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气候变化适应及其影响因素研究——山东胶州湾地区居民的实证分析
引用本文:汪海欧,於琍,杨书运,吕明辉.气候变化适应及其影响因素研究——山东胶州湾地区居民的实证分析[J].中国农学通报,2019,35(11):103-109.
作者姓名:汪海欧  於琍  杨书运  吕明辉
作者单位:1.安徽省六安市金寨县气象局;2.国家气候中心;3.安徽农业大学资源与环境学院;4.中国气象局公共气象服务中心
基金项目:国家自然科学基金青年基金项目“海岸带社会-生态系统对气候变化的脆弱性与适应力机理研究——以胶州湾地区为例”(41201198)。
摘    要:为探索气候变化感知在适应决策过程中的作用机理,本研究以深度访谈数据为基础,基于“感知-适应”分析框架,采用二元Probit模型和泊松回归模型,分析胶州湾地区居民气候变化适应决策和适应选择的影响因素。研究表明,胶州湾地区绝大多数居民已经感知到气候变化,半数以上居民采取了一定的适应措施,大多数居民对适应措施效果的感到满意。居民采取适应措施介于0-4项,平均为1.07项,适应措施的普及率和多样化仍有提升空间。影响胶州湾地区居民气候变化适应决策与适应选择的主要因素存在一定差异性,但“居民对气候变化的感知”不论是对适应决策还是对适应选择的影响都较大,其中又以“对降水变化的感知”和“对气象灾害损失的感知”最为显著。

关 键 词:气候变化  感知  气候变化适应  适应决策  适应选择
收稿时间:2018/10/25 0:00:00
修稿时间:2018/11/30 0:00:00

Climate Change Adaptation and Its Influencing Factors in Jiaozhou Bay Area, Shangdong: An Empirical Analysis on Local Residents
Abstract:The paper aims to explore the mechanism of perception to climate change in the adaptive decisionmaking process. Based on the in-depth interview data and the framework of“perception-adaptation”, we analyzed the factors affecting climate change adaptation decision and options of residents in Jiaozhou Bay by using the binary Probit model and Poisson regression model. The results showed that the majority of residents already perceived climate change, and more than half of the residents adopted adaptation measures; most residents were satisfied with the effects of the adaptation measures; measures adopted by the residents were from 0 to 4, with an average of 1.07; there were still great gaps in the popularization and diversity of the adaptation measures. The results also showed that there were some differences among the main factors that affected adaptation decision and options in Jiaozhou Bay; however,“the perception to climate change of residents”had a great impact on both adaptation decision-making and adaptation options, among which“the perception of precipitation change” and“the perception of meteorological disaster loss” were the most significant factors.
Keywords:climate change perception  adaptation  adaptive decision mechanism  in-depth interview  Probit model  Poisson regression
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