##Graceful Kelp Crab Analysis
#Set Working directory and add libraries
setwd("~/Documents/Bates/Thesis/FHL 2020/GracefulKelpCrab")
library(nlme)
library(ggplot2)
library(ggpubr)
library(tidyverse)
library(broom)
library(AICcmodavg)

#Import feeding preference data
crab.data <- read.csv("1KelpCrabData.csv",header=T)
#Import temperature data
tempdata <- read.csv("PaperMetric.csv")
temptest <- read.csv("TEST.csv")

#viewing feeding preference data
crabchoice<-subset(crab.data, Treatment=="Choice")
head(crabchoice)
crabnochoice<-subset(crab.data, Treatment=="NoChoice")
head(crabnochoice)
summary (crabchoice)
summary (crabnochoice)

#normality and equal variances
crabchoicelme<-lme(fixed=GAlgalPerGCrab~Food,random=~1|Crab, data=crabchoice)
summary(crabchoicelme)
par(mfrow=c(1,1))
residualscrabchoice<-residuals(crabchoicelme)
plot(residualscrabchoice)
shapiro.test(residualscrabchoice) #W=0.95599, p=0.4126
bartlett.test(GAlgalPerGCrab~Food, data=crabchoice) #K-squared=0.53862, df=1, p-value=0.463

#normality and equal variances
crabnochoicelme<-lme(fixed=GAlgalPerGCrab~Food,random=~1|Crab, data=crabnochoice)
summary(crabnochoicelme)
par(mfrow=c(1,1))
residualscrabnochoice<-residuals(crabnochoicelme)
plot(residualscrabnochoice)
shapiro.test(residualscrabnochoice) #W=0.98517, p=0.9729
bartlett.test(GAlgalPerGCrab~Food, data=crabnochoice) #K-squared=0.29886, df=1, p-value=0.5846

#box plots for choice
ggplot(crabchoice, aes(x = Food, y = GAlgalPerGCrab)) + geom_boxplot() + geom_point(size = 4, color = 'lightgrey', alpha = 0.5) + xlab("Food Source") + ylab("Algal Mass Consumed (g) Per Crab Mass (g)") + theme_bw() + theme(axis.text.x=element_text(face=c("italic","italic","italic","italic")))
#box plots for no choice
ggplot(crabnochoice, aes(x = Food, y = GAlgalPerGCrab)) + geom_boxplot() + geom_point(size = 4, color = 'lightgrey', alpha = 0.5) + xlab("Food Source") + ylab("Algal Mass Consumed (g) Per Crab Mass (g)") + theme_bw() + theme(axis.text.x=element_text(face=c("italic","italic","italic","italic")))

#t-test for choice
t.test(GAlgalPerGCrab~Food, data=crabchoice, paired=T) #t=3.0378, df=10, p-value=0.01251
#t-test for no-choice
t.test(GAlgalPerGCrab~Food, data=crabnochoice, paired=F, var.equal = TRUE) #t=0.74643, df=20.028, p-value=0.4637

#viewing temperature data
summary(tempdata)
#box plot for temperature data
ggplot(tempdata, aes(x= Temp, y = Mass)) + geom_boxplot() + geom_point(size = 4, color = 'lightgrey', alpha = 0.5) + xlab("Temperature") + ylab("Algal Mass Consumed (g) Per Crab Mass (g)") + theme_bw()

#welch's test for temp data
t.test(temptest$Ambient, temptest$Elevated)