aligned 00 99 session

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")
+

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 ####

session.R

 
 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)