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Density-dependent migration and human population structure in historical Massachusetts.

J H Relethford

    American Journal of Physical Anthropology
    |March 1, 1986
    PubMed
    Summary

    Migration rates in historical Massachusetts populations are density-dependent, not linear. Small and large populations show high migration, while medium populations exhibit low gene flow.

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    Area of Science:

    • Population genetics
    • Historical demography
    • Human migration patterns

    Background:

    • Population structure studies often examine population size and migration's impact on genetic variation.
    • The relationship between population size and migration rates remains under-investigated.
    • This study explores density-dependent migration in historical Massachusetts populations.

    Observation:

    • Analyzed 4,859 marriage records from four north-central Massachusetts populations (1741-1849).
    • Data divided into 29 population and time cohorts, calculating exogamy and gene flow estimates (local, long-distance, effective migration).
    • Identified nonlinear density-dependent migration patterns unrelated to temporal trends.

    Findings:

    • Migration is highest in small (<800) and large (>1,600) populations, and lowest in medium-sized populations.
    Keywords:
    AmericasBiologyDemographic FactorsDemographyDeveloped CountriesDeveloping CountriesGeneticsGenetics, PopulationHistorical DemographyMassachusettsMigrationNorth AmericaNorthern AmericaPopulationPopulation DynamicsPopulation SizeSocial SciencesUnited States

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  • This curvilinear relationship is attributed to mate availability/land in small populations and economic pull in large populations.
  • Observed unusually low migration rates in three samples, reflecting settlement history.
  • Implications:

    • Density-dependent migration can influence genetic drift, either enhancing or counteracting its effects.
    • Understanding migration patterns is crucial for interpreting genetic variation within and between populations.
    • Findings provide insights into historical population dynamics and their genetic consequences.