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15.02.2020

Influence of Indigenous Knowledge and Scientific Climate Forecasts on Arable Farmers’ Climate Adaptation Methods in the Rwenzori region, Western Uganda

Zeitschrift:
Environmental Management
Autoren:
Michael Robert Nkuba, Raban Chanda, Gagoitseope Mmopelwa, Edward Kato, Margaret N. Mangheni, David Lesolle
Wichtige Hinweise
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Abstract

This paper investigates the influence of using indigenous forecasts (IF) and scientific forecasts (SF) on arable farmers’ adaptation methods in the Rwenzori region, Western Uganda. Despite the dissemination of scientific forecasts (SF) from national meteorological systems, arable farmers in rural areas are still very vulnerable to the impacts of climate variability and change. Using mixed methods approach, the study adopted random and stratified sampling in the selection of 580 arable farmers to investigate the problem under this study. Data were collected using a household survey and focus group discussions, and the multivariate probit model was used in the analysis. The findings indicated that use of IF only positively influenced crop diversification, soil and water conservation. Using both SF and IF positively influenced livestock diversification. Use of either IF only or both SF and IF positively influenced tree-planting and tree crop production as an adaptive strategy. The study recommends that although forecasts are important drivers of adaptation, other factors could also help efforts to enhance climate-change adaptation, such as improving land rights through more recognition of formal customary rights and land tenure and capacity building of farmer-to-farmer networks with climate-change information. Increasing the spread of weather stations in the different agro-ecological zones by national governments and development partners would improve the predictive accuracy and local specificity of scientific forecasts, resulting in improved climate-change adaptation.

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