## ----------------------------------------------------------------------------- #Load package for calculation of multivariate richness & sensitivity analysis tools library(multirich) #Set up labels sp.lbl = sprintf("sp%s",seq(1,15,1)) com.lbl = c("pool","com1","com2","com3") tr.lbl = c("tr1","tr2") #Set up traits and species x trait matrix tr1 = c(1,1,1,1,1,2,2,2,2,3,3,3,4,4,5) tr2 = c(1,2,3,4,5,1,2,3,4,1,2,3,1,2,1) in.mat = matrix(c(tr1,tr2),ncol = 2, dimnames = list(sp.lbl,tr.lbl)) #Set up communities pool = rep(1,15) com1 = c(1,0,0,0,1,0,0,0,0,0,0,1,0,0,1) com2 = c(1,1,0,0,0,1,1,0,0,0,0,0,0,0,0) com3 = c(1,0,0,0,0,0,1,0,0,0,0,0,0,0,0) in.com = matrix(c(pool,com1,com2,com3),nrow = 4,byrow = T,dimnames = list(com.lbl,sp.lbl)) tr1.breaks = tr2.breaks = get.breaks(1,5) breaks = list(tr1.breaks, tr2.breaks) out.pdf = "none" #Specifying a file here will save the result to file. # Traitspace here is less than whole - because of a "known" trade-off between the two traits in.traitspaces = c(3,6,10,15) # The results object can be used to do further manipulations of the output data results = sensitivity.analysis(in.mat, in.com, breaks, out.pdf, in.traitspaces = in.traitspaces)