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resumen

Resumen
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 [ver mas...]
dc.contributor.authorAlvarez, Stephanie
dc.contributor.authorTimler, Carl J.
dc.contributor.authorMichalscheck, Mirja
dc.contributor.authorPaas, Wim
dc.contributor.authorDescheemaeker, Katrien
dc.contributor.authorTittonell, Pablo Adrian
dc.contributor.authorAndersson, Jens A.
dc.contributor.authorGroot, Jeroen C.J.
dc.date.accessioned2020-05-28T13:54:21Z
dc.date.available2020-05-28T13:54:21Z
dc.date.issued2018-05-15
dc.identifier.issn0748-7711
dc.identifier.otherhttps://doi.org/10.1371/journal.pone.0194757
dc.identifier.urihttp://hdl.handle.net/20.500.12123/7321
dc.identifier.urihttps://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194757
dc.description.abstractCreating 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.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherPlos ONEes_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourcePlos One 13 (5) : sp. (Mayo 2018)es_AR
dc.subjectAgricultura Familiares_AR
dc.subjectFamily Farmingeng
dc.subjectExplotaciones Agrariases_AR
dc.subjectFarmseng
dc.subjectEstructura Agrariaes_AR
dc.subjectAgrarian Structureeng
dc.subjectTipologíaes_AR
dc.subjectTypologyeng
dc.subject.otherSistemas Agrícolases_AR
dc.titleCapturing farm diversity with hypothesisbased typologies: An innovative methodological framework for farming system typology developmentes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.description.origenEstación Experimental Agropecuaria Barilochees_AR
dc.description.filFil: Alvarez, Stephanie. Wageningen University & Research. Farming Systems Ecology; Holandaes_AR
dc.description.filFil: Timler, Carl J. Wageningen University & Research. Farming Systems Ecology; Holandaes_AR
dc.description.filFil: Michalscheck, Mirja. Wageningen University & Research. Farming Systems Ecology; Holandaes_AR
dc.description.filFil: Paas, Wim. Wageningen University & Research. Farming Systems Ecology; Holandaes_AR
dc.description.filFil: Descheemaeker, Katrien. Wageningen University & Research. Plant Production Systems; Holandaes_AR
dc.description.filFil: Tittonell, Pablo Adrian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bariloche. Área de Recursos Naturales; Argentinaes_AR
dc.description.filFil: Andersson, Jens A. International Maize and Wheat Improvement Center (CIMMYT); Zimbawees_AR
dc.description.filFil: Groot, Jeroen C. J. Wageningen University & Research. Farming Systems Ecology Group, Plant Sciences; Holandaes_AR
dc.subtypecientifico


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