Open AccessSpatial distribution of rural population from a climate perspective: Evidence from Jiangxi Province in China
Author(s) -
Liguo Zhang,
Xiaola Lin,
Langping Leng,
Zeng Yong-ming
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0248078
Subject(s) - population , distribution (mathematics) , geography , spatial distribution , china , rural area , endowment , ecology , physical geography , demography , biology , medicine , mathematical analysis , philosophy , remote sensing , mathematics , archaeology , epistemology , pathology , sociology
The research on rural population distribution from a climate perspective is rare. Therefore, this study adopts this perspective and uses the ordinary least squares and spatial econometric models to explore the spatial distribution characteristics of the rural population in the Poyang Lake ecological economic zone. Results show that (1) a significant spatial autocorrelation is present in the distribution of rural population, and a spatial correlation exists between the population distribution and climatic factors, (2) the influence of climatic factors on the distribution of rural population in the Poyang Lake ecological economic zone is greater than that of economic factors, and (3) the annual average sunshine and annual average rainfall have a significant negative effect on the distribution of the regional rural population, which is contrary to the expectations., so we then analyze this negative effect on the regional rural population distribution. It is found that (1) the influence of climate factors on the distribution of rural population in lake area is far more than that of economic factors, and more consideration should be given to the influence of climate factors on the population distribution in the lake area, (2) different geographical capital and natural resource endowment, the influence of climate on micro-regional population distribution may be different from the general law, (3) the spatial measurement model which takes spatial dependence into account can reveal the influence of climate on rural population distribution more accurately.