NBSI2 | R Documentation |
If users already have species identified by other barcodes or methods, they can use this function given the identified species names and corresponding probabilities to make further confirm by environmental niche model.
NBSI2(
ref.infor = NULL,
que.infor = NULL,
ref.env = NULL,
que.env = NULL,
barcode.identi.result,
model = "MAXENT",
en.vir = NULL,
bak.vir = NULL
)
ref.infor |
Data frame, reference dataset containing sample IDs, taxon information,longitude and latitude of each sample. |
que.infor |
Data frame, query samples,containing sample IDs,longitude and latitude of each sample. |
ref.env |
Data frame,containing reference sampleIDs, species names, and a set of environmental variables collected by users. |
que.env |
Data frame,containing query sampleIDs,and a set of corresponding environmental variables collected by users. |
barcode.identi.result |
Data frame, species identifications by other methods or barocodes, containing query IDs, species identified, and corresponding probabilities. |
model |
Character, string indicating which niche model will be used. Must be one of "MAXENT" (default) or "RF". "MAXENT" can only be applied when the java program paste(system.file(package="dismo"), "/java/maxent.jar", sep=”) exists. |
en.vir |
RasterBrick, the global bioclimate data output from "raster::getData" function. |
bak.vir |
Matrix, bioclimate variables of random background points. |
A dataframe of identifications for query samples and their niche-based reliability.
Cai-qing YANG (Email: yangcq(at)cnu.edu.cn) and Ai-bing ZHANG (Email:zhangab2008(at)cnu.edu.cn), Capital Normal University (CNU), Beijing, CHINA.
Breiman, L. 2001. Random forests. Machine Learning 45(1):5-32.
Liaw, A. and M. Wiener. 2002. Clasification and regression by randomForest. R News, 2/3:18-22.
Phillips, S.J., R.P. Anderson and R.E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190:231-259.
Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis. 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25(15):1965-1978.
data(en.vir)
data(bak.vir)
#envir<-raster::getData("worldclim",download=FALSE,var="bio",res=2.5)
#en.vir<-raster::brick(envir)
#back<-dismo::randomPoints(mask=en.vir,n=5000,ext=NULL,extf=1.1,
# excludep=TRUE,prob=FALSE,
# cellnumbers=FALSE,tryf=3,warn=2,
# lonlatCorrection=TRUE)
#bak.vir<-raster::extract(en.vir,back)
data(LappetMoths)
barcode.identi.result<-LappetMoths$barcode.identi.result
ref.infor<-LappetMoths$ref.infor
que.infor<-LappetMoths$que.infor
if(class(en.vir) == "NULL"){
NBSI2.out<-NBSI2(ref.infor=ref.infor,que.infor=que.infor,
barcode.identi.result=barcode.identi.result,
model="MAXENT",en.vir=NULL,bak.vir=NULL)
}else{
NBSI2.out<-NBSI2(ref.infor=ref.infor,que.infor=que.infor,
barcode.identi.result=barcode.identi.result,
model="maxent",en.vir=en.vir,bak.vir=bak.vir)
}
NBSI2.out
ref.env<-LappetMoths$ref.env
que.env<-LappetMoths$que.env
NBSI2.out2<-NBSI2(ref.env=ref.env,que.env=que.env,
barcode.identi.result=barcode.identi.result,
model="MAXENT",en.vir=en.vir,bak.vir=bak.vir)
NBSI2.out2
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.