Beta diversity within and between cluster comparisons
vasc.D.groups.within.mean<-cbind(vasc.D.grps.within.1.mean, vasc.D.grps.within.2.mean, vasc.D.grps.within.3.mean, vasc.D.grps.within.4.mean, vasc.D.grps.within.5.mean)
vasc.D.groups.within.sd<-cbind(vasc.D.grps.within.1.sd, vasc.D.grps.within.2.sd, vasc.D.grps.within.3.sd, vasc.D.grps.within.4.sd, vasc.D.grps.within.5.sd)
vasc.D.groups.within.nrows<-c(nrow(vasc.D.grps.within.1), nrow(vasc.D.grps.within.2), nrow(vasc.D.grps.within.3),
nrow(vasc.D.grps.within.4), nrow(vasc.D.grps.within.5))
vasc.D.groups.within<-rbind(vasc.D.groups.within.mean, vasc.D.groups.within.sd, vasc.D.groups.within.nrows)
colnames(vasc.D.groups.within)<-c("1", "2", "3", "4", "5")
rownames(vasc.D.groups.within)<-c("Mean", "SD", "n")
signif(vasc.D.groups.within,digits=3)
## 1 2 3 4 5
## Mean 0.796 0.783 0.801 0.793 0.797
## SD 0.144 0.222 0.184 0.165 0.170
## n 561.000 406.000 406.000 1380.000 465.000
# Extract non-similar values from group vectors of matrix
vasc.D.grps.diff.1.2<-apply(as.matrix(1:15400),1,function(x) vasc.D.grps$Grp1[x]==1&vasc.D.grps$Grp2[x]==2|vasc.D.grps$Grp1[x]==2&vasc.D.grps$Grp2[x]==1)
vasc.D.grps.diff.1.2<-vasc.D.grps[which(vasc.D.grps.diff.1.2==TRUE),]
nrow(vasc.D.grps.diff.1.2)
## [1] 986
vasc.D.groups.diff<-rbind(vasc.D.groups.diff.mean, vasc.D.groups.diff.sd, vasc.D.groups.diff.nrows)
colnames(vasc.D.groups.diff)<-c("1x2","1x3", "1x4", "1x5", "2x3", "2x4", "2x5", "3x4", "3x5", "4x5")
rownames(vasc.D.groups.diff)<-c("Mean", "SD", "n")
signif(vasc.D.groups.diff,digits=3)
## 1x2 1x3 1x4 1x5 2x3 2x4 2x5 3x4
## Mean 0.9150 0.920 0.802 0.896 0.836 0.915 0.857 0.915
## SD 0.0943 0.104 0.161 0.110 0.192 0.112 0.165 0.118
## n 986.0000 986.000 1800.000 1050.000 841.000 1540.000 899.000 1540.000
## 3x5 4x5
## Mean 0.895 0.878
## SD 0.135 0.127
## n 899.000 1640.000
vasc.rich.groups.within.mean<-cbind(vasc.rich.grps.within.1.mean, vasc.rich.grps.within.2.mean, vasc.rich.grps.within.3.mean, vasc.rich.grps.within.4.mean, vasc.rich.grps.within.5.mean)
vasc.rich.groups.within.sd<-cbind(vasc.rich.grps.within.1.sd, vasc.rich.grps.within.2.sd, vasc.rich.grps.within.3.sd, vasc.rich.grps.within.4.sd, vasc.rich.grps.within.5.sd)
vasc.rich.groups.within.nrows<-c(nrow(vasc.rich.grps.within.1), nrow(vasc.rich.grps.within.2), nrow(vasc.rich.grps.within.3),
nrow(vasc.rich.grps.within.4), nrow(vasc.rich.grps.within.5))
vasc.rich.groups.within<-rbind(vasc.rich.groups.within.mean, vasc.rich.groups.within.sd, vasc.rich.groups.within.nrows)
colnames(vasc.rich.groups.within)<-c("1", "2", "3", "4", "5")
rownames(vasc.rich.groups.within)<-c("Mean", "SD", "n")
signif(vasc.rich.groups.within,digits=3)
## 1 2 3 4 5
## Mean 0.224 0.296 0.358 0.233 0.322
## SD 0.165 0.203 0.265 0.165 0.202
## n 561.000 406.000 406.000 1380.000 465.000
vasc.rich.groups.diff<-rbind(vasc.rich.groups.diff.mean, vasc.rich.groups.diff.sd, vasc.rich.groups.diff.nrows)
colnames(vasc.rich.groups.diff)<-c("1x2","1x3", "1x4", "1x5", "2x3", "2x4", "2x5", "3x4", "3x5", "4x5")
rownames(vasc.rich.groups.diff)<-c("Mean", "SD", "n")
signif(vasc.rich.groups.diff,digits=3)
## 1x2 1x3 1x4 1x5 2x3 2x4 2x5 3x4
## Mean 0.304 0.293 0.226 0.275 0.356 0.293 0.323 0.298
## SD 0.182 0.230 0.167 0.186 0.244 0.179 0.203 0.233
## n 986.000 986.000 1800.000 1050.000 841.000 1540.000 899.000 1540.000
## 3x5 4x5
## Mean 0.335 0.277
## SD 0.240 0.186
## n 899.000 1640.000
# Do the same with the replacement values
vasc.repl.plots <- data.frame(t(combn(rownames(abd.sp.allsp),2)), as.numeric(beta.div.comp.vasc$repl))
vasc.repl.plot.names<-data.frame(t(combn(rownames(abd.sp.allsp),2)))
vasc.repl.grps<-cbind(vasc.repl.plots, vasc.repl.plot.names )
Grp1<-vector()
for(i in 1:length(vasc.5.groups)){
to.change<-names(vasc.5.groups[i])
index<-which(as.character(vasc.repl.grps[,4])==to.change)
Grp1[index]<-as.numeric(vasc.5.groups[i])
}
Grp2<-vector()
for(i in 1:length(vasc.5.groups)){
to.change<-names(vasc.5.groups[i])
index<-which(as.character(vasc.repl.grps[,5])==to.change)
Grp2[index]<-as.numeric(vasc.5.groups[i])
}
vasc.repl.grps<-cbind(vasc.repl.plots, as.factor(Grp1), as.factor(Grp2))
names(vasc.repl.grps)<-c("Plot1", "Plot2", "repl", "Grp1", "Grp2")
# Extract matching groups from Group 1 and Groups 2
vasc.repl.grps.within.1<-apply(as.matrix(1:15400),1,function(x) vasc.repl.grps$Grp1[x]==1 & vasc.repl.grps$Grp2[x]==1)
vasc.repl.grps.within.1<-vasc.repl.grps[which(vasc.repl.grps.within.1==TRUE),]
nrow(vasc.repl.grps.within.1)
## [1] 561
vasc.repl.grps.within.1.mean<-mean(vasc.repl.grps.within.1$repl)
vasc.repl.grps.within.1.mean
## [1] 0.5716533
vasc.repl.grps.within.1.sd<-sd(vasc.repl.grps.within.1$repl)
vasc.repl.grps.within.1.sd
## [1] 0.1863324
vasc.repl.grps.within.2<-apply(as.matrix(1:15400),1,function(x) vasc.repl.grps$Grp1[x]==2 & vasc.repl.grps$Grp2[x]==2)
vasc.repl.grps.within.2<-vasc.repl.grps[which(vasc.repl.grps.within.2==TRUE),]
nrow(vasc.repl.grps.within.2)
## [1] 406
vasc.repl.grps.within.2.mean<-mean(vasc.repl.grps.within.2$repl)
vasc.repl.grps.within.2.mean
## [1] 0.4872342
vasc.repl.grps.within.2.sd<-sd(vasc.repl.grps.within.2$repl)
vasc.repl.grps.within.2.sd
## [1] 0.2297573
vasc.repl.grps.within.3<-apply(as.matrix(1:15400),1,function(x) vasc.repl.grps$Grp1[x]==3 & vasc.repl.grps$Grp2[x]==3)
vasc.repl.grps.within.3<-vasc.repl.grps[which(vasc.repl.grps.within.3==TRUE),]
nrow(vasc.repl.grps.within.3)
## [1] 406
vasc.repl.grps.within.3.mean<-mean(vasc.repl.grps.within.3$repl)
vasc.repl.grps.within.3.mean
## [1] 0.4426757
vasc.repl.grps.within.3.sd<-sd(vasc.repl.grps.within.3$repl)
vasc.repl.grps.within.3.sd
## [1] 0.2513197
vasc.repl.grps.within.4<-apply(as.matrix(1:15400),1,function(x) vasc.repl.grps$Grp1[x]==4 & vasc.repl.grps$Grp2[x]==4)
vasc.repl.grps.within.4<-vasc.repl.grps[which(vasc.repl.grps.within.4==TRUE),]
nrow(vasc.repl.grps.within.4)
## [1] 1378
vasc.repl.grps.within.4.mean<-mean(vasc.repl.grps.within.4$repl)
vasc.repl.grps.within.4.mean
## [1] 0.5601164
vasc.repl.grps.within.4.sd<-sd(vasc.repl.grps.within.4$repl)
vasc.repl.grps.within.4.sd
## [1] 0.2160498
vasc.repl.grps.within.5<-apply(as.matrix(1:15400),1,function(x) vasc.repl.grps$Grp1[x]==5 & vasc.repl.grps$Grp2[x]==5)
vasc.repl.grps.within.5<-vasc.repl.grps[which(vasc.repl.grps.within.5==TRUE),]
nrow(vasc.repl.grps.within.5)
## [1] 465
vasc.repl.grps.within.5.mean<-mean(vasc.repl.grps.within.5$repl)
vasc.repl.grps.within.5.mean
## [1] 0.4748534
vasc.repl.grps.within.5.sd<-sd(vasc.repl.grps.within.5$repl)
vasc.repl.grps.within.5.sd
## [1] 0.213798
vasc.repl.groups.within.mean<-cbind(vasc.repl.grps.within.1.mean, vasc.repl.grps.within.2.mean, vasc.repl.grps.within.3.mean, vasc.repl.grps.within.4.mean, vasc.repl.grps.within.5.mean)
vasc.repl.groups.within.sd<-cbind(vasc.repl.grps.within.1.sd, vasc.repl.grps.within.2.sd, vasc.repl.grps.within.3.sd, vasc.repl.grps.within.4.sd, vasc.repl.grps.within.5.sd)
vasc.repl.groups.within.nrows<-c(nrow(vasc.repl.grps.within.1), nrow(vasc.repl.grps.within.2), nrow(vasc.repl.grps.within.3),
nrow(vasc.repl.grps.within.4), nrow(vasc.repl.grps.within.5))
vasc.repl.groups.within<-rbind(vasc.repl.groups.within.mean, vasc.repl.groups.within.sd, vasc.repl.groups.within.nrows)
colnames(vasc.repl.groups.within)<-c("1", "2", "3", "4", "5")
rownames(vasc.repl.groups.within)<-c("Mean", "SD", "n")
signif(vasc.repl.groups.within,digits=3)
## 1 2 3 4 5
## Mean 0.572 0.487 0.443 0.560 0.475
## SD 0.186 0.230 0.251 0.216 0.214
## n 561.000 406.000 406.000 1380.000 465.000
vasc.repl.groups.diff<-rbind(vasc.repl.groups.diff.mean, vasc.repl.groups.diff.sd, vasc.repl.groups.diff.nrows)
colnames(vasc.repl.groups.diff)<-c("1x2","1x3", "1x4", "1x5", "2x3", "2x4", "2x5", "3x4", "3x5", "4x5")
rownames(vasc.repl.groups.diff)<-c("Mean", "SD", "n")
signif(vasc.repl.groups.diff,digits=3)
## 1x2 1x3 1x4 1x5 2x3 2x4 2x5 3x4
## Mean 0.611 0.627 0.577 0.621 0.479 0.621 0.533 0.617
## SD 0.184 0.227 0.205 0.196 0.240 0.193 0.216 0.234
## n 986.000 986.000 1800.000 1050.000 841.000 1540.000 899.000 1540.000
## 3x5 4x5
## Mean 0.560 0.601
## SD 0.237 0.201
## n 899.000 1640.000
#Compare within and among groups
vasc.D.groups.within
## 1 2 3 4 5
## Mean 0.7958000 0.7831778 0.800797 0.7929639 0.7965634
## SD 0.1436872 0.2219213 0.184044 0.1651796 0.1704064
## n 561.0000000 406.0000000 406.000000 1378.0000000 465.0000000
vasc.rich.groups.within
## 1 2 3 4 5
## Mean 0.2241467 0.2959436 0.3581213 0.2328475 0.3217101
## SD 0.1654654 0.2029446 0.2645945 0.1647176 0.2015790
## n 561.0000000 406.0000000 406.0000000 1378.0000000 465.0000000
vasc.repl.groups.within
## 1 2 3 4 5
## Mean 0.5716533 0.4872342 0.4426757 0.5601164 0.4748534
## SD 0.1863324 0.2297573 0.2513197 0.2160498 0.2137980
## n 561.0000000 406.0000000 406.0000000 1378.0000000 465.0000000
vasc.D.groups.diff
## 1x2 1x3 1x4 1x5 2x3
## Mean 0.91526347 0.9197237 0.8024350 0.8959609 0.8357421
## SD 0.09432423 0.1041256 0.1611749 0.1104454 0.1923259
## n 986.00000000 986.0000000 1802.0000000 1054.0000000 841.0000000
## 2x4 2x5 3x4 3x5 4x5
## Mean 0.9146473 0.8565390 0.9145783 0.8952288 0.878292
## SD 0.1120741 0.1646083 0.1184867 0.1347141 0.126833
## n 1537.0000000 899.0000000 1537.0000000 899.0000000 1643.000000
vasc.rich.groups.diff
## 1x2 1x3 1x4 1x5 2x3
## Mean 0.3040599 0.2928844 0.2257138 0.2753732 0.3564609
## SD 0.1822009 0.2301109 0.1670974 0.1864531 0.2435215
## n 986.0000000 986.0000000 1802.0000000 1054.0000000 841.0000000
## 2x4 2x5 3x4 3x5 4x5
## Mean 0.2932989 0.3233046 0.2977389 0.3347957 0.2774573
## SD 0.1791971 0.2032539 0.2330723 0.2399900 0.1861403
## n 1537.0000000 899.0000000 1537.0000000 899.0000000 1643.0000000
vasc.repl.groups.diff
## 1x2 1x3 1x4 1x5 2x3
## Mean 0.6112035 0.6268393 0.5767212 0.6205877 0.4792812
## SD 0.1836065 0.2272347 0.2046841 0.1960249 0.2400030
## n 986.0000000 986.0000000 1802.0000000 1054.0000000 841.0000000
## 2x4 2x5 3x4 3x5 4x5
## Mean 0.6213484 0.5332343 0.6168393 0.5604331 0.6008347
## SD 0.1927200 0.2164440 0.2343640 0.2372252 0.2008297
## n 1537.0000000 899.0000000 1537.0000000 899.0000000 1643.0000000
vasc.within.rich.repl<-rbind( vasc.rich.groups.within[1,], vasc.repl.groups.within[1,])
rownames(vasc.within.rich.repl)<-c("Rich", "Repl")
vasc.diff.rich.repl<-rbind( vasc.rich.groups.diff[1,], vasc.repl.groups.diff[1,])
rownames(vasc.diff.rich.repl)<-c("Rich", "Repl")
Relationships within and between different clusters
#dev.new(width=11.8, height=6)
layout(matrix(1:2,ncol=2), width = c(1,1.75),height = c(1,1))
#par(mfrow=c(1,2))
barplot(as.matrix(vasc.within.rich.repl), cex.lab=1.25, ylim=c(0,1), ylab="Relative contribution to beta diversity", xlab="Within cluster")
legend("topleft", c("Richness", "Replacement"), col = c("grey85", "grey35" ), cex=1.1,
lty = c(1, 1), pch = c(NA, NA), lwd=10 , bg = "white", bty="n")
barplot(as.matrix(vasc.diff.rich.repl), cex.lab=1.25, ylim=c(0,1), ylab="Relative contribution to beta diversity", xlab="Cluster combinations")
#dev.new(width=5.9, height=8)
par(mfrow=c(3,2))
barplot(as.matrix(vasc.within.between.1), cex.lab=1.25, ylim=c(0,1), ylab="Relative contribution to beta diversity", xlab="Clusters")
barplot(as.matrix(vasc.within.between.2), cex.lab=1.25, ylim=c(0,1), ylab="Relative contribution to beta diversity", xlab="Clusters")
barplot(as.matrix(vasc.within.between.3), cex.lab=1.25, ylim=c(0,1), ylab="Relative contribution to beta diversity", xlab="Clusters")
barplot(as.matrix(vasc.within.between.4), cex.lab=1.25, ylim=c(0,1), ylab="Relative contribution to beta diversity", xlab="Clusters")
barplot(as.matrix(vasc.within.between.5), cex.lab=1.25, ylim=c(0,1), ylab="Relative contribution to beta diversity", xlab="Clusters")
plot.new()
legend("topleft", c("Richness", "Replacement"), col = c("grey85", "grey35" ), cex=1.1,
lty = c(1, 1), pch = c(NA, NA), lwd=10 , bg = "white", bty="n")
