#1-2
bru<-read.csv2("bruslarky.csv")
summary(bru)

#3
library(vegan)
pca.b<-rda(bru[,4:11], scale=T)

# pca.b
# Call: rda(X = bru[, 4:11], scale =
# T)
# 
#               Inertia Rank
# Total               8     
# Unconstrained       8    8
# Inertia is correlations 
# 
# Eigenvalues for unconstrained axes:
#   PC1   PC2   PC3   PC4   PC5   PC6 
# 7.639 0.251 0.056 0.021 0.014 0.008 
#   PC7   PC8 
# 0.007 0.005 

screeplot(pca.b)

#4
aa<-ordiplot(pca.b, type="n", scaling=2)
points(aa, what="si")
text(aa, what="spe", arrows = T, length=0.03)

#4d
par(mar=c(5,4,2,5))
aa<-ordiplot(pca.b, type="n", scaling=1, display="si")
points(aa, what="si", pch=".")

palette(palette.colors(n=6, palette="Paired", alpha=127/256))
ordihull(pca.b, groups=as.character(bru$instar), 
         scaling=1, draw="poly", col=1:6, lty=0)
legend(x=1.2, y=0, legend=1:6, fill=1:6, ncol=1, xpd=T, 
       title="Instar")

#6
bru.6<-bru[bru$instar==6,]
pca.6<-rda(bru.6[,4:11], scale=T)
pca.6
# Call: rda(X = bru.6[, 4:11], scale = T)
# 
#               Inertia Rank
# Total               8     
# Unconstrained       8    8
# Inertia is correlations 
# 
# Eigenvalues for unconstrained axes:
#   PC1   PC2   PC3   PC4   PC5   PC6   PC7   PC8 
# 6.831 0.790 0.203 0.061 0.058 0.027 0.020 0.011 
screeplot(pca.6)

unique(bru.6$species)

par(mar=c(5,4,2,7))
aa<-ordiplot(pca.6, type="n", display="si", scaling=1)
palette(palette.colors(n=6, palette="Okabe-Ito"))
ordispider(pca.6, scaling=1, groups=bru.6$species, col=1:6)
legend(x=1.2, y=.5, legend=unique(bru.6$species), 
       lwd=1, col=1:6, ncol=1, xpd=T, 
       title="Species")

#7
pako<-read.csv2("pako_opr.csv", row.names = 1)
summary(pako)


#8
pako[is.na(pako)]<-0

#9
dca.p<-decorana(log(pako+1))

dca.p
# all:
# decorana(veg = log(pako + 1)) 
# 
# Detrended correspondence analysis with 26 segments.
# Rescaling of axes with 4 iterations.
# 
#                   DCA1    DCA2    DCA3    DCA4
# Eigenvalues     0.2543 0.11840 0.06108 0.03274
# Decorana values 0.2641 0.08218 0.04726 0.02332
# Axis lengths    1.9497 1.34634 1.08653 0.95123

sh.names<-make.cepnames(names(pako), seconditem = T)
substr(sh.names,5,5)<-toupper(substr(sh.names,5,5))
hist(weights(dca.p, display="sp"))
?weights.decorana
sel<-weights(dca.p, display="sp")>20

par(mar=c(5,4,2,2))
aa<-ordiplot(dca.p, type="n", display="sp",
             scaling=2)
text(aa, what="sp", labels=sh.names,
     select = sel)
points(aa, what="sp", select = !sel,
       col="grey")