library(vegan)
library(multcomp)

#Sex ratio comprison 
data<-read.table("File_1.csv",header=TRUE,sep=";",dec=",",stringsAsFactors = T)
data$rk<-as.factor(data$year)
attach(data)
mod1<-glm(cbind(Male,Female)~rk*specie,data=data,family="quasibinomial")

plot(mod1)
anova(mod1,test="F")
summary(mod1)
anova(mod1,test="F")[2:4,2]/anova(mod1,test="F")[1,4]
prd<-expand.grid(specie=levels(data$specie),rk=levels(data$rk))
prd$fit<-predict(mod1,newdata=prd,type="link")
prd$SE<-predict(mod1,newdata=prd,type="link",se.fit=T)$se
prd$prum<-exp(prd$fit)/(1+exp(prd$fit))
prd$lcl<-exp(prd$fit-2*prd$SE)/(1+exp(prd$fit-2*prd$SE))
prd$ucl<-exp(prd$fit+2*prd$SE)/(1+exp(prd$fit+2*prd$SE))
prd

#Diversity index
data2<-read.table("index.csv",header=TRUE,sep=";",dec=",",stringsAsFactors = T)
summary(data2)
attach(data2)
diversity(data2, index = "shannon",MARGIN = 1)