Cargando…
Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China
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 mos...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281284/ https://www.ncbi.nlm.nih.gov/pubmed/35835909 http://dx.doi.org/10.1038/s41598-022-14801-x |
_version_ | 1784746845270966272 |
---|---|
author | He, Huanhuan Ding, Rijia Tian, Xinpeng |
author_facet | He, Huanhuan Ding, Rijia Tian, Xinpeng |
author_sort | He, Huanhuan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9281284 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92812842022-07-14 Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China He, Huanhuan Ding, Rijia Tian, Xinpeng Sci Rep Article 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. Nature Publishing Group UK 2022-07-14 /pmc/articles/PMC9281284/ /pubmed/35835909 http://dx.doi.org/10.1038/s41598-022-14801-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article He, Huanhuan Ding, Rijia Tian, Xinpeng Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China |
title | Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China |
title_full | Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China |
title_fullStr | Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China |
title_full_unstemmed | Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China |
title_short | Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China |
title_sort | spatiotemporal characteristics and influencing factors of grain yield at the county level in shandong province, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9281284/ https://www.ncbi.nlm.nih.gov/pubmed/35835909 http://dx.doi.org/10.1038/s41598-022-14801-x |
work_keys_str_mv | AT hehuanhuan spatiotemporalcharacteristicsandinfluencingfactorsofgrainyieldatthecountylevelinshandongprovincechina AT dingrijia spatiotemporalcharacteristicsandinfluencingfactorsofgrainyieldatthecountylevelinshandongprovincechina AT tianxinpeng spatiotemporalcharacteristicsandinfluencingfactorsofgrainyieldatthecountylevelinshandongprovincechina |