Agricultural livelihoods in coastal Bangladesh under climate and environmental change - a model framework
Agricultural livelihoods in coastal Bangladesh under climate and environmental change - a model framework
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DOI：
10.1039/c4em00600c
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发表时间：
2015-01-01
影响因子：
5.5
通讯作者：
Moslehuddin, Abu Zofar Md.
中科院分区：
文献类型：
--
作者：
Lazar, Attila N.;Clarke, Derek;Moslehuddin, Abu Zofar Md.
孟加拉国沿海地区今天经历着严重的贫困和灾害，在未来几十年中极易受到气候和环境变化的影响。沿海利益攸关方要求获得信息，以协助决策进程，包括模拟模型，以探讨在不同的合理的未来社会经济和环境情景下，不同的干预措施如何减轻环境风险和促进发展。许多现有的模拟模型忽略了孟加拉国沿海地区的社会经济和环境系统之间复杂的相互依赖关系。在这方面，提出了一种综合办法，以开发一个模拟模型，支持孟加拉国沿海地区的农业和基于贫穷的分析和决策。特别是，我们展示了如何在家庭层面上的农民的生计模拟模型可以实现。粮农组织的CROPWAT农业模型的扩展版本已与缩小规模的区域人口模型相结合，以模拟农业净利润。这与家庭收支平衡和贷款逻辑树一起用来模拟粮食安全指标和贫困程度的演变。模拟确定，由于大气中的二氧化碳浓度是一个强化因素，盐度和温度胁迫是作物生产力和施肥的限制因素。作物模拟结果与预期结果比较良好，但也揭示了一些意想不到的行为。例如，根据目前的模型假设，温度比盐度对作物生产更重要。以农业为基础的生计和贫穷模拟突出表明，通过非正式和正式贷款产生的债务水平持续损害以农业为生的家庭的福祉，这一点至关重要。模拟还表明，由于更容易受到气候变化的影响，从定价的角度来看，渐进的农业方法（即多元化）可能无法提供明显的经济效益。生计和贫穷问题的结果突出表明，必须从整体上考虑人与自然系统，并认真选择贫穷指标。尽管现阶段的模拟模型包含了模拟孟加拉国沿海地区农民生计相互作用的复杂性所需的最低要素，但作物和社会经济调查结果与预期行为相比很好。所提出的综合模型是第一步，开发一个整体的，可转移的分析方法和工具，沿海孟加拉国。
Coastal Bangladesh experiences significant poverty and hazards today and is highly vulnerable to climate and environmental change over the coming decades. Coastal stakeholders are demanding information to assist in the decision making processes, including simulation models to explore how different interventions, under different plausible future socio-economic and environmental scenarios, could alleviate environmental risks and promote development. Many existing simulation models neglect the complex interdependencies between the socio-economic and environmental system of coastal Bangladesh. Here an integrated approach has been proposed to develop a simulation model to support agriculture and poverty-based analysis and decision-making in coastal Bangladesh. In particular, we show how a simulation model of farmer's livelihoods at the household level can be achieved. An extended version of the FAO's CROPWAT agriculture model has been integrated with a downscaled regional demography model to simulate net agriculture profit. This is used together with a household income-expenses balance and a loans logical tree to simulate the evolution of food security indicators and poverty levels. Modelling identifies salinity and temperature stress as limiting factors to crop productivity and fertilisation due to atmospheric carbon dioxide concentrations as a reinforcing factor. The crop simulation results compare well with expected outcomes but also reveal some unexpected behaviours. For example, under current model assumptions, temperature is more important than salinity for crop production. The agriculture-based livelihood and poverty simulations highlight the critical significance of debt through informal and formal loans set at such levels as to persistently undermine the well-being of agriculture-dependent households. Simulations also indicate that progressive approaches to agriculture (i.e. diversification) might not provide the clear economic benefit from the perspective of pricing due to greater susceptibility to climate vagaries. The livelihood and poverty results highlight the importance of the holistic consideration of the human-nature system and the careful selection of poverty indicators. Although the simulation model at this stage contains the minimum elements required to simulate the complexity of farmer livelihood interactions in coastal Bangladesh, the crop and socio-economic findings compare well with expected behaviours. The presented integrated model is the first step to develop a holistic, transferable analytic method and tool for coastal Bangladesh.