1d:T793,# Principal component analysis of ecological niche among unknown species and the potential species to which they may belong Determine whether unknown species belong to a known species through principal component analysis of ecological niche according to their distribution information. ```r niche.PCA(ref.lonlat, que.lonlat, en.vir = NULL) ``` ## Arguments - `ref.lonlat`: Data frame, longitude and latitude of the known species. - `que.lonlat`: Data frame, longitude and latitude of unknown species. - `en.vir`: RasterBrick, the globle bioclimate data obtained from "raster::getData" function. ## Returns A list containing inportance and loadings of the components. A dataframe of points that within the 95% confidence interval of the reference dataset ecological space. A figure shows whether the query points (blue solid circles) are located in the 95%CI range of the niche space of reference species. ## Examples ```r data(en.vir) #envir<-raster::getData("worldclim",download=FALSE,var="bio",res=2.5) #en.vir<-raster::brick(envir) data(LappetMoths) ref.infor<-LappetMoths$ref.infor que.infor<-LappetMoths$que.infor #windows() # open a new plot window when the image format is abnormal nPCA<-niche.PCA(ref.lonlat=ref.infor[,3:5], que.lonlat=que.infor[,c(2,4:5)], en.vir=en.vir) nPCA$summary nPCA$que.CI data<-data.frame(species=rep("Acosmeryx anceus",3), Lon=c(145.380,145.270,135.461), Lat=c(-16.4800,-5.2500,-16.0810)) simuSites<-pseudo.present.points(data,500,4,2,en.vir) ref.lonlat<-simuSites[1:480,] que.lonlat<-simuSites[481:500,] #windows() # open a new plot window when the image format is abnormal nPCA2<-niche.PCA(ref.lonlat,que.lonlat,en.vir=en.vir) nPCA2$summary nPCA2$que.CI ``` ## Author(s) Cai-qing YANG (Email: yangcq_ivy(at)163.com) and Ai-bing ZHANG (Email:zhangab2008(at)cnu.edu.cn), Capital Normal University (CNU), Beijing, CHINA.1e:T49a,M7.49933 0.25C3.49635 0.25 0.25 3.49593 0.25 7.50024C0.25 10.703 2.32715 13.4206 5.2081 14.37

niche.PCA function