Tulane University School of Public Health & Tropical Medicine, 1440 Canal Street, New Orleans, LA, 70112, USA.
Wenzhou-Kean University, Zhejiang Province, Wenzhou, 325060, China.
Ambio. 2024 Mar;53(3):435-451. doi: 10.1007/s13280-023-01954-w. Epub 2023 Dec 15.
Seasonal hunger is the most common food insecurity experience for millions of small dryland farmers. This study tests the relationships between food insecurity, farm forests, and biomass poverty using a longitudinal dataset from the Amhara region of Ethiopia. These data form part of the Ethiopia Socioeconomic Survey, which collected panel data over three survey rounds from 530 households between 2011 and 2016. This dataset represents a collection of unique socioeconomic, wellbeing, and micro-land use measures, including farm forests. Hierarchical mixed effect regression models assessed the relationship between food insecurity and farm forests as well as the conditional effects of biomass poverty among the poorest farmers and women-headed households. Over a six-year study period, farmers reported increased stress from smaller land holdings, higher prices, and climate-related shocks. A clear trend towards spontaneous dispersed afforestation is observed by both researchers and satellite remote sensing. Model results indicate, dedicating approximately 10% of farm area to forest reduces months of food insecurity by half. The greatest reductions in food insecurity from farm forests are reported by ultra-poor and crop residue-burning households, suggesting that biomass poverty may be a major constraint to resilient food security on these farms. This research provides novel quantitative evidence of induced intensification and food security impacts of farm management preserving and building stores of biomass value as green assets. The results reported here have important implications for nature-based solutions as a major strategy to achieve sustainable development in some contexts.
季节性饥饿是数以百万计的小型旱地农民最常见的粮食不安全经历。本研究使用来自埃塞俄比亚阿姆哈拉地区的纵向数据集,测试了粮食不安全、人工林和生物质贫困之间的关系。这些数据是埃塞俄比亚社会经济调查的一部分,该调查在 2011 年至 2016 年期间通过三轮调查从 530 户家庭中收集了面板数据。该数据集代表了一系列独特的社会经济、福利和微观土地利用措施,包括人工林。分层混合效应回归模型评估了粮食不安全与人工林之间的关系,以及生物质贫困对最贫困农民和妇女户主家庭的条件影响。在六年的研究期间,农民报告说,土地持有量减少、价格上涨和与气候相关的冲击使他们面临更大的压力。研究人员和卫星遥感都观察到了自发分散造林的明显趋势。模型结果表明,将约 10%的农场面积用于造林可将粮食不安全月数减少一半。来自超贫和农作物残茬燃烧家庭的人工林对粮食不安全的缓解作用最大,这表明生物质贫困可能是这些农场实现有弹性粮食安全的主要制约因素。本研究提供了关于人工林管理对粮食安全的诱发强化和影响的新的定量证据,将生物质价值储存和积累为绿色资产作为一种强化管理的方法。这里报告的结果对基于自然的解决方案具有重要意义,因为在某些情况下,这是实现可持续发展的主要战略。