Functional farm household typologies through archetypal responses to disturbances

Methods to construct farm household typologies may differ in their approach but they share a common feature: they rely mostly on structural farm data. Methods to build functional typologies are far less abundant. Households or communities are complex social-ecological systems that often exhibit patt...

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Autores principales: Tittonell, Pablo Adrian, Bruzzone, Octavio Augusto, Solano-Hernández, A., López-Ridaura, Santiago, Easdale, Marcos Horacio
Formato: Artículo
Lenguaje:Inglés
Publicado: Elsevier 2020
Materias:
Acceso en línea:http://hdl.handle.net/20.500.12123/6968
https://www.sciencedirect.com/science/article/abs/pii/S0308521X18314379
https://doi.org/10.1016/j.agsy.2019.102714
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author Tittonell, Pablo Adrian
Bruzzone, Octavio Augusto
Solano-Hernández, A.
López-Ridaura, Santiago
Easdale, Marcos Horacio
author_browse Bruzzone, Octavio Augusto
Easdale, Marcos Horacio
López-Ridaura, Santiago
Solano-Hernández, A.
Tittonell, Pablo Adrian
author_facet Tittonell, Pablo Adrian
Bruzzone, Octavio Augusto
Solano-Hernández, A.
López-Ridaura, Santiago
Easdale, Marcos Horacio
author_sort Tittonell, Pablo Adrian
collection INTA Digital
description Methods to construct farm household typologies may differ in their approach but they share a common feature: they rely mostly on structural farm data. Methods to build functional typologies are far less abundant. Households or communities are complex social-ecological systems that often exhibit patterns in their response to disturbances (e.g., droughts, floods, price shocks, policy change). We propose building functional typologies – classifiable ´behaviours´ of rural actors – using archetype analysis to categorise such responses and identify salient behaviours. We illustrate this approach by examining the response of rural households to recurrent droughts in northern Patagonia, Argentina, as revealed by 23 in-depth interviews about perceptions and strategies concerning droughts. Using the algorithm from Mørup and Hansen (2012), and the corrected Akaike decision rule, we identified three archetypes (A–C) that represented three distinct aggregated responses of households to droughts. Archetype A presented variable degrees of resistance to droughts (production losses<40%), avoidance and diversification, whereas archetype B exhibited tolerance (higher losses) and some degree of transformability (off-farm income). Archetype C farms exhibited high levels of vulnerability, if some degree of tolerance to high losses, but no real adaptive strategy to speak of. Such pattern could not have been identified through the more commonly used typology building methods such as using multivariate and clustering techniques. By allowing to combine qualitative and quantitative information, and to deal with a relatively small number of observations, archetype analysis appears as highly suitable to delineate functional farm household typologies.
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spelling INTA69682020-03-19T13:42:30Z Functional farm household typologies through archetypal responses to disturbances Tittonell, Pablo Adrian Bruzzone, Octavio Augusto Solano-Hernández, A. López-Ridaura, Santiago Easdale, Marcos Horacio Construcciones Vivienda Vivienda Rural Sequía Vulnerabilidad Adaptación Buildings Housing Rural Housing Drought Vulnerability Adaptation Región Patagónica Sistemas Rurales Methods to construct farm household typologies may differ in their approach but they share a common feature: they rely mostly on structural farm data. Methods to build functional typologies are far less abundant. Households or communities are complex social-ecological systems that often exhibit patterns in their response to disturbances (e.g., droughts, floods, price shocks, policy change). We propose building functional typologies – classifiable ´behaviours´ of rural actors – using archetype analysis to categorise such responses and identify salient behaviours. We illustrate this approach by examining the response of rural households to recurrent droughts in northern Patagonia, Argentina, as revealed by 23 in-depth interviews about perceptions and strategies concerning droughts. Using the algorithm from Mørup and Hansen (2012), and the corrected Akaike decision rule, we identified three archetypes (A–C) that represented three distinct aggregated responses of households to droughts. Archetype A presented variable degrees of resistance to droughts (production losses<40%), avoidance and diversification, whereas archetype B exhibited tolerance (higher losses) and some degree of transformability (off-farm income). Archetype C farms exhibited high levels of vulnerability, if some degree of tolerance to high losses, but no real adaptive strategy to speak of. Such pattern could not have been identified through the more commonly used typology building methods such as using multivariate and clustering techniques. By allowing to combine qualitative and quantitative information, and to deal with a relatively small number of observations, archetype analysis appears as highly suitable to delineate functional farm household typologies. Estación Experimental Agropecuaria Bariloche Fil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Consejo Nacional de Investigaciones Cientificas y Técnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina. Groningen University. Groningen Institute of Evolutionary Life Sciences; Holanda. Université de Montpellier. Centre de coopération Internationale en Recherche Agronomique pour le Développement (CIRAD). Agroécologie et Intensification Durable (AïDA); Francia Fil: Bruzzone, Octavio Augusto. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Consejo Nacional de Investigaciones Cientificas y Técnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina Fil: Solano-Hernández, A. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Consejo Nacional de Investigaciones Cientificas y Técnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina Fil: López-Ridaura, Santiago. Centro Internacional de Mejoramiento de Maíz y Trigo; Mexico Fil: Easdale, Marcos Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Consejo Nacional de Investigaciones Cientificas y Técnicas. Instituto de Investigaciones Forestales y Agropecuarias Bariloche; Argentina 2020-03-19T13:29:38Z 2020-03-19T13:29:38Z 2020-02 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/6968 https://www.sciencedirect.com/science/article/abs/pii/S0308521X18314379 0308-521X https://doi.org/10.1016/j.agsy.2019.102714 eng info:eu-repo/semantics/restrictedAccess application/pdf Elsevier Agricultural Systems 178 : 102714 (Febrero 2020)
spellingShingle Construcciones
Vivienda
Vivienda Rural
Sequía
Vulnerabilidad
Adaptación
Buildings
Housing
Rural Housing
Drought
Vulnerability
Adaptation
Región Patagónica
Sistemas Rurales
Tittonell, Pablo Adrian
Bruzzone, Octavio Augusto
Solano-Hernández, A.
López-Ridaura, Santiago
Easdale, Marcos Horacio
Functional farm household typologies through archetypal responses to disturbances
title Functional farm household typologies through archetypal responses to disturbances
title_full Functional farm household typologies through archetypal responses to disturbances
title_fullStr Functional farm household typologies through archetypal responses to disturbances
title_full_unstemmed Functional farm household typologies through archetypal responses to disturbances
title_short Functional farm household typologies through archetypal responses to disturbances
title_sort functional farm household typologies through archetypal responses to disturbances
topic Construcciones
Vivienda
Vivienda Rural
Sequía
Vulnerabilidad
Adaptación
Buildings
Housing
Rural Housing
Drought
Vulnerability
Adaptation
Región Patagónica
Sistemas Rurales
url http://hdl.handle.net/20.500.12123/6968
https://www.sciencedirect.com/science/article/abs/pii/S0308521X18314379
https://doi.org/10.1016/j.agsy.2019.102714
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