Paul R. Voss

Temporal and spatial variation in age-specific net migration in the United States.

As fertility differences in the United States diminish, population redistribution trends are increasingly dependent on migration. This research used newly developed county-level age-specific net migration estimates for the 1990s, supplemented with longitudinal age-specific migration data spanning the prior 40 years, to ascertain whether there are clear longitudinal trends in age-specific net migration and to determine if there is spatial clustering in the migration patterns. The analysis confirmed the continuation into the 1990s of distinct net migration “signature patterns” for most types of counties, although there was temporal variation in the overall volume of migration across the five decades. A spatial autocorrelation analysis revealed large, geographically contiguous regions of net in-migration (in particular, Florida and the Southwest) and geographically contiguous regions of net out-migration (the Great Plains, in particular) that persisted over time. Yet the patterns of spatial concentration and fragmentation over time in these migration data demonstrate the relevance of this “neighborhood” approach to understanding spatiotemporal change in migration.

Exploring the Spatial Relationship Between Census and Land-Cover Data

Landscapes are shaped by complex relationships between human population, social structure, and environmental conditions. Traditionally, these factors have been studied separately within their respective disciplines. Few studies explore the relationship between indicators of social structure and ecological factors. Our objective was to examine the relationship between housing density, as recorded in the U.S. Census data, and a satellite land-cover classification in the northwest Wisconsin Pine Barrens region. We used a geographical information system (GIS) to integrate these two data sets. Our results revealed strong patterns. For example, housing densities were higher where water is more abundant, a possible case where land cover influences housing density. In other cases, housing density appears to influence land cover. These complex relationships are discussed. Our approach represents an initial methodology to integrate social and ecological data, a task needed to improve our understanding of rural societies and to facilitate broad-scale ecosystem management.L andscapes are shaped by complex relationships between human population, social structure, and environmental conditions. T raditionally, these factors have been studied separately within their respective disciplines. Few studies explore the relationship between indicators of social structure and ecological factors. Our objective was to examine the relationship between housing density, as recorded in the U.S. Census data, and a satellite land-cover classi‐cation in the northwest W isconsin Pine Barrens region. W e used a geographical information system (GIS) to integrate these two data sets. Our results revealed strong patterns. For example, housing densities were higher where water is more abundant, a possible case where land cover inNuences housing density. In other cases, housing density appears to inNuence land cover. T hese complex relationships are discussed. Our approach represents an initial methodology to integrate social and ecological data, a task needed to improve our understanding of rural societies and to facilitate broad-scale ecosystem management.

Reaffirming Social Landscape Analysis in Landscape Ecology: A Conceptual Framework

Landscape ecology continues to mature as its theoretical grounding is strengthened, its precepts and principles become increasingly accepted in other disciplines, and its broad multidisciplinary perspective becomes adopted as a framework for a growing body of empirical work. The same may be said about a social landscape analysis that draws upon its theoretical foundations in applied demography, human ecology, and rural community studies. In this article, we highlight the theoretical parallels between concepts, principles, and theories in landscape ecology and those in demography. The objective is to expand the scope of landscape ecology by including a more coherent characterization of people, social organizational structure and social relations on the land. We believe an enhanced landscape framework that fully embraces social and demographic processes is essential for obtaining a truly comprehensive understanding of landscape patterns and processes.

Rethinking Highway Effects on Population Change

Little systematic work has been undertaken to explain highway impacts on population change. In this study, the authors review the literature in regional economics and demographics in an attempt to shed light on the mechanisms by which investments in highway infrastructure influence population change. First, they categorize the indirect causal paths by which highways influence population change at the county and municipal levels. Then they propose a spatio-temporal approach to revisit highway effects on population change from the stage of highway development and areal characteristics specifically. Finally, it is concluded that at the county and municipal levels, the effect of highways on population change varies from preconstruction to postconstruction periods and across urban, suburban, and rural areas.

Highways and Population Change.

In this paper we return to an issue often discussed in the literature regarding the relationship between highway expansion and population change. Typically it simply is assumed that this relationship is well established and understood. We argue, following a thorough review of the relevant literature, that the notion that highway expansion leads to increased population growth in the vicinity of the improved

Explorations in Spatial Demography

In this chapter, we have discussed the role of geographic space in quantitative demography. A re-emerging interest in spatial demography is evidenced by an increasing number of demographers seeking to adopt the formal tools of spatial econometrics to improve on traditional regression models of demographic processes operating in space. The concept of spatial autocorrelation and ways to specify correctly multiple regression models in the presence of spatial autocorrelation are made more concrete through an illustration of spatial modeling of county-level growth in the U.S. Great Plains region during the 1990s.

Nature, society and history in two contrasting landscapes in Wisconsin, USA: Interactions between lakes and humans during the twentieth century

Abstract Landscapes result from the interaction between nature and society. To understand current landscapes, it is essential to disentangle this interaction; to accomplish this, an historical approach is necessary. Here we focus on the interaction between humans and lakes during the last century in two sites in Wisconsin, USA, a state where lakes, in excess of 10,000, have played an important role in the evolution of the landscapes they belong to. We draw contrasts between the two localities, which are set in landscapes that differ in their physiographic setting, environmental history, and current structure. One, in northern Wisconsin, is a forested recreational lake district; the other, in southern Wisconsin, is dominated by agricultural uses and urban and suburban development. We contend that a common development in both localities has been the increase in the value that society attaches to lakes. As a consequence, lakes are playing a bigger role in the evolution of the terrestrial landscapes surrounding them.

Death Taxes and Elderly Interstate Migration

This study was undertaken to test the proposition that the relative levels of death taxes in the different states contribute to the interstate migration flows of the U.S. elderly population. A statistical model incorporating state-to-state elderly migration flows and the state death tax levels for each of the 50 states and the District of Columbia was tested. The results of the analysis point to a separation of the decision made to leave a state of origin from the decision regarding where to move. The data do not support the idea that the level of death taxes within a given state contributes to the out-migration of elderly residents; however, once the decision to migrate has been made, there is evidence that the destination area will have lower death tax rates, but the effect is considerably less important than the impact of climate and other factors measured by the model.

A test of the “gangplank syndrome” among recent migrants to the upper great lakes region

Abstract That newcomers to environmentally attractive rural areas typically oppose local growth and development in order to preserve what they have recently obtained is an idea first popularized more than 20 years ago by research on “exurbanites” who had moved to the distant fringes of the New York City commuting zone. Subsequent research has essentially confirmed this “gangplank syndrome” but, again, only in the context of rural areas which are adjacent to large cities. In spite of this contextually limited demonstration, recent studies of post‐1970 migration to nonmetropolitan areas — even to those rural places well outside the daily commuting range to a large city — frequently assume that newcomers will automatically adopt a last‐one‐in stance. In this paper the universal application of this syndrome is questioned and is found inappropriate. Interview data recently obtained in rapidly growing nonmetropolitan counties of the Upper Great Lakes Region fail to reveal any significant difference between newc...

The Effects of Integrating the U.S. Census Bureau's Small Area Income and Poverty Estimates Into the Appalachian Regional Commission's Designation of Economically Distressed Counties

The Appalachian Regional Commission (ARC) has used the “distressed county” designation to identify counties with the most structurally disadvantaged economies. The ARC annually updates distressed status of counties with current unemployment and per capita market income data. This research evaluates the potential impact of incorporating the U.S. Census Bureau Small Area Income and Poverty Estimates (SAIPE) into the ARC distressed county designation. The distressed status accuracy results from the end of the 1980s and the magnitude and causes of distressed status transitions in the early 1990s indicate that using the SAIPE would alter the distressed designation but not to a radical degree. However, combining the SAIPE point estimate and the SAIPE upper bound estimate in the determination of distressed status would achieve the objective of using more current estimates of poverty while reducing the negative consequences of using an estimate of poverty with greater statistical variation than decennial census-derived estimates.