The use of indigenous climate forecasting methods by the pastoralists of Northern Kenya

Abstract

This paper focused on the early warning signs of climate variation as indicated by the Borana community of Isiolo County, Kenya. The objective of the study was to determine the indigenous early warning signs used by the Borana to predict the onset of rainfall, floods and droughts and their efficacy. The study was guided by cultural ecological theory, and data was collected through secondary sources, semi-structured interviews, focus group discussions and direct observation. The findings revealed that the Borana had many indigenous early warning signs to predict different weather changes. These included the behaviour of animals and birds, presence of insects, clouds, the colour of the intestines of slaughtered domestic animals, interpreting dreams, flowering of plants and the pattern of stars. The study also indicated that the indigenous early warning signs have been reliable since time immemorial; however, the increasing severity and frequency of drought over the last decade has rendered indigenous forecasting less reliable than it has been in the past. Early warning of weather changes is very important as it helps the community to apply the most appropriate coping strategy when faced with certain natural calamities. This study recommends a combination of the existing indigenous early warning indicators with modern forecasting methods, to make them more appropriate.

Climate change perception and impacts on cattle production in pastoral communities of northern Tanzania

“…Findings from this study revealed the use of 'indigenous knowledge' by shine elders (these are lead elders with particular knowledge and responsibility in the community) and 'common sense' as frequent sources of climate information especially for pastoralists to forecast the onset of rainfall or prediction for a bad or a good year. Other studies in similar communities have also reported the use of 'indigenous knowledge' for predicting rains or droughts (Abate 2016;Kagunyu et al 2016;Egeru 2016). However, due to increasing climate variability and uncertainties, the traditional forecasting methods are perceived to be less reliable (Kagunyu et al 2016).…”

“…Other studies in similar communities have also reported the use of 'indigenous knowledge' for predicting rains or droughts (Abate 2016;Kagunyu et al 2016;Egeru 2016). However, due to increasing climate variability and uncertainties, the traditional forecasting methods are perceived to be less reliable (Kagunyu et al 2016). The modern/formal pathways represented by radio and television were not seen by participants as a reliable means for gaining climate information.…”

“…This reflects the fact that the majority of pastoralists are rural dwellers where there is limited access to radio and television. Information on climate risks is vital for improving resilience particularly for the most vulnerable pastoral communities (Kagunyu et al 2016). When pastoralists are aware of possible extreme weather events and change in weather conditions, they are more likely to respond positively by applying appropriate coping strategies (Silvestri et al 2012).…”

A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1

“…A4a, c). Kauffman and Cummings (1998), looking at three other pastures in Amazonia, found a range of 0.8-1.5 kgC m −2 of fine fuels, which included both live and dead leaf material as well as fine woody debris. Again, this corresponds well with our results (Fig.…”

A fire model with distinct crop, pasture, and non-agricultural burning: Use of new data and a model-fitting algorithm for FINALv1

“…Climate change has and will continue to affect the timing, length, and quality of growing seasons (Porter et al, 2014); the associated impacts on planting and harvest date will affect the timing of crop residue burning, and people will shift the timing of burns to match the shifting phenology and how much to burn. Literature reviews and new research could shed light on indigenous methods for climate forecasting based on changes in the weather and vegetation (e.g., Kagunyu et al, 2016), as well as how these cues might be tied to the timing of prescribed fire for various purposes (e.g., Laris, 2002). Advanced analytical methods could also be applied to climate and fire history observations to look for lagged, region-specific relationships of agricultural burning with weather at weekly to 10 monthly time scales.…”