Knowledge is like a bird of the forest, one person alone can never catch it (Ewe proverb) Pursuing the Bird of the Forest: Advances in Ethnographic and Participatory Methods C. Roncoli et al Climate Forecasting and Agricultural Resources Project University of Georgia Photo by Christine Jost

Structure of this review Ethnographic and participatory methods Cognitive and cultural setting (front-end) Cultural models of climate Local forecasting knowledge Representing probability Constructing credibility Decision processes and decision makers (back-end) Learning forecast responses Characterizing decision makers Understanding constraints Institutional environment Conclusions

Ethnography and participation: strengths ‘Insider’ point of view Contextual understanding Rapport with research subjects

Ethnography and participation: weaknesses Reliance on key informants may introduce biases Public nature of participatory methods favors prominent, educated members of community Group-based methods obfuscate difference, dissent Emphasis on local context makes findings less generalizeable May neglect structural analysis of power relations that local to global

Cultural and cognitive context: cultural models of climate Ziervogel and Calder 2003 Seasonal calendar (local classification of time) Activity calendars (constraints, entry points) Significant event calendars (rainfall and yields)

Cultural and cognitive context cultural models of climate Moore typology of rain events, Central Plateau, Burkina Faso, CFAR project

Cultural and cognitive context cultural models of climate Influence diagram of farmer mental model of climate variability Hansen et al 2004 Morgan MG, et al (2002) Risk communication: a mental model approach. Cambridge University Press

Cultural and cognitive context local forecasting knowledge Hansen et al 2004 Luseno et 2003 Key informant interviews with local experts, Focus groups to compile inventories of indicators and their attributes Surveys to validate the distribution across representative samples of the population. Ranking of indicators according to levels of confidence

Cultural and cognitive context local forecasting knowledge Ziervogel and Calder 2003 Luseno et al 2003

Cultural and cognitive context local forecasting knowledge Hansen et al 2004 “relatively malleable knowledge that is finely tuned to the continually changing circumstances that define a particular locality” (De Walt, in Eakin 1999).

Cultural and cognitive context representing probability Examples from farmers’ daily life more effective than instructional games or tools

Cultural and cognitive context representing probability Roncoli et al 2005 Operationalizing comprehension of terciles (Phillips and Orlove 2003): a) least two outcomes are possible b) at least some possibility of the occurrence of three possible outcomes c) highest ranked outcome likely to occur but not for certain

Cultural and cognitive context representing probability The role of media

Cultural and cognitive context representing probability SOFITEX (cotton export company) memo to field agents, announcing that ‘meteorological predictions seem to indicate a ‘good’ rainy season

Cultural and cognitive context constructing credibility Luseno et al 2003 formal education, off-farm income urban residence, access to roads appear to be associated with lower level of confidence in local predictions among Bolivian farmers and East African pastoralists (Valdivia et al 2000, Luseno et al 2003)

Cultural and cognitive context constructing credibility Ziervogel 2004

… it must be recalled that at the beginning of the season farmers were afraid because of a difficult onset of the rains, some farmers had to plant five times before rains got established in July. Today we can thank God that until now we continue to receive rain and the harvest will be good this year, there is the proof (sorghum field)… Cultural and cognitive context constructing credibility

Decision processes and decision makers simulating farmer responses C. Gladwin (1989) Ethnographic decision tree modeling. Sage Publications.

Decision processes and decision makers simulating farmer responses Hansen et al 2004

Decision processes and decision makers simulating farmer responses Ziervogel 2004

Decision processes and decision makers characterizing decision makers Archer 2003

Decision processes and decision makers characterizing decision makers Roncoli et al (2001) livestock and assets Finan and Nelson (2002) production of subsistence crops cash crop sales livestock assets

Decision processes and decision makers characterizing decision makers Valdivia et al 2003 Livelihood portfolios (Bolivia, Peru)

Decision processes and decision makers understanding constraints Land (Vogel 2000) Inputs (Phillips et al 2001) Seed (Ingram et al 2002) Farm credit (Vogel 2000, Phillips et al 2001) Animal traction (Phillips et al 2001, Ingram et al 2002) Information is not enough! (O’Brien et al 1999)

Decision processes and decision makers understanding constraints Zimbabwe, Phillips et al (2001) found that among 225 farmers: many considered climate forecasts to be accurate but few used them. In Kenya and Ethiopia, Luseno et al (2003) found that among 300 pastoralists few used local or scientific forecasts. In Argentina Letson et al (2001) found that more than half of those who heard the La Nina forecast of 1998/99 did not change their decisions. In Bolivian and Peru Valdivia and Gere (2000) found that, while most farmers were aware of the El Niño/La Niña, only a few innovators adapted their production. In Brazil, Lemos et al (2002) found that few farmers in northeast Brazil believed or used scientific forecasts.

Decision processes and decision makers understanding constraints Roncoli et al 2005

Decision processes and decision makers Institutional environment Pfaff et al 2002

Decision processes and decision makers Institutional environment Ziervogel and Downings 2004

Sustainable livelihood approaches Valdivia et al 2003 Ziervogel and Calder 2003

The way forward….