Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.

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Main Authors: Alvarez, Stephanie, Timler, Carl J., Michalscheck, Mirja, Paas, Wim, Descheemaeker, Katrien, Tittonell, Pablo Adrian, Andersson, Jens A., Groot, Jeroen C.J.
Format: info:ar-repo/semantics/artículo biblioteca
Language:eng
Published: Plos ONE 2018-05-15
Subjects:Agricultura Familiar, Explotaciones Agrarias, Estructura Agraria, Tipología, Family Farming, Farms, Agrarian Structure, Typology, Sistemas Agrícolas,
Online Access:http://hdl.handle.net/20.500.12123/7321
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194757
https://doi.org/10.1371/journal.pone.0194757
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spelling oai:localhost:20.500.12123-73212024-02-29T11:58:27Z Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development Alvarez, Stephanie Timler, Carl J. Michalscheck, Mirja Paas, Wim Descheemaeker, Katrien Tittonell, Pablo Adrian Andersson, Jens A. Groot, Jeroen C.J. Agricultura Familiar Explotaciones Agrarias Estructura Agraria Tipología Family Farming Farms Agrarian Structure Typology Sistemas Agrícolas Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies. Estación Experimental Agropecuaria Bariloche Fil: Alvarez, Stephanie. Wageningen University & Research. Farming Systems Ecology; Holanda Fil: Timler, Carl J. Wageningen University & Research. Farming Systems Ecology; Holanda Fil: Michalscheck, Mirja. Wageningen University & Research. Farming Systems Ecology; Holanda Fil: Paas, Wim. Wageningen University & Research. Farming Systems Ecology; Holanda Fil: Descheemaeker, Katrien. Wageningen University & Research. Plant Production Systems; Holanda Fil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Naturales; Argentina Fil: Andersson, Jens A. International Maize and Wheat Improvement Center (CIMMYT); Zimbawe Fil: Groot, Jeroen C. J. Wageningen University & Research. Farming Systems Ecology Group, Plant Sciences; Holanda 2020-05-28T13:54:21Z 2020-05-28T13:54:21Z 2018-05-15 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/7321 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194757 0748-7711 https://doi.org/10.1371/journal.pone.0194757 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Plos ONE Plos One 13 (5) : sp. (Mayo 2018)
institution INTA AR
collection DSpace
country Argentina
countrycode AR
component Bibliográfico
access En linea
databasecode dig-inta-ar
tag biblioteca
region America del Sur
libraryname Biblioteca Central del INTA Argentina
language eng
topic Agricultura Familiar
Explotaciones Agrarias
Estructura Agraria
Tipología
Family Farming
Farms
Agrarian Structure
Typology
Sistemas Agrícolas
Agricultura Familiar
Explotaciones Agrarias
Estructura Agraria
Tipología
Family Farming
Farms
Agrarian Structure
Typology
Sistemas Agrícolas
spellingShingle Agricultura Familiar
Explotaciones Agrarias
Estructura Agraria
Tipología
Family Farming
Farms
Agrarian Structure
Typology
Sistemas Agrícolas
Agricultura Familiar
Explotaciones Agrarias
Estructura Agraria
Tipología
Family Farming
Farms
Agrarian Structure
Typology
Sistemas Agrícolas
Alvarez, Stephanie
Timler, Carl J.
Michalscheck, Mirja
Paas, Wim
Descheemaeker, Katrien
Tittonell, Pablo Adrian
Andersson, Jens A.
Groot, Jeroen C.J.
Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development
description Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.
format info:ar-repo/semantics/artículo
topic_facet Agricultura Familiar
Explotaciones Agrarias
Estructura Agraria
Tipología
Family Farming
Farms
Agrarian Structure
Typology
Sistemas Agrícolas
author Alvarez, Stephanie
Timler, Carl J.
Michalscheck, Mirja
Paas, Wim
Descheemaeker, Katrien
Tittonell, Pablo Adrian
Andersson, Jens A.
Groot, Jeroen C.J.
author_facet Alvarez, Stephanie
Timler, Carl J.
Michalscheck, Mirja
Paas, Wim
Descheemaeker, Katrien
Tittonell, Pablo Adrian
Andersson, Jens A.
Groot, Jeroen C.J.
author_sort Alvarez, Stephanie
title Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development
title_short Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development
title_full Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development
title_fullStr Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development
title_full_unstemmed Capturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology development
title_sort capturing farm diversity with hypothesisbased typologies: an innovative methodological framework for farming system typology development
publisher Plos ONE
publishDate 2018-05-15
url http://hdl.handle.net/20.500.12123/7321
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194757
https://doi.org/10.1371/journal.pone.0194757
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