untitled3

library(vegan)

## Warning: package 'vegan' was built under R version 4.4.3

## Loading required package: permute

## Warning: package 'permute' was built under R version 4.4.3

library(readxl)

## Warning: package 'readxl' was built under R version 4.4.3

p1=read_excel("Book1_1.xlsx")

colnames(p1)

## [1] "Area"               "Shannon"            "Simpson"           
## [4] "Riqueza específica"

attach(p1)

length(Area)

## [1] 27

length(Shannon)

## [1] 27

boxplot_p1=boxplot(as.numeric(p1$Shannon) ~ p1$Area,
                       col=c("darkred","darkorange","darkgreen"),xlab="Area",ylab="Shannon",outline=FALSE)

pairwise.wilcox.test(as.numeric(p1$Shannon),as.factor(p1$Area), p.adjust.method =  "bonferroni",paired = F)

## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot compute
## exact p-value with ties

## 
##  Pairwise comparisons using Wilcoxon rank sum test with continuity correction 
## 
## data:  as.numeric(p1$Shannon) and as.factor(p1$Area) 
## 
##   N     
## S 0.0016
## 
## P value adjustment method: bonferroni

#Tree_HRA=vars[c(1:52),]
#mann-whitney test

# Ensure Area is a factor (grouping variable)
#p1$Area <- as.factor(p1$Area)

# Ensure Shannon is numeric
#p1$Shannon <- as.numeric(p1$Shannon)

# Perform the pairwise Wilcoxon test
#pairwise.wilcox.test(p1$Shannon, p1$Area, 
                     #p.adjust.method = "bonferroni", 
                    # paired = FALSE)

boxplot_p2=boxplot(as.numeric(p1$Simpson) ~ p1$Area,
                       col=c("#FFF68F","#473C8B"),xlab="Area",ylab="Simpson",outline=FALSE)

pairwise.wilcox.test(as.numeric(p1$Simpson),as.factor(p1$Area), p.adjust.method =  "holm",
                     paired = F)

## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot compute
## exact p-value with ties

## 
##  Pairwise comparisons using Wilcoxon rank sum test with continuity correction 
## 
## data:  as.numeric(p1$Simpson) and as.factor(p1$Area) 
## 
##   N    
## S 0.026
## 
## P value adjustment method: holm

boxplot_p3=boxplot(as.numeric(p1$`Riqueza específica`) ~ p1$Area,
                       col=c("#FFAEB9","#008B45"),xlab="Area",ylab="Riqueza específica",outline=FALSE)

pairwise.wilcox.test(as.numeric(p1$`Riqueza específica`),as.factor(p1$Area), p.adjust.method =  "holm",
                     paired = F)

## Warning in wilcox.test.default(xi, xj, paired = paired, ...): cannot compute
## exact p-value with ties

## 
##  Pairwise comparisons using Wilcoxon rank sum test with continuity correction 
## 
## data:  as.numeric(p1$`Riqueza específica`) and as.factor(p1$Area) 
## 
##   N      
## S 0.00069
## 
## P value adjustment method: holm