多时期演变视角下中国人口收缩区的识别、空间特征与成因类型分析

近年来,中国人口增长进入关键转折期,人口收缩现象在区域尺度上呈现快速蔓延趋势。利用全国人口普查和1%人口抽样调查数据,论文从多时期演变视角对1990—2015年县市尺度人口收缩区进行识别,并分析其空间特征;然后,在人口收缩影响因素理论分析的基础上,利用聚类分析的方法划分出不同的成因类型,并进一步选取典型案例进行分析,主要结果如下：① 人口收缩区存在不同的演变路径,约24%的县市为波动收缩,约13%的县市为持续收缩,约5%的县市为近期增长转收缩。② 波动收缩型分布较为广泛,包括长江中游地区、川黔渝地区、甘肃、陕西、江苏北部、福建西部等,持续收缩型主要集中在川黔渝地区和东北地区,而近期增长转收缩型主要集中在东北地区、河南和新疆。③ 人口收缩的成因特征存在明显的区域差异,经济滞后驱动型占比最高,以中西部地区分布最为集中;经济放缓和自然增长低双驱动型主要分布在东北地区;自然增长低驱动型占比较低,主要分布在东部地区。基于以上研究结果,论文认为需要重视区域尺度的人口收缩现象,并根据不同区域人口收缩演变趋势及成因的差异,采取针对性的应对措施。

Spatial distribution of population decline areas in China and underlying causes from a multi-periodical perspective

Regional population decline has gradually become a new phenomenon in recent years, which has attracted extensive attention from scholars and the government. Using the national census data and 1% population sampling survey data, this study identified the population decline areas at the county level from 1990 to 2015 from a multi-periodical perspective. Based on the theoretical analysis of the driving factors of population decline, a cluster analysis has been conducted to reveal the spatial differences of the driving factors of population decline, which resulted in four typical cases of causes. The findings are as follows: First, the population decline areas have very different trajectories: while about 24% of them are characterized by fluctuating but overall decline, about 13% of them have experienced continuous decline, and about 5% of them have only experienced recent decline. Second, the fluctuating but overall decline county units were mainly distributed in the middle reaches of the Yangtze River and Gansu, Shaanxi, Jiangsu, and Fujian Provinces, and the continuous decline county units were mainly concentrated in Sichuan, Guizhou, Chongqing, and the Northeast region, and the recent decline county units were mainly concentrated in the Northeast region, Henan, and Xinjiang. Third, there are obvious regional differences in the driving factors of population decline: the county units driven by lagged economy accounted for the highest percentage, and these units were mainly distributed in the central and western regions; the county units in the Northeast region were mainly driven by the slowed economic development and the low natural growth level; in contrast, the percentage of county units only driven by the low natural growth level is relatively low, and these units were mainly distributed in the eastern region. Based on these findings, we argue that it is necessary to pay more attention to the phenomenon of population decline at the regional scale, and take targeted measures by fully considering the trend of change and driving factors of population decline in different regions.