Quantifying socioeconomic characteristics of drought-sensitive regions: Evidence from Chinese provincial agricultural data

被引:23
|
作者
Fraser, Evan D. G. [1 ]
Termansen, Mette [1 ]
Sun, Ning [2 ]
Guan, Dabo [3 ]
Simelton, Elisabeth [1 ]
Dodds, Paul [1 ]
Feng, Kuishang [1 ]
Yu, Yang [1 ]
机构
[1] Univ Leeds, Sch Earth & Environm, Sustainabil Res Inst, Leeds LS2 9JT, W Yorkshire, England
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
[3] Univ Cambridge, Judge Business Sch, Cambridge CB2 1TN, England
基金
英国自然环境研究理事会; 英国经济与社会研究理事会;
关键词
Socioeconomic characteristics; Drought-sensitive regions; Eastern China; Agricultural data; Rainfall data;
D O I
10.1016/j.crte.2008.07.004
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
In some cases, even relatively minor perturbations to growing season rainfall cause major harvest losses. In other cases, harvests are unaffected even by major rainfall perturbations. The purpose of this paper is to investigate possible socioeconomic reasons why some regions' harvests are especially sensitive to changes in rainfall using rainfall and agricultural data from eastern China. Results suggest that for wheat and maize farmers, technical inputs were significant factors for maintaining harvest levels in low rainfall years. Rice harvests were more dependent on indicators related to access to labour. This work provides a preliminary step to quantitatively assess characteristics that enhance adaptive capacity in different cropping systems. To cite this article: E.D.G. Fraser et al., C R. Geoscience 340 (2008). (C) 2008 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.
引用
收藏
页码:679 / 688
页数:10
相关论文
共 50 条
  • [41] How does industrial policy affect manufacturing carbon emission? Evidence from Chinese provincial sub-sectoral data
    Song, Li
    Zhou, Xiaoliang
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 28 (43) : 61608 - 61622
  • [42] How does industrial policy affect manufacturing carbon emission? Evidence from Chinese provincial sub-sectoral data
    Li Song
    Xiaoliang Zhou
    Environmental Science and Pollution Research, 2021, 28 : 61608 - 61622
  • [43] Assessing regional energy security characteristics: Evidence from Chinese province-level data
    Du, Juntao
    Gu, Hongwei
    Shen, Zhiyang
    Song, Malin
    Vardanyan, Michael
    ENERGY ECONOMICS, 2024, 140
  • [44] Impacts of Cross-Sectoral Climate Policy on Forest Carbon Sinks and Their Spatial Spillover: Evidence from Chinese Provincial Panel Data
    Zhu, Hongge
    Cai, Yingli
    Lin, Hong
    Tian, Yuchen
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (21)
  • [45] Evaluating the Impact of the Highway Infrastructure Construction and the Threshold Effect on Cultivated Land Use Efficiency: Evidence from Chinese Provincial Panel Data
    Lu, Xinhai
    Hou, Jiao
    Tang, Yifeng
    Wang, Ting
    Li, Tianyi
    Zhang, Xupeng
    LAND, 2022, 11 (07)
  • [46] Can environmental regulations and R&D subsidies promote GTFP in pharmaceutical industry? Evidence from Chinese provincial panel data
    Yang, Yue-Di
    FRONTIERS IN PUBLIC HEALTH, 2022, 10
  • [47] Impacts of COVID-19 Pandemic on Dietary Consumption among Chinese Residents: Evidence from Provincial-Level Panel Data
    Zheng, Xiaodong
    Wang, Yinglin
    Zhang, Yue
    Deng, Tinghe
    Yang, Yuanzheng
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (13)
  • [48] How does income and green technology innovation influence the emissions reduction effect of renewable energy: evidence from Chinese provincial data
    Pei-Hua Zhu
    Kun Zhang
    Environmental Science and Pollution Research, 2023, 30 : 74056 - 74069
  • [49] A SHAP machine learning-based study of factors influencing urban residents' electricity consumption - evidence from chinese provincial data
    Wang, Yuanping
    Hu, Lang
    Hou, Lingchun
    Wang, Lin
    Chen, Juntao
    He, Yu
    Su, Xinyue
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024, 26 (12) : 30445 - 30476
  • [50] How does income and green technology innovation influence the emissions reduction effect of renewable energy: evidence from Chinese provincial data
    Zhu, Pei-Hua
    Zhang, Kun
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (29) : 74056 - 74069