Department of Environmental sciences, University of Botswana, 4775 Notwane Road, Private Bag 00704, Gaborone, Botswana.
International Food Policy and Research Institute, 2033 K Street, NW, Washington, DC, 20006-1002, USA.
Environ Manage. 2020 Apr;65(4):500-516. doi: 10.1007/s00267-020-01264-x. Epub 2020 Feb 15.
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.
本文探讨了在乌干达西部鲁文佐里地区,使用本土预测(IF)和科学预测(SF)对耕地农民适应方法的影响。尽管国家气象系统传播了科学预测(SF),但农村地区的耕地农民仍然非常容易受到气候变化的影响。本研究采用混合方法,在选择 580 名耕地农民进行调查时采用了随机和分层抽样。通过家庭调查和焦点小组讨论收集数据,并使用多元概率模型进行分析。研究结果表明,仅使用 IF 会积极影响作物多样化、水土保持。同时使用 SF 和 IF 会积极影响畜牧业多样化。仅使用 IF 或同时使用 SF 和 IF 会积极影响植树和树木作物生产作为适应策略。本研究建议,尽管预测是适应的重要驱动因素,但其他因素也有助于加强适应气候变化的努力,例如通过更多地承认正式的习惯权利和土地保有权,以及通过农民间网络建设提高土地权,同时传播气候变化信息。国家政府和发展伙伴增加不同农业生态区的气象站数量,将提高科学预测的预测准确性和局部特异性,从而改善气候变化适应。