1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
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