##########################################################################################################################
# --------------------------------------------- Figures with Source Data ----------------------------------------------- #
# R code related to                                                                                                      #
# Title: Plant diversity effects on forage quality, yield and revenues of semi-natural grasslands                        #
# Authors: Schaub. S., Finger, R., Leiber, F., Probst, S., Kreuzer, M., Weigelt, A., Buchmann, N., Scherer-Lorenzen, M.  #
##########################################################################################################################

#############################
#### 0. pre-settings
#############################
# clear workspace: 
rm(list = ls())  

# set working directory (note this directory needs to be specified):
setwd("H:/Jena_Management_Experiment/schaub_etal_2019_source_files")

# install and load packages:
# install.packages("tidyverse")
# install.packages("ggpubr")

# load packages:
require(tidyverse)
require(ggpubr)

# defining colors:
color_range <-  c("#f0e442","#0072B2","#009e73","#cc79a7", "#d55e00" ) 
color_range_ucp <-  c("#0072B2","#009e73","#cc79a7", "#d55e00" )
# we use colors based on colorblind: 'Colorblind Color Palette (Discrete) and Scales'.
#f0e442
#0072B2
#009e73
#cc79a7
#d55e00

#############################
#### 1. plot figures
#############################

#----------------------------------------------------------------------------------------------------------
# a) figure 1
#----------------------------------------------------------------------------------------------------------

# load data
dat_f1 <- read.csv("figure_1.csv", header=T, sep=",") 

# plot figure 
figure_1 <- ggplot(data=dat_f1)+
  geom_line( aes(x=SD,y= value,linetype=yield_type),size=1.2) +
  facet_grid(splitFigure2~splitFigure,switch = "both",labeller =label_bquote(cols = "Plant diversity")) +
  labs(x = NULL)+labs(y = NULL)+
  theme(axis.title.x = element_text( size=18), axis.text.x  = element_text( size=14,margin=margin(20,7,14,7,"pt")), 
        axis.title.y = element_text( size=18), axis.text.y  = element_text( size=14,margin=margin(7,7,14,7,"pt")),
        legend.text  = element_text( size=18),
        legend.title = element_text(size=18),
        legend.key = element_blank(),
        legend.key.size = unit(1.5,"cm"),
        legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1),
        strip.background = element_blank(),strip.text = element_text(size = 18)) +
  scale_y_continuous(limits = c(3, 13),breaks = c())+
  scale_x_continuous(limits = c(1, 10),breaks = c())+
  guides(linetype = guide_legend(""))+
  scale_linetype_manual(values = c("solid","dotted","longdash"),labels=c("Biomass yield", "Forage quality", "Quality-adjusted yield"))

figure_1



#----------------------------------------------------------------------------------------------------------
# b) figure 2
#----------------------------------------------------------------------------------------------------------

# load and adjust data
dat_f2    <- read.csv("figure_2.csv", header=T, sep=",") 
me_yield  <- dat_f2 %>% filter(variable == "me_yield")
mpp_yield <- dat_f2 %>% filter(variable == "mpp_yield")
cp_yield  <- dat_f2 %>% filter(variable == "cp_yield")
ucp_yield <- dat_f2 %>% filter(variable == "ucp_yield")
om_yield  <- dat_f2 %>% filter(variable == "om_yield")
ndf_yield <- dat_f2 %>% filter(variable == "ndf_yield")


# plot figures
## figure 2a - me yield
figure_2a <- ggplot()+                           
  geom_line(data=me_yield, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=me_yield, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=me_yield, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=me_yield, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=me_yield, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Metabolizable energy yield")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,4,8,12),limits = c(0,13))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_2a


## figure 2b - mpp yield
figure_2b <- ggplot()+                           
  geom_line(data=mpp_yield, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=mpp_yield, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=mpp_yield, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=mpp_yield, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=mpp_yield, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Milk production potential yield")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60)) + 
  scale_y_continuous(breaks = c(0,1,2,3),limits = c(0,3))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_2b


## figure 2c - cp yield
figure_2c <- ggplot()+                           
  geom_line(data=cp_yield, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=cp_yield, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=cp_yield, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=cp_yield, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=cp_yield, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Crude protein yield")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,100,200,300),limits = c(0,250))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_2c


## figure 2d - ucp yield
figure_2d <- ggplot()+                           
  geom_line(data=ucp_yield, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=ucp_yield, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=ucp_yield, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=ucp_yield, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Utilizable crude protein yield")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range_ucp,labels=c("C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,50,100,150),limits = c(0,150))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_2d


## figure 2e - om yield
figure_2e <- ggplot()+                           
  geom_line(data=om_yield, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=om_yield, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=om_yield, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=om_yield, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=om_yield, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Organic matter yield")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,500,1000,1500),limits = c(0,1500))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_2e


## figure 2f - ndf yield
figure_2f <- ggplot()+                           
  geom_line(data=ndf_yield, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=ndf_yield, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=ndf_yield, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=ndf_yield, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=ndf_yield, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Neutral detergent fiber yield")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,300,600,900),limits = c(0,900))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_2f


## figure 2
figure_2 <- ggarrange(figure_2a,figure_2b,figure_2c,figure_2d,figure_2e,figure_2f,nrow=3, ncol=2,align = "hv")
figure_2


#----------------------------------------------------------------------------------------------------------
# c) figure 4
#----------------------------------------------------------------------------------------------------------

# load data
dat_f4 <- read.csv("figure_4.csv", header=T, sep=",") 


# plot figure 
figure_4 <- ggplot()+                           
  geom_line(data=dat_f4, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=dat_f4, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=dat_f4, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=dat_f4, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=dat_f4, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Biomass yield")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,500,1000,1500),limits = c(0,1500))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_4


#----------------------------------------------------------------------------------------------------------
# c) figure 5
#----------------------------------------------------------------------------------------------------------

# load and adjust data
dat_f5      <- read.csv("figure_4.csv", header=T, sep=",") 
me_content  <- dat_f5 %>% filter(variable == "me_content")
mpp         <- dat_f5 %>% filter(variable == "mpp")
cp_content  <- dat_f5 %>% filter(variable == "cp_content")
ucp_content <- dat_f5 %>% filter(variable == "ucp_content")
om_content  <- dat_f5 %>% filter(variable == "om_content")
ndf_content <- dat_f5 %>% filter(variable == "ndf_content")


# plot figures
## figure 5a - me content
figure_5a <- ggplot()+                           
  geom_line(data=me_content, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=me_content, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=me_content, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=me_content, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=me_content, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Metabolizable energy content")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,4,8,12),limits = c(0,12))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_5a


## figure 5b - mpp 
figure_5b <- ggplot()+                           
  geom_line(data=mpp, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=mpp, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=mpp, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=mpp, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=mpp, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Milk production potential")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,1,2,3),limits = c(0,3))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_5b


## figure 5c - cp content
figure_5c <- ggplot()+                           
  geom_line(data=cp_content, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=cp_content, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=cp_content, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=cp_content, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=cp_content, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Crude protein content")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,100,200,300),limits = c(0,300))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_5c


## figure 5d - ucp content
figure_5d <- ggplot()+                          
  geom_line(data=ucp_content, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=ucp_content, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=ucp_content, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=ucp_content, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Utilizable crude protein content")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range_ucp,labels=c("C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,100,200,300),limits = c(0,300))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_5d


## figure 5e - om content
figure_5e <- ggplot()+                           
  geom_line(data=om_content, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=om_content, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=om_content, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=om_content, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=om_content, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Organic matter content")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(limits = c(800,950))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_5e


## figure 5f - ndf content
figure_5f <- ggplot()+                           
  geom_line(data=ndf_content, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=ndf_content, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=ndf_content, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=ndf_content, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=ndf_content, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Neutral detergent fiber content")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,250,500,750),limits = c(0,750))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))

figure_5f


## figure 5
figure_5 <- ggarrange(figure_5a,figure_5b,figure_5c,figure_5c,figure_5e,figure_5f,nrow=3, ncol=2,align = "hv")
figure_5


#----------------------------------------------------------------------------------------------------------
# e) figure 6
#----------------------------------------------------------------------------------------------------------

# load data
dat_f6 <- read.csv("figure_6.csv", header=T, sep=",") 


# plot figure 
figure_6 <- ggplot()+                           
  geom_line(data=dat_f5, aes(inter_T1+DE_SRxT1_coef , x=SR ,color= "T1" ),size=1)+
  geom_line(data=dat_f5, aes(inter_T2+DE_SRxT2_coef   , x=SR ,color= "T2" ),size=1)+
  geom_line(data=dat_f5, aes(inter_T3+DE_SRxT3_coef , x=SR ,color= "T3" ),size=1)+
  geom_line(data=dat_f5, aes(inter_T4+DE_SRxT4_coef, x=SR ,color= "T4" ),size=1)+  
  geom_line(data=dat_f5, aes(inter_T5+DE_SRxT5_coef , x=SR ,color= "T5" ),size=1)+
  
  theme(axis.title.x = element_text( size=38), axis.text.x  = element_text( size=34), 
        axis.title.y = element_text( size=38), axis.text.y  = element_text( size=38),legend.text  = element_text( size=38) ,
        legend.title = element_text(size=38),
        legend.key = element_blank(),legend.key.size = unit(1.5,"cm"),legend.position="bottom",
        panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1))+      
  labs(y = "Revenues")+labs(x = "Plant diversity (number of species)")+
  scale_colour_manual(values = color_range,labels=c("C1F0","C2F0","C2F100","C4F100","C4F200" ))+
  guides(color= guide_legend(""))+ 
  scale_x_continuous(breaks = c(1,10,20,30,40,50,60),limits = c(1,60))+
  scale_y_continuous(breaks = c(0,2500,5000,7500),limits = c(0,8000))+
  theme(legend.position="none",axis.text.x = element_text(margin=margin(7,7,14,7,"pt")),axis.text.y = element_text(margin=margin(7,7,14,7,"pt")))


figure_6



#----------------------------------------------------------------------------------------------------------
# f) figure 7
#----------------------------------------------------------------------------------------------------------

# load data
dat_f7 <- read.csv("figure_7.csv", header=T, sep=",") 


figure_7 <-   ggplot() + 
  geom_point(data= (dat_f6),aes( number_species, price_area, color = factor(mix_category), shape = mix_category), size=3) +
  theme(axis.title.x = element_text( size=21), axis.text.x  = element_text( size=14), 
        axis.title.y = element_text( size=21), axis.text.y  = element_text( size=14),legend.text  = element_text( size=21) ,
        title= element_text( size=21),
        legend.position=c(0.50,0.9))+  
  theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
        panel.background = element_blank(),panel.border = element_rect(colour = "black", fill=NA, size=1),
        strip.background = element_blank(),strip.text = element_text(size=21),
        legend.margin = margin(6, 6, 6, 6))+
  scale_color_manual(values = c("#1b9e77","#1b9e77","#d95f02"))+
  scale_shape_manual(values = c(16,17,17))+
  guides(fill=F)+
  labs(y ="Price (Euro per ha)", x = "Species number",color = "",  shape = "") +
  scale_y_continuous(limits = c(0,2000),  breaks = c(0,500,1000,1500,2000))

figure_7


#############################
#### 2. save figures
#############################

# ggsave("v1_figure_1.pdf", plot=figure_1, width = 20, height = 11)
# ggsave("v1_figure_2.pdf", plot=figure_2, width = 30, height = 33)
# ggsave("v1_figure_4.pdf", plot=figure_4, width = 15, height = 11)
# ggsave("v1_figure_5.pdf", plot=figure_5, width = 30, height = 33)
# ggsave("v1_figure_6.pdf", plot=figure_6, width = 15, height = 11)
# ggsave("v1_figure_7.pdf", plot=figure_7, width = 11, height = 8)

