Family Name Origins and Intergenerational Demographic Change in Great Britain

We develop bespoke geospatial routines to typify 88,457 surnames by their likely ancestral geographic origins within Great Britain. Linking this taxonomy to both historic and contemporary population data sets, we characterize regional populations using surnames that indicate whether their bearers are likely to be long-settled. We extend this approach in a case study application, in which we summarize intergenerational change in local populations across Great Britain over a period of 120 years. We also analyze much shorter term demographic dynamics and chart likely recent migratory flows within the country. Our research demonstrates the value of family names in characterizing long-term population change at regional and local scales. We find evidence of selective migratory flows in both time periods alongside increasing demographic diversity and distinctiveness between regions in Great Britain

Using linked consumer registers to estimate residential moves in the United Kingdom

This paper argues that frequently updated data on the nature of residential moves and the circumstances of movers in the United Kingdom are insufficient for many research purposes. Accordingly, we develop previous research reported in this Journal to re-purpose consumer and administrative data in order to develop annual estimates of residential mobility between all UK neighbourhoods. We use a unique digital corpus of linked individual and household-level consumer registers compiled by the UK Consumer Data Research Centre, comprising over 143 million unique address records pertaining to the entire UK adult population over the period 1997–2016. We describe how records pertaining to individuals vacating a property can be assigned to their most probable residential destination, based on novel methods of matching names, assessing household composition, and using information on the date and probable distance of residential moves. We believe that the results of this analysis contribute highly granular, frequently updated estimates of residential moves that can be used to chart population-wide outcomes of residential mobility and migration behaviour, as well as the socio-spatial characteristics of the sedentary population

Using linked consumer and administrative data to model demographic changes in London’s city fringe

This unique book demonstrates the utility of big data approaches in human geography and planning. Offering a carefully curated selection of case studies, it reveals how researchers are accessing big data, what this data looks like and how such data can offer new and important insights and knowledge

Family Names, City Size Distributions and Residential Differentiation in Great Britain, 1881-1901

Cities have specialised in particular urban functions throughout history, with consequential implications for urban and regional patterns of economic and social change. This specialisation takes place within overall national city size distributions and is manifest in different but often similarly variegated residential structures. Here we develop a novel and consistent methodological approach for measuring macro-scale city size and micro-scale residential differentiation using individual digital census records for the period 1881–1901. The use of family names and neighbourhood classification of dominant economic and social roles makes it possible to relate the changing city size distribution in Great Britain to patterns of urban growth and residential differentiation within urban areas. Together, we provide an integrated and consistent methodology that links the classification of all major urban area growth in Great Britain to attendant intra-urban geodemographic changes in urban residential structures. We suggest ways in which this manifests social and economic change across the settlement system for both new and long-established residents

Linking consumer datasets to chart residential moves in private rental housing in England and Wales

With sufficient preparation for purpose, consumer datasets may be used alongside conventional statistical sources to provide more granular and frequently updated estimates of housing market conditions than are otherwise available. Here we describe linkage of Zoopla rental market listings and Linked Consumer Register data to establish the pattern of residential moves in England and Wales between 2014-2019

Mutation supply and the repeatability of selection for antibiotic resistance

Whether evolution can be predicted is a key question in evolutionary biology. Here we set out to better understand the repeatability of evolution. We explored experimentally the effect of mutation supply and the strength of selective pressure on the repeatability of selection from standing genetic variation. Different sizes of mutant libraries of an antibiotic resistance gene, TEM-1 $\beta$-lactamase in Escherichia coli, were subjected to different antibiotic concentrations. We determined whether populations went extinct or survived, and sequenced the TEM gene of the surviving populations. The distribution of mutations per allele in our mutant libraries- generated by error-prone PCR- followed a Poisson distribution. Extinction patterns could be explained by a simple stochastic model that assumed the sampling of beneficial mutations was key for survival. In most surviving populations, alleles containing at least one known large-effect beneficial mutation were present. These genotype data also support a model which only invokes sampling effects to describe the occurrence of alleles containing large-effect driver mutations. Hence, evolution is largely predictable given cursory knowledge of mutational fitness effects, the mutation rate and population size. There were no clear trends in the repeatability of selected mutants when we considered all mutations present. However, when only known large-effect mutations were considered, the outcome of selection is less repeatable for large libraries, in contrast to expectations. Furthermore, we show experimentally that alleles carrying multiple mutations selected from large libraries confer higher resistance levels relative to alleles with only a known large-effect mutation, suggesting that the scarcity of high-resistance alleles carrying multiple mutations may contribute to the decrease in repeatability at large library sizes.Comment: 31pages, 9 figure