Biomass vs Crude Protein

ARFor <- read.csv("./arforage.csv")

Pasture.Pro <- ddply(ARFor, .(Pasture, Patch, Month), 
      summarise, 
      PROTEIN=round(mean(PROTEIN), 1),
      Fecal=round(mean(Fecal), 1),
      Biomass=round(mean(Biomass), 1))

Pasture.Pro$Month = factor(Pasture.Pro$Month, levels(Pasture.Pro$Month)[c(3,2,1)])

Pasture.Pro$Patch <- revalue(Pasture.Pro$Patch, 
                          c("B"="burned", 
                            "U"="unburned"))

# CP vs Bio, basic graph

ggplot(Pasture.Pro, aes(x=Biomass, y=PROTEIN))+
  geom_point(size=3)+
  geom_smooth(method="lm", se=FALSE)+
  labs(x="Biomass (g)", y="Crude protein (%)")+
  theme_bw(16)

# CP vs Bio, color=Patch

ggplot(Pasture.Pro, aes(x=Biomass, y=PROTEIN, color=Patch))+    
  geom_point(size=3)+
  geom_smooth(method="lm", se=FALSE)+
  labs(x="Biomass (g)", y="Crude protein (%)")+
  theme_bw(16)

CP vs Bio, color=Month

ggplot(Pasture.Pro, aes(x=Biomass, y=PROTEIN, color=Month))+
  geom_point(size=3)+
  geom_smooth(method="lm", se=FALSE)+
  labs(x="Biomass (g)", y="Crude protein (%)")+
  theme_bw(16)

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.