diff --git a/00_Mesobromion_DataPreparation.R b/00_Mesobromion_DataPreparation.R
index 3386d0f09291359f1f693d3f27b54ab8b853c9f5..54c33b0a0b17849abcac3eb0b7b2d4b4fb53ab12 100644
--- a/00_Mesobromion_DataPreparation.R
+++ b/00_Mesobromion_DataPreparation.R
@@ -279,14 +279,12 @@ env <- env %>%
# pull(RELEVE_NR)
#
-
-
-
-
+species <- species %>%
+ rownames_to_column("RELEVE_NR")
##export for Valerio
write_delim(species, path="_data/Mesobromion/species.out.10perc.txt", delim="\t")
-write_delim(traits, path="_data/Mesobromion/traits.out.10perc.cov.txt", delim="\t")
+write_delim(traits, path="_data/Mesobromion/traits.out.10perc.txt", delim="\t")
write_delim(env, path="_data/Mesobromion/env.10perc.cov.txt", delim="\t")
@@ -302,18 +300,24 @@ write_delim(species %>%
dplyr::select(RELEVE_NR),
path="_derived/Mesobromion/ReleveList.txt", delim="\t")
+###### 5. Species data with cover values #####
### version with cover values ### 4/08/2020
+env0 <- read_delim("_data/Mesobromion/GVRD_MES2_site.csv", delim = ",")
species.proz <- read_csv("_data/Mesobromion/GVRD_Mes2_proz.csv", locale = locale(encoding = 'latin1'))
species.proz$RELEVE_NR <- env0$RELEVE_NR
species.proz <- species.proz %>%
filter(RELEVE_NR %in% (species %>% pull(RELEVE_NR))) %>%
- #transform percentage cover to relative.cover
+ ## delete species not appearing in any plot
+ dplyr::select(colnames(.)[which(colSums(.)!=0)])
+dim(species.proz)
+write_delim(species.proz , path="_data/Mesobromion/species.out.10perc.proz.txt", delim="\t")
+
+#transform percentage cover to relative.cover
+species.proz <- species.proz %>%
mutate(sumVar = rowSums(.[-1])) %>%
mutate_at(.vars=vars(-RELEVE_NR),
.funs=~./sumVar) %>%
- dplyr::select(-sumVar) %>%
- ## delete species not appearing in any plot
- dplyr::select(colnames(.)[which(colSums(.)!=0)])
+ dplyr::select(-sumVar)
dim(species.proz) #[1] 558 533
write_delim(species.proz , path="_data/Mesobromion/species.out.10perc.cov.txt", delim="\t")
@@ -349,3 +353,94 @@ write_delim(traits.proz, path="_data/Mesobromion/traits.out.10perc.cov.txt", del
#### CORRELATION BETWEEN FUZZY WEIGHTED AND BEALS MATRICES
#### WAS RUN IN THE CLUSTER WITH THE SCRIPT 01b_MesobromionCluster.R
+
+
+
+
+
+
+
+### PART 2 ####
+source("01b_MesobromionCluster.R")
+#### 1. Traits individually significant for COVER data####
+traits <- read_delim("_data/Mesobromion/traits.out.10perc.cov.txt", delim="\t")
+myfilelist <- list.files(path="_derived/Mesobromion/Cover", pattern="HIDDENproz_[0-9]+_.RData", full.names = T)
+dataFiles = purrr::map(myfilelist, function(x){get(load(x))})
+corXY = bind_rows(dataFiles) %>%
+ as_tibble()
+rm( dataFiles)
+
+trait.labs <- data.frame(Trait.comb=as.character(1:(ncol(traits)-1)),
+ trait.name=colnames(traits)[-1])
+
+corXY.ci <- get.ci(corXY)
+corXY.ci <- corXY.ci %>%
+ arrange(desc(sign_plus), desc(Coef.obs)) %>%
+ left_join(trait.labs, by="Trait.comb") %>%
+ dplyr::select(-Test)
+
+## NO significant TRAITS when using Cover values
+# traits.sign.alone <- corXY.ci %>%
+# filter(sign_plus) %>%
+# pull(trait.name)
+#
+# traits.sign <- traits %>%
+# dplyr::select(species0, any_of(traits.sign.alone))
+# write_delim(traits.sign, path="_data/Mesobromion/traits.out.10perc.cov.sign.txt", delim="\t")
+
+"# A tibble: 50 x 11
+ Trait.comb Coef.obs Coef.perm q025 q975 greater.than.perm n sign_plus sign_minus ntraits trait.name
+ <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <lgl> <lgl> <int> <fct>
+ 1 17 0.335 0.205 0.275 0.436 0.903 999 FALSE FALSE 1 V_VER_Fragmentation
+ 2 12 0.255 0.139 0.235 0.315 0.690 999 FALSE FALSE 1 V_VER_Rhizom
+ 3 11 0.226 0.170 0.218 0.279 0.533 999 FALSE FALSE 1 V_VER_Ausläufer
+ 4 5 0.199 0.340 0.194 0.247 0.502 999 FALSE FALSE 1 LEB_F_Hemiphanerophyt
+ 5 2 0.198 0.232 0.191 0.247 0.447 999 FALSE FALSE 1 LEB_F_Nanophanerophyt
+ 6 19 0.198 0.217 0.193 0.245 0.539 999 FALSE FALSE 1 V_VER_Sprossknolle
+ 7 44 0.194 0.171 0.199 0.242 0.299 999 FALSE FALSE 1 BLU_KL
+ 8 45 0.192 0.188 0.187 0.238 0.526 999 FALSE FALSE 1 REPR_T
+ 9 10 0.191 0.187 0.187 0.240 0.366 999 FALSE FALSE 1 V_VER_Wurzelspross
+10 42 0.190 0.235 0.192 0.236 0.261 999 FALSE FALSE 1 Disp.unit.leng
+# … with 40 more rows"
+
+#### 2. Traits individually significant for Presence|absence data####
+traits <- read_delim("_data/Mesobromion/traits.out.10perc.txt", delim="\t")
+myfilelist <- list.files(path="_derived/Mesobromion/PresAbs", pattern="HIDDENpa_[0-9]+_.RData", full.names = T)
+dataFiles = purrr::map(myfilelist, function(x){get(load(x))})
+corXY = bind_rows(dataFiles) %>%
+ as_tibble()
+rm( dataFiles)
+
+trait.labs <- data.frame(Trait.comb=as.character(1:(ncol(traits)-1)),
+ trait.name=colnames(traits)[-1])
+
+corXY.ci <- get.ci(corXY)
+corXY.ci <- corXY.ci %>%
+ arrange(desc(sign_plus), desc(Coef.obs)) %>%
+ left_join(trait.labs, by="Trait.comb") %>%
+ dplyr::select(-Test)
+
+"# A tibble: 52 x 11
+ Trait.comb Coef.obs Coef.perm q025 q975 greater.than.perm n sign_plus sign_minus ntraits trait.name
+ <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <int> <lgl> <lgl> <int> <fct>
+ 1 35 0.300 0.0714 0.270 0.350 0.993 999 TRUE FALSE 1 PlantHeight
+ 2 34 0.279 0.201 0.250 0.326 0.993 999 TRUE FALSE 1 LeafP
+ 3 31 0.253 0.165 0.231 0.303 0.987 999 TRUE FALSE 1 SLA
+ 4 37 0.244 0.0847 0.218 0.293 0.986 999 TRUE FALSE 1 Seed.length
+ 5 33 0.243 0.0984 0.218 0.290 0.994 999 TRUE FALSE 1 LeafN
+ 6 32 0.240 0.0846 0.218 0.290 0.986 999 TRUE FALSE 1 LeafC.perdrymass
+ 7 44 0.234 0.145 0.208 0.288 0.980 999 TRUE FALSE 1 Disp.unit.leng
+ 8 2 0.234 0.263 0.216 0.283 0.593 1998 FALSE FALSE 1 LEB_F_Nanophanerophyt
+ 9 5 0.233 0.267 0.214 0.287 0.571 999 FALSE FALSE 1 LEB_F_Hemiphanerophyt
+10 30 0.227 0.177 0.203 0.281 0.970 999 FALSE FALSE 1 LeafArea
+# … with 42 more rows"
+
+
+traits.sign.alone <- corXY.ci %>%
+ filter(sign_plus) %>%
+ pull(trait.name)
+
+traits.sign <- traits %>%
+ dplyr::select(species0, any_of(traits.sign.alone))
+write_delim(traits.sign, path="_data/Mesobromion/traits.out.10perc.sign.txt", delim="\t")
+
diff --git a/99_HIDDEN_functions.R b/99_HIDDEN_functions.R
index 00c6328cdf3a6025cdf137b9059c3519114d1d4f..23bab26838c62017824ae65723a2767c86e44061 100644
--- a/99_HIDDEN_functions.R
+++ b/99_HIDDEN_functions.R
@@ -14,40 +14,6 @@ library(ade4)
library(energy)
-#### Function 1 - CorXY ####
-get.corXY <- function(comm, traits, trait.sel="all", stat=c("mantel", "RV", "procrustes")){
- if(identical(trait.sel, "all")) {trait.sel <- 1:ncol(traits)}
- ii <- trait.sel
- lab.tmp <- paste(ii, collapse="_")
- ### delete potential missing species
- if(any(colSums(comm)==0)){
- empty <- which(colSums(comm)==0)
- traits <- traits[-empty,]
- comm <- comm[,-empty]
- }
- syn.out.tmp <- matrix.x(comm=comm, traits=traits[,ii,drop=F], scale=T)$matrix.X
- W.beals <- as.data.frame(beals(comm, include=T, type=2))
- corXY <- NULL
- if("mantel" %in% stat){
- W.beals.d <- dist(W.beals)
- mantel.tmp <- mantel(W.beals.d, dist(syn.out.tmp[]))
- corXY <- rbind(corXY,
- data.frame(Trait.comb=lab.tmp, Test="Mantel", Coef=mantel.tmp$statistic, pvalue=mantel.tmp$signif))
- }
- if("RV" %in% stat){
- RV.tmp <- RV.rtest(W.beals, as.data.frame(syn.out.tmp))
- corXY <- rbind(corXY,
- data.frame(Trait.comb=lab.tmp, Test="RV", Coef=RV.tmp$obs, pvalue=RV.tmp$pvalue))
- }
- if("procrustes" %in% stat){
- prot.tmp <- protest(W.beals, syn.out.tmp)
- corXY <- rbind(corXY,
- data.frame(Trait.comb=lab.tmp, Test="Procrustes", Coef=prot.tmp$t0, pvalue=prot.tmp$signif))
- }
- return(corXY)
-}
-
-
#### Function 1b - CorXY bootstrap####
get.corXY.bootstrap <- function(comm, traits, trait.sel="all", bootstrap=199){
if(identical(trait.sel, "all")) {trait.sel <- 1:ncol(traits)}
@@ -107,6 +73,44 @@ get.corXY.bootstrap <- function(comm, traits, trait.sel="all", bootstrap=199){
+##### NOT ACTIVELY MANTAINED BELOW ####
+
+
+#### Function 1 - CorXY ####
+get.corXY <- function(comm, traits, trait.sel="all", stat=c("mantel", "RV", "procrustes")){
+ if(identical(trait.sel, "all")) {trait.sel <- 1:ncol(traits)}
+ ii <- trait.sel
+ lab.tmp <- paste(ii, collapse="_")
+ ### delete potential missing species
+ if(any(colSums(comm)==0)){
+ empty <- which(colSums(comm)==0)
+ traits <- traits[-empty,]
+ comm <- comm[,-empty]
+ }
+ syn.out.tmp <- matrix.x(comm=comm, traits=traits[,ii,drop=F], scale=T)$matrix.X
+ W.beals <- as.data.frame(beals(comm, include=T, type=2))
+ corXY <- NULL
+ if("mantel" %in% stat){
+ W.beals.d <- dist(W.beals)
+ mantel.tmp <- mantel(W.beals.d, dist(syn.out.tmp[]))
+ corXY <- rbind(corXY,
+ data.frame(Trait.comb=lab.tmp, Test="Mantel", Coef=mantel.tmp$statistic, pvalue=mantel.tmp$signif))
+ }
+ if("RV" %in% stat){
+ RV.tmp <- RV.rtest(W.beals, as.data.frame(syn.out.tmp))
+ corXY <- rbind(corXY,
+ data.frame(Trait.comb=lab.tmp, Test="RV", Coef=RV.tmp$obs, pvalue=RV.tmp$pvalue))
+ }
+ if("procrustes" %in% stat){
+ prot.tmp <- protest(W.beals, syn.out.tmp)
+ corXY <- rbind(corXY,
+ data.frame(Trait.comb=lab.tmp, Test="Procrustes", Coef=prot.tmp$t0, pvalue=prot.tmp$signif))
+ }
+ return(corXY)
+}
+
+
+
#### Function 2 - CorTE ####
diff --git a/session.R b/session.R
index 07dc7d3601fe7b2e8e69ad661d586e309ff30429..78b6f932caef24f863d324c3fbabd74494c9e1c3 100644
--- a/session.R
+++ b/session.R
@@ -1,19 +1,18 @@
species.path <- "_data/Mesobromion/species.out.10perc.cov.txt"
traits.path <- "_data/Mesobromion/traits.out.10perc.cov.txt"
-output <- "_derived/Mesobromion/HIDDEN"
+output <- "_derived/Mesobromion/Cover/HIDDENtest"
myfunction <- "get.corXY.bootstrap"
-max.inter.t <- 2
-chunk.i <- NA
-nperm <- 5
-ncores <- 8
-chunkn <- 3*ncores
-combinations <- "sequential"
+max.inter.t <- 1
+chunk.i <- 1
+nperm <- 49
+ncores <- 1
+chunkn <- 1
+combinations <- "all"
start.round <- 1
-relax.round <- 2
+relax.round <- 1
source("01b_MesobromionCluster.R")
-#Mesobromion(species.path, traits.path, output, myfunction, max.inter.t, chunkn, chunk.i, nperm)
Mesobromion(species.path, traits.path, output, myfunction,
combinations, start.round, relax.round, max.inter.t,
chunkn, chunk.i, nperm, ncores)