收藏设为首页 广告服务联系我们在线留言

干旱区地理 ›› 2020, Vol. 43 ›› Issue (1): 237-247.doi: 10.12118/j.issn.1000-6060.2020.01.27

• 区域发展 • 上一篇    下一篇

秦巴山特困区农户生计资本及生计策略研究——以商洛市为例

刘倩12,张2何艳冰3杨新军2   

  1. 1 重庆师范大学地理与旅游学院,重庆401331 2 西北大学城市与环境学院,陕西西安710127; 3 河南理工大学建筑与艺术设计学院,河南焦作454000
  • 收稿日期:2019-07-24 修回日期:2019-11-07 出版日期:2020-01-05 发布日期:2020-01-05
  • 通讯作者: 杨新军(1972-),男,陕西扶风人,教授,博士生导师,主要从事旅游地理学与人地关系的社会—生态系统整合研究.
  • 作者简介:刘倩(1989-),女,山东肥城人,博士研究生,主要从事乡村发展与农户生计研究. E-mail: liuqianvivi@163.com
  • 基金资助:
    国家自然科学基金项目(41771574);重庆师范大学基金项目(19XLB008)

Livelihood capital and livelihood strategies of the farmer household in the exceptional poverty regions of Qinling-Daba mountainous area:A case of Shangluo City

LIU Qian1,2,ZHANG Jian2,HE Yan-bing3,YANG Xin-jun2   

  1. 1 School of Geography And Tourism,Chongqing Normal University,Chongqing 401331,China;  (2 College of Urban and Environmental Sciences,Northwest University,Xi’an 710127,Shaanxi,China; 3 School of Architectural and Artistic Design,Henan Polytechnic University,Jiaozuo 454000,Henan,China
  • Received:2019-07-24 Revised:2019-11-07 Online:2020-01-05 Published:2020-01-05

摘要: 基于秦巴山商洛地区农户问卷调查数据,在可持续生计框架下,聚焦不同群体之间生计资本状况,并探讨其农户生计资本对生计策略选择的影响以及生计资本的耦合性。结果表明:(1 山区农户生计策略出现明显分化,依据非农收入比重分为纯务工型、务工主导型、兼业型和纯农型4种类型。(2 调研样本中农户生计资本有限和不均衡,呈现金融资本和社会资本相对较高,自然资本、人力资本偏低的特征。非贫困户中兼业型生计资本总值最高,务工主导型、纯务工型次之,纯农型最低;贫困户中务工主导型生计资本总值最高,纯务工型、兼业型次之,纯农型最低。(3 非贫困户中人均耕地面积、人均林地面积、耕地质量、职业技能水平、政治资源、就业网络对纯务工型农户向务工主导型、兼业型转变有着积极影响,家庭人均收入、男性劳动力比例则具有负向影响;家庭人均收入和职业技能水平对于纯务工型向纯农型转变有负向影响。贫困户中人均耕地面积、人均林地面积、政治资源对纯务工型农户向务工主导型、兼业型和纯农型转变具有正向影响,家庭人均收入、劳动力教育水平、职业技能水平、联系成本则具有负向影响。(4 非贫困农户生计资本耦合度依次为兼业型>务工主导型>纯务工型>纯农型;贫困农户则为兼业型>纯务工型>务工主导型>纯农型。因此,开展农户可持续性生计研究,对于农户减贫、促进乡村地区发展具有重要意义。

关键词: 农户, 生计资本, 生计策略, 秦巴山区

Abstract: To study the sustainable livelihood is significant for poverty alleviation and the development of rural area. Based on the sustainable livelihood framework, 484 farmer householders were investigated in Shangluo City of Qinling-Daba mountainous area, Shaanxi Province, China. The survey data was used to analyze household livelihood capital between different groups by constructing the indexes system of households livelihood assets, then the impact of livelihood capital on the livelihood strategies as well as their coupling coordinative degree were discussed using the Multinomial Logit regression model and the livelihood capital coupling coordinative degree model respectively. The results showed as follows: (1) The livelihood strategies of rural households were obviously different. According to the proportion of non-agricultural income, there were four types of household livelihoods, namely, exclusively employed by others (Type A),employed by others most of the time (Type B),work part time for others (Type C) and 100% doing the farm work (Type D). (2) In the survey samples, the livelihood capital of farmers was limited and unbalanced, which presented the characteristics of relatively high financial capital and social capital and relatively low natural capital and human resources capital. Among the non-poor households, the total livelihood capital of the Type C was the highest (0.451), followed by the Type B (0.393) and the Type A (0.382), the Type D (0.215) was the lowest. While among the poor households, the Type B (0.348) was the highest, followed by the Type A (0.345) and the Type C (0.342),the Type D (0.184) was the lowest. (3) The impact of livelihood capital on the livelihood strategy choice of non-poor households and poor households was different. For the non-poor households, the per capita cultivated land, the per capita forest land area, the cultivated land quality, vocational skill level, political resources and the employment network had a positive effect on the transformation from the Type A to the Type B and the Type C, but per capita household income and male labor ratio had a negative effect. The per capita household income and vocational skill level had a negative effect on the transformation from the Type A to the Type D. For the poor households, the transformation from the Type A to the Type B, Type C and Type D was positively impacted by the per capita cultivated land, the per capita forest land area and political resources, and the per capita household income, labor education level, vocational skill level and communication expenditure were negative factors.(4) If lining the coupling coordinative degree of non-poor households' livelihood capital up in order, from the largest to the smallest we have the list as follows: the Type C (0.114),the Type B (0.106),the Type A (0.103),and the Type D (0.045).Similarly for the coupling coordinative degree of poor households livelihood capital we have the list as follows: the Type C (0.095),the Type A (0.094),the Type B (0.092) and the Type D (0.086).This study could provide useful information for the optimization of livelihood strategies and effective poverty alleviation.

Key words: household, livelihood capital, livelihood strategy, Qinling-Daba mountainous area