Examining population structure through the use of surname matrices: methodology for visualizing nonrandom mating

Area of Science:

• Population genetics
• Human microevolution
• Social network analysis

Background:

• Marital isonymy analysis indirectly measures population structure.
• Traditional methods lose information due to large surname matrices.
• A direct analysis of mating structure is needed.

Purpose of the Study:

• To develop and apply a sophisticated computer graphing technique for direct analysis of community mating structures.
• To visualize and statistically analyze the differences between observed and expected mating frequencies based on surnames.
• To investigate patterns of nonrandom mating and their implications for population microevolution.

Main Methods:

• Calculated expected mating frequencies (E = P x Q) from male (P) and female (Q) surname proportions.
• Computed the difference matrix (D = O - E) between observed (O) and expected frequencies.
• Utilized 3D computer graphing to visualize the D matrix, with axes representing male surnames, female surnames, and difference values.

Main Results:

• Applied the technique to 5417 marriages in Tasmania (1840-1963) using 194 core surnames.
• Visual analysis of the graphed difference matrix revealed significant patterns of nonrandom mating.
• Demonstrated evidence of frequency-dependent selection acting on surnames within the population.

Conclusions:

• The developed computer graphing method offers a direct and informative approach to analyzing mating structures.
• Frequency-dependent selection of surnames has significant implications for understanding human population microevolution.
• This technique provides a powerful tool for exploring microevolutionary dynamics over historical timescales.