论文标题
有效缓解农村贫困取决于生产力,营养,水和土壤质量之间的相互作用
Effective alleviation of rural poverty depends on the interplay between productivity, nutrients, water and soil quality
论文作者
论文摘要
世界上大多数最贫穷的人来自农村地区,并依靠其当地生态系统进行粮食生产。最近的研究强调了低土壤质量和持续贫困之间的自我强化动态的重要性,但在如何影响贫困方面鲜为人知。我们研究了家庭资产,养分(尤其是磷),水和土壤质量的交织动力学如何影响粮食生产,并确定逃避农村贫困贫困的条件。我们已经开发了一系列动态的,多维的贫困陷阱模型的家庭,这些模型将增长的经济方面与土壤质量,水和养分流的生态动态结合在一起,以分析常见减轻贫困策略的有效性,例如通过耕种,能源输入,能量来源和保护耕种的多样化,通过耕种的贫困策略来分析。我们的结果表明,(i)农业化的投入可以通过降解土壤质量来加强贫困,(ii)家庭能源的多样化可以为有效应用其他策略创造可能性,并且(iii)干预的测序可以提高保护耕作的有效性。我们基于模型的方法证明了经济和生态动力学的相互依存关系,这些动态排除了缓解贫困的解决方案。此处开发的风格化模型可用于测试目标区域中生物物理和经济环境的不同策略的有效性。
Most of the world poorest people come from rural areas and depend on their local ecosystems for food production. Recent research has highlighted the importance of self-reinforcing dynamics between low soil quality and persistent poverty but little is known on how they affect poverty alleviation. We investigate how the intertwined dynamics of household assets, nutrients (especially phosphorus), water and soil quality influence food production and determine the conditions for escape from poverty for the rural poor. We have developed a suite of dynamic, multidimensional poverty trap models of households that combine economic aspects of growth with ecological dynamics of soil quality, water and nutrient flows to analyze the effectiveness of common poverty alleviation strategies such as intensification through agrochemical inputs, diversification of energy sources and conservation tillage. Our results show that (i) agrochemical inputs can reinforce poverty by degrading soil quality, (ii) diversification of household energy sources can create possibilities for effective application of other strategies, and (iii) sequencing of interventions can improve effectiveness of conservation tillage. Our model-based approach demonstrates the interdependence of economic and ecological dynamics which preclude blanket solution for poverty alleviation. Stylized models as developed here can be used for testing effectiveness of different strategies given biophysical and economic settings in the target region.