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中国山东省县级粮食产量的时空特征及影响因素。

Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China.

机构信息

School of Management, China University of Mining and Technology (Beijing), Beijing, 100083, China.

CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai, 264003, China.

出版信息

Sci Rep. 2022 Jul 14;12(1):12001. doi: 10.1038/s41598-022-14801-x.

Abstract

China's food security has always been a high priority issue on the political agenda with rapid urbanization affecting agricultural land, and it is challenged by several factors, such as human activities, social politics and policy. Shandong is an important grain-producing province and the second most populous province in China. In this paper, the spatiotemporal characteristics of grain yield and their potential influencing factors were explored at the county level in Shandong by using panel data over a 19-year period. The location Gini coefficient (L-Gini) and exploratory spatial data analysis (ESDA) were used to study the spatial agglomeration characteristics of grain yield, and spatial regression methods (SRMs) were used to analyse the influencing factors. The results indicated that grain yield increased from 38.3 million metric tons to 53.2 million metric tons in 2000-2018, with a growth rate of approximately 28.0%. The increase in grain yield in Shandong was due to the driving effect of radiation from high-yield counties to surrounding moderate-yield counties. This revealed an upward trend of spatial polarization in Shandong's grain yield. In 2000-2018, the L-Gini and global Moran's I increased from 0.330 to 0.479 and from 0.369 to 0.528, respectively. The number of counties in high-high (HH) and low-low (LL) agglomeration areas increased, and the spatial polarization effect was significant. SRMs analysis showed that irrigation investment and non-grain attention have significant positive and negative effects on grain production, respectively. The spatial relationship between grain yield and its influencing factors was explored to provide a reference for formulating scientific and rational agricultural policies.

摘要

中国的粮食安全一直是政治议程上的一个高度优先事项,快速的城市化正在影响农业用地,并且受到多种因素的挑战,如人类活动、社会政治和政策。山东是一个重要的粮食生产省份,也是中国第二人口大省。本文利用 19 年的面板数据,探讨了山东省县域粮食产量的时空特征及其潜在影响因素。采用位置基尼系数(L-Gini)和探索性空间数据分析(ESDA)研究了粮食产量的空间集聚特征,并采用空间回归模型(SRMs)分析了影响因素。结果表明,2000-2018 年山东省粮食产量从 3830 万吨增加到 5320 万吨,增长率约为 28.0%。山东省粮食产量的增加是由于高产量县对周围中产量县的辐射带动效应。这表明山东省粮食产量的空间极化呈上升趋势。2000-2018 年,L-Gini 和全局 Moran's I 从 0.330 增加到 0.479,从 0.369 增加到 0.528。HH 和 LL 集聚区的县数量增加,空间极化效应显著。SRMs 分析表明,灌溉投资和非粮食关注对粮食生产分别有显著的正向和负向影响。探讨了粮食产量与其影响因素之间的空间关系,为制定科学合理的农业政策提供了参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1f7/9283428/7331bcdaae39/41598_2022_14801_Fig1_HTML.jpg

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