Comparison of environmental indicator sets using a unified indicator classification framework
- Autores
- Brambila, Alejandro; Flombaum, Pedro
- Año de publicación
- 2017
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Environmental indicator sets (EIS) are tools to monitor and assess sustainability, and many environmental organizations have embraced their use. Due to the large number of EIS, it is a challenge to compare and reconcile their differences and gain a comprehensive view of their utility. To compare EIS, the first step is to classify their component indicators, for which several frameworks exist. Among the most widely used, is the causal-chain framework, also referred to as PSR after its categories of Pressure, State and Response. Other frameworks classify indicators by subject, yet none is widely applied. Aiming to compare EIS, we first proposed a unified classification criteria for indicators using PSR and five subject categories (i.e., biodiversity and ecosystem health, E; natural resources, N; physical and chemical contamination, C; human environment, H; and general, G). Then, we used these classification criteria to describe and compare fourteen existing environmental indicator sets. Finally, we compared EIS based on their production characteristics and goals. Across the fourteen EIS, we analyzed 706 indicators (which represent ∼1200 variables) and selected 16 and 79 keywords for classification in the PSR and ENCHG categories respectively. We found on average that the ratio of categories in the causal chain framework was 2.5S:1.5P:1R, while we observed a large variability across EIS. For the subject categories, C-E-N were nearly equally represented among EIS, and better represented than H-G. Also, the evaluated EIS showed a polarization between C-H and E categories that we interpreted as a human vs. natural-ecosystem welfare focus. Finally, we identified three broad categories of EIS based primarily on the organization that produced them, non-governmental organizations, governmental organizations, and international organizations. Our results can contribute to the design and implementation of scientifically robust and representative EIS, which are key to incorporate environmental data to policymaking in the search of sustainability.
Fil: Brambila, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina
Fil: Flombaum, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Departamento de Ecología Genética y Evolución; Argentina - Materia
-
Causal Chain Framework
Environmental Indicator Sets
Sustainability Index - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/58907
Ver los metadatos del registro completo
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Comparison of environmental indicator sets using a unified indicator classification frameworkBrambila, AlejandroFlombaum, PedroCausal Chain FrameworkEnvironmental Indicator SetsSustainability Indexhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Environmental indicator sets (EIS) are tools to monitor and assess sustainability, and many environmental organizations have embraced their use. Due to the large number of EIS, it is a challenge to compare and reconcile their differences and gain a comprehensive view of their utility. To compare EIS, the first step is to classify their component indicators, for which several frameworks exist. Among the most widely used, is the causal-chain framework, also referred to as PSR after its categories of Pressure, State and Response. Other frameworks classify indicators by subject, yet none is widely applied. Aiming to compare EIS, we first proposed a unified classification criteria for indicators using PSR and five subject categories (i.e., biodiversity and ecosystem health, E; natural resources, N; physical and chemical contamination, C; human environment, H; and general, G). Then, we used these classification criteria to describe and compare fourteen existing environmental indicator sets. Finally, we compared EIS based on their production characteristics and goals. Across the fourteen EIS, we analyzed 706 indicators (which represent ∼1200 variables) and selected 16 and 79 keywords for classification in the PSR and ENCHG categories respectively. We found on average that the ratio of categories in the causal chain framework was 2.5S:1.5P:1R, while we observed a large variability across EIS. For the subject categories, C-E-N were nearly equally represented among EIS, and better represented than H-G. Also, the evaluated EIS showed a polarization between C-H and E categories that we interpreted as a human vs. natural-ecosystem welfare focus. Finally, we identified three broad categories of EIS based primarily on the organization that produced them, non-governmental organizations, governmental organizations, and international organizations. Our results can contribute to the design and implementation of scientifically robust and representative EIS, which are key to incorporate environmental data to policymaking in the search of sustainability.Fil: Brambila, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Flombaum, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Departamento de Ecología Genética y Evolución; ArgentinaElsevier Science2017-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/58907Brambila, Alejandro; Flombaum, Pedro; Comparison of environmental indicator sets using a unified indicator classification framework; Elsevier Science; Ecological Indicators; 83; 12-2017; 96-1021470-160XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolind.2017.07.023info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1470160X17304375info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:07:14Zoai:ri.conicet.gov.ar:11336/58907instacron: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 10:07:14.566CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Comparison of environmental indicator sets using a unified indicator classification framework |
title |
Comparison of environmental indicator sets using a unified indicator classification framework |
spellingShingle |
Comparison of environmental indicator sets using a unified indicator classification framework Brambila, Alejandro Causal Chain Framework Environmental Indicator Sets Sustainability Index |
title_short |
Comparison of environmental indicator sets using a unified indicator classification framework |
title_full |
Comparison of environmental indicator sets using a unified indicator classification framework |
title_fullStr |
Comparison of environmental indicator sets using a unified indicator classification framework |
title_full_unstemmed |
Comparison of environmental indicator sets using a unified indicator classification framework |
title_sort |
Comparison of environmental indicator sets using a unified indicator classification framework |
dc.creator.none.fl_str_mv |
Brambila, Alejandro Flombaum, Pedro |
author |
Brambila, Alejandro |
author_facet |
Brambila, Alejandro Flombaum, Pedro |
author_role |
author |
author2 |
Flombaum, Pedro |
author2_role |
author |
dc.subject.none.fl_str_mv |
Causal Chain Framework Environmental Indicator Sets Sustainability Index |
topic |
Causal Chain Framework Environmental Indicator Sets Sustainability Index |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Environmental indicator sets (EIS) are tools to monitor and assess sustainability, and many environmental organizations have embraced their use. Due to the large number of EIS, it is a challenge to compare and reconcile their differences and gain a comprehensive view of their utility. To compare EIS, the first step is to classify their component indicators, for which several frameworks exist. Among the most widely used, is the causal-chain framework, also referred to as PSR after its categories of Pressure, State and Response. Other frameworks classify indicators by subject, yet none is widely applied. Aiming to compare EIS, we first proposed a unified classification criteria for indicators using PSR and five subject categories (i.e., biodiversity and ecosystem health, E; natural resources, N; physical and chemical contamination, C; human environment, H; and general, G). Then, we used these classification criteria to describe and compare fourteen existing environmental indicator sets. Finally, we compared EIS based on their production characteristics and goals. Across the fourteen EIS, we analyzed 706 indicators (which represent ∼1200 variables) and selected 16 and 79 keywords for classification in the PSR and ENCHG categories respectively. We found on average that the ratio of categories in the causal chain framework was 2.5S:1.5P:1R, while we observed a large variability across EIS. For the subject categories, C-E-N were nearly equally represented among EIS, and better represented than H-G. Also, the evaluated EIS showed a polarization between C-H and E categories that we interpreted as a human vs. natural-ecosystem welfare focus. Finally, we identified three broad categories of EIS based primarily on the organization that produced them, non-governmental organizations, governmental organizations, and international organizations. Our results can contribute to the design and implementation of scientifically robust and representative EIS, which are key to incorporate environmental data to policymaking in the search of sustainability. Fil: Brambila, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina Fil: Flombaum, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Departamento de Ecología Genética y Evolución; Argentina |
description |
Environmental indicator sets (EIS) are tools to monitor and assess sustainability, and many environmental organizations have embraced their use. Due to the large number of EIS, it is a challenge to compare and reconcile their differences and gain a comprehensive view of their utility. To compare EIS, the first step is to classify their component indicators, for which several frameworks exist. Among the most widely used, is the causal-chain framework, also referred to as PSR after its categories of Pressure, State and Response. Other frameworks classify indicators by subject, yet none is widely applied. Aiming to compare EIS, we first proposed a unified classification criteria for indicators using PSR and five subject categories (i.e., biodiversity and ecosystem health, E; natural resources, N; physical and chemical contamination, C; human environment, H; and general, G). Then, we used these classification criteria to describe and compare fourteen existing environmental indicator sets. Finally, we compared EIS based on their production characteristics and goals. Across the fourteen EIS, we analyzed 706 indicators (which represent ∼1200 variables) and selected 16 and 79 keywords for classification in the PSR and ENCHG categories respectively. We found on average that the ratio of categories in the causal chain framework was 2.5S:1.5P:1R, while we observed a large variability across EIS. For the subject categories, C-E-N were nearly equally represented among EIS, and better represented than H-G. Also, the evaluated EIS showed a polarization between C-H and E categories that we interpreted as a human vs. natural-ecosystem welfare focus. Finally, we identified three broad categories of EIS based primarily on the organization that produced them, non-governmental organizations, governmental organizations, and international organizations. Our results can contribute to the design and implementation of scientifically robust and representative EIS, which are key to incorporate environmental data to policymaking in the search of sustainability. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-12 |
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/11336/58907 Brambila, Alejandro; Flombaum, Pedro; Comparison of environmental indicator sets using a unified indicator classification framework; Elsevier Science; Ecological Indicators; 83; 12-2017; 96-102 1470-160X CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/58907 |
identifier_str_mv |
Brambila, Alejandro; Flombaum, Pedro; Comparison of environmental indicator sets using a unified indicator classification framework; Elsevier Science; Ecological Indicators; 83; 12-2017; 96-102 1470-160X CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolind.2017.07.023 info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S1470160X17304375 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier Science |
publisher.none.fl_str_mv |
Elsevier Science |
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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