R Code to make Figs 4, S2 and S3 in the paper: 

Langhammer et al. "The Positive Impact of Conservation Action". Science. 

__________________

library(ggplot2)

### Make Fig. 4 ###
Fig_4_data<- read.csv("[directory]", header=TRUE, na="", stringsAsFactors=TRUE)
Fig_4<-ggplot(Fig_4_data) + geom_point(aes(x=Year, y=Hedges_g, colour=Intervention, size=Variance, alpha=0.5), shape=21, fill="White", stroke=2) +
  geom_smooth(method='lm',(aes(x=Year, y=Hedges_g))) + 
  ylab ("Standardised Effect Size (Hedges' g)") + 
  xlab ("Publication year") + 
  theme(axis.title.y = element_text(size=12)) + 
  theme(axis.title.x = element_text(size=12)) 
plot (Fig_4)


### Regression for Fig. 4 ###
lm = lm(Year~Hedges_g, data = Fig_4_data)
summary(lm)


### Make Fig. S2 ###
Fig_S2_data<- read.csv("[directory]", header=TRUE, na="", stringsAsFactors=TRUE)
ggplot(Fig_S2_data, aes(x = reorder(Row, Hedges_g), y=Hedges_g)) + 
  geom_col(aes(fill = Intervention)) + 
  theme (panel.grid.major.x = element_blank()) +
  ylab ("Standardised effect size (Hedges' g)")


### Make Fig. S3 ###
Fig_S3_data <- read.csv("[directory]", header=TRUE, na="", stringsAsFactors=TRUE)
Fig_S3<-ggplot(Fig_S3_data) + geom_point(aes(x=Study_duration, y=Hedges_g, colour=Intervention, size=Variance, alpha=0.5), shape=21, fill="White", stroke=2) +
  geom_smooth((aes(x=Study_duration, y=Hedges_g, colour=Intervention))) + 
  ylab ("Standardised Effect Size (Hedges' g)") + 
  xlab ("Study duration (months)") + 
  theme(axis.title.y = element_text(size=12)) + 
  theme(axis.title.x = element_text(size=12)) 
plot (Fig_S3)
Fig_S3+facet_wrap(~Intervention, ncol=2, scales="free")