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Typologies may be used as tools for dealing with farming system heterogeneity. This is achieved by classifying farms into groups that have common characteristics, i.e. farm types, which can support the implementation of a more tailored approach to agricultural development. This article explored patterns of farming system diversity through the classification of 70 smallholder farm households in two districts (Savelugu-Nanton and Tolon-Kumbungu) of Ghana⿿s Northern Region. Based on 2013 survey data, the typology was constructed using the multivariate statistical techniques of principal component analysis and cluster analysis. Results proposed six farm types, stratified on the basis of household, labour, land use, livestock and income variables, explaining the structural and functional differences between farming systems. Types 1 and 2 were characterized by relatively high levels of resource endowment and oriented towards non-farm activities and crop sales respectively. Types 3 and 4 were moderately resource-endowed with income derived primarily from on-farm activities. Types 5 and 6 were resource constrained, with production oriented towards subsistence. The most salient differences among farm types concerned herd size (largest for Type 1), degree of legume integration (largest for Types 2⿿4), household size and hired labour (smallest household size for Types 4 and 6, and largest proportion of hired labour for Type 4), degree of diversification into off/non-farm activities (highest for Type 1 and lowest for Type 5) and severity of resource constraints (Type 6 was most constrained with a small farm area and herd comprised mainly of poultry). It was found that livelihood strategies reflected the distinctive characteristics of farm households; with poorly-endowed types restricted to a ⿿survival strategy⿿ and more affluent types free to pursue a ⿿development strategy⿿. This study clearly demonstrates that using the established typology as a practical framework allows identification of type-specific farm household opportunities and constraints for the targeting of agricultural interventions and innovations, which will be further analysed in the research-for-development project. We conclude that a more flexible approach to typology construction, for example through the incorporation of farmer perspectives, might provide further context and insight into the causes, consequences and negotiation of farm diversity.

Somalia has frequently been affected by droughts, famines and water-related humanitarian crises. Water is scarce and the only perennial streams, the Juba and Shabelle rivers, are trans-boundary wit...

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

This study measures the long-run effect of the Abu Tawfeer media campaign in Jordan. Based on a representative sample (N = 367) conducted five years after the end of the campaign, a multivariate instrumental variable regression analysis shows that the campaign only marginally changed people’s water conservation awareness and behaviour. The rigorous methodological approach allows disentangling the distinct channels through which the effect of the conservation campaign was transmitted. Moreover, this is one of the first studies that comprehensively examines the role of awareness in determining water conservation behaviour.

Typologies are often used to understand and capture smallholder farming system heterogeneity, and may be derived using different approaches and methods. This article aims to compare a quantitative, statistical typology based on a survey dataset and multivariate analysis, with a qualitative participatory typology based on informal group sessions and activities with local stakeholders from three communities in Northern Ghana. The statistical typology resulted in six clusters, with farm households categorized on the basis of their structural (resource endowment)- and functional (production objectives/livelihood strategies) characteristics. The participatory typology identified five farm types, based primarily on endowment (farm size, income investment), gender and age-related criteria. While the entire household was adopted as the unit of analysis of the statistical typology, the participatory typology provided a more nuanced differentiation by grouping individual farmers; with possibly several farmer types per household (e.g. ‘small’ and ‘female farmers’) as well as ‘farm-less’ individuals as a result. Other sources of dissimilarity which contributed to limited overlap between the typologies included changes that occurred in the communities between the two data collection efforts and inaccuracies in the data. The underlying causes of the latter seemed to mainly relate to socio-cultural issues that distorted information collection in both typologies; including power and status differences between both the researchers and farmers, as well as the farmers themselves. We conclude that although statistical techniques warrant objectivity and reproducibility in the analysis, the complexity of data collection and representation of the local reality might limit their effectiveness in selection of farms, innovation targeting and out-scaling in R4D projects. In addition, while participatory typologies offer a more contextualized representation of heterogeneity, their accuracy can still be compromised by socio-cultural constraints. Therefore, we recommend making effective use of the advantages offered by each approach by applying them in a complementary manner.