Abstract: The aim was to study the coevolutionary relationship of sucking lice and their small mammal hosts by numerical taxonomy. Based on hierarchical clustering analysis on SPSS 12.0, the numerical taxonomy of 16 important communities of sucking lice was carried on. Total 54 variables were measured for the 16 communities. Based on these data, the relative dominant rate (D_r), louse infection rate (R_L), louse index (I_L), total louse infection rate (R_LT), total louse index (I_LT) of dominant species of sucking lice and the average index of community structure ( ′, , , ) of every sucking lice community were calculated. The 16 communities of sucking lice were divided into 8 groups in the dendrogram of hierarchical clustering analysis. The sucking louse communities on the same genus of small mammal hosts showed a high similarity and were clustered into the same group. The clustering tendency was concordant with the taxonomic classification of the corresponding small mammal hosts on which the sucking lice exist. When the small mammal hosts were very close in the zoological taxonomy, the communities of sucking lice on their body surface tend to be similar. The results indicated that there would be a synchronized evolutionary relationship between sucking lice and their small mammal hosts. A stable parasitism of sucking lice has been established on the body surface of small mammals. The results suggested that a coevolutionary relationship may link sucking lice and their small hosts together.

Key words: Sucking louse, community, numerical classification, ecology, coevolution