Using socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant

One of the greatest challenges when addressing issues in complex social-ecological systems (SES), is the need for an efficient interdisciplinary framework when large-magnitude social and ecological disturbances occur. Teams comprising of scientists from different backgrounds and disciplines are freq...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Hendrik Davi, Laetitia Tuffery, Emmanuel Garbolino, Bernard Prévosto, Bruno Fady
Formato: article
Lenguaje:EN
Publicado: Resilience Alliance 2020
Materias:
Acceso en línea:https://doaj.org/article/8755c98ad5804d5daa636439ffee1c95
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:8755c98ad5804d5daa636439ffee1c95
record_format dspace
spelling oai:doaj.org-article:8755c98ad5804d5daa636439ffee1c952021-12-02T14:14:42ZUsing socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant1708-308710.5751/ES-11929-250416https://doaj.org/article/8755c98ad5804d5daa636439ffee1c952020-12-01T00:00:00Zhttps://www.ecologyandsociety.org/vol25/iss4/art16/https://doaj.org/toc/1708-3087One of the greatest challenges when addressing issues in complex social-ecological systems (SES), is the need for an efficient interdisciplinary framework when large-magnitude social and ecological disturbances occur. Teams comprising of scientists from different backgrounds and disciplines are frequently called upon to propose research methods and results that can be useful for policy and decision makers. However, most of the outcomes from these pluri-disciplinary teams appear extremely difficult to implement within a bigger picture because concepts, hypotheses, methods, and results are specific to each discipline. Here, we propose a reverse-engineering (RE) method to define the scientific needs that could help policy makers and citizens to assess the impacts of socioeconomic "disruptors" on social-ecological systems. We present this method using the example of an ongoing wood biomass energy plant (Gardanne) in the French Mediterranean region. In the Mediterranean region, species diversity is high, the forest cover is ample, but difficult access and low forest productivity make any biomass policy an ecological and social disruption. Our method is based on three complementary approaches to (1) describe the social-ecosystems, (2) draw up a map of interactions between actors and the impacts on the ecosystem, and (3) identify relevant questions needed for a global analysis of the impacts and potentialities of adaptation of actors and the ecosystems to the perturbation and the connections needed between the different disciplines. Our analysis showed that knowledge gaps have to be filled to assess forest resource vulnerability and better estimate how the different resource used (solid wood, biomass, landscape) competed together. Finally, we discuss how this method could be integrated into a broader transdisciplinary work allowing a coproduction of knowledge and solutions on a SES.Hendrik DaviLaetitia TufferyEmmanuel GarbolinoBernard PrévostoBruno FadyResilience Alliancearticleforestinterdisciplinarymodelreverse-engineeringwood energyBiology (General)QH301-705.5EcologyQH540-549.5ENEcology and Society, Vol 25, Iss 4, p 16 (2020)
institution DOAJ
collection DOAJ
language EN
topic forest
interdisciplinary
model
reverse-engineering
wood energy
Biology (General)
QH301-705.5
Ecology
QH540-549.5
spellingShingle forest
interdisciplinary
model
reverse-engineering
wood energy
Biology (General)
QH301-705.5
Ecology
QH540-549.5
Hendrik Davi
Laetitia Tuffery
Emmanuel Garbolino
Bernard Prévosto
Bruno Fady
Using socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant
description One of the greatest challenges when addressing issues in complex social-ecological systems (SES), is the need for an efficient interdisciplinary framework when large-magnitude social and ecological disturbances occur. Teams comprising of scientists from different backgrounds and disciplines are frequently called upon to propose research methods and results that can be useful for policy and decision makers. However, most of the outcomes from these pluri-disciplinary teams appear extremely difficult to implement within a bigger picture because concepts, hypotheses, methods, and results are specific to each discipline. Here, we propose a reverse-engineering (RE) method to define the scientific needs that could help policy makers and citizens to assess the impacts of socioeconomic "disruptors" on social-ecological systems. We present this method using the example of an ongoing wood biomass energy plant (Gardanne) in the French Mediterranean region. In the Mediterranean region, species diversity is high, the forest cover is ample, but difficult access and low forest productivity make any biomass policy an ecological and social disruption. Our method is based on three complementary approaches to (1) describe the social-ecosystems, (2) draw up a map of interactions between actors and the impacts on the ecosystem, and (3) identify relevant questions needed for a global analysis of the impacts and potentialities of adaptation of actors and the ecosystems to the perturbation and the connections needed between the different disciplines. Our analysis showed that knowledge gaps have to be filled to assess forest resource vulnerability and better estimate how the different resource used (solid wood, biomass, landscape) competed together. Finally, we discuss how this method could be integrated into a broader transdisciplinary work allowing a coproduction of knowledge and solutions on a SES.
format article
author Hendrik Davi
Laetitia Tuffery
Emmanuel Garbolino
Bernard Prévosto
Bruno Fady
author_facet Hendrik Davi
Laetitia Tuffery
Emmanuel Garbolino
Bernard Prévosto
Bruno Fady
author_sort Hendrik Davi
title Using socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant
title_short Using socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant
title_full Using socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant
title_fullStr Using socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant
title_full_unstemmed Using socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant
title_sort using socioeconomic system analysis to define scientific needs: a reverse engineering method applied to the conversion of a coal-fired to a wood biomass power plant
publisher Resilience Alliance
publishDate 2020
url https://doaj.org/article/8755c98ad5804d5daa636439ffee1c95
work_keys_str_mv AT hendrikdavi usingsocioeconomicsystemanalysistodefinescientificneedsareverseengineeringmethodappliedtotheconversionofacoalfiredtoawoodbiomasspowerplant
AT laetitiatuffery usingsocioeconomicsystemanalysistodefinescientificneedsareverseengineeringmethodappliedtotheconversionofacoalfiredtoawoodbiomasspowerplant
AT emmanuelgarbolino usingsocioeconomicsystemanalysistodefinescientificneedsareverseengineeringmethodappliedtotheconversionofacoalfiredtoawoodbiomasspowerplant
AT bernardprevosto usingsocioeconomicsystemanalysistodefinescientificneedsareverseengineeringmethodappliedtotheconversionofacoalfiredtoawoodbiomasspowerplant
AT brunofady usingsocioeconomicsystemanalysistodefinescientificneedsareverseengineeringmethodappliedtotheconversionofacoalfiredtoawoodbiomasspowerplant
_version_ 1718391737437650944