研究报道

黑龙江省漠河县乡村人群对气候变化的感知方式与认知结果

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  • 1. 北京师范大学地理学与遥感科学学院, 北京 100875;
    2. Atmospheric Sciences Research Center, State University of New York, Albany, NY12202, USA
云雅如(1978- ),女(蒙古族),内蒙古呼和浩特市人,在站博士后,主要从事气候变化的影响与适应性对策研究。E-mail: yaru.yun@gmail.com

收稿日期: 2008-09-17

  修回日期: 2009-02-20

  网络出版日期: 2009-09-20

基金资助

国家自然科学基金项目(40501026,40271115)、北师大青年教师基金项目(319107190)资助。

Peasants'Perception and Cognition to Climate Change in Mohe County, Heilongjiang Province

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  • 1. School of Geography, Beijing Normal University, Beijing 100875;
    2. Atmospheric Sciences Research Center, State University of New York, Albany, NY12202, USA

Received date: 2008-09-17

  Revised date: 2009-02-20

  Online published: 2009-09-20

摘要

以中国东北地区漠河县气象站点1960~2005年逐日平均气温数据为参照,通过问卷调查和访谈的方式,探讨漠河县乡村人群感知气候变化的方式与特征,以及认知的形成过程。结果发现:生活活动、生产活动和观察自然现象是漠河县乡村人群感知气候变化的主要途径,其中人群对生活活动的敏感度最高;基于上述感知渠道,乡村人群形成了对当地过去50 a气候变化总体趋势、极端天气现象和四季持续时间的认知。

本文引用格式

云雅如, 方修琦, 田青, 张学珍 . 黑龙江省漠河县乡村人群对气候变化的感知方式与认知结果[J]. 地理科学, 2009 , 29(5) : 745 -749 . DOI: 10.13249/j.cnki.sgs.2009.05.745

Abstract

Climate change marked by global warming had been becoming an inconvenient fact and changing the world remarkably. Human behavior as the most significant determinant constraints the adaptation to climate change. Based on the statistic data and information from investigation in Mohe, Heilongjiang Province, theories of Environmental Psychology and Behavioral Economics have been used to analyze the human perception and cognition to climate change. (1) Life activities, agricultural production activities and natural phenomena observation activities are three important paths of human perception. Among them, people are more sensitive to the change of life activities, and then the natural phenomena. (2) On the basis of the perception, peasants’ environmental cognition have been formed, which showed that the temperature has continued to increase from the 1960s, the beginning and the end time of four seasons have changed, as well as the duration of them. (3) Human cognition on climate change in Mohe corresponds well with the statistic data.

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