...
首页> 外文期刊>Journal of Cleaner Production >Spatial-temporal dynamics of grain yield and the potential driving factors at the county level in China
【24h】

Spatial-temporal dynamics of grain yield and the potential driving factors at the county level in China

机译:中国县级粮食产量的空间动态及潜在驾驶因素

获取原文
获取原文并翻译 | 示例
           

摘要

Understanding the spatial-temporal dynamics of grain production and the influencing factors at the county level in China may promote the knowledge of land-use management and local policymaking, which are conducive to food security and the sustainable development of society. This study aims to evaluate China's grain yield (GY) from 2000 to 2014 and investigate the potential driving factors (PDFs) that affect the spatial-temporal dynamics of GY, including land, labor force, capital, and macro-background. Specifically, the locational Gini coefficient and exploratory spatial data analysis (ESDA) were used to characterize the spatial patterns of GY and its correlations with PDFs. Spatial regression models (SRMs) were employed to investigate the spatial dependence of GY on each PDF in 2000, 2005, 2010 and 2014. Results reveal that China's grain production has been on the rise with high-yield regions distributed mainly within the northeastern agricultural regions. Moreover, the proportion of counties in the northeastern agricultural regions with high grain yield has increased, while the number of low-yielding counties has increased in other agricultural regions. This finding highlights the increasing trend of spatial polarization in grain production. The significant bivariate Moran's I (p 0.05) further revealed a global spatial spillover effect in the spatial correlation of GY and four PDFs. The spatial correlations could be categorized into four types: high GY and high PDFs, high GY and low PDFs, low GY and high PDFs, and low GY and low PDFs. SRMs were capable of quantifying the spatial dependence of GY on various PDFs, thereby revealing that land factors had a substantial effect on the grain production dynamics nationwide. The exploration of the spatial relationships between GY and PDFs provide a reference for formulating scientific and reasonable agricultural policies. (C) 2020 Elsevier Ltd. All rights reserved.
机译:了解粮食生产的空间动态和中国县级的影响因素可能促进土地利用管理和地方政策制定的知识,这有利于粮食安全和社会可持续发展。本研究旨在从2000年到2014年度评估中国的粮食产量(GY),并调查影响GY的空间动态的潜在驾驶因素(PDF),包括土地,劳动力,资本和宏观背景。具体地,定位基尼系数和探索性空间数据分析(ESDA)用于表征GY的空间模式及其与PDF的相关性。使用空间回归模型(SRMS)来研究GY在2000年,2005年,2010年和2014年对每个PDF的空间依赖性。结果表明,中国的粮食产量一直在东北农业地区分布的高产地区的崛起。此外,高粮食产量东北农业地区县的比例增加,而低产县的数量在其他农业地区增加。这一发现凸显了粮食生产中空间极化的越来越大的趋势。重要的双变量莫兰的I(P <0.05)进一步揭示了GY和四种PDF的空间相关性的全局空间溢出效应。空间相关性可以分为四种类型:高GY和高PDF,高GY和低PDF,低GY和高PDF,以及低GY和低PDF。 SRMS能够量化GY对各种PDF的空间依赖性,从而揭示土地因素对全国粮食生产动力产生了重大影响。 GY和PDF之间的空间关系探索为制定科学合理的农业政策提供了参考。 (c)2020 elestvier有限公司保留所有权利。

著录项

  • 来源
    《Journal of Cleaner Production》 |2020年第may10期|120312.1-120312.16|共16页
  • 作者单位

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China;

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China|Chinese Acad Sci State Key Lab Soil & Sustainable Agr Nanjing 210008 Peoples R China|Univ Cambridge Ctr Dev Studies Cambridge CB3 9DT England;

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China;

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China;

    Univ Cambridge Ctr Dev Studies Cambridge CB3 9DT England|Univ Cambridge Dept Land Econ Cambridge CB3 9EP England;

    Univ Cambridge Dept Land Econ Cambridge CB3 9EP England;

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China;

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China;

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China;

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China;

    Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Hubei Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Food security; Grain yield; Potential driving forces; ESDA; County;

    机译:粮食安全;谷物产量;潜在的驱动力;esda;县;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号