Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment

Autores
D'Andrea, María Florencia; Brodeur, Julie Céline
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Living organisms have different sensitivities to toxicants. This variability can be represented by constructing a species sensitivity distribution(SSD) curve, where by the toxicity of a substance to a group of species is described by a statistical distribution. Building the SSD curve allows calculating the Hazard Concentration 5% (HC5), that is, the concentration at which 5% of the considered species are affected. The HC5 is widely used as an environmental quality criterion and a tool for ecological risk assessment (Posthuma, Suter II, & Traas, 2001). The shinyssd web application is a versatile and easy to use tool that serves to simultaneously model the SSD curve of a user-defined toxicity dataset based on four different statistical distribution models (log-normal, log-logistic, Weibull, Pareto). shinyssd directly calculate sthree estimators HC1, HC5 and HC10 associated to the four distribution models together with its confidence intervals, allowing the user to select the statistical distribution and associated HC values that best adjust the dataset. Thelevel of confidence of the result sobtained from a SSD curve will depend on the number of species used to produce the SSD. In this sense, the first tab of the user interface is used for visualizing the number of species for which toxicological data are available for each toxicant, species group, and endpoint combination in the uploaded dataset. A minimum of species is necessary to build a SSD curve varies according to the literature (Belanger et al., 2016; Newman et al., 2000; Plant Protection Products & Residues, 2013; Wheeler, Grist, Leung, Morritt, & Crane, 2002). After selecting the toxicant and species groups, the user can filter and select subsets of data from the whole database by applying different quality criteria (e.g., if the studies reported a chemical confirmation of the concentration sof the toxicanttested). The values enteredineach column of the data base serveas categories to filter the data basein relation to characteristics of the bioassays. The final SSD curve is fitted to different distributions using the package fitdistrplus and actuar. The HC is estimated for all the distributions. By facilitating and streamlining toxicity data analysis and the creation of SSD curves, the user interface proposed here should be useful for environmental managers and regulators conducting ecological risk assessments and scientific research.
Fil: D'Andrea, María Florencia. Consejo de Investigaciones Científicas y Técnicas (CONICET); Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina
Fil: Brodeur, Julie Céline. Consejo de Investigaciones Científicas y Técnicas (CONICET); Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina
Fuente
Journal of open source software 4 (37) : 785 (2019)
Materia
Ecotoxicology
Risk
Ecotoxicología
Riesgo
Species Ssensitivity Distribution
Web Application
Shinyssd
Distribución de Sensibilidad de Especies
Aplicación Web
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/6310

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oai_identifier_str oai:localhost:20.500.12123/6310
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network_name_str INTA Digital (INTA)
spelling Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessmentD'Andrea, María FlorenciaBrodeur, Julie CélineEcotoxicologyRiskEcotoxicologíaRiesgoSpecies Ssensitivity DistributionWeb ApplicationShinyssdDistribución de Sensibilidad de EspeciesAplicación WebLiving organisms have different sensitivities to toxicants. This variability can be represented by constructing a species sensitivity distribution(SSD) curve, where by the toxicity of a substance to a group of species is described by a statistical distribution. Building the SSD curve allows calculating the Hazard Concentration 5% (HC5), that is, the concentration at which 5% of the considered species are affected. The HC5 is widely used as an environmental quality criterion and a tool for ecological risk assessment (Posthuma, Suter II, & Traas, 2001). The shinyssd web application is a versatile and easy to use tool that serves to simultaneously model the SSD curve of a user-defined toxicity dataset based on four different statistical distribution models (log-normal, log-logistic, Weibull, Pareto). shinyssd directly calculate sthree estimators HC1, HC5 and HC10 associated to the four distribution models together with its confidence intervals, allowing the user to select the statistical distribution and associated HC values that best adjust the dataset. Thelevel of confidence of the result sobtained from a SSD curve will depend on the number of species used to produce the SSD. In this sense, the first tab of the user interface is used for visualizing the number of species for which toxicological data are available for each toxicant, species group, and endpoint combination in the uploaded dataset. A minimum of species is necessary to build a SSD curve varies according to the literature (Belanger et al., 2016; Newman et al., 2000; Plant Protection Products & Residues, 2013; Wheeler, Grist, Leung, Morritt, & Crane, 2002). After selecting the toxicant and species groups, the user can filter and select subsets of data from the whole database by applying different quality criteria (e.g., if the studies reported a chemical confirmation of the concentration sof the toxicanttested). The values enteredineach column of the data base serveas categories to filter the data basein relation to characteristics of the bioassays. The final SSD curve is fitted to different distributions using the package fitdistrplus and actuar. The HC is estimated for all the distributions. By facilitating and streamlining toxicity data analysis and the creation of SSD curves, the user interface proposed here should be useful for environmental managers and regulators conducting ecological risk assessments and scientific research.Fil: D'Andrea, María Florencia. Consejo de Investigaciones Científicas y Técnicas (CONICET); Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; ArgentinaFil: Brodeur, Julie Céline. Consejo de Investigaciones Científicas y Técnicas (CONICET); Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina2019-11-07T17:06:06Z2019-11-07T17:06:06Z2019-05-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/6310https://joss.theoj.org/papers/10.21105/joss.007852475-9066https://doi.org/10.21105/joss.00785Journal of open source software 4 (37) : 785 (2019)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo: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)2025-09-29T13:44:48Zoai:localhost:20.500.12123/6310instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-09-29 13:44:49.251INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment
title Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment
spellingShingle Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment
D'Andrea, María Florencia
Ecotoxicology
Risk
Ecotoxicología
Riesgo
Species Ssensitivity Distribution
Web Application
Shinyssd
Distribución de Sensibilidad de Especies
Aplicación Web
title_short Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment
title_full Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment
title_fullStr Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment
title_full_unstemmed Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment
title_sort Shinyssd v1.0: Species sensitivity distributions for ecotoxicological risk assessment
dc.creator.none.fl_str_mv D'Andrea, María Florencia
Brodeur, Julie Céline
author D'Andrea, María Florencia
author_facet D'Andrea, María Florencia
Brodeur, Julie Céline
author_role author
author2 Brodeur, Julie Céline
author2_role author
dc.subject.none.fl_str_mv Ecotoxicology
Risk
Ecotoxicología
Riesgo
Species Ssensitivity Distribution
Web Application
Shinyssd
Distribución de Sensibilidad de Especies
Aplicación Web
topic Ecotoxicology
Risk
Ecotoxicología
Riesgo
Species Ssensitivity Distribution
Web Application
Shinyssd
Distribución de Sensibilidad de Especies
Aplicación Web
dc.description.none.fl_txt_mv Living organisms have different sensitivities to toxicants. This variability can be represented by constructing a species sensitivity distribution(SSD) curve, where by the toxicity of a substance to a group of species is described by a statistical distribution. Building the SSD curve allows calculating the Hazard Concentration 5% (HC5), that is, the concentration at which 5% of the considered species are affected. The HC5 is widely used as an environmental quality criterion and a tool for ecological risk assessment (Posthuma, Suter II, & Traas, 2001). The shinyssd web application is a versatile and easy to use tool that serves to simultaneously model the SSD curve of a user-defined toxicity dataset based on four different statistical distribution models (log-normal, log-logistic, Weibull, Pareto). shinyssd directly calculate sthree estimators HC1, HC5 and HC10 associated to the four distribution models together with its confidence intervals, allowing the user to select the statistical distribution and associated HC values that best adjust the dataset. Thelevel of confidence of the result sobtained from a SSD curve will depend on the number of species used to produce the SSD. In this sense, the first tab of the user interface is used for visualizing the number of species for which toxicological data are available for each toxicant, species group, and endpoint combination in the uploaded dataset. A minimum of species is necessary to build a SSD curve varies according to the literature (Belanger et al., 2016; Newman et al., 2000; Plant Protection Products & Residues, 2013; Wheeler, Grist, Leung, Morritt, & Crane, 2002). After selecting the toxicant and species groups, the user can filter and select subsets of data from the whole database by applying different quality criteria (e.g., if the studies reported a chemical confirmation of the concentration sof the toxicanttested). The values enteredineach column of the data base serveas categories to filter the data basein relation to characteristics of the bioassays. The final SSD curve is fitted to different distributions using the package fitdistrplus and actuar. The HC is estimated for all the distributions. By facilitating and streamlining toxicity data analysis and the creation of SSD curves, the user interface proposed here should be useful for environmental managers and regulators conducting ecological risk assessments and scientific research.
Fil: D'Andrea, María Florencia. Consejo de Investigaciones Científicas y Técnicas (CONICET); Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina
Fil: Brodeur, Julie Céline. Consejo de Investigaciones Científicas y Técnicas (CONICET); Argentina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina
description Living organisms have different sensitivities to toxicants. This variability can be represented by constructing a species sensitivity distribution(SSD) curve, where by the toxicity of a substance to a group of species is described by a statistical distribution. Building the SSD curve allows calculating the Hazard Concentration 5% (HC5), that is, the concentration at which 5% of the considered species are affected. The HC5 is widely used as an environmental quality criterion and a tool for ecological risk assessment (Posthuma, Suter II, & Traas, 2001). The shinyssd web application is a versatile and easy to use tool that serves to simultaneously model the SSD curve of a user-defined toxicity dataset based on four different statistical distribution models (log-normal, log-logistic, Weibull, Pareto). shinyssd directly calculate sthree estimators HC1, HC5 and HC10 associated to the four distribution models together with its confidence intervals, allowing the user to select the statistical distribution and associated HC values that best adjust the dataset. Thelevel of confidence of the result sobtained from a SSD curve will depend on the number of species used to produce the SSD. In this sense, the first tab of the user interface is used for visualizing the number of species for which toxicological data are available for each toxicant, species group, and endpoint combination in the uploaded dataset. A minimum of species is necessary to build a SSD curve varies according to the literature (Belanger et al., 2016; Newman et al., 2000; Plant Protection Products & Residues, 2013; Wheeler, Grist, Leung, Morritt, & Crane, 2002). After selecting the toxicant and species groups, the user can filter and select subsets of data from the whole database by applying different quality criteria (e.g., if the studies reported a chemical confirmation of the concentration sof the toxicanttested). The values enteredineach column of the data base serveas categories to filter the data basein relation to characteristics of the bioassays. The final SSD curve is fitted to different distributions using the package fitdistrplus and actuar. The HC is estimated for all the distributions. By facilitating and streamlining toxicity data analysis and the creation of SSD curves, the user interface proposed here should be useful for environmental managers and regulators conducting ecological risk assessments and scientific research.
publishDate 2019
dc.date.none.fl_str_mv 2019-11-07T17:06:06Z
2019-11-07T17:06:06Z
2019-05-29
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/6310
https://joss.theoj.org/papers/10.21105/joss.00785
2475-9066
https://doi.org/10.21105/joss.00785
url http://hdl.handle.net/20.500.12123/6310
https://joss.theoj.org/papers/10.21105/joss.00785
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identifier_str_mv 2475-9066
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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
dc.source.none.fl_str_mv Journal of open source software 4 (37) : 785 (2019)
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