#########################################################################
################Making the presence/absence matrix#######################
#########################################################################

#####ITS

comITS  <- read.csv("input/ITS_Fungi_taxonomy_metadata2.csv")
comITS <- comITS[,c(-1,-78)]
comITS [comITS  > 1] <- 1
comITS <- as.data.frame(comITS)
nrow (comITS)
#write.csv(comITS , "otu_ITS_presence_absence.csv")

######18S

com18S  <- read.csv("input/18S_Fungi_taxonomy_metadata.csv")
com18S <- com18S[,c(-1,-78)]
com18S [com18S  > 1] <- 1
com18S <- as.data.frame(com18S)
nrow (com18S)
#write.csv(com18S , "otu_18S_presence_absence.csv")

######COI

comCOI  <- read.csv("input/COI_Fungi_taxonomy_metadata.csv")
comCOI <- comCOI[,c(-1,-78)]
comCOI [comCOI  > 1] <- 1
comCOI <- as.data.frame(comCOI)
nrow (comCOI)
#write.csv(comCOI , "otu_COI_presence_absence.csv")

##########Betadiversity analysis

biol <- read.csv("input/meta_soil_data2.csv")
head(biol)

#####ITS

ITS.nmds <- metaMDS(as.matrix(t(Abu_VST_ITS2)), distance="jaccard",k=2, autotransform=F)
ITS.nmds <- metaMDS(as.matrix(t(Abu_VST_ITS2)), distance="jaccard",k=2, autotransform=F, previou.best = ITS.nmds)
summary(ITS.nmds)
scITS <- data.frame(scores(ITS.nmds))
scITS$ID <- rownames(scITS)
write.csv(scITS, "ITS_NMDS_metadata.csv")


scITS <- scITS %>%
  as_data_frame()%>%
  inner_join(biol, by = "ID")

#####18S

s18S.nmds <- metaMDS(as.matrix(t(Abu_VST_18S2)), distance="jaccard",k=2, autotransform=F)
s18S.nmds <- metaMDS(as.matrix(t(Abu_VST_18S2)), distance="jaccard",k=2, autotransform=F, previou.best = s18S.nmds)
summary(s18S.nmds)
sc18S <- data.frame(scores(s18S.nmds))
sc18S$ID <- rownames(sc18S)
write.csv(sc18S, "18S_NMDS_metadata.csv")


sc18S <- sc18S %>%
  as_data_frame()%>%
  inner_join(biol, by = "ID")

#####COI

COI.nmds <- metaMDS(as.matrix(t(Abu_VST_COI2)), distance="jaccard",k=2, autotransform=F)
COI.nmds <- metaMDS(as.matrix(t(Abu_VST_COI2)), distance="jaccard",k=2, autotransform=F, previou.best = COI.nmds)
summary(COI.nmds)
scCOI <- data.frame(scores(COI.nmds))
scCOI$ID <- rownames(scCOI)
write.csv(scCOI, "COI_NMDS_metadata.csv")


scCOI <- scCOI %>%
  as_data_frame()%>%
  inner_join(biol, by = "ID")

##envfit

###Eukaryote(ITS)
envfit(scITS[,1:2] ~ as.factor(scITS$locality))
envfit(scITS[,1:2] ~ as.factor(scITS$habitat))
envfit(scITS[,1:2] ~ as.factor(scITS$kind))

###Eukaryote(18S)
envfit(sc18S[,1:2] ~ as.factor(sc18S$locality))
envfit(sc18S[,1:2] ~ as.factor(sc18S$habitat))
envfit(sc18S[,1:2] ~ as.factor(sc18S$kind))


###Eukaryote(COI)
envfit(scCOI[,1:2] ~ as.factor(scCOI$locality))
envfit(scCOI[,1:2] ~ as.factor(scCOI$habitat))
envfit(scCOI[,1:2] ~ as.factor(scCOI$kind))


cols1 <- c("#fddbc7",
           "#5e3c99",
           "#e66101",
           "#a6dba0")

cols2 <- c("#ca0020",
           "#dfc27d",
           "#92c5de",
           "#0571b0")


#subfigure A
figA <- scITS %>%
  ggplot()+
  geom_point(aes(x = NMDS1, y = NMDS2, colour = habitat, shape = kind), size = 5)+
  ggtitle("A - ITS Habitat")+
  xlab("")+
  ylab("")+
  scale_fill_discrete(name = "Environmental\ntype")+
  scale_color_manual(values=cols1)+
  theme(panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        panel.background = element_blank(),
        axis.line = element_line(colour = "black"),
        panel.border = element_rect(colour = "black", fill=NA, size=1),
        legend.position = ("left"))


#subfigure B
figB <- scITS %>%
  ggplot()+
  geom_point(aes(x = NMDS1, y = NMDS2, colour = locality, shape = kind), size = 5)+
  ggtitle("B - ITS Locality")+
  xlab("")+
  ylab("")+
  scale_fill_discrete(name = "Environmental\ntype")+
  scale_shape_manual(values=c(16:17))+
  scale_color_manual(values=cols2)+
  theme(panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        panel.background = element_blank(),
        axis.line = element_line(colour = "black"),
        panel.border = element_rect(colour = "black", fill=NA, size=1),
        legend.position = ("left"))

#subfigure C
figC <- sc18S %>%
  ggplot()+
  geom_point(aes(x = NMDS1, y = NMDS2, colour = habitat, shape = kind), size = 5)+
  ggtitle("C - 18S Habitat")+
  xlab("")+
  ylab("")+
  scale_fill_discrete(name = "Environmental\ntype")+
  scale_color_manual(values=cols1)+
  theme(panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        panel.background = element_blank(),
        axis.line = element_line(colour = "black"),
        panel.border = element_rect(colour = "black", fill=NA, size=1),
        legend.position = ("left"))


#subfigure D
figD <- sc18S %>%
  ggplot()+
  geom_point(aes(x = NMDS1, y = NMDS2, colour = locality, shape = kind), size = 5)+
  ggtitle("D - 18S Locality")+
  xlab("")+
  ylab("")+
  scale_fill_discrete(name = "Environmental\ntype")+
  scale_shape_manual(values=c(16:17))+
  scale_color_manual(values=cols2)+
  theme(panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        panel.background = element_blank(),
        axis.line = element_line(colour = "black"),
        panel.border = element_rect(colour = "black", fill=NA, size=1),
        legend.position = ("left"))

#subfigure E
figE <- scCOI %>%
  ggplot()+
  geom_point(aes(x = NMDS1, y = NMDS2, colour = habitat, shape = kind), size = 5)+
  ggtitle("E - COI Habitat")+
  xlab("")+
  ylab("")+
  scale_fill_discrete(name = "Environmental\ntype")+
  scale_color_manual(values=cols1)+
  theme(panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        panel.background = element_blank(),
        axis.line = element_line(colour = "black"),
        panel.border = element_rect(colour = "black", fill=NA, size=1),
        legend.position = ("left"))


#subfigure F
figF <- scCOI %>%
  ggplot()+
  geom_point(aes(x = NMDS1, y = NMDS2, colour = locality, shape = kind), size = 5)+
  ggtitle("F - COI Locality")+
  xlab("")+
  ylab("")+
  scale_fill_discrete(name = "Environmental\ntype")+
  scale_shape_manual(values=c(16:17))+
  scale_color_manual(values=cols2)+
  theme(panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(),
        panel.background = element_blank(),
        axis.line = element_line(colour = "black"),
        panel.border = element_rect(colour = "black", fill=NA, size=1),
        legend.position = ("left"))


fig2 <- gridExtra::grid.arrange(figA,figB,figC,figD,figE,figF,bottom = "NMDS1", left = "NMDS2")
ggsave("output/Fig_NMDS_Habitat_and_Locality.pdf", plot = fig2, width =10, height = 12)



#########################################################
###################PERMANOVA#############################
#########################################################

###ITS

tcomITS <- t(Abu_VST_ITS2)
tcomITS <- as.data.frame (tcomITS)


adoITS <- adonis2(tcomITS ~ biol$habitat + biol$locality+ biol$kind + soil_phy_che_st$pH + soil_phy_che_st$C + Chemical.pc1 + Physical.PC1, strata = biol$ID, data = tcomITS, type = 'Jaccard', binary = TRUE)
adoITS 

###Posthoc test multiple categorical variables
#install.packages('devtools')
library(devtools)
#install_github("pmartinezarbizu/pairwiseAdonis/pairwiseAdonis") 
library(pairwiseAdonis)
pair.mod.hab<-pairwise.adonis(tcomITS,factors=biol$habitat)
pair.mod.loc<-pairwise.adonis(tcomITS,factors=biol$locality)
pair.mod.kin<-pairwise.adonis(tcomITS,factors=biol$kind)


adoITS2 <- adonis(tcomITS ~ biol$habitat + biol$locality+ biol$kind + soil_phy_che_st$pH + soil_phy_che_st$C + Chemical.pc1 + Physical.PC1, strata = biol$ID, data = tcomITS, type = 'Jaccard', binary = TRUE)
adoITS2

###18S

tcom18S <- t(Abu_VST_18S2)
tcom18S <- as.data.frame (tcom18S)


ado18S <- adonis2(tcom18S ~ biol$habitat + biol$locality+ biol$kind + soil_phy_che_st$pH + soil_phy_che_st$C + Chemical.pc1 + Physical.PC1, strata = biol$ID, data = tcom18S, type = 'Jaccard', binary = TRUE)
ado18S 
pair.mod.hab18s<-pairwise.adonis(tcom18S,factors=biol$habitat)
pair.mod.loc18s<-pairwise.adonis(tcom18S,factors=biol$locality)
pair.mod.kin18<-pairwise.adonis(tcom18S,factors=biol$kind)

ado18S2 <- adonis(tcom18S ~ biol$habitat + biol$locality+ biol$kind + soil_phy_che_st$pH + soil_phy_che_st$C + Chemical.pc1 + Physical.PC1, strata = biol$ID, data = tcom18S, type = 'Jaccard', binary = TRUE)
ado18S2

###COI

tcomCOI <- t(Abu_VST_COI2)
tcomCOI <- as.data.frame (tcomCOI)


adoCOI <- adonis2(tcomCOI ~ biol$habitat + biol$locality+ biol$kind + soil_phy_che_st$pH + soil_phy_che_st$C + Chemical.pc1 + Physical.PC1, strata = biol$ID, data = tcomCOI, type = 'Jaccard', binary = TRUE)
adoCOI 
pair.mod.habcoi<-pairwise.adonis(tcomCOI,factors=biol$habitat)
pair.mod.loccoi<-pairwise.adonis(tcomCOI,factors=biol$locality)
pair.mod.kincoi<-pairwise.adonis(tcomCOI,factors=biol$kind)

adoCOI2 <- adonis(tcomCOI ~ biol$habitat + biol$locality+ biol$kind + soil_phy_che_st$pH + soil_phy_che_st$C + Chemical.pc1 + Physical.PC1, strata = biol$ID, data = tcomCOI, type = 'Jaccard', binary = TRUE)
adoCOI2

################################################################
##################       Mantel        #########################
################################################################

###ITS

disITS  <- vegdist(as.matrix(t(Abu_VST_ITS2)), method = "jaccard")


###18S

dis18S  <- vegdist(as.matrix(t(Abu_VST_18S2)), method = "jaccard")


###COI

disCOI  <- vegdist(as.matrix(t(Abu_VST_COI2)), method = "jaccard")



#Correlation between datasets similarity matrices

vegan::mantel(disITS, disCOI, method="pearson", permutations=999)
vegan::mantel(disITS, dis18S, method="pearson", permutations=999)
vegan::mantel(dis18S, disCOI, method="pearson", permutations=999)



####################################################
### Community structure and soil characteristics ####
####################################################


# multiple regresioon with dissimilarity matrix


#soil

metaPCs <- cbind(meta[,1:7], meta[,13:14], Chemical.pc1, Physical.PC1)

metaPCs.s <- metaPCs[39:76, ]
latlong.s <- cbind(metaPCs.s$long,  metaPCs.s$lat)
geo.dist.s <- vegdist((latlong.s), method = "euclidean")
log.geo.dist.s <- log(geo.dist.s)

#litter

metaPCs.l <- metaPCs[1:38, ]
latlong.l <- cbind(metaPCs.l$long,  metaPCs.l$lat)
geo.dist.l <- vegdist((latlong.l), method = "euclidean")
log.geo.dist.l <- log(geo.dist.l)


#18S

s18s <- Abu_VST_18S2[,39:76]
s18s <-t(s18)

s18sjac.dist <- vegdist((s18), method = "jaccard")

glm18ss <- MRM(s18sjac.dist ~ geo.dist.s+ dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.s, nperm=10000, mrank = T)
glm18ss

glm18ss2 <- MRM(s18sjac.dist ~ log.geo.dist.s+  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.s, nperm=10000, mrank = T)
glm18ss2

s18l <- Abu_VST_18S2[,1:38]
s18l <-t(s18l)

l18sjac.dist <- vegdist((s18l), method = "jaccard")

glm18sl <- MRM(l18sjac.dist ~ geo.dist.l +  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.l, nperm=10000, mrank = T)
glm18sl

glm18sl2 <- MRM(l18sjac.dist ~ log.geo.dist.l +  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.l, nperm=10000, mrank = T)
glm18sl2

#COI

sCOI <- Abu_VST_COI2[,39:76]
sCOI <-t(sCOI)

sCOIjac.dist <- vegdist((sCOI), method = "jaccard")

glmCOIs <- MRM(sCOIjac.dist ~ geo.dist.s+  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.s, nperm=10000, mrank = T)
glmCOIs

glmCOIs2 <- MRM(sCOIjac.dist ~ log.geo.dist.s+  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.s, nperm=10000, mrank = T)
glmCOIs2

COIl <- Abu_VST_COI2[,1:38]
COIl <-t(COIl)

lCOIjac.dist <- vegdist((COIl), method = "jaccard")

glmCOIl <- MRM(lCOIjac.dist ~ geo.dist.l +  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.l, nperm=10000, mrank = T)
glmCOIl

glmCOIl2 <- MRM(lCOIjac.dist ~ log.geo.dist.l +  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.l, nperm=10000, mrank = T)
glmCOIl2

#ITS

sITS <- Abu_VST_ITS2[,39:76]
sITS <-t(sITS)

sITSjac.dist <- vegdist((sITS), method = "jaccard")

glmITSs <- MRM(sITSjac.dist ~ geo.dist.s+  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.s, nperm=10000, mrank = T)
glmITSs

glmITSs2 <- MRM(sITSjac.dist ~ log.geo.dist.s+  dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.s, nperm=10000, mrank = T)
glmITSs2

ITSl <- Abu_VST_ITS2[,1:38]
ITSl <-t(ITSl)

lITSjac.dist <- vegdist((ITSl), method = "jaccard")

glmITSl <- MRM(lITSjac.dist ~ geo.dist.l + dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.l, nperm=10000, mrank = T)
glmITSl

glmITSl2 <- MRM(lITSjac.dist ~ log.geo.dist.l + dist(pH)+ dist(C)+ dist(Chemical.pc1) + dist(Physical.PC1),data=metaPCs.l, nperm=10000, mrank = T)
glmITSl2