1. Libraries and settings
# Libraries
library(plyr)
library(tidyverse)
library(reshape2)
library(ggthemes)
library(lubridate)
# Default ggplot settings
ggthe_bw<-theme(plot.background=element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
legend.box.background = element_rect(),
panel.background =element_rect(fill = NA, color = "black")
)+
theme_bw()
2. Import the temperature data
Temperature<-read.csv("Day_Tem.csv", header = T)
Temperature$Period<-factor((Temperature$Period),levels=c
("Acer","Ofav-Ssid","Nutrients", "Ramping up",
"Bleaching","Ramping down", "Recovery2"))
# Temperature data available from each treatment-replicate-day
Periods.days <- ddply (Temperature, .(Period, Treatment),summarise,
Dmin = min (Day, na.rm = F),
Dmax = max (Day, na.rm = F))
Periods.days
Temperature.82<-subset(Temperature, Day=="82")
Temperature.111<-subset(Temperature, Day=="111")
Periods.82 <- ddply (Temperature.82, .(Treatment),summarise,
Tmean = mean (Temperature, na.rm = F),
Tmin = min (Temperature, na.rm = F),
Tmax = max (Temperature, na.rm = F))
Periods.82
Periods.82 <- ddply (Temperature.82, .(Day),summarise,
Tmean = mean (Temperature, na.rm = F),
Tmin = min (Temperature, na.rm = F),
Tmax = max (Temperature, na.rm = F))
Periods.82
Periods.82 <- ddply (Temperature.82, .(Day),summarise,
Tmean = mean (Temperature, na.rm = F),
Tsd = sd (Temperature, na.rm = F))
Periods.82
Periods.110 <- ddply (Temperature.111, .(Day),summarise,
Tmean = mean (Temperature, na.rm = F),
Tsd = sd (Temperature, na.rm = F))
Periods.110
3. Look at temperature conditions during each period of the experiment:
- during recovery from collection and fragmentation and
- during the experiment (nutrient addition, ramping up, and bleaching)
- during recovery from bleaching
Temperature_Periods_R<- ggplot(Temperature, aes (Day, Temperature,
colour=factor(Period))) +
stat_summary(fun.data = "mean_cl_boot",geom = "errorbar", width = 0.2 )+
stat_summary(fun.y=mean, geom="line") + ggthe_bw +
xlab("Days in the experiment") + guides(colour=guide_legend("Period")) +
ylab("Temperature (C)") + facet_grid(Replicate~.)
Temperature_Periods_R

Summary_Period <- ddply (Temperature, .(Period),summarise,
Temp = mean (Temperature, na.rm = T),
Tsd = sd (Temperature, na.rm = T),
Tmax = max (Temperature, na.rm = T),
Tmin = min (Temperature, na.rm = T))
Summary_Period
Summary_Tanks <- ddply (Temperature, .(Period, Treatment, Replicate),summarise,
Temp = mean (Temperature, na.rm = T),
Tsd = sd (Temperature, na.rm = T),
Tmax = max (Temperature, na.rm = T),
Tmin = min (Temperature, na.rm = T))
Summary_Tanks
4. Get the sample times and merge them with the temperature
Meassurments<-read.csv("Time_data.csv", header = T)
Meassurments$Date<-as.Date(Meassurments$Date)
Meassurments$Day<-as.numeric(Meassurments$Date)-17483
Meassurments$Date<-NULL
Temperature<-subset(Temperature, Day<114)
Temperature<-subset(Temperature, Day>-1)
data<-join(Temperature, Meassurments, by="Day")
Figure 1: Experimental conditions
Design<- ggplot(data) + theme_bw() +
scale_y_continuous(limits = c(24,33.4),
name=(expression("Temperature"~(degree*C))),
breaks = seq(24, 32, 1),
expand = c(0, 0)) +
scale_x_continuous(name="Days in the experiment",
limits = c(-1,114),
breaks = seq(0, 113, 15),
expand = c(0, 0))+
annotate("segment", x = 2, xend = 91, y = 32, yend = 32,
colour = "black", linetype=2)+
annotate("segment", x = 79, xend = 79, y = 24, yend = 32,
colour = "gray", linetype=1)+
annotate("segment", x = 91, xend = 91, y = 24, yend = 32,
colour = "gray", linetype=1)+
annotate("text", x= c(46, 84, 101), y = c(32.5,25.5,24.5),
label=c("Nutrient treatments (Ambient, NH4, NH4+PO4)", " ", " "), size=3) +
annotate("text", x= c(40, 84, 102), y = c(24.5, 24.5, 24.5),
label=c("Phase 1: Control temperature",
"Phase2: \n Ramp-up",
"Phase 3:\n Heat stress"), size=3) +
geom_smooth(aes (Day, Temperature),
method="loess",
span=0.1, colour="black")+
# Samples
annotate("point",x=c(75, 100, 111), y=c(32),
shape=21, size=2, fill="white") +
annotate("point",x=c(82, 111), y=c(32, 32.5),
shape=21, size=2, fill="white")+
annotate("point",x=c(82, 111), y=c(32, 32.5),
shape=4, size=2)+
# Labels
annotate("point",x=c(3, 3), y=c(29, 30),
shape=21, size=2, fill="white")+
annotate("point",x=c(3), y=c(29),
shape=4, size=2)+
annotate("text", x= c(28,25), y = c(29,30),
label=c( "Sacrificial samples - censored events",
"Microbiome samples"), size=3)+
geom_point(aes (Day, Y, colour=Data, shape=Data))+
scale_shape_manual(values=c(21,2,24))+
scale_colour_manual(values = c("gray35","gray70", "gray70"))+
theme(legend.position=c(0.2, 0.4),
plot.background=element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
legend.box.background = element_rect(),
panel.background =element_rect(fill = NA, color = "black")
)
Design

#ggsave(file="Outputs/Figure_1_Experiment_design.svg", plot=Design, dpi = 300, width=6, height=4)