Population Development Index Research Articles

The Largest Urban Agglomerations of the Ural Federal District: Comparative Analysis

The article is devoted to the study of urban agglomeration processes in the territory of the Ural Federal District. The purpose of the article is to assess the development of the largest urban agglomerations of the Ural Federal District. The authors included in the sample three urban agglomerations, the core of which are the capital centers of the constituent entities of the Russian Federation located in the Urals: Yekaterinburg, Chelyabinsk and Tyumen urban agglomerations. The research methods are fundamental research methods (abstraction and generalization, systematic approach, structural and functional method, comparative analysis method, etc.), as well as technical analysis methods (classical analysis, indicator method, etc.). The authors rely on statistics provided by Rosstat, official sites of the administrations of the regions and cities under study, as well as Yandex maps. The most developed from an agglomeration point of view is the Yekaterinburg urban agglomeration, followed by the Chelyabinsk agglomeration, and, finally, the Tyumen agglomeration is in third place. In general, the analysis of urban agglomeration processes demonstrated that the latter are very unevenly developed in the territory of the Ural Federal District, which indicates an insufficient connection between the space adjacent to the border between Europe and Asia. The calculation of indicators showed a «problem field» of agglomeration processes characteristic of the Ural Federal District space: for the Yekaterinburg agglomeration there is a significant spread in the population of a large city and small settlements in terms of population, which indicates uneven resettlement; in the Chelyabinsk region — a decrease in population growth of the entire agglomeration; in the Tyumen agglomeration — a low value of the centralization coefficient of the «core» of the agglomeration, the agglomeration coefficient, the agglomeration index, the population development index. The authors made recommendations for the authorities of the macroregion aimed at strengthening the space occupying a middle position on the Eurasian continent.

Spatial Pattern of Underground Space Development in Major Cities in China: Evaluation and Analysis

Underground space development has gradually become an organic part of China’s urban development and construction. Comprehensively developing underground space scientifically and rationally to give full play to its comprehensive benefits is the main problem faced by China’s underground space development at this stage. This research starts with the measurement of the level of urban underground space (UUS) development. This paper constructs a UUS development level measurement indicator system, which is composed of Construction of UUS (D1), urban economic development indicators (D2), and urban population development indicators (D3), which has 12 secondary indicators, and then we use entropy-TOPSIS method to quantitatively evaluate the development level of underground public space in 39 prefecture-level cities and above in my country and analyze its spatial differentiation. The results show that the urban agglomeration has the characteristics of “high-high” cluster distribution with the development level of underground space. However, the overall level of underground space development in China’s major cities is not high and there are apparent differences in the level of UUS development. In terms of spatial distribution, the sustainable development level of cities in the eastern coastal regions of China is relatively high, with towns in the central and northeastern areas ranking second and western towns and northeastern cities ranking the lowest. At the same time, we found that there is a mismatch between the underground space development index and the economic population development index in the evaluation index. Finally, some suggestions are put forward to realize the balanced development of UUS development in our country.

Exploring the Dependence and Influencing Factors of Carbon Emissions from the Perspective of Population Development.

Working towards sustainable population development is an important part of carbon mitigation efforts, and decoupling carbon emissions from population development has great significance for carbon mitigation. Based on the construction of a comprehensive population development index (PDI), this study adopts a decoupling model to explore the dependence between carbon emissions and PDI across 30 Chinese provinces from 2001 to 2017. Then, the stochastic impacts by regression on population, affluence and technology (STIRPAT) model is used to investigate the impact of population factors on carbon emissions. The results show that the decoupling relationship between carbon emissions and PDI has experienced a transformation from expansive negative coupling to expansive coupling and then to weak decoupling at the national level, while some provinces have experienced the same evolutionary process, but the decoupling state in most provinces is not ideal. Sending talent to western provinces and developing low-carbon supporting industries will accelerate carbon decoupling. At the national level, incorporating environmental protection into the existing education system as part of classroom teaching could contribute to carbon decoupling.

Urban and Rural Population and Development Research on Medical Coordination: In View of Dalian 2008-2017 Official Statistics.

Providing universal quality health services is one of the Sustainable Development Goals (SDG) to achieve by 2030. We evaluated the sustainable and coordinated development of urban and rural medical care from 2008–2017 in Dalian, China, by developing an evaluation system based on population and health services. We used a comprehensive development index model and a coupling coordination model to evaluate the status and sustainable development of population and medical services in Dalian. The overall level of population development index in urban areas was significantly lower than in rural areas in the past decade. Comparing the data for 2008 and 2017, Zhongshan District (−31.51%), Ganjingzi District (−25.67%), Lyshunkou District (−35.45%), and Pulandian District (−19.59%) posted significant declines in the population development index. The overall medical service development index for both urban and rural areas registered a steady upward trend. In terms of the relationship between population and medical services, a more pronounced coupling running-in stage was observed among urban areas than among rural areas. Among urban areas, the coupling running-in stage in Zhongshan District (2013–2016) and Shahekou District (2011–2014) was most pronounced, while among rural areas, Jinzhou District (2012–2016, 0.684~0.756) had the most distinct coupling running-in stage. In terms of coordination development, we found that both urban and rural areas experienced a long period of moderate coordination stage. Among urban areas, except for some middle and mountainous districts with unstable changes in the coordination degree, the overall development trend in the region showed a stable transition from moderate coordination stage towards high coordination stage. From 2008 to 2017, only the coordination degree in Jinzhou District (−9.17%) showed negative growth. Although considerable efforts have been initiated to improve the coordinated development of Dalian’s urban and rural populations and its medical services, the medical and healthcare systems still face numerous challenges.

Interannual phenological variability in two North-East Atlantic populations of Calanus finmarchicus

ABSTRACTPhenological variations of the marine copepod Calanus finmarchicus were studied in Svalbard and northern Iceland, where samples were collected in summer and spring, respectively, over two decades. Four phenological indices, developed for copepodite stage-structured data, were used: the proportion of CV to total abundance (CVT), the population development index (PDI), the average weighted stage (AWS), and the average age in days (AAD). The variation of these indices was compared within and between locations to evaluate their suitability for the analysis of phenological effects. For both populations, phenology was related to local temperature and spring bloom dynamics, influenced by Atlantic water inflow. Large-scale climate was related to phenological variation only in the Svalbard population. C. finmarchicus phenology advanced under warmer conditions in both locations. We conclude that vertical phenological indices, i.e. based on interannual changes in copepodite stage structure, are useful to investigate zooplankton phenology, especially when data series covering the whole life cycle are unavailable. We suggest that AWS and AAD can be applied irrespective of sampling time, while PDI and CVT should be applied for early and late sampling seasons, respectively. When multiple phenological indices are needed, AAD in combination with either CVT or PDI should be preferred.

Spatio-Temporal Patterns of Urban-Rural Development and Transformation in East of the “Hu Huanyong Line”, China

Urban-rural development and transformation is profoundly changing the socioeconomic system as well as the natural environment. The study uses the AHP (Analytic Hierarchy Process) method to construct a top-down index of human activity based around five dimensions (population, land, industry, society, and environment) to evaluate the spatial characteristics in the region east of the Hu Huanyong line, China, in 1994 and 2010. Then, we investigate the spatial-temporal pattern using the methods of hotspot analysis, local Moran’s I index and Pearson correlation coefficient. The calculation showed that: (1) northeast China was experiencing an economic recession during study period, and the implementation of revitalization plan have not controlled the recession trend yet; (2) Pearson correlation analysis showed that the improvement of population quality promote the development of industry and society systems significantly during study period; and (3) negative correlation between Population Development Index (PDI) change and Population Transformation Index (PTI) change (along with the Society Transformation Index (STI) change and Industry Transformation Index (ITI) change) reflected that east of the Hu Huanyong line, China was in a “demographic dividend” period. Then, with the help of SOFM neural network algorithm, we divided the study area into six types of region, and found that municipalities, provincial capitals, Yangtze River Delta region and cities on the North China Plain owned the greatest development, while cities in southwest and northeast China showed relatively poor development during study period.