A novel multivariate similarity clustering analysis (MSCA) approach was used to estimate a biogeographical division scheme for the global terrestrial fauna and was compared against other widely used clustering algorit...A novel multivariate similarity clustering analysis (MSCA) approach was used to estimate a biogeographical division scheme for the global terrestrial fauna and was compared against other widely used clustering algorithms. The faunal dataset included almost all terrestrial and freshwater fauna, a total of 4631 families, 141,814 genera, and 1,334,834 species. Our findings demonstrated that suitable results were only obtained with the MSCA method, which was associated with distinct hierarchies, reasonable structuring, and furthermore, conformed to biogeographical criteria. A total of seven kingdoms and 20 sub-kingdoms were identified. We discovered that the clustering results for the higher and lower animals did not differ significantly, leading us to consider that the analysis result is convincing as the first zoogeographical division scheme for global all terrestrial animals.展开更多
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 simi...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.展开更多
文摘A novel multivariate similarity clustering analysis (MSCA) approach was used to estimate a biogeographical division scheme for the global terrestrial fauna and was compared against other widely used clustering algorithms. The faunal dataset included almost all terrestrial and freshwater fauna, a total of 4631 families, 141,814 genera, and 1,334,834 species. Our findings demonstrated that suitable results were only obtained with the MSCA method, which was associated with distinct hierarchies, reasonable structuring, and furthermore, conformed to biogeographical criteria. A total of seven kingdoms and 20 sub-kingdoms were identified. We discovered that the clustering results for the higher and lower animals did not differ significantly, leading us to consider that the analysis result is convincing as the first zoogeographical division scheme for global all terrestrial animals.
基金This study was financially supported by the Zhengzhou Science and Technology Leading Talent Project(131PLJRC654)。
文摘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.
