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Commit ff5dfb1c authored by Francesco Sabatini's avatar Francesco Sabatini
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Corrected typo

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02_Mesobromion_ExamineOutput.R
+ 122
− 123
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...@@ -27,7 +27,7 @@ get.best <- function(x, N, labs){ ...@@ -27,7 +27,7 @@ get.best <- function(x, N, labs){
traits <- read_delim("_data/Mesobromion/traits.v2.10perc.txt", delim="\t") traits <- read_delim("_data/Mesobromion/traits.v2.10perc.txt", delim="\t")
traits <- traits %>% traits <- traits %>%
rename(Schlerophylly=Leaf_Scleroph) rename(Sclerophylly=Leaf_Scleroph)
#traits.sign.cov <- read_delim("_data/Mesobromion/traits.v2.10perc.cov.sign.txt", delim="\t") #traits.sign.cov <- read_delim("_data/Mesobromion/traits.v2.10perc.cov.sign.txt", delim="\t")
#traits.sign.pa <- read_delim("_data/Mesobromion/traits.v2.10perc.pa.sign.txt", delim="\t") #traits.sign.pa <- read_delim("_data/Mesobromion/traits.v2.10perc.pa.sign.txt", delim="\t")
trait.labs <- data.frame(trait.name=colnames(traits)[-1]) %>% trait.labs <- data.frame(trait.name=colnames(traits)[-1]) %>%
...@@ -41,7 +41,7 @@ species.cov <- read_delim("_data/Mesobromion/species.v2.10perc.cov.txt", delim=" ...@@ -41,7 +41,7 @@ species.cov <- read_delim("_data/Mesobromion/species.v2.10perc.cov.txt", delim="
traits <- traits %>% traits <- traits %>%
as.data.frame() %>% as.data.frame() %>%
mutate_at(.vars=vars(Schlerophylly, LifeSpan, Rosette), mutate_at(.vars=vars(Sclerophylly, LifeSpan, Rosette),
.funs=~as.ordered(.)) %>% .funs=~as.ordered(.)) %>%
# filter(species0 %in% colnames(species)) %>% # filter(species0 %in% colnames(species)) %>%
mutate_if(~is.character(.), .funs=~as.factor(.)) %>% mutate_if(~is.character(.), .funs=~as.factor(.)) %>%
...@@ -617,7 +617,6 @@ ggsave(filename = "_pics/SXXX_Best_AllCombinations_CI_pa.png", dpi=400, ...@@ -617,7 +617,6 @@ ggsave(filename = "_pics/SXXX_Best_AllCombinations_CI_pa.png", dpi=400,
#species <- read_delim("_data/Mesobromion/species.out.10perc.txt", delim="\t") #species <- read_delim("_data/Mesobromion/species.out.10perc.txt", delim="\t")
species.cov <- read_delim("_data/Mesobromion/species.v2.10perc.cov.txt", delim="\t") species.cov <- read_delim("_data/Mesobromion/species.v2.10perc.cov.txt", delim="\t")
#traits <- traits.backup
traits <- traits %>% traits <- traits %>%
rownames_to_column("species0") %>% rownames_to_column("species0") %>%
mutate_if(.predicate=~is.ordered(.), mutate_if(.predicate=~is.ordered(.),
...@@ -954,130 +953,130 @@ PCA3_4.sp <- basemap0 %+% tmp + ...@@ -954,130 +953,130 @@ PCA3_4.sp <- basemap0 %+% tmp +
ylab(paste("PC4 (", varexpl[4], "%)", sep="")) ylab(paste("PC4 (", varexpl[4], "%)", sep=""))
ggsave("_pics/Fig6a_PCA_Beals_1-2_wSpecies.png", width=8, height=8, dpi=300, PCA1_2.sp) ggsave("_pics/S10a_PCA_Beals_1-2_wSpecies.png", width=8, height=8, dpi=300, PCA1_2.sp)
ggsave("_pics/Fig6b_PCA_Beals_3-4_wSpecies.png", width=8, height=8, dpi=300, PCA3_4.sp) ggsave("_pics/S10b_PCA_Beals_3-4_wSpecies.png", width=8, height=8, dpi=300, PCA3_4.sp)
###### _ ###### ###### _ ######
#### 4.2 RDA of Beals ~ FWMs #### #### 4.2 RDA of Beals ~ FWMs ####
RDA.beals <- rda(W.beals ~ scores(pca.fuzz, choices=1:3)$sites, scale=F) # RDA.beals <- rda(W.beals ~ scores(pca.fuzz, choices=1:3)$sites, scale=F)
# var explained by CONSTRAINED axes # # var explained by CONSTRAINED axes
varexpl <- round((RDA.beals$CCA$eig)/(sum(RDA.beals$CA$eig) + sum(RDA.beals$CCA$eig))*100,1) # varexpl <- round((RDA.beals$CCA$eig)/(sum(RDA.beals$CA$eig) + sum(RDA.beals$CCA$eig))*100,1)
#
scores.rda <- scores(RDA.beals, choices = 1:3)$sites # # scores.rda <- scores(RDA.beals, choices = 1:3)$sites #
#scores.rda <- RDA.beals$CA$u[,1:3] # #scores.rda <- RDA.beals$CA$u[,1:3]
(cwms.cor <- cor(CWM.wide, RDA.beals$CCA$u[,1:3])) # (cwms.cor <- cor(CWM.wide, RDA.beals$CCA$u[,1:3]))
env.cor <- cor(env %>% # env.cor <- cor(env %>%
dplyr::select(Temp, Prec, pH=PHIPHOX, C.org=ORCDRC), # dplyr::select(Temp, Prec, pH=PHIPHOX, C.org=ORCDRC),
RDA.beals$CCA$u[,1:3], use = "pairwise.complete.obs") #double check # RDA.beals$CCA$u[,1:3], use = "pairwise.complete.obs") #double check
(fuzz.cor <- cor(pca.fuzz$CA$u, RDA.beals$CCA$u[,1:3])) #RDA.beals$CCA$biplot # # (fuzz.cor <- cor(pca.fuzz$CA$u, RDA.beals$CCA$u[,1:3])) #RDA.beals$CCA$biplot #
#
myvectors.rda <- as.data.frame(env.cor) %>% # myvectors.rda <- as.data.frame(env.cor) %>%
rownames_to_column("mylab") %>% # rownames_to_column("mylab") %>%
mutate(category="Env") %>% # mutate(category="Env") %>%
bind_rows(as.data.frame(cwms.cor) %>% # bind_rows(as.data.frame(cwms.cor) %>%
rownames_to_column("mylab") %>% # rownames_to_column("mylab") %>%
mutate(category="Trait")) %>% # mutate(category="Trait")) %>%
bind_rows(as.data.frame(fuzz.cor) %>% # bind_rows(as.data.frame(fuzz.cor) %>%
rownames_to_column("mylab") %>% # rownames_to_column("mylab") %>%
mutate(mylab=paste0("FWM-", mylab)) %>% # mutate(mylab=paste0("FWM-", mylab)) %>%
mutate(category="Fuzzy-Weighted")) %>% # mutate(category="Fuzzy-Weighted")) %>%
mutate(fontface0=ifelse(mylab %in% best.traits.cov, "bold", "italic")) %>% # mutate(fontface0=ifelse(mylab %in% best.traits.cov, "bold", "italic")) %>%
mutate(category=as.factor(category)) %>% # mutate(category=as.factor(category)) %>%
mutate(mycol=ifelse(category=="Trait", oilgreen, orange)) %>% # mutate(mycol=ifelse(category=="Trait", oilgreen, orange)) %>%
mutate(mycol=ifelse(category=="Fuzzy-Weighted", myblue, mycol)) %>% # mutate(mycol=ifelse(category=="Fuzzy-Weighted", myblue, mycol)) %>%
mutate(categorical=ifelse(grepl(pattern=paste(categorical.traits, collapse="|"), mylab), 1, 0)) %>% # mutate(categorical=ifelse(grepl(pattern=paste(categorical.traits, collapse="|"), mylab), 1, 0)) %>%
rowwise() %>% # rowwise() %>%
mutate(mylab=gsub(pattern="LeafPersistence", replacement = "LeafPers", x = mylab)) # mutate(mylab=gsub(pattern="LeafPersistence", replacement = "LeafPers", x = mylab))
#
#
#
basemap0 <- ggplot(data=as.data.frame(scores.rda)) + # basemap0 <- ggplot(data=as.data.frame(scores.rda)) +
theme_bw() + # theme_bw() +
scale_color_identity() + # scale_color_identity() +
scale_y_continuous(limits=c(-1, 1)) + # scale_y_continuous(limits=c(-1, 1)) +
scale_x_continuous(limits=c(-1, 1)) + coord_equal() + # scale_x_continuous(limits=c(-1, 1)) + coord_equal() +
theme(panel.grid = element_blank()) # theme(panel.grid = element_blank())
#
#
RDA1_2 <- basemap0 + # RDA1_2 <- basemap0 +
geom_point(data=as.data.frame(scores.rda), # geom_point(data=as.data.frame(scores.rda),
aes(x=RDA1, y=RDA2), pch="+", size=2, alpha=0.8) + # aes(x=RDA1, y=RDA2), pch="+", size=2, alpha=0.8) +
geom_segment(data=myvectors.rda %>% # geom_segment(data=myvectors.rda %>%
filter(categorical==0), # filter(categorical==0),
aes(x=0, xend=RDA1, y=0, yend=RDA2, col=mycol), # aes(x=0, xend=RDA1, y=0, yend=RDA2, col=mycol),
arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) + # 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_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
geom_label_repel(data=myvectors.rda, # geom_label_repel(data=myvectors.rda,
aes(x=RDA1, y=RDA2, label=mylab, col=mycol, fontface=fontface0), size=2, # aes(x=RDA1, y=RDA2, label=mylab, col=mycol, fontface=fontface0), size=2,
position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) + # position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) + # xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
ylab(paste("RDA2 (", varexpl[2], "%)", sep="")) # ylab(paste("RDA2 (", varexpl[2], "%)", sep=""))
#
ggsave("_pics/Fig6v2_RDA_Beals_1-2.png", width=10, height=5, dpi=300, RDA1_2) # ggsave("_pics/Fig6v2_RDA_Beals_1-2.png", width=10, height=5, dpi=300, RDA1_2)
#
#
RDA1_3 <- basemap0 + # RDA1_3 <- basemap0 +
geom_point(data=as.data.frame(scores.rda), # geom_point(data=as.data.frame(scores.rda),
aes(x=RDA1, y=RDA3), pch="+", size=2, alpha=0.8) + # aes(x=RDA1, y=RDA3), pch="+", size=2, alpha=0.8) +
geom_segment(data=myvectors.rda %>% # geom_segment(data=myvectors.rda %>%
filter(categorical==0), # filter(categorical==0),
aes(x=0, xend=RDA1, y=0, yend=RDA3, col=mycol), # aes(x=0, xend=RDA1, y=0, yend=RDA3, col=mycol),
arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) + # 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_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
geom_label_repel(data=myvectors.rda, # geom_label_repel(data=myvectors.rda,
aes(x=RDA1, y=RDA3, label=mylab, col=mycol, fontface=fontface0), size=2, # aes(x=RDA1, y=RDA3, label=mylab, col=mycol, fontface=fontface0), size=2,
position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) + # position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) + # xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
ylab(paste("RDA3 (", varexpl[3], "%)", sep="")) # ylab(paste("RDA3 (", varexpl[3], "%)", sep=""))
#
panel.RDA_beals <- cowplot::plot_grid(RDA1_2,RDA1_3, nrow=1) # panel.RDA_beals <- cowplot::plot_grid(RDA1_2,RDA1_3, nrow=1)
#
ggsave("_pics/Fig6v2_RDA_Beals_1-2-3.png", width=10, height=5, dpi=300, panel.RDA_beals) # ggsave("_pics/Fig6v2_RDA_Beals_1-2-3.png", width=10, height=5, dpi=300, panel.RDA_beals)
#
#### 4.2.1 Alternative showing species scores #### # #### 4.2.1 Alternative showing species scores ####
tmp <- as.data.frame(scores(RDA.beals, choices = 1:3)$species*4) %>% # tmp <- as.data.frame(scores(RDA.beals, choices = 1:3)$species*4) %>%
#tmp <- as.data.frame(RDA.beals$CCA$v*4) %>% # #tmp <- as.data.frame(RDA.beals$CCA$v*4) %>%
mutate(species0=rownames(RDA.beals$CCA$v)) %>% # mutate(species0=rownames(RDA.beals$CCA$v)) %>%
mutate(species=species0) %>% # mutate(species=species0) %>%
separate(species0, sep="_", into=c("Gen", "Spe")) %>% # separate(species0, sep="_", into=c("Gen", "Spe")) %>%
mutate(Gen=substr(Gen, 1, 3)) %>% # mutate(Gen=substr(Gen, 1, 3)) %>%
mutate(Spe=substr(Spe, 1, 3)) %>% # mutate(Spe=substr(Spe, 1, 3)) %>%
mutate(labels=paste(Gen, Spe, sep="_")) # mutate(labels=paste(Gen, Spe, sep="_"))
#
tmp <- fix.duplicate.labels(tmp) # tmp <- fix.duplicate.labels(tmp)
#
#
RDA1_2.sp <- basemap0 %+% tmp + # RDA1_2.sp <- basemap0 %+% tmp +
geom_text(aes(x=RDA1, y=RDA2, label=labels), size=2, alpha=0.8) + # geom_text(aes(x=RDA1, y=RDA2, label=labels), size=2, alpha=0.8) +
geom_segment(data=myvectors.rda%>% # geom_segment(data=myvectors.rda%>%
filter(categorical==0), # filter(categorical==0),
aes(x=0, xend=RDA1, y=0, yend=RDA2, col=mycol), # aes(x=0, xend=RDA1, y=0, yend=RDA2, col=mycol),
arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) + # 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_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
geom_label_repel(data=myvectors.rda, # geom_label_repel(data=myvectors.rda,
aes(x=RDA1, y=RDA2, label=mylab, col=mycol, fontface=fontface0), size=2, # aes(x=RDA1, y=RDA2, label=mylab, col=mycol, fontface=fontface0), size=2,
position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) + # position = position_dodge(1), segment.alpha=0.5, segment.colour=gray(0.8)) +
xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) + # xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
ylab(paste("RDA2 (", varexpl[2], "%)", sep="")) # ylab(paste("RDA2 (", varexpl[2], "%)", sep=""))
#
RDA1_3.sp <- basemap0 %+% tmp + # RDA1_3.sp <- basemap0 %+% tmp +
geom_text(aes(x=RDA1, y=RDA3, label=labels), size=2, alpha=0.8) + # geom_text(aes(x=RDA1, y=RDA3, label=labels), size=2, alpha=0.8) +
geom_segment(data=myvectors.rda%>% # geom_segment(data=myvectors.rda%>%
filter(categorical==0), # filter(categorical==0),
aes(x=0, xend=RDA1, y=0, yend=RDA3, col=mycol), # aes(x=0, xend=RDA1, y=0, yend=RDA3, col=mycol),
arrow = arrow(length = unit(0.08, "inches")), alpha=0.8) + # 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_path(data=dat,aes(x,y), col=gray(0.8), lwd=0.5) + #add correlation circle
geom_label_repel(data=myvectors.rda, # geom_label_repel(data=myvectors.rda,
aes(x=RDA1, y=RDA3, label=mylab, col=mycol, fontface=fontface0), size=2, # aes(x=RDA1, y=RDA3, 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) + # position = position_dodge(1), segment.alpha=0.8, segment.colour=gray(0.7), segment.size = 0.5) +
xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) + # xlab(paste("RDA1 (", varexpl[1], "%)", sep="")) +
ylab(paste("RDA3 (", varexpl[3], "%)", sep="")) # ylab(paste("RDA3 (", varexpl[3], "%)", sep=""))
#
#
ggsave("_pics/Fig6v2a_RDA_Beals_1-2_wSpecies.png", width=8, height=8, dpi=300, RDA1_2.sp) # ggsave("_pics/Fig6v2a_RDA_Beals_1-2_wSpecies.png", width=8, height=8, dpi=300, RDA1_2.sp)
ggsave("_pics/Fig6v2b_RDA_Beals_1-3_wSpecies.png", width=8, height=8, dpi=300, RDA1_3.sp) # ggsave("_pics/Fig6v2b_RDA_Beals_1-3_wSpecies.png", width=8, height=8, dpi=300, RDA1_3.sp)
#
......
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