#Supplemental 8: Data used by Curtis & Larson to create figures and estimate biomass loss

##Fig3A Code: 
  cray<-read.csv("C:/Users/ loss over time.csv", header=TRUE) 
  ##Read in Supplemental3_Data used in Fig 3A .csv file
  library(ggplot2)
  library(drc)
  model.drm<-drm(loss~day, data=cray, fct=MM.2())
  mm1<-data.frame(day=seq(0, max(cray$day, length.out=30)))
  mm1$loss<-predict(model.drm, newdata=mm1); 
  ggplot(cray, aes(x=day, y=loss))+theme_bw()+xlab("Day")+ylab("% Loss in Biomass")+geom_point(alpha=0.5)+geom_line(data=mm1, aes(x=day, y=loss))+
    theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
          panel.background = element_blank(), axis.line = element_line(colour = "black"))+theme(axis.text=element_text(size=12), axis.title=element_text(size=14,face="bold"))
  summary(model.drm)
  ##Modified x-axis from day to date of sampling using Adobe Editor 
  
  #Fig3B Code: 
  ##Read in Supplemental4_Data used in Fig 3B .csv file
  craywt<-read.csv("C:/Users/craywt.csv", header=TRUE)
  #To fix the order of the x-axis use the relevel function here
  craywt2<-with(craywt, relevel(Time, "Initial"))
  p1<-ggplot(craywt, aes(x=craywt2, y=Wt))+xlab("Time")+ylab("Mass (g)")+geom_boxplot()
  p1+theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
           panel.background = element_blank(), axis.line = element_line(colour = "black"))+theme(axis.text=element_text(size=12), axis.title=element_text(size=14,face="bold"))
  
  #To calculate means and standard errors of the weights:
  ##Read in Supplemental5_Data_to_estimate_decay_enclosures
  craywt3<-read.csv("C:/Users/craywt3.csv", header=TRUE)
  library(pastecs)
  #weight before deployment
  stat.desc(craywt3$B)
  #weight after deployment
  stat.desc(craywt3$A)
  
  #t-test; testing assumptions
  hist(craywt3$A)
  qqplot(craywt3$A)
  pl<-lm(B~Initial, data=craywt3)
  gvlma(pl)
  qqplot(B~Initial, data=craywt3)
  shapiro.test(craywt3$B)
  boxplot(B~Initial, data=crayw3t)
  shapiro.test(craywt3$B)
  shapiro.test(craywt3$A)
  t.test(craywt3$B, craywt$A, paired=TRUE) #t-value= 14.318; df=11; p=1.858E-08
  boxplot(B~Initial, data = craywt3)
  
  #Overall biomass loss
  ##Read in Supplemental6_Data_to_estimate_biomassloss.csv
  craywt4<-read.csv("C:/Users/craywt4.csv", header=TRUE)
  library(pastecs)
  stat.desc(craywt4$initial)
  stat.desc(craywt4$final)
  
  
  #Fig4 code:
  ##Read in Supplemental7:Data used to create Fig4 here
  cq<-read.csv("cray_cq.csv", header=TRUE, stringsAsFactors = FALSE)
  as.numeric(cq[,2])
  as.numeric(cq[,1])
  sample<-sample(c("100zg", "100fg", "10fg", "1fg", "100ag", "10ag", "1ag", "1pg"))
  
  df<-df%>%mutate(positon=factor(standard), positon=factor(standard, levels=rev(levels(standard))))
  
  cq1<-ggboxplot(cq, x = "standard", y = "Cq", color="sample",
                 palette = c("royalblue4", "cyan3"))
  cq1+aes(x=reorder(standard, desc(standard)), y=Cq)+scale_y_continuous(name="Cq", limits=c(10, 40))+scale_color_manual(values = c("#999999","#000000"))+theme(axis.text=element_text(size=16),
                                                                                                                                                               axis.title=element_text(size=20,face="bold"))+theme(legend.position = c(0.9, 0.9))+theme(legend.key=element_blank())+
    theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),panel.background = element_blank(), axis.line = element_line(colour = "black") , axis.title = element_text(size=16))