A study of the spatial distribution characteristics of Chinese surnames.

OBJECTIVES: The spatial distribution of Chinese surnames is diverse and provides rich information about the evolution of human society. This study aims to propose several indices to quantify the spatial distribution characteristics of Chinese common surnames and to explore how these distributions are related to historical evolution. METHODS: This study uses data from China's ID information system covering 1.28 billion people across 362 cities. Based on the location quotient, several new concepts, such as "moderately concentrated cities" and "highly concentrated cities," are defined. Then indices such as range, ununiformity and spatial autocorrelation are proposed and calculated to analyze the spatial characteristics of Chinese common surnames. RESULTS: A significant correlation is observed between the commonness of a surname and its spatial characteristics: the more common the surname, the wider its spatial range, the lower the ununiformity, and the higher the autocorrelation coefficient. These patterns reflect the complex interplay of historical, geographical, and cultural factors influencing surname spatial distribution. CONCLUSIONS: The spatial distribution of Chinese surnames is intricately linked to their historical evolution. Most common surnames, often with deeper historical roots, exhibit wider distributions and lower ununiformity, whereas less common surnames show higher concentrations in specific areas. These quantitative results provide a comprehensive understanding of the evolutionary characteristics of Chinese surnames.

An index of Chinese surname distribution and its implications for population dynamics.

OBJECTIVE: We propose an index to characterize the key feature of Chinese surname distributions and investigate its implications for population structure and dynamics. MATERIALS AND METHODS: The surname dataset was obtained from the National Citizen Identity Information Center, which contains 1.28 billion Chinese citizens enrolled in 2007, excluding those of Hong Kong, Macao, and Taiwan. An index, the coverage ratio of stretched exponential distribution (CRSED), is proposed based on the crossover point of stretched exponential truncated power-law distribution, where the stretched exponential term and the power-law term contribute equally. We use multidimensional scaling technique to demonstrate the dependence of the similarity of one prefecture to the others on the CRSED. RESULTS: The CRSEDs of 362 prefectures exhibit an uneven distribution. The consistency of this index is evident by strong positive correlations of CRSEDs at the three administrative levels. This new index has a strong negative correlation with the proportion of the rare surnames. The prefectures with similar CRSEDs tend to adjoin each other on the administrative map, resulting in several distinct regions, each of which shares similar terrain features or historical migrations. The prefectures with lower CRSEDs are more dissimilar to the other prefectures, while the ones with higher CRSEDs are more similar to the others. DISCUSSION: The population dynamics of the prefectures with higher CRSEDs are more likely dominated by migratory movements, the dominant evolutionary forces of the prefectures with lower CRSEDs can be attributed to drift and mutation.

Regional surname affinity: A spatial network approach.

OBJECTIVE: We investigate surname affinities among areas of modern-day China, by constructing a spatial network, and making community detection. It reports a geographical genealogy of the Chinese population that is result of population origins, historical migrations, and societal evolutions. MATERIALS AND METHODS: We acquire data from the census records supplied by China's National Citizen Identity Information System, including the surname and regional information of 1.28 billion registered Chinese citizens. We propose a multilayer minimum spanning tree (MMST) to construct a spatial network based on the matrix of isonymic distances, which is often used to characterize the dissimilarity of surname structure among areas. We use the fast unfolding algorithm to detect network communities. RESULTS: We obtain a 10-layer MMST network of 362 prefecture nodes and 3,610 edges derived from the matrix of the Euclidean distances among these areas. These prefectures are divided into eight groups in the spatial network via community detection. We measure the partition by comparing the inter-distances and intra-distances of the communities and obtain meaningful regional ethnicity classification. DISCUSSION: The visualization of the resulting communities on the map indicates that the prefectures in the same community are usually geographically adjacent. The formation of this partition is influenced by geographical factors, historic migrations, trade and economic factors, as well as isolation of culture and language. The MMST algorithm proves to be effective in geo-genealogy and ethnicity classification for it retains essential information about surname affinity and highlights the geographical consanguinity of the population.

A study of surnames in China through isonymy.

The isonymy structure of 1.28 billion people registered in China's National Citizen Identity Information System was studied at the provincial, prefectural, and county administrative division levels. The isonymy was 0.026 for China as a whole. The average value of isonymy was 0.033 for the 30 provinces, 0.035 for the 334 prefectures, and 0.040 for the 2811 counties. The isonymy in China was much higher than in other countries. This finding may be partly explained by the low number of surnames in the Chinese language. Two regional features can be identified from the geographic distributions of isonymy. One feature is that the middle and lower reaches of the Yangtze River had the lowest values of isonymy at both the provincial and county levels. The second feature is that most counties with the highest values of isonymy were distributed in the provinces with high proportions of ethnic minorities. According to the dendrogram of surname distances, several clusters could be identified. Most provinces in a cluster were conterminous with one another. The one exception could be explained by demic migration called "braving the journey to the northeast of China." Isolation by distance could be detected because the correlation coefficients between Nei's distance and the geographic distances at the provincial, prefectural, and county levels were 0.64, 0.43, and 0.37, respectively. Human behaviors in Chinese history that may have caused these results have been discussed, including cultural origin, migration, residential patterns, and ethnic distribution.