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Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/34322
Title: Synchronizing histories of exposure and demography: the construction of an agent- based model of the ecuadorian amazon colonization and exposure to oil pollution hazards
Authors: Saenz Echeverria, Melio Altamir
Peláez, José Ignacio
Belem, Mahamadou
Elger, Arnaud
Durango Cordero, Juan
Ferrant, Sylvain
Gaudou, Benoit
Maestripieri, Nicolas
Jaderne Houssou, Noudéhouénou Lionel
Maurice, Laurence
Morin, Lucie
Lerigoleur, Emilie
Saqalli, Mehdi
Bouadjio Boulic, Audren
metadata.dc.ucuenca.correspondencia: Saqalli, Mehdi, mehdi.saqalli@univ-tlse2.f
Keywords: Oil pollution exposure
Historical Modeling Reconstruction
Ecuadorian Amazon
Agent-based modeling
Colonization demography
metadata.dc.ucuenca.areaconocimientofrascatiamplio: 5. Ciencias Sociales
metadata.dc.ucuenca.areaconocimientofrascatidetallado: 5.9.1 Ciencias Sociales Interdisciplinarias
metadata.dc.ucuenca.areaconocimientofrascatiespecifico: 5.9 Otras Ciencias Sociales
metadata.dc.ucuenca.areaconocimientounescoamplio: 03 - Ciencias Sociales, Periodismo e Información
metadata.dc.ucuenca.areaconocimientounescodetallado: 0314 - Sociología y Estudios Culturales
metadata.dc.ucuenca.areaconocimientounescoespecifico: 031 - Ciencias Sociales y Ciencias del Comportamiento
Issue Date: 2019
metadata.dc.ucuenca.volumen: Volumen 22, número 2
metadata.dc.source: Journal of Artificial Societies and Social Simulation JASSS
metadata.dc.identifier.doi: 10.18564 / jasss.3957
metadata.dc.type: ARTÍCULO
Abstract: 
© 2019, University of Surrey. All rights reserved. Since the 1970s, the northern part of the Amazonian region of Ecuador has been colonized with the support of intensive oil extraction that has opened up roads and supported the settlement of people from Outside Amazonia. These dynamics have caused important forest cuttings but also regular oil leaks and spills, contaminating both soil and water. The PASHAMAMA Model seeks to simulate these dynamics on both environment and population by examining exposure and demography over time thanks to a retro-prospective and spatially explicit agent-based approach. The aim of the present paper is to describe this model, which integrates two dynamics: (a) Oil companies build roads and oil infrastructures and generate spills, inducing leaks and pipeline ruptures a_ecting rivers, soils and people. This infrastructure has a probability of leaks, ruptures and other accidents that produce oil pollution a_ecting rivers, soils and people. (b) New colonists settled in rural areas mostly as close as possible to roads and producing food and/or cash crops. The innovative aspect of this work is the presentation of a qualitative-quantitative approach explicitly addressed to formalize interdisciplinary modeling when data contexts are almost always incomplete.
Description: 
Since the 1970s, the northern part of the Amazonian region of Ecuador has been colonized with the support of intensive oil extraction that has opened up roads and supported the settlement of people from Outside Amazonia. These dynamics have caused important forest cuttings but also regular oil leaks and spills, contaminating both soil and water. The PASHAMAMA Model seeks to simulate these dynamics on both environment and population by examining exposure and demography over time thanks to a retro-prospective and spatially explicit agent-based approach. The aim of the present paper is to describe this model, which integrates two dynamics: (a) Oil companies build roads and oil infrastructures and generate spills, inducing leaks and pipeline ruptures a_ecting rivers, soils and people. This infrastructure has a probability of leaks, ruptures and other accidents that produce oil pollution a_ecting rivers, soils and people. (b) New colonists settled in rural areas mostly as close as possible to roads and producing food and/or cash crops. The innovative aspect of this work is the presentation of a qualitative-quantitative approach explicitly addressed to formalize interdisciplinary modeling when data contexts are almost always incomplete. © 2019, University of Surrey. All rights reserved.
URI: http://dspace.ucuenca.edu.ec/handle/123456789/34322
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065480628&origin=inward
metadata.dc.ucuenca.urifuente: http://jasss.soc.surrey.ac.uk/index_by_issue.html
ISSN: 14607425
Appears in Collections:Artículos

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