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

Meng Xu; Joel E Cohen

doi:10.1371/journal.pone.0226096

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

PLoS One. 2019 Dec 11;14(12):e0226096. doi: 10.1371/journal.pone.0226096. eCollection 2019.

Authors

Meng Xu¹, Joel E Cohen^{2

3

4}

Affiliations

¹ Department of Mathematics, Pace University, New York, New York, United States of America.
² Laboratory of Populations, The Rockefeller University and Columbia University, New York, New York, United States of America.
³ Earth Institute and Department of Statistics, Columbia University, New York, New York, United States of America.
⁴ Department of Statistics, University of Chicago, Chicago, Illinois, United States of America.

Abstract

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.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Databases, Factual
Demography
Ecological and Environmental Phenomena
Humans
Models, Biological*
Population Density*
Spatio-Temporal Analysis
United States

Grants and funding

J.E.C. received partial support during an initial phase of this project from U.S. National Science Foundation grant DMS-1225529 (https://www.nsf.gov) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.