Historical Census Research Articles

Long-term population trends of Sooty Terns Onychoprion fuscatus: implications for conservation status

Seabirds have suffered dramatic declines in population over recent decades. The most abundant seabirds of tropical oceans are Sooty Terns Onychoprion fuscatus and they have an IUCN Red List category of ‘Least Concern’. Ascension Island has the largest colony of Sooty Terns in the Atlantic Ocean and censuses between 1990 and 2013 have shown that its population size is static. In this study we have used historical data and recent censuses to describe the population status of Sooty Terns on Ascension Island over a century. We show that the breeding population contained over 2 million individuals in the 1870s and remained at this level for at least 70 years. However, the population declined from >2 million birds in 1942 to 350,000 birds by 1990. The population trend spanning a period equivalent to three generations of the species (63 years; 1942–2005) showed an approximate 84% decline in population size. Using IUCN criteria this suggests that Sooty Terns on Ascension could be considered ‘Critically Endangered’. We conclude that a re-evaluation of Sooty Tern conservation status is necessary at the local level and possibly globally. Our study highlights that for long-lived species historic demographic data should be considered when determining conservation status.

Historic Roots of Modern Residential Segregation in a Southwestern Metropolis: San Antonio, Texas in 1910 and 2010

This study seeks to understand the historic roots of modern segregation by comparing residential racial patterns in the city of San Antonio over time. The year 1910 is recreated for San Antonio by georeferencing and digitizing historic Sanborn maps and aligning residential structures with historical census and city directory race data for the head of household. The historical point data are aggregated to the census block level and compared to 2010 householder race data by calculating the two most common dimensions of residential segregation: evenness (dissimilarity and Theil’s index) and exposure (isolation and interaction). The findings reveal that by 1910 San Antonio was already a remarkably segregated city and the original patterns of residential segregation resemble contemporary San Antonio. Particularly, residential racial segregation in the Hispanic concentrated southwestern portion of the city has increased over time resulting in an exceptionally racially divided metropolis.

The enduring impact of historical and structural racism on urban violence in Philadelphia

Public health approaches to crime and injury prevention are increasingly focused on the physical places and environments where violence is concentrated. In this study, our aim is to explore the association between historic place-based racial discrimination captured in the 1937 Home Owners Loan Corporation (HOLC) map of Philadelphia and present-day violent crime and firearm injuries. The creators of the 1937 HOLC map zoned Philadelphia based in a hierarchical system wherein first-grade and green color zones were used to indicate areas desirable for government-backed mortgage lending and economic development, a second-grade or blue zone for areas that were already developed and stable, a third-grade or yellow zone for areas with evidence of decline and influx of a “low grade population,” and fourth-grade or red zone for areas with dilapidated or informal housing and an “undesirable population” of predominately Black residents. We conducted an empirical spatial analysis of the concentration of firearm assaults and violent crimes in 2013 through 2014 relative to zoning in the 1937 HOLC map. After adjusting for socio-demographic factors at the time the map was created from the 1940 Census, firearm injury rates are highest in historically red-zoned areas of Philadelphia. The relationship between HOLC map zones and general violent crime is not supported after adjusting for historical Census data. This analysis extends historic perspective to the relationship between emplaced structural racism and violence, and situates the socio-ecological context in which people live at the forefront of this association.

Advanced methods for linking complex historical birth, death, marriage and census data

ABSTRACT
 ObjectiveRecent years have seen the development of novel techniques for linking complex types of data that contain records about different types of entities, for example bibliographic databases with records about authors, publications, and venues. Advanced approaches have been devised to link individuals and groups of records. These approaches exploit both the similarities between record attributes as well as the relationships between entities. Rather than linking records about different types of entities, in this work we study the novel problem of linking records where the same entity can have different roles and where these roles can change over time.
 ApproachWe specifically develop novel techniques for linking historical birth, death, marriage, and census certificates with the aim to reconstruct the population covered by these certificates over a period of time. Our techniques make use of constraints that consider roles, relationships, as well as time. Our first technique links certificates based on the specific roles of their individuals, and greedily selects pairs of certificates with the highest overall similarity while also considering 1-to-1 and 1-to-many linkage constraints. Our second hybrid technique combines graph, group, and temporal linkage, and also considers relationship information between individuals and groups. We compare these techniques with state-of-the-art group, collective, and graph-based linkage approaches.
 ResultsWe evaluate our proposed techniques on real Scottish data from 1861 to 1901 that cover the population of the Isle of Skye. In total, these data sets contain 119,042 certificates for 234,365 individuals. As ground truth we have a set of life-segments of records manually linked by domain experts. Our results indicate that even advanced techniques have difficulty in achieving high linkage quality compared to careful manual linkage. Two reasons for this are the very small name pool in our data and the changing nature of people's personal details over time. Both our proposed techniques, however, significantly outperform traditional pair-wise attribute similarity and group linkage approaches, with the greedy role-based technique achieving better results than the hybrid technique.
 ConclusionOur experiments on real data show that even with advanced linkage techniques that employ group, graph, relationship, and temporal approaches it is challenging to achieve high quality links from complex data such as birth, death, marriage and census certificates that span several decades. As future work we will improve all steps of our techniques with the goal of developing highly accurate, scalable, and automatic techniques for linking large-scale complex population databases.

Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009

ABSTRACTLarge-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates. Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes. Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit. Here we make use of recently released multi-temporal high-resolution global settlement layers, historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast. We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach. Strategies used to fill data gaps may vary according to the local context and the objective of the study. This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields.

Downdating high-resolution population density maps using sealed surface cover time series

Many countries in Europe and North America see their natural and agricultural landscapes being replaced by a fragmented, sprawled landscape. Spatially detailed modelling of changes in land use, population and transport could help to forecast the impact of scenarios aimed at mitigating the process of urban sprawl. A common problem with land-use change models however, is the lack of historical data for proper model calibration. In this paper we describe an approach for developing historical population density maps by downdating a recent high-resolution population density raster, using a time series of sealed surface data and historical census data as an input. In the proposed approach, we hypothesise a local relationship between increasing population densities and increasing sealed surface fraction estimates, the latter obtained from remote sensing imagery. We apply the method to Flanders, Belgium, a region where population growth and improved transport networks led to a diffuse urban expansion, with ribbon development along many roads and a strong fragmentation of open space. The resulting population and sealed surface maps provide interesting data on the urban sprawl phenomenon in the past decades. By computing a densification index we observe that most urban areas witness a recent population density increase while in several rural areas the built-up area per inhabitant is still growing. The downdated time series of population maps obtained in this study will be used to set up a historical calibration for an activity-based cellular automata model for Flanders and Brussels which, among other data, needs high-resolution population maps.

The impact of extreme weather events on education

This paper provides new evidence on the long- and medium-term impact of extreme weather events on education. Our focus is on Mongolia, where two extremely severe winters caused mass livestock mortality. We use household panel data with information on households’ preshock location, combined with historic district-level livestock census data and climate data. Our econometric strategy exploits exogenous variation in shock intensity across space and time, using a difference-in-differences approach. Results indicate that individuals who experience the shock while of schooling age and living in severely affected districts are significantly less likely to complete mandatory education, both in the long and medium terms. The effects are driven by individuals from herding households, while no significant effects are found for individuals from nonherding households. This finding renders it unlikely that extreme winters affect education through school closures during extreme climatic conditions, to which all children were exposed. Moreover, there is no evidence for a differential impact of extreme weather events by gender. This suggests that the effects are not mainly channeled through increased child labor in herding but rather they are related to reductions in household income.

CEDAR: The Dutch historical censuses as Linked Open Data

In this document we describe the CEDAR dataset, a five-star Linked Open Data representation of the Dutch historical censuses, conducted in the Netherlands once every 10 years from 1795 to 1971. We produce a linked dataset from a digitized sample of 2,288 tables. The dataset contains more than 6.8 million statistical observations about the demography, labour and housing of the Dutch society in the 18th, 19th and 20th centuries. The dataset is modeled using the RDF Data Cube vocabulary for multidimensional data, uses Open Annotation to express rules of data harmonization, and keeps track of the provenance of every single data point and its transformations using PROV. We link these observations to well known standard classification systems in social history, such as the Historical International Standard Classification of Occupations (HISCO) and the Amsterdamse Code (AC), which in turn link to DBpedia and GeoNames. The two main contributions of the dataset are the improvement of data integration and access for historical research, and the emergence of new historical data hubs, like classifications of historical religions and historical house types, in the Linked Open Data cloud.

Measuring urban agglomeration using a city-scale dasymetric population map: A study in the Pearl River Delta, China

The rates of urbanization and increase in urban sprawl that have occurred in China over the past thirty years have been unprecedented. This article presents a new city-scale dasymetric modelling approach that incorporates historical census data for 28 cities in the Pearl River Delta area of southern China. It combines Landsat imagery (from 2000, 2005, 2010, and 2015) with a ‘limiting variable’ estimation algorithm to generate a gridded estimate of population density. These gridded population patches are organized as a city-network to reveal the influence of urban agglomeration on population spreading processes. We then combine population patches and graph-based connectivity metrics to describe the spatial-temporal evolution of each city within the urban agglomeration. Our population disaggregation results yield accuracy improvements of 40%–60% over three traditional population disaggregation methods, to reflect the population distribution characteristics more explicitly and in greater detail. The probability of connectivity metrics from dasymetric population maps in Pearl River Delta (1) outline the role of urban agglomeration in population spread, (2) simulate the evolution of ‘polycentric’ urban agglomeration, and (3) outline the individual components of the polycentric megaregion. Our outlined approach is a transferable and an improved means of producing city-scale dasymetric population maps. Our case study provides practical guidance on wide applications of the medium resolution remote sensing data in delineating, measuring, and quantifying the evolution of urban agglomeration across different jurisdictional boundaries and time periods.

Scenarios of population change in the coastal Ganges Brahmaputra Delta (2011-2051)

This paper provides an overview of population dynamics and scenarios of population change in the environmentally vulnerable coastal Ganges Brahmaputra Delta region. The main data sources used for the study include the most recent and historical census data, data from the Sample Vital Registration System (SVRS) and Demographic and Health Surveys (DHS). The research adopts the standard cohort component approach for population projections and provides population estimates for the period from 2011 to 2051. Research outcomes include scenarios of future population change in the coastal Ganges Brahmaputra Delta region and district-level population projections by age and sex. The results show that population growth is likely to continue in some, but not all, districts in the study area. The results also suggest that future migration flows are most likely to be the deciding component of population change in the study area. Given the expected shifts in population distribution and population structure, policy initiatives will have to address the challenges related to informal settlements and population ageing.

A stem-family society without the stem-family ideology? The case of eighteenth-century Poland

This paper mobilizes historical census microdata and quantitative methods to answer a seemingly qualitative question of whether the stem-family organization, profoundly described in sociological and anthropological literature, existed in historical western Poland. The paper’s narrative takes a threefold argumentation format, each step relying on different methodologies. First, using household registers data and basic tools of historical demography we come to the point where a conjectural hypothesis of stem-family prevalence in the territories in question seems to be necessarily rejected. However, the vivid prevalence of the stem family is brought back to the fore in the second step, when empirical data are combined with more sophisticated statistical tools (computer microsimulation of kin sets). Finally, the latter observation is problematized in light of the historical contextual information, which altogether makes the incidence of stem-family organization in the region unthinkable given the existing socio-cultural and political-economic framework. We close with a contemplation of the limits of quantitative approaches to concerns over historical family systems, and with a discussion of the extent to which – given this apparent conundrum – our findings may illuminate existing models of historical family systems.

Physical properties and spatial controls of stone walls in the northeastern USA: Implications for Anthropocene studies of 17th to early 20th century agriculture

Abstract English-style agriculture in the northeastern United States spurred widespread deforestation beginning in the 17th century. Heavy plowing within a rocky, glacial till-mantled landscape resulted in soil erosion and deep frosts. For hundreds of years, stones exposed at the surface due to these processes were built into walls that have become an iconic feature of this landscape, and indicative of past human impacts and land use dynamics in areas that are now reforested. We investigate stone walls in five towns in Connecticut, USA, using airborne Light Detection and Ranging (LiDAR), field measurements, surficial geology maps, and historic agricultural census data. Stone walls are prevalent throughout the study region (∼2113 km over ∼569 km 2 ), but spatial density ranges widely from 0 to 12 km/km 2 . Important controls on the density of stone walls include surficial materials (e.g., ∼4.0 km/km 2 on glacial till compared to 1.5 km/km 2 on floodplain alluvium), and whether land had been “improved” for agriculture (∼5.2 km/km 2 ). The length of stone walls derived from analysis of LiDAR data combined with field measurements (average height of 0.76 ± 0.23 m; width of 0.96 ± 0.50 m), indicates that an average of ∼1.4 × 10 6 m 3 of stone was moved for constructing walls in the study towns alone. Overall, this study highlights the spatial distribution of 17th-20th century agriculture and Anthropocene landscape change in the northeastern USA, providing important implications for human-environment studies in other deglaciated regions of the United States and landscapes with stone-rich soils on a global scale where historic agriculture occurred.

Racist housing practices as a precursor to uneven neighborhood change in a post-industrial city

Racial dynamics and discrimination have been extremely important in influencing decline in the American Rust Belt. The mid-twentieth century departure of white and middle-class populations from cities was precipitated by a breakdown of discriminatory housing practices. This study examines the relationship among housing condition, vacancies, poverty, and demographics in Flint, Michigan, from 1950 to 2010. Historical census data from the National Historical GIS and housing condition data from the City of Flint government are aggregated to neighborhoods defined by economic condition factor (n = 102). Results of rank-difference correlation and geographically weighted regression indicate that, across neighborhoods with the greatest decline in housing condition, the strongest correlate was most often the increase in vacancy rates driven initially by racially motivated suburbanization – suggesting that demographic change alone is not primarily responsible for neighborhood decline. This research is important to understanding the long-term and ongoing consequences of mid-twentieth century racist housing practices, particularly as it relates to the implications of maintaining legacy infrastructure.

From Patrick to John F.: Ethnic Names and Occupational Success in the Last Era of Mass Migration.

Taking advantage of historical census records that include full first and last names, we apply a new approach to measuring the effect of cultural assimilation on economic success for the children of the last great wave of immigrants to the United States. We created a quantitative index of ethnic distinctiveness of first names and show the consequences of ethnic-sounding names for the occupational achievement of the adult children of European migrants. We find a consistent tendency for the children of Irish, Italian, German, and Polish immigrants with more "American"-sounding names to have higher occupational achievement. About one-third of this effect appears to be due to social class differences in name-giving, and the remaining two-thirds to signaling effects of the names themselves. An exception is found for Russian, predominantly Jewish, immigrants, where we find a positive effect of ethnic naming on occupational achievement. The divergent effects of our new measure of cultural assimilation, sometimes hurting and sometimes helping, lend historical empirical support to more recent theories of the advantages of different paths to assimilation. The effects of first names are robust to controls for the ethnic recognizability of last names, suggesting that immigrants' success depended on being perceived as making an effort to assimilate rather than hiding one's origins.

Source Oriented Harmonization of Aggregate Historical Census Data: a flexible and accountable approach in RDF

Source Oriented Harmonization of Aggregate Historical Census Data: a flexible and accountable approach in RDF

Current status of the California sea lion (Zalophus californianus) and the northern elephant seal (Mirounga angustirostris) at the San Benito Archipelago, Mexico

The California sea lion (CSL) and the northern elephant seal (NES) are the two most abundant pinniped species inhabiting the San Benito Archipelago (Baja California, Mexico). This study reports the results of the first survey to gather abundance information from continuous breeding seasons (2012–2015) and over the course of a single year (2014). Relative to the previous year, the abundance of CSLs declined in July 2014; however, based on historical censuses, the colony at the archipelago was catalogued as “stable”. Intra-annually, the CSL abundance was regulated by pups and adult females, which reached their peak during the breeding season (July). Moreover, we hypothesize that subadult males from the west coast of Baja California enter the Gulf of California. The NES fluctuations were most affected by the breeding season (February), when the number of pups and adult females peaked, and by the important presence of juveniles in May and September. The NES colony at the archipelago was catalogued as “in decline”, based on previous countings. This high-resolution survey complements past and future studies in the region, and adds another dimension to our understanding of these species, which is largely based on information from their main rookeries in California.

The Aggregate Dutch Historical Censuses

Historical censuses have an enormous potential for research. In order to fully use this potential, harmonization of these censuses is essential. During the last decades, enormous efforts have been undertaken in digitizing the published aggregated outcomes of the Dutch historical censuses (1795–1971). Although the accessibility has been improved enormously, researchers must cope with hundreds of heterogeneous and disconnected Excel tables. As a result, the census is still for the most part an untapped source of information. The authors describe the main harmonization challenges of the census and how they work toward one harmonized dataset. They propose a specific approach and model in creating an interlinked census dataset in the Semantic Web using the Resource Description Framework technology.

Measuring and mitigating agricultural greenhouse gas production in the US Great Plains, 1870–2000

The Great Plains region of the United States is an agricultural production center for the global market and, as such, an important source of greenhouse gas (GHG) emissions. This article uses historical agricultural census data and ecosystem models to estimate the magnitude of annual GHG fluxes from all agricultural sources (e.g., cropping, livestock raising, irrigation, fertilizer production, tractor use) in the Great Plains from 1870 to 2000. Here, we show that carbon (C) released during the plow-out of native grasslands was the largest source of GHG emissions before 1930, whereas livestock production, direct energy use, and soil nitrous oxide emissions are currently the largest sources. Climatic factors mediate these emissions, with cool and wet weather promoting C sequestration and hot and dry weather increasing GHG release. This analysis demonstrates the long-term ecosystem consequences of both historical and current agricultural activities, but also indicates that adoption of available alternative management practices could substantially mitigate agricultural GHG fluxes, ranging from a 34% reduction with a 25% adoption rate to as much as complete elimination with possible net sequestration of C when a greater proportion of farmers adopt new agricultural practices.

Macroecological factors explain large-scale spatial population patterns of ancient agriculturalists

Aim: It has been well demonstrated that the large-scale distribution patterns of numerous species are driven by similar macroecological factors. However, understanding of this topic remains limited when applied to our own species. Here we take a large-scale look at ancient agriculturalist populations over the past two millennia. The main aim of this study was to test the hypothesis that the patterns of agriculturalist populations were shaped by relevant macroecological factors. Location: China. Methods: Using detailed historical census data, we reconstructed spatial patterns of human population density over 13 imperial dynasties in ancient China, which was dominated by agrarian societies. We used simultaneous autoregressive models to examine the population densities of agriculturalists in relation to climatic, topographic, edaphic and hydrological variables, together with the spatial structure of a concentration of population toward national capitals. The pure and shared effects of these variables and the population-concentration structure were decomposed using a variation partitioning procedure. Results: Spatial population patterns of ancient agriculturalists can be well modelled by climate, topography, soil properties and local hydrological systems. A plausible explanation is that by influencing crop yield these environmental factors essentially drive the distribution of agriculturalists. The population-concentration structure can also explain agriculturalist patterns to a considerable extent. This structure and those environmental factors have largely shared effects in simultaneously shaping these agriculturalist patterns. Main conclusions: While humans can effectively temper environmental constraints at small spatial scales, our results demonstrate that macroecological factors underpin the spatial patterns of humans at large scales. Macroecological constraints and their relative importance are found to be similar for humans and other species, suggesting that similar mechanisms are likely to underlie these macroecological patterns. Our findings have potential implications for the assessment of future responses of humans to global environmental changes.

Urban Stream Deserts as a Consequence of Excess Stream Burial in Urban Watersheds

The Rouge River watershed, a highly urbanized watershed in southeast Michigan, has substantial impervious surface coverage, relatively high population density, and modified stream network (e.g., stream straightening and burial, dams, and underground retention). The number of stream channels and order decreases, increasing flooding, reducing water quality, and decreasing aquatic species. This study defines, identifies, and describes the progression of the geographic pattern of urban stream deserts—defined as those areas within a watershed that exhibit no surface stream channels due to the effects of human development and population growth. Urban stream deserts are identified and characterized using three data sets: (1) historical aerial imagery, (2) historical census boundary and tables, and (3) stream network data. Flowlines digitized off aerial photos from 1949 are compared against 2013 flowlines to identify areas of the watershed now devoid of stream channels. In the Rouge River watershed, stream density has decreased since 1949, which coincides with a rapid population increase and systematic burial of urban streams. Urban stream deserts in the Rouge River watershed constitute 23 percent of the watershed area, but these areas included as much as 66 percent of the watershed population in 1950 (as the urban stream deserts were developing) and dropped to 41 percent in 2010. This conceptual model of urban stream deserts is applicable to many urban and industrialized areas that have replaced stream channels with infrastructure during periods of economic growth, only to experience depopulation, aging infrastructure, and, as a result, degraded, modified, or altogether buried stream networks.