Multivariate similarity clustering analysis: a new method regarding biogeography and its application in global insects

Abstract A new method, multivariate similarity clustering analysis (MSCA) method, was established for biogeographical distribution analyzing. General similarity formula (GSF), the core of MSCA method, can be used to calculate the similarity coefficients between 2 and among any ≥ 3 geographical units. Taking the global insects as example, we introduced the steps to use of GSF and consequent clustering processes of this method in details. Firstly, geographical distributions of certain taxa (e.g. Insecta) were categorized into basic geographical units (BGUs); Secondly, similarity coefficients between 2 and among n BGUs were calculated using GSF. Thirdly, hierarchical clustering was conducted according to values of similarity coefficients (from high to low); then a clustering diagram was generated. Finally, a framework of biogeographical division map was established for the target taxa (e.g. Insecta). We concluded that the MSCA method was efficiently applied in analyzing the biogeographical distribution of given biological taxa; the geographical regions regarding global insects were categorized into 7 Realms with 20 sub‐Realms based on the results of MSCA method.