NBSI {NicheBarcoding}

Niche-model-Based Species Identification (NBSI)

Description

Species identification using DNA barcoding integrated with niche model.

Usage

NBSI(
  ref.seq,
  que.seq,
  model = "RF",
  independence = TRUE,
  ref.add = NULL,
  variables = "ALL",
  en.vir = NULL,
  bak.vir = NULL
)

Arguments

ref.seq

DNAbin, the reference dataset containing sample IDs, taxon information,longitude and latitude, and barcode sequences of samples.

que.seq

DNAbin, the query dataset containing sample IDs, longitude and latitude, and barcode sequences of samples.

model

Character, string indicating which niche model will be used. Must be one of "RF" (default) or "MAXENT". "MAXENT" can only be applied when the java program paste(system.file(package="dismo"), "/java/maxent.jar", sep=”) exists.

independence

Logical. Whether the barcode sequences are related to the ecological variables?

ref.add

Data.frame, the additional coordinates collected from GBIF or literatures.

variables

Character, the identifier of selected bioclimate variables. Default of "ALL" represents to use all the layers in en.vir; the alternative option of "SELECT" represents to randomly remove the highly-correlated variables (|r| larger than 0.9) with the exception of one layer.

en.vir

RasterBrick, the global bioclimate data output from "raster::getData" function.

bak.vir

Matrix, bioclimate variables of random background points.

Value

A dataframe of barcoding identification result for each query sample and corresponding niche model-based probability.

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.

References

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.

Zhang, A.B., M.D. Hao, C.Q. Yang and Z.Y. Shi. (2017). BarcodingR: an integrated R package for species identification using DNA barcodes. Methods in Ecology and Evolution, 8:627-634.

Jin, Q., H.L. Han, X.M. Hu, X.H. Li, C.D. Zhu, S.Y.W. Ho, R.D. Ward and A.B. Zhang. 2013. Quantifying species diversity with a DNA barcoding-based method: Tibetan moth species (Noctuidae) on the Qinghai-Tibetan Plateau. PloS One, 8:e644.

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.

Examples

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)

library(ape)
data(LappetMoths)
ref.seq<-LappetMoths$ref.seq[1:50,]
que.seq<-LappetMoths$que.seq[1:5,]
NBSI.out<-NBSI(ref.seq,que.seq,ref.add=NULL,
               independence=TRUE,
               model="RF",variables="SELECT",
               en.vir=en.vir,bak.vir=bak.vir)
NBSI.out

### Add a parameter when additional reference coordinates are available ###
#ref.add<-LappetMoths$ref.add
#NBSI.out2<-NBSI(ref.seq,que.seq,ref.add=ref.add,
#                independence=TRUE,
#                model="RF",variables="SELECT",
#                en.vir=en.vir,bak.vir=bak.vir)
#NBSI.out2