diff --git a/01_Mesobromion.R b/01_Mesobromion.R
index 98aa7d63326229340d3d0fa544ff650623a47e19..4d68ad45cde0ffd86b8a22ca00eb7a43a4ad8532 100644
--- a/01_Mesobromion.R
+++ b/01_Mesobromion.R
@@ -678,9 +678,16 @@ myvectors <- as.data.frame(env.cor) %>%
mutate(fontface0=ifelse(mylab %in% best.5traits, "bold", "plain")) %>%
mutate(category=as.factor(category)) %>%
mutate(mycol=ifelse(category=="Trait", "Dark blue", "Dark red"))
+
+basemap0 <- ggplot(data=as.data.frame(pca.out$CA$u[,1:4]*5)) +
+ theme_bw() +
+ scale_color_identity() +
+ scale_y_continuous(limits=c(-1, 1)) +
+ scale_x_continuous(limits=c(-1, 1)) + coord_equal() +
+ theme(panel.grid = element_blank())
-PCA1_2 <- ggplot() +
+PCA1_2 <- basemap0 +
geom_point(data=as.data.frame(pca.out$CA$u[,1:2]*5),
aes(x=PC1, y=PC2), pch="+", size=2, alpha=0.8) +
geom_segment(data=myvectors,
@@ -692,15 +699,10 @@ PCA1_2 <- ggplot() +
aes(x=PC1, y=PC2, label=mylab, col=mycol, fontface=fontface0), size=2,
position = position_dodge(1)) +#, segment.alpha=0.5, segment.colour=gray(0.8)) +
xlab(paste("PC1 (", varexpl[1], "%)", sep="")) +
- ylab(paste("PC2 (", varexpl[2], "%)", sep="")) +
- theme_bw() +
- scale_color_identity() +
- scale_y_continuous(limits=c(-1, 1)) +
- scale_x_continuous(limits=c(-1, 1)) + coord_equal() +
- theme(panel.grid = element_blank())
+ ylab(paste("PC2 (", varexpl[2], "%)", sep=""))
-PCA3_4 <- ggplot() +
+PCA3_4 <- basemap0 +
geom_point(data=as.data.frame(pca.out$CA$u[,3:4]*5),
aes(x=PC3, y=PC4), pch="+", size=2, alpha=0.8) +
geom_segment(data=myvectors,
@@ -711,19 +713,53 @@ PCA3_4 <- ggplot() +
aes(x=PC3, y=PC4, label=mylab, col=mycol, fontface=fontface0), size=2,
position = position_dodge(1), segment.alpha=0.8, segment.colour=gray(0.7), segment.size = 0.5) +
xlab(paste("PC3 (", varexpl[3], "%)", sep="")) +
- ylab(paste("PC4 (", varexpl[4], "%)", sep="")) +
- theme_bw() +
- scale_color_identity() +
- scale_y_continuous(limits=c(-1, 1)) +
- scale_x_continuous(limits=c(-1, 1)) +
- coord_equal() +
- theme(panel.grid = element_blank())
+ ylab(paste("PC4 (", varexpl[4], "%)", sep=""))
PC_beals <- cowplot::plot_grid(PCA1_2,PCA3_4, nrow=1)
ggsave("_pics/Fig6_PC_Beals_1-4.png", width=10, height=5, dpi=300, last_plot())
+#### 4.1b Alternative showing species scores ####
+tmp <- as.data.frame(pca.out$CA$v[,1:4]*5) %>%
+ mutate(species0=rownames(pca.out$CA$v)) %>%
+ mutate(species=species0) %>%
+ separate(species0, sep="_", into=c("Gen", "Spe")) %>%
+ mutate(Gen=substr(Gen, 1, 3)) %>%
+ mutate(Spe=substr(Spe, 1, 3)) %>%
+ mutate(labels=paste(Gen, Spe, sep="_"))
+
+
+PCA1_2.sp <- baseplot %+% tmp +
+ geom_text(aes(x=PC1, y=PC2, label=labels), size=2, alpha=0.8) +
+ geom_segment(data=myvectors,
+ aes(x=0, xend=PC1, y=0, yend=PC2, col=mycol),
+ arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
+ geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
+ geom_label(data=myvectors %>%
+ mutate_if(~is.numeric(.), ~(.)*1.2),
+ aes(x=PC1, y=PC2, label=mylab, col=mycol, fontface=fontface0), size=2,
+ position = position_dodge(1)) +#, segment.alpha=0.5, segment.colour=gray(0.8)) +
+ xlab(paste("PC1 (", varexpl[1], "%)", sep="")) +
+ ylab(paste("PC2 (", varexpl[2], "%)", sep=""))
+
+PCA3_4.sp <- baseplot %+% tmp +
+ geom_text(aes(x=PC3, y=PC4, label=labels), size=2, alpha=0.8) +
+ geom_segment(data=myvectors,
+ aes(x=0, xend=PC3, y=0, yend=PC4, col=mycol),
+ arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) +
+ geom_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
+ geom_label_repel(data=myvectors,
+ aes(x=PC3, y=PC4, label=mylab, col=mycol, fontface=fontface0), size=2,
+ position = position_dodge(1), segment.alpha=0.8, segment.colour=gray(0.7), segment.size = 0.5) +
+ xlab(paste("PC3 (", varexpl[3], "%)", sep="")) +
+ ylab(paste("PC4 (", varexpl[4], "%)", sep=""))
+
+
+ggsave("_pics/Fig6a_PCA_Traits_1-2_wSpecies.png", width=8, height=8, dpi=300, PCA1_2.sp)
+ggsave("_pics/Fig6b_PCA_Traits_3-4_wSpecies.png", width=8, height=8, dpi=300, PCA3_4.sp)
+
+
@@ -750,7 +786,7 @@ ggplot() +
theme(panel.grid = element_blank()) +
title("PCA of CWMs")
-#### 4.3 PCoA of individual traits #####
+#### 4.3 PCA of individual traits #####
# assign weights to traits [Growth forms and root structures are coded as binary, but should be downweighted]
#myweights <- c(rep(1/9, 9), rep(1/17, 17), rep(1, 26))
#traits.gowdis <- FD::gowdis(traits, w=myweights, ord="podani")
@@ -806,14 +842,15 @@ PCA.t2 <- baseplot +
rownames_to_column("Trait") %>%
mutate(fontface0=ifelse(Trait %in% best.5traits, "bold", "plain")),
aes(x=Comp.3, y=Comp.4, label=Trait, col="Dark green", fontface=fontface0), size=2,
- position = position_dodge(2),segment.alpha=0.5, segment.colour=gray(0.8))
+ position = position_dodge(2),segment.alpha=0.5, segment.colour=gray(0.8)) +
+ xlab(paste("PC3 (", varexpl[3], "%)", sep="")) +
+ ylab(paste("PC4 (", varexpl[4], "%)", sep=""))
PC_traits <- cowplot::plot_grid(PCA.t1, PCA.t2, nrow=1)
ggsave("_pics/FigS6_PCA_Traits_1-4_only11.png", width=10, height=5, dpi=300, PC_traits)
-
-## alternative version of figS6, showing the species
+##### 4.3b Alternative version of figS6, showing the species ####
tmp <- as.data.frame(pca.scores[,1:4]*.2) %>%
mutate(species0=rownames(pca.scores)) %>%
mutate(species=species0) %>%
@@ -846,8 +883,9 @@ PCA.t2.sp <- baseplot %+% tmp +
rownames_to_column("Trait") %>%
mutate(fontface0=ifelse(Trait %in% best.5traits, "bold", "plain")),
aes(x=Comp.3, y=Comp.4, label=Trait, col="Dark green", fontface=fontface0), size=2,
- position = position_dodge(2),segment.alpha=0.5, segment.colour=gray(0.8))
-#PC_traits_sp <- cowplot::plot_grid(PCA.t1.sp, PCA.t2.sp, nrow=1)
+ position = position_dodge(2),segment.alpha=0.5, segment.colour=gray(0.8)) +
+ xlab(paste("PC3 (", varexpl[3], "%)", sep="")) +
+ ylab(paste("PC4 (", varexpl[4], "%)", sep=""))
ggsave("_pics/FigS6_PCA_Traits_1-2_wSpecies.png", width=8, height=8, dpi=300, PCA.t1.sp)
ggsave("_pics/FigS6_PCA_Traits_3-4_wSpecies.png", width=8, height=8, dpi=300, PCA.t2.sp)