Published December 11, 2019 | Version v1
Journal article Open

Analyzing and interpreting spatial and temporal variability of the United States county population distributions using Taylor's law

  • 1. Pace University
  • 2. University of Chicago

Description

We study the spatial and temporal variation of the human population in the United States (US) counties from 1790 to 2010, using an ecological scaling pattern called Taylor's law (TL). TL states that the variance of population abundance is a power function of the mean population abundance. Despite extensive studies of TL for non-human populations, testing and interpreting TL using data on human populations are rare. Here we examine three types of TL that quantify the spatial and temporal variation of US county population abundance. Our results show that TL and its quadratic extension describe the mean-variance relationship of county population distribution well. The slope and statistics of TL reveal economic and demographic trends of the county populations. We propose TL as a useful statistical tool for analyzing human population variability. We suggest new ways of using TL to select and make population projections.

Data availability

The data underlying the results presented in the study are publicly available. County data are downloaded from NHGIS (National Historical Geographic Information System) Data Finder on 19 July 2018 (Manson et al. 2018) provide county population count (number of individuals residing in a county) in the decennial censuses from 1790 to 2010. County area (in square meters) and coordinates (latitude and longitude of the geographic centroid of each county) come from the 2000 TIGER/Line shapefile from 1790 to 2010. Manson S, Schroeder J, Riper DV, Ruggles S. PUMS National Historical Geographic Information System: Version 13.0; 2018 [cited 2018 July 19]. Minneapolis: University of Minnesota. Available from: http://doi.org/10.18128/D050.V13.0.

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Additional details

Identifiers

DOI
10.1371/journal.pone.0226096
Other
oai:uchicago.tind.io:6241

Funding

U.S. National Science Foundation
DMS-1225529

UChicago Information

Division(s)
Physical Sciences Division
Department(s)
Statistics