ArticlePloS one2019
Analyzing and interpreting spatial and temporal variability of the United States county population distributions using Taylor's law.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Spatial Dynamics and Multiscale Regression Modelling of Population Level Indicators for COVID-19 Spread in Malaysia.International journal of environmental research and public health · 2022Article
- Variance in Landscape Connectivity Shifts Microbial Population Scaling.Frontiers in microbiology · 2022Article
- Spatial and temporal autocorrelations affect Taylor's law for US county populations: Descriptive and predictive models.PloS one · 2021Article
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Authors and funding
2 authors.
Funding
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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.
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