Ethnographic context and spatial coherence of climate indicators for farming communities - A multi-regional comparative assessment

Accurate seasonal predictions of rainfall may reduce climatic risks that farmers are usually faced with across the tropical and subtropical zones. However, although regional-scale seasonal amounts have regularly been forecasted since 1997/98, the practical use of these seasonal predictions is still limited by myriad factors. This paper synthesizes the main results of a multi-disciplinary ethnographic and climatic project (PICREVAT). Its main objective was to seek the climatic information – beyond the seasonal amounts – critical for crops, both as an actual constraint to crop yields and as identified by the current and past practices and perceptions of farmers. A second goal was to confront the relevance and significance of this climatic information with its spatial coherence, which gives an upper bound of its potential predictability. The ethnographic and climatic analyses were carried out on three very different fields: North Cameroon (mixed food crops associated with a cash crop – cotton – integrated into a national program); Eastern slopes of Mt Kenya (mixed food crops, with a recent development of maize at the expense of sorghum and pearl millet); and Central Argentina (mixed crops and livestock recently converting to monoculture of transgenic soybean, referred to as soybeanization).The ethnographic surveys, as well as yield–climate functions, emphasized the role played by various intra-seasonal characteristics of the rainy seasons beyond the seasonal rainfall amounts, in both actual yields and people’s representations and/or crop management strategies. For instance, the onset of the rainy season in East Africa and North Cameroon, the season duration in the driest district of the eastern slopes of Mount Kenya, or rains at the core (August) and at the end of the rainy season in North Cameroon have been highlighted. The dynamics of farming systems (i.e. soybeanization in Central Argentina, increasing popularity of maize in East Africa, recent decline of cotton in North Cameroon) were also emphasized as active drivers; these slow changes could increase climatic vulnerability (i.e. soybean is far more sensitive to rainfall variations than wheat, maize is less drought-resistant than sorghum or millet), at least for the least flexible actors (such as the non-capitalized farmers in Central Argentina). The cross between ethnographic surveys and climatic analyses enabled us to identify climate variables that are both useful to farmers and potentially predictable. These variables do not appear to be common across the surveyed fields. The best example is the rainy season onset date whose variations, depending on regions, crop species and farming practices may either have a major/minor role in crop performance and/or crop management, or may have a high/low potential predictability.