Indigenous Past Climate Knowledge as Cultural Built-in Object and Its Accuracy

Abstract

ABSTRACT. In studying indigenous climate knowledge, two approaches can be envisioned. In the first, traditional knowledge is a cultural built-in object; conceived as a whole, its relevance can be assessed by referring to other cultural, economic, or technical components at work within an indigenous society. In the second, the accuracy of indigenous climate knowledge is assessed with western science knowledge used as an external reference. However, assessing the accuracy of indigenous climate knowledge remains a largely untapped area. We aim to show how accurate the culturally built indigenous climate knowledge of extreme climatic events is, and how amenable it is to fuzzy logic. A retrospective survey was carried out individually and randomly among 195 Eastern African farmers on climatic reasons for loss of on-farm crop diversity from 1961 to 2006. More than 3000 crop loss events were recorded, and reasons given by farmers were mainly related to droughts or heavy rainfall. Chisquare statistics computed by Monte Carlo simulations based on 999 replicates clearly rejected independence between indigenous knowledge of drought and heavy rainfall that occurred in the past and rainfall records. The fuzzy logic nature of indigenous climatic knowledge appears in the clear association of drought or heavy rainfall events, as perceived by farmers, with corresponding extreme rainfall values, contrasting with a fuzzy picture in the intermediate climatic situations. We discuss how the cultural built-in knowledge helps farmers in perceiving and remembering past climate variations, considering the specificity of the contexts where extreme climatic events were experienced. The integration of indigenous and scientific climate knowledge could allow development of drought monitoring that considers both climatic and contextual data.

Climate smart agriculture rapid appraisal (CSA-RA): A tool for prioritizing context-specific climate smart agriculture technologies

“…Although recorded data is often used to assess climate variability, farmer reports allow us to translate it not only to climate events but also how they are experienced by different groups. Leclerc et al (2013) have shown that farmer knowledge of past extreme climatic events is in agreement with climatic records. Assessment of climate vulnerability and impacts on livelihoods is integral, as CSA aims to improve the adaptive capacity of agricultural systems to climate stress, while decreasing GHG-emissions from agricultural practices contributing to climate change (Campbell et al, 2014;Harvey et al, 2014).…”

Local perceptions as a guide for the sustainable management of natural resources: empirical evidence from a small-scale society in Bolivian Amazonia

“…On the one hand, perceptions of environmental change are based on factual and direct knowledge or continued observation of biophysical phenomena (Gearheard et al 2010, Orlove et al 2010. On the other hand, they also encompass embodied experience directly acquired through perceptual information (Leclerc et al 2013). Given this dual character, the literature has to date interchangeably used the terms "perception" (e.g., Oldekop et al 2012) and "knowledge" (e.g., Riseth et al 2011) to refer to accounts of environmental changes reported by small-scale societies.…”

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

“…In this paper we synthesize the main results of a multidisciplinary framework, the PICREVAT project (January 2009-June 2013), combining statistical analyses of interannual and intra-annual variability of rainfall and of crop-rainfall relationships (papers by Boyard-Micheau et al, 2013;Moron et al, 2013;Camberlin et al, 2014;Philippon et al, 2015a,b;Hernández et al, 2015) with ethnographic surveys (papers by Leclerc et al, 2013Leclerc et al, , 2014Mwongera et al, 2014;Hernández et al, 2015). All the agro-climatic and ethnographic analyses were carried out on three contrasted fields: (1) North Cameroon in the SudanoSahelian belt, mixing cotton with subsistence crops (mainly sorghum and maize); (2) Kenya and North Tanzania (Camberlin et al, 2009Philippon et al, 2015a,b) with a focus on eastern slopes of Mt Kenya, where small-scale subsistence farming is based on mixed cropping systems but maize has gradually surpassed traditional (and less drought-vulnerable) crops like sorghum and pearl millet (Leclerc et al, 2013Mwongera et al, 2014); and (3) central Pampa in Argentina, where the farming system has recently shifted from mixed crops and livestock to dominant transgenic soybean cropping system (Magrin et al, 2005;Pengue, 2005Pengue, , 2006Caviglia and Andrade, 2010;Hernandez et al, 2015).…”

“…All the agro-climatic and ethnographic analyses were carried out on three contrasted fields: (1) North Cameroon in the SudanoSahelian belt, mixing cotton with subsistence crops (mainly sorghum and maize); (2) Kenya and North Tanzania (Camberlin et al, 2009Philippon et al, 2015a,b) with a focus on eastern slopes of Mt Kenya, where small-scale subsistence farming is based on mixed cropping systems but maize has gradually surpassed traditional (and less drought-vulnerable) crops like sorghum and pearl millet (Leclerc et al, 2013Mwongera et al, 2014); and (3) central Pampa in Argentina, where the farming system has recently shifted from mixed crops and livestock to dominant transgenic soybean cropping system (Magrin et al, 2005;Pengue, 2005Pengue, , 2006Caviglia and Andrade, 2010;Hernandez et al, 2015). A major goal of PICREVAT was to analyze the critical climatic information for crops, both as a constraint on yields through a classical production-function approach linking observed yields and climate variations (Mendelsohn et al, 1994), and as explicitly identified by local farmers and stakeholders, either through their farming practices or their perception/memory of any adverse climate events detrimental to farming.…”