Explain how shifting of settlement heplps increase population
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Abstract
Population growth (or decline) is influenced by many factors that fall into the broad realms of demographic characteristics, socioeconomic conditions, transportation infrastructure, natural amenities, and land use and development across space and time. This paper adopts an integrated spatial regression approach to investigate the spatial and temporal variations of these factors' effects on population change. Specifically, we conduct the analysis at the minor civil division level in Wisconsin, USA, from 1970 to 2000. The results suggest that the factors have varying effects on population change over time and across rural, suburban, and urban areas. Their effects depend upon the general trend of population redistribution processes, local dynamics, and areal characteristics. Overall, a systematic examination of population change should consider a variety of factors, temporal and spatial variation of their effects, and spatial spillover effects. The examination should have the flexibility to identify and incorporate influential factors at a given point in time and space, not to adhere to a single set of drivers in all circumstances. The findings have important implications for population predictions used for local and regional planning.
1. Introduction
Land-use conflicts, regional/tribal warfare, environmental degradation, and competition for scarce resources are all exacerbated by growing populations. Holistic or systematic approaches are becoming critically important in tackling the complexity of development and population change [1–3]. Research findings have suggested that population growth (or decline) is determined jointly by demographic, social, economic, political, geographic, and cultural forces as well as temporal and spatial influences [4]. However, the majority of existing research is focused on only some of the factors and influences and does not consider others [5]. This might be due to the fact that development and population change are complex and require interdisciplinary knowledge, but existing studies are often conducted within disciplinary boundaries [3, 6]. In addition, simulating the complexity of population change requires well-grounded expertise in methodology, and putting together a dataset with a variety of variables across space and time is expensive. A wide range of results is possible by omitting relevant factors and influences from empirical models [7]. Therefore, because the various studies tend to focus on specific factors and influences within disciplinary boundaries and omit others, the existing research on population change often generates different and sometimes conflicting findings [8]. This had led to a gap in the literature of a systematic view of population change. This paper attempts to help fill this gap by systematically examining population change’s influential factors as well as their temporal and spatial dynamics. This study provides a more dynamic and less biased estimates of the effects and a more comprehensive understanding of population change.
Development and population change are complex—they have exhibited spatial variations in different time periods driven by different factors. For example, we recognize several distinctive periods in the United States history: monocentric cities from about 1850 to 1930, the rise of suburban patterns around the beginning of the 20th century, “turnaround migration” bringing people back to amenity-rich rural areas in the 1970s, “renewed metropolitan growth” in the 1980s, rural rebound in the 1990s, and selective deconcentration in the 2000s (for an extensive literature review, see [9]). These different population redistribution processes—centralization, decentralization, rural renaissance, renewed metropolitan growth, rural rebound, and selective deconcentration—are characterized by different principal driving factors. One important factor in a certain time period may become unimportant in another, and vice versa. When the principal determinants change, population redistribution patterns also change. These factors can be characterized in broad realms, including demographic characteristics, socioeconomic conditions, transportation accessibility, natural amenities, and policies and biophysical conditions related to land use and development [8].